Podcasts about un declaration

Susan M. Akram, Clinical Professor and Director of the International Human Rights Clinic at Boston University School of Law, discusses a significant report she co-authored and published through the University Network for Human Rights. Titled "Apartheid in Israel: An Analysis of Israel's Laws and Policies and the Responsibilities of U.S. Academic and Other Institutions," the report presents a detailed legal analysis demonstrating how Israel's treatment of Palestinians meets the internationally recognized legal definition of apartheid. Building on this conclusion, the report goes further to explore the ethical and legal obligations of academic institutions in the United States when engaging with or supporting a state accused of committing the crime of apartheid. It underscores that, rather than facing punishment, students and others who protest these injustices should be afforded protection under the UN Declaration on the Rights of Human Rights Defenders.

Elsa Stamatopoulou's Indigenous Peoples in the International Arena: The Global Movement for Self-Determination (Routledge 2025) provides a definitive account of the creation and rise of the international Indigenous Peoples' movement. In the late 1970s, motivated by their dire situation and local struggles, and inspired by worldwide movements for social justice and decolonization, including the American civil rights movement, Indigenous Peoples around the world got together and began to organize at the international level. Although each defined itself by its relation to a unique land, culture, and often language, Indigenous Peoples from around the world made an extraordinary leap, using a common conceptual vocabulary and addressing international bodies that until then had barely recognized their existence. At the intersection of politics, law, and culture, this book documents the visionary emergence of the international Indigenous movement, detailing its challenges and achievements, including the historic recognition of Indigenous rights through the adoption of the UN Declaration on the Rights of Indigenous Peoples in 2007. The winning by Indigenous Peoples of an unprecedented kind and degree of international participation – especially at the United Nations, an institution centered on states – meant overcoming enormous institutional and political resistance. The book shows how this participation became an increasingly assertive self-expression and even an exercise of self-determination by which Indigenous Peoples could both benefit from and contribute to the international community overall – now, crucially, by sharing their knowledge about climate change, their approaches to development and well-being, and their struggles against the impact of extractive industries on their lands and resources. Written by the former Chief of the Secretariat of the United Nations Permanent Forum on Indigenous Issues, this book will be of interest to researchers, teachers, students, advocates, practitioners, and others with interests in Indigenous legal and political issues. Elsa Stamatopoulou is Director of the Indigenous Peoples' Rights Program and Adjunct Professor in the Institute for the Study of Human Rights, the Department of Anthropology, and the Center for the Study of Ethnicity and Race at Columbia University, USA. Elsa is also Former (the first) Chief of the Secretariat of the UN Permanent Forum on Indigenous Issues (among other functions at the UN). Tim Wyman-McCarthy is a Lecturer in the discipline of Human Rights and Associate Director of Graduate Studies at the Institute for the Study of Human Rights and the Department of Sociology at Columbia University. He can be reached at tw2468@columbia.edu. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/new-books-network

Elsa Stamatopoulou's Indigenous Peoples in the International Arena: The Global Movement for Self-Determination (Routledge 2025) provides a definitive account of the creation and rise of the international Indigenous Peoples' movement. In the late 1970s, motivated by their dire situation and local struggles, and inspired by worldwide movements for social justice and decolonization, including the American civil rights movement, Indigenous Peoples around the world got together and began to organize at the international level. Although each defined itself by its relation to a unique land, culture, and often language, Indigenous Peoples from around the world made an extraordinary leap, using a common conceptual vocabulary and addressing international bodies that until then had barely recognized their existence. At the intersection of politics, law, and culture, this book documents the visionary emergence of the international Indigenous movement, detailing its challenges and achievements, including the historic recognition of Indigenous rights through the adoption of the UN Declaration on the Rights of Indigenous Peoples in 2007. The winning by Indigenous Peoples of an unprecedented kind and degree of international participation – especially at the United Nations, an institution centered on states – meant overcoming enormous institutional and political resistance. The book shows how this participation became an increasingly assertive self-expression and even an exercise of self-determination by which Indigenous Peoples could both benefit from and contribute to the international community overall – now, crucially, by sharing their knowledge about climate change, their approaches to development and well-being, and their struggles against the impact of extractive industries on their lands and resources. Written by the former Chief of the Secretariat of the United Nations Permanent Forum on Indigenous Issues, this book will be of interest to researchers, teachers, students, advocates, practitioners, and others with interests in Indigenous legal and political issues. Elsa Stamatopoulou is Director of the Indigenous Peoples' Rights Program and Adjunct Professor in the Institute for the Study of Human Rights, the Department of Anthropology, and the Center for the Study of Ethnicity and Race at Columbia University, USA. Elsa is also Former (the first) Chief of the Secretariat of the UN Permanent Forum on Indigenous Issues (among other functions at the UN). Tim Wyman-McCarthy is a Lecturer in the discipline of Human Rights and Associate Director of Graduate Studies at the Institute for the Study of Human Rights and the Department of Sociology at Columbia University. He can be reached at tw2468@columbia.edu. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/world-affairs

Elsa Stamatopoulou's Indigenous Peoples in the International Arena: The Global Movement for Self-Determination (Routledge 2025) provides a definitive account of the creation and rise of the international Indigenous Peoples' movement. In the late 1970s, motivated by their dire situation and local struggles, and inspired by worldwide movements for social justice and decolonization, including the American civil rights movement, Indigenous Peoples around the world got together and began to organize at the international level. Although each defined itself by its relation to a unique land, culture, and often language, Indigenous Peoples from around the world made an extraordinary leap, using a common conceptual vocabulary and addressing international bodies that until then had barely recognized their existence. At the intersection of politics, law, and culture, this book documents the visionary emergence of the international Indigenous movement, detailing its challenges and achievements, including the historic recognition of Indigenous rights through the adoption of the UN Declaration on the Rights of Indigenous Peoples in 2007. The winning by Indigenous Peoples of an unprecedented kind and degree of international participation – especially at the United Nations, an institution centered on states – meant overcoming enormous institutional and political resistance. The book shows how this participation became an increasingly assertive self-expression and even an exercise of self-determination by which Indigenous Peoples could both benefit from and contribute to the international community overall – now, crucially, by sharing their knowledge about climate change, their approaches to development and well-being, and their struggles against the impact of extractive industries on their lands and resources. Written by the former Chief of the Secretariat of the United Nations Permanent Forum on Indigenous Issues, this book will be of interest to researchers, teachers, students, advocates, practitioners, and others with interests in Indigenous legal and political issues. Elsa Stamatopoulou is Director of the Indigenous Peoples' Rights Program and Adjunct Professor in the Institute for the Study of Human Rights, the Department of Anthropology, and the Center for the Study of Ethnicity and Race at Columbia University, USA. Elsa is also Former (the first) Chief of the Secretariat of the UN Permanent Forum on Indigenous Issues (among other functions at the UN). Tim Wyman-McCarthy is a Lecturer in the discipline of Human Rights and Associate Director of Graduate Studies at the Institute for the Study of Human Rights and the Department of Sociology at Columbia University. He can be reached at tw2468@columbia.edu. Learn more about your ad choices. Visit megaphone.fm/adchoices Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/law

Elsa Stamatopoulou's Indigenous Peoples in the International Arena: The Global Movement for Self-Determination (Routledge 2025) provides a definitive account of the creation and rise of the international Indigenous Peoples' movement. In the late 1970s, motivated by their dire situation and local struggles, and inspired by worldwide movements for social justice and decolonization, including the American civil rights movement, Indigenous Peoples around the world got together and began to organize at the international level. Although each defined itself by its relation to a unique land, culture, and often language, Indigenous Peoples from around the world made an extraordinary leap, using a common conceptual vocabulary and addressing international bodies that until then had barely recognized their existence. At the intersection of politics, law, and culture, this book documents the visionary emergence of the international Indigenous movement, detailing its challenges and achievements, including the historic recognition of Indigenous rights through the adoption of the UN Declaration on the Rights of Indigenous Peoples in 2007. The winning by Indigenous Peoples of an unprecedented kind and degree of international participation – especially at the United Nations, an institution centered on states – meant overcoming enormous institutional and political resistance. The book shows how this participation became an increasingly assertive self-expression and even an exercise of self-determination by which Indigenous Peoples could both benefit from and contribute to the international community overall – now, crucially, by sharing their knowledge about climate change, their approaches to development and well-being, and their struggles against the impact of extractive industries on their lands and resources. Written by the former Chief of the Secretariat of the United Nations Permanent Forum on Indigenous Issues, this book will be of interest to researchers, teachers, students, advocates, practitioners, and others with interests in Indigenous legal and political issues. Elsa Stamatopoulou is Director of the Indigenous Peoples' Rights Program and Adjunct Professor in the Institute for the Study of Human Rights, the Department of Anthropology, and the Center for the Study of Ethnicity and Race at Columbia University, USA. Elsa is also Former (the first) Chief of the Secretariat of the UN Permanent Forum on Indigenous Issues (among other functions at the UN). Tim Wyman-McCarthy is a Lecturer in the discipline of Human Rights and Associate Director of Graduate Studies at the Institute for the Study of Human Rights and the Department of Sociology at Columbia University. He can be reached at tw2468@columbia.edu. Learn more about your ad choices. Visit megaphone.fm/adchoices

Elsa Stamatopoulou's Indigenous Peoples in the International Arena: The Global Movement for Self-Determination (Routledge 2025) provides a definitive account of the creation and rise of the international Indigenous Peoples' movement. In the late 1970s, motivated by their dire situation and local struggles, and inspired by worldwide movements for social justice and decolonization, including the American civil rights movement, Indigenous Peoples around the world got together and began to organize at the international level. Although each defined itself by its relation to a unique land, culture, and often language, Indigenous Peoples from around the world made an extraordinary leap, using a common conceptual vocabulary and addressing international bodies that until then had barely recognized their existence. At the intersection of politics, law, and culture, this book documents the visionary emergence of the international Indigenous movement, detailing its challenges and achievements, including the historic recognition of Indigenous rights through the adoption of the UN Declaration on the Rights of Indigenous Peoples in 2007. The winning by Indigenous Peoples of an unprecedented kind and degree of international participation – especially at the United Nations, an institution centered on states – meant overcoming enormous institutional and political resistance. The book shows how this participation became an increasingly assertive self-expression and even an exercise of self-determination by which Indigenous Peoples could both benefit from and contribute to the international community overall – now, crucially, by sharing their knowledge about climate change, their approaches to development and well-being, and their struggles against the impact of extractive industries on their lands and resources. Written by the former Chief of the Secretariat of the United Nations Permanent Forum on Indigenous Issues, this book will be of interest to researchers, teachers, students, advocates, practitioners, and others with interests in Indigenous legal and political issues. Elsa Stamatopoulou is Director of the Indigenous Peoples' Rights Program and Adjunct Professor in the Institute for the Study of Human Rights, the Department of Anthropology, and the Center for the Study of Ethnicity and Race at Columbia University, USA. Elsa is also Former (the first) Chief of the Secretariat of the UN Permanent Forum on Indigenous Issues (among other functions at the UN). Tim Wyman-McCarthy is a Lecturer in the discipline of Human Rights and Associate Director of Graduate Studies at the Institute for the Study of Human Rights and the Department of Sociology at Columbia University. He can be reached at tw2468@columbia.edu. Learn more about your ad choices. Visit megaphone.fm/adchoices

What if the key to protecting Native American sacred sites lies not within the confines of existing religious freedom laws, but in a reimagined legal strategy? Join us as we engage with Michael McNally, the insightful author of "Defend the Sacred: Native American Religious Freedom Beyond the First Amendment." Together, we unravel the complexities of how religious language, despite its colonial roots, can be harnessed to uphold Native American rights. Drawing on the American Indian Religious Freedom Act and the pivotal work of advocates like Suzanne Schoenharjo, McNally suggests a more adaptable interpretation of these laws that could empower Native communities and fortify their battles for sacred land protection.Our discussion takes a profound turn as we examine indigenous treaties and their deeper meanings beyond financial arrangements. By highlighting the Dakota, Lakota, and Little Traverse Band of Odawa lands, we recognize these treaties as living expressions of an inherent bond with nature, advocating for a paradigm shift from ownership to stewardship. The episode delves into the Doctrine of Discovery, inviting indigenous voices to reshape the narrative and affirm the interconnectedness of all life. Through these conversations, we seek to bridge legal frameworks with universal principles, aiming for a holistic appreciation of indigenous perspectives.The exploration doesn't stop there; we navigate the enduring impact of colonial legacies on Native sovereignty and governance. From the contentious history of the Bureau of Indian Affairs to the inspiring traditional governance of nations like the Onondaga, we uncover stories of resilience and hope. As we touch on legal resistance, landmark cases, and international law strategies like the UN Declaration on the Rights of Indigenous Peoples, we emphasize the persistent struggle and triumph of Native nations. With reflections on contemporary resistance movements and the challenges of safeguarding sacred land, the discussion is both a testament to Native perseverance and a call to honor their enduring wisdom.Support the showView the transcript and show notes at podcast.doctrineofdiscovery.org. Learn more about the Doctrine of Discovery on our site DoctrineofDiscovery.org.

The Prism of America's Education with Host Karen Schoen – First, Communists/Democrats/Globalists came for the Constitution... they call it a living, breathing document subject to constant change. They want it replaced with their UN Declaration of Human Rights, which claims the Government and UN grant your rights. Whatever man grants, man can take away...

UNESCO's global study on Indigenous media analyzes challenges and opportunities, supporting Indigenous peoples' right to establish their own media per the UN Declaration on the Rights of Indigenous Peoples (UNDRIP), Article 16. Indigenous Rights Radio Producer Dev Kumar Sunuwar spoke to Irmgarda Kasinskaite-Buddeberg, Advisor for Communication and Information, UNESCO, organizer of the Expert Meeting and Media Partnership Forum on Indigenous Peoples and the Media, held from 26 to 27 November at UNESCO headquarters in Paris, France. Program Producer: Dev Kumar Sunuwar Interviewee: Irmgarda Kasinskaite-Buddeberg, Advisor for Communication and Information, UNESCO Music: 'Whispers,' by Ziibiwan, used with permission. 'Burn your village to the ground', by Haluci Nation, used with permission.

Hello Interactors,On October 12th, the United States observed Indigenous Peoples' Day, a recognition first proposed in 1977 during a UN conference in Geneva. Indigenous delegates called“to observe October 12, the day of so-called ‘discovery' of America, as an international day of solidarity with the indigenous peoples of the Americas”drawing attention to the broken treaties between Indigenous nations and the U.S. government. Thirty years later, the UN Declaration on the Rights of Indigenous Peoples affirmed that these treaties are of international concern, though the United States and a few other countries initially refused to endorse the declaration, and the resolution remains non-binding.On Indigenous People's Day, the satirical news outlet, The Onion, used the occasion to post a story with this headline: “Nation's Indigenous People Confirm They Don't Need Special Holiday, Just Large Swaths Of Land Returned Immediately”Today, there are 574 recognized Indigenous nations within the U.S., many of which still struggle for recognition and rights. As trade agreements like NAFTA dominate discussions on labor, immigration, and environmental impact, little attention is paid to the intricate trade systems Indigenous nations developed long before European contact. Here in the Pacific Northwest, societies like the Coast Salish had sophisticated economies driven by geographic access to key resources, especially salmon. Their control over rich fishing sites shaped trade, reinforced social hierarchies, and created territorial dynamics that predated modern trade systems.Yet, colonization disrupted these Indigenous networks, imposing disorienting and often exploitative systems of land ownership and resource extraction. This week, I hope to explore how the adaptive strategies of Indigenous nations—despite the hardships imposed by colonization—can inspire decentralized solutions to today's environmental and socio-economic challenges, just as these nations did for millennia.COASTAL CONTROL AND CULTURAL COMPLEXITYThe Pacific Northwest is one of the most ecologically diverse regions in North America. It was this natural abundance that enabled the Coast Salish peoples to establish rich, complex societies. Unlike the simplistic and often nomadic image of hunter-gatherers, the Coast Salish exhibited a diversity of approaches to resource management that reflect an intimate knowledge of their environment.According to Colin Grier, an anthropologist and archaeologist known for his research on Indigenous societies of the Pacific Northwest, there are expanded and diverse notions of hunter-gatherer strategies. His research demonstrates how the Coast Salish were able to create surplus production, social hierarchies, and sophisticated trade networks due to their advanced understanding of the ecological systems they lived within.At the heart of Coast Salish society was the salmon fishery, a resource so abundant and predictable that it allowed for the development of semi-sedentary communities. Grier emphasizes that their use of ecological niche construction — such as the creation of clam gardens and fish weirs — enabled the Coast Salish to actively shape their environment to increase resource availability.These inventions and engineered environmental modifications were essential for producing the surpluses that underpinned the region's complex social and economic systems. Unlike the traditional view of hunter-gatherers as passive foragers, the Coast Salish were active managers of their environment, designing and building a system that could support a large population through environmental and economically sustainable practices.The abundance of salmon, clams, and other marine resources also enabled the Coast Salish to develop highly stratified societies. Social hierarchies were reinforced by cultural practices such as the potlatch, where surplus wealth was redistributed by elites in ceremonial gatherings that solidified their social status. As Grier points out, the ability to control key resource sites — such as salmon fishing locations — allowed some families to accumulate wealth and power. This led to a clear division between elites, commoners, and slaves.The behavioral ecology of the Coast Salish extended far beyond simple resource extraction, encompassing complex social and economic strategies that allowed them to thrive in a resource-rich environment. Through kinship-based alliances and trade networks, coastal tribes maintained social cohesion and managed environmental variability, including managing large swaths of inland crops. These resources gave coastal tribes a significant advantage over inland freshwater groups, leading to unequal trade exchanges and the subjugation of inland tribes.This dynamic of resource exploitation created internal socio-economic imbalances, as coastal elites reinforced their power and prestige through their dominance over resource-poor inland tribes. While this form of resource-based exploitation was characteristic of the Coast Salish, it foreshadowed the more rigid and racialized systems of chattel slavery that would later be imposed through European colonization, where individuals were commodified as property and permanently stripped of their freedom and rights.SETTLER SYSTEMS AND STOLEN SOVEREIGNTYThe arrival of European settlers in the Pacific Northwest, beginning in the late 18th and early 19th centuries, marked the beginning of a profound transformation in the social, economic, and environmental landscape of the region. As Cole Harris, a renowned historical geographer, details in his book The Resettlement of British Columbia: Essays on Colonialism and Geographical Change, European colonization imposed new systems of land ownership and resource extraction that displaced Indigenous peoples and fundamentally altered their relationship with the land.Harris's work focuses on how colonial forces reshaped the geography and socio-economic structures of Indigenous communities, leading to the dispossession of their traditional territories and resources. Harris's analysis of the colonization of British Columbia reveals how Indigenous resource management systems, which had been developed over millennia, were systematically dismantled and replaced by European notions of private property and capitalist resource exploitation.The Indigenous peoples of the Pacific Northwest, including the Coast Salish, relied on communal access to resources, particularly salmon fishing grounds. Control over these resources was a crucial element of their social and political organization. However, as European settlers arrived, they imposed new territorial boundaries and claimed ownership over key resource areas, such as rivers and forests. The imposition of colonial land policies eroded Indigenous control over their traditional territories, leading to the displacement of Indigenous peoples from the most productive fishing sites and hunting grounds.Harris's work highlights the environmental degradation that came with European settlement. The introduction of intensive logging, fishing, and agricultural practices by settlers led to the over-exploitation of resources that had once been sustainably managed by Indigenous societies. Salmon populations, which had been the lifeblood of Coast Salish society, were drastically reduced by the construction of dams and the depletion of spawning habitats. The environmental changes wrought by European settlers not only disrupted the ecological balance of the region but also undermined the socio-economic systems that had sustained Indigenous peoples for generations.The loss of control over their lands and resources had profound social consequences for the Coast Salish and other Indigenous groups. As Harris notes, the colonial imposition of new economic systems — rooted in the extraction of natural resources for profit — displaced Indigenous peoples from their traditional economies and marginalized them within the emerging capitalist order. This dispossession of Indigenous lands and the environmental destruction that accompanied European settlement prophesied the global dynamics of resource exploitation that would come to define modern systems of trade and capitalism.GLOBAL GREED AND GEOGRAPHIC GRABThe dynamics of resource control and dispossession seen during European colonization are reflected in today's global economic systems. World-Systems Theory, developed by Immanuel Wallerstein, a prominent sociologist and economic historian, explains how wealthier core nations dominate peripheral regions by extracting their resources and labor. This global division of labor, where core nations exploit the natural resources and workforce of less developed regions, perpetuates global inequalities—a system rooted in colonial practices and still evident today.Trade agreements like NAFTA (North American Free Trade Agreement) highlight these core-periphery dynamics. NAFTA, implemented in 1994, aimed to increase trade between the U.S., Canada, and Mexico by reducing tariffs and promoting economic growth. However, the benefits were unevenly distributed, with the U.S. and Canada, as core nations, reaping most of the profits, while Mexico, a peripheral nation, became vulnerable to economic and environmental exploitation. This mirrors the power imbalances between coastal and inland Indigenous tribes, where coastal elites controlled key resources and exerted dominance over less powerful inland groups.NAFTA's impact on Mexico's agricultural sector illustrates this exploitation. Industrial agriculture, particularly in crops like corn and avocados for export, expanded under NAFTA. U.S. and Canadian corporations capitalized on Mexico's cheap labor and weak environmental regulations, resulting in significant environmental degradation. This includes soil depletion, overuse of water, deforestation, and pollution from pesticides and fertilizers. Large-scale farming operations prioritize profit over sustainability, depleting natural resources and harming local ecosystems.The environmental damage is compounded by severe social consequences. Small-scale Mexican farmers struggle to compete with the rise of large agribusinesses, leading to widespread displacement. Many are forced to abandon their land and migrate to urban areas or across the U.S. border in search of work. This displacement mirrors the historical marginalization of Indigenous peoples during European colonization, where resource loss left communities economically vulnerable and socially marginalized.NAFTA's exploitation of Mexico exemplifies the core-periphery dynamics described by Wallerstein. Core nations extract resources and labor from peripheral regions, reinforcing global inequalities. Mexico, economically marginalized within the global system, provides cheap labor and raw materials to wealthier nations while bearing the brunt of environmental and social costs.Much like Indigenous peoples displaced by European settlers, Mexico remains trapped in a global system of resource extraction and dependency, a legacy of exploitation that continues to shape the world today.The story of the Coast Salish and other Indigenous peoples of the Pacific Northwest reminds us of how deeply we can connect to the land, each other, and the resources that sustain us. For millennia, these societies thrived by adapting to their surroundings, developing diverse ways to live in balance with the environment. Their ability to nurture the land and build lasting communities offers important lessons for the challenges we face today.As we confront climate change, inequality, and environmental collapse, these ancient strategies of cooperation and sustainability offer perspective. The Coast Salish thrived by embracing diversity—in localized resource management, relationship-based trade, and communities rooted in reciprocity. They show us it's possible to prosper without exploiting the earth or one another.Though exploitation existed in these societies, its legacy continues today. Resource monopolies and social hierarchies remain short-sighted responses to complex issues, with global profit-seeking leaving behind destruction — exhausted soils, polluted waters, and displaced people.Still, there is hope. Indigenous strategies — focused on coexistence and sustainability—prove that a different path is possible. We need to stop seeing the earth as something to conquer and start caring for it, as these early societies did. Their adaptability and long-term focus on communal survival offer valuable lessons.The core message is simple: survival is about finding balance — between people, communities, and the earth. By learning from these Indigenous societies, we can build a future that's not just sustainable but flourishing, where diversity is our strength and guide forward. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit interplace.io

What is human dignity? Is it a real thing, or merely an idea? If it's real, then where does it come from? And why do only human beings have dignity? What about other intelligent beings? What about the octopus?These are only some of the many questions that Damir Marusic and Santiago Ramos talk about in a slow-burn, philosophical episode of Wisdom of Crowds. Because Santiago is executive editor of Wisdom of Crowds, Damir wants to learn more about his bedrock convictions. He cross-examines Santiago about his religion, politics, and formative experiences.At first, Damir finds in Santiago a kindred spirit: both are skeptical about power and about big political theories. But Santiago does have one fundamental conviction that he is not skeptical about: universal human dignity. Damir presses Santiago on this topic. What is human dignity? How do you know it exists? And do only human beings have dignity? What about other intelligent animals? What about … octopi?The ending is one of the richest parts of the conversation, so we made this episode is free for all subscribers. * Daniel Patrick Moynihan documentary (PBS).* Song about the guerrilla priest: Victor Jara, “Camilo Torres” (YouTube).* “Of New Things,” Pope Leo XIII (Vatican.va).* “On the Progress of Peoples,” Paul VI (Vatican.va).* Jacques Maritain and the UN Declaration of Human Rights (UNESCO).* The Cold War in Latin America (RetroReport).* Michael Novak obituary (New York Times). * Iraq War timeline (Council on Foreign Relations).* Thomas Aquinas on the human soul (Summa Theologiae, New Advent).* Valladolid debate on the rights of indigenous people (In Our Time, BBC).* Octopus intelligence (Natural History Museum).Wisdom of Crowds is a platform challenging premises and understanding first principles on politics and culture. Join us! This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit wisdomofcrowds.live/subscribe

According to Mischa Geracoulis, of Project Censored, media is a public good and journalism is a public service. “Being able to access information, being able to join in, participate in the free flow of information, to have an opinion, to formulate a stance –that is actually considered a human right, under Article 19 of the UN Declaration of Human Rights.” It only follows that censorship is a violation of human rights. Project Censored defines censorship more broadly than a government's control over the media. It is the suppression of information, whether purposefully or not, by any method – (including) bias, omission, underreporting, or even self-censorship by the reporter or publisher. Steve and Mischa discuss the urgency of getting the public to understand the genocide in Gaza, and crucial for Americans to see their government's role in it. They look at the challenges faced by independent press, as well as special problems of news deserts. They also talk about the need for media literacy while much of the public relies on social media, where algorithms play a suppressive role. Mischa Geracoulis is a media literacy expert, writer, and educator, serving as Project Censored's curriculum development coordinator. Mischa is on the editorial boards of the Censored Press and the Markaz Review. @MGeracoulis, @ProjectCensored on Twitter

Content warning for discussion of genocide, torture, mutilation, rape, and slavery Hey, Hi, Hello, this is the History Wizard and welcome back for Day 13 of Have a Day w/ The History Wizard. Thank you to everyone who tuned in for Day 12 last week, and especially thank you to everyone who rated and/or reviewed the podcast. I hope you all learned something last week and I hope the same for this week. This week marks the 4th part of our mini series of currently ongoing genocides and humanitarian crises. Episode 2 was on Palestine, Episode 11 was on Congo, episode 12 was on Sudan and today's will be on a very widely denied genocide, especially in left wing political circles. The Uyghur Genocide. But first, let's fortify ourselves with the waters of life and remember that part of our activism needs to always be finding joy in life and getting ourselves a little treat. It's time for the Alchemist's Table. Today's libation is called a Rumsberry Breeze. In your shaker muddle some raspberries with half an ounce of simple syrup. Add two ounces of dark rum. Shake well and double strain over ice. Top with ginger beer and enjoy. The genocide of the Uyghur people and the longer history of ethnic tensions between Han Chinese and the Uyghur peoples has centered around Xinjiang for as long as it's been around. First thing's first. Let's dive a bit into the history of the Uyghur people. The Uyghur are an ethnically Turkic people living, mostly in the Tarim and Dzungarian Basins in East Turkestan (what is sometimes called Uyghurstan) today. Xinjiang, sometimes also called the Xinjiang Uyghur Autonomous Region, has been under Chinese control since it was conquered from the Dzungar Khanate in around 1759. Now, how long have the Uyghur people been living in the area? Well, that's a matter of some contention and the answer you get will depend on what sources you go with. The history of the Uyghur people, including their ethnic origin, is an issue of contention between Uyghur nationalists and Chinese authorities. Uyghur historians view Uyghurs as the original inhabitants of Xinjiang, with a long history. Uyghur politician and historian Muhammad Amin Bughra wrote in his book A history of East Turkestan, stressing the Turkic aspects of his people, that the Turks have a 9,000-year history, while historian Turgun Almas incorporated discoveries of Tarim mummies to conclude that Uyghurs have over 6,400 years of history. The World Uyghur Congress has claimed a 4,000-year history. However, the official Chinese view, as documented in the white paper History and Development of Xinjiang, asserts that the Uyghurs in Xinjiang formed after the collapse of the Uyghur Khaganate in ninth-century CE Mongolia, from the fusion of many different indigenous peoples of the Tarim Basin and the westward-migrating Old Uyghurs. Regardless of which timeline we go with, the Uyghur people have certainly been living in the region for far longer than the Chinese Empires that have been dominating them for hundreds of years. And, make no mistake, modern day China is still very much imperial. Something that we'll cover in more detail later, as it is very relevant to the current genocide, is that the Uyghur people are, as a general rule, Muslim. The earliest records we have indicate that before this conversion to Islam around the 10th century CE the Old Uyghur people (Old Uyghur is meant to differentiate the Pre-Chinese Uyghur population from the modern one) followed the Tocharian religion. We don't really have any details about what, exactly, that religion entailed, but today most of the Tocharian inscriptions are based on Buddhist monastic texts, which suggests that the Tocharians largely embraced Buddhism. The pre-Buddhist beliefs of the Tocharians are largely unknown, but several Chinese goddesses are similar to the reconstructed Proto-Indo-European sun goddess and the dawn goddess, which implies that the Chinese were influenced by the pre-Buddhist beliefs of the Tocharians when they traveled on trade routes which were located in Tocharian territories.  The history of China's abuses over the peoples they conquered is a long one, but details on the exact situation of the Uyghur people are somewhat few and far between. However two of the most important parts of Uyghur-Chinese history in the region come from the 19th century CE with the Dungan Revolt and the Dzungar genocide. Something we need to note right now is that the modern Uyghur Ethnic group wasn't called the Uyghur before the Soviet Union gave them that name in 1921, although the modern Ughurs are descended from the Old Uyghurs, at the time of the Dungan Revolt and the Dzungar Genocide they were known by the Chinese as Turki or Taranchi. So if you're ever reading sources about these two events, you might not ever see the word Uyghur, despite them being involved in both events. The Dungan Revolt lasted from 1862 until 1877 and saw a roughly 21 million people killed. According to research by modern historians, at least 4 million Hui were in Shaanxi before the revolt, but only 20,000 remained in the province afterwards, with most of the Hui either killed in massacres and reprisals by government and militia forces, or deported out of the province. It has its roots in the ongoing ethnic tensions between the Hui (Muslim) minorities of China and the ethnic Han peoples. It also stemmed from economic conflicts as Han merchants were known to greatly overcharge Hui peoples and there was massive corruption and fiscal instability resulting from the Taiping Rebellion that led to the peoples of Xinjiang being heavily burdened by unfair taxes.  All of these tensions would explode into a riot in 1862 (some sources say over inflated pricing on bamboo stalks). As a result of this there was a massacre of Han people's by the Hui and everything snowballed from there. With the start of the revolt in Gansu and Shaanxi in 1862, rumors spread among the Hui (Dungans) of Xinjiang that the Qing authorities were preparing a wholesale preemptive slaughter of the Hui people in Xinjiang, or in a particular community. Opinions as to the veracity of these rumors vary: while the Tongzhi Emperor described them as "absurd" in his edict of September 25, 1864, Muslim historians generally believe that massacres were indeed planned, if not by the imperial government then by various local authorities. Thus it was the Dungans who usually revolted in most Xinjiang towns, although the local Turkic people—Taranchis, Kyrgyzs, and Kazakhs—would usually quickly join the fray. The revolt would rage for 15 years, with many Muslim people of Xinjiang and China been slaughtered or forced to convert away from Islam. Though these reprisal killings and forced conversions really only took place in areas that were in active revolt. There were many Chinese Muslims in the Qing armies during the pacification of the Revolt and many also received great acclaim and promotions once the war was over.  Although, it needs to be stated that there were some cities that were actively committing genocide, such as the city of Kashgar which carried out a preemptive slaughter of their Hui population in 1864. So, there was a genocide of the Hui people, as genocide is defined as actions taken with intent to destroy in whole or in part a particular national, racial, ethnic or religious group. Hell, the Taranchi Turkic peoples, our modern Uyghurs, originally aided the Hui, but wound up turning against them to join the Qing armies once they learned that the Hui wanted to put Xinjiang under their specific rule. I technically did these events out of order, but I'm not going to fix that. We've got to dip 100 years into the past to find the Dzungar Genocide. This genocide happened at the end of Mongol Rule in Xinjiang and around the time the Qing initially came in. We're going to talk about this very briefly, as we still have all our modern issues to discuss. The main reason we even need to bring up the Dzungar genocide in a podcast episode on the Uyghur Genocide is that the Uyghurs participated in this genocide on the side of the Qing army as part of an uprising against the Dzungar Khanate. The Dzungar Genocide killed between 70 and 80% of their original population of about 600,000. The Qianlong Emperor had this to say when ordering the extermination of the Dzungari people. "Show no mercy at all to these rebels. Only the old and weak should be saved. Our previous military campaigns were too lenient. If we act as before, our troops will withdraw, and further trouble will occur. If a rebel is captured and his followers wish to surrender, he must personally come to the garrison, prostrate himself before the commander, and request surrender. If he only sends someone to request submission, it is undoubtedly a trick. Tell Tsengünjav to massacre these crafty Zunghars. Do not believe what they say." So, Xinjiang was once again under Qing rule and would remain so until the Wuchang Uprising overthrew the Qing Dynasty and established the Republic of China (not to be confused with the modern day Republic of China, which is actually the nation of Taiwan under Chinese imperialist control.  All of this context is to show that relations between the Chinese government and the various Muslim ethnicities within its borders have always been one of Master and Slave. The Chinese government has always treated non-Han peoples as lesser, and the presence of Muslim Chinese peoples was only tolerated for as long as they worked in lock step with Beijing. Once they didn't, they were prime targets for reprisal massacres and forced conversion. We would see this scenario play out again during the time of the Chinese Republic in 1931 with the Kumul Rebellion.  The Kumul Rebellion began because of the actions of Jin Shuren, the governor of Xinjiang from 1928 until 1933. Jin was notoriously intolerant of Turkic peoples and openly antagonized them. Such acts of discrimination included restrictions on travel, increased taxation, seizure of property without due process and frequent executions for suspected espionage or disloyalty. However, the event that would spark the rebellion would be the annexation of the Kumul Khanate, a semi autonomous region in northern Xinjiang. At the end of the Rebellion Jin was dead and the First East Turkestan Republic was established around the city of Kashgar in the far west of Xinjiang. The First East Turkestan Republic would only last for a year before being conquered by a Chinese warlord named Shen Shicai, who had backing and support from the Soviet Union. In 1937, specifically to coincide with Stalin's own Great Purge, Shicai planned and executed the elimination of "traitors", "pan-Turkists", "enemies of the people", "nationalists" and "imperialist spies". His purges swept the entire Uyghur and Hui political elite. The NKVD provided the support during the purges. In the later stages of the purge, Sheng turned against the "Trotskyites", mostly a group of Han Chinese sent to him by Moscow. It's estimated that he killed between 50 and 100,000 people in these purges. Shicai would eventually betray the Soviets to join with the Kuomintang, the Chinese Nationalist Party, which would lead to the Soviets backing the Uyghur people in the Ili Rebellion leading to the creation of the Second East Turkestan Republic, which would eventually get folded into Mao Zedong's People's Republic of China in 1949. From the 1950s to the 1970s China enacted two main policies against the Uyghur people. They instituted mass migrations of Han Chinese people into Xinjiang as well as passing various laws designed to infringe and smother Uyghur ethnic and religious identity. Uyghurs are barred from freely practicing their religion, speaking their language, and expressing other fundamental elements of their identity. Restrictions apply to many aspects of life, including dress, language, diet, and education. The Chinese government closely monitors Uyghur religious institutions. Even ordinary acts such as praying or going to a mosque may be a basis for arrest or detention. While repression of Uyghur cultural beliefs and identity had existed from day 1 on the PRC, it was in 1990 that everything started to go pear shaped. The Barin Uprising took place between the 4th and 10th of April, 1990. Violence began on the evening of 4 April, when a group of 200 to 300 Uyghur men attempted to breach the gates of the local government office in a protest against alleged forced abortions of Uyghur women and Chinese rule in Xinjiang. Following the uprising in an unprecedented move, Chinese authorities arrested 7,900 people, labelled "ethnic splittists" and "counter-revolutionaries", from April to July 1990. Throughout the 1990s and early 2000s there were various terrorist attacks committed by Uyghur resistance groups and freedom fighters, leading to further crackdowns and tightening of police control in Xinjiang throughout the years. Until 2001 Beijing spoke about these attacks as isolated incidents and made no broad statements of all Uyghur being terrorists, despite regularly arresting thousands of Uyghur people for no real reason. Many of those arrested Uyghur people wound up in Laogai (reform through labor) camps or in laojiao (re-education through labor) camps scattered throughout China. But, after the 9/11 attacks on the United States the tone shifted and more and more anti-Uyghur rhetoric started to become anti-terrorist rhetoric. This type of shift in language always precedes an uptick in genocidal violence. Now that all Uyghur are being labeled as terrorists, all Uyghur can be arbitrarily arrested and put in camps or even merely killed and no one will really care because it's not ethnic based discrimination. It's an anti terrorism campaign designed to protect the people from violent thugs.  After 2001 Beijing Sided with the U.S. in the new “global war against terrorism,” the Chinese government initiated an active diplomatic and propaganda campaign against “East Turkestan terrorist forces.” This label was henceforth to be applied indiscriminately to any Uighur suspected of separatist activities. There has been no sign of any attempt by the Chinese authorities to distinguish between peaceful political activists, peaceful separatists, and those advocating or using violence. Although, it needs to be said that violence is a perfectly valid political tool when resisting genocide and imperialism. This leads us to China's Strike Hard Campaign Against Violent Terrorism and the creation of their “vocational education and training centers” (both laogai and laojiao allegedly closing down in around 2013, although satellite evidence says that's bullshit).   In early 2014, Chinese authorities in Xinjiang launched the renewed "strike hard" campaign around New Year. It included measures targeting mobile phones, computers, and religious materials belonging to Uyghurs. The government simultaneously announced a "people's war on terror" and local government introduced new restrictions that included the banning of long beards and the wearing of veils in public places. Over the life of the camps it is estimated, by various sources that between a few hundred thousand and 1.8 million people have been arbitrarily detained in these camps and subjected to forced labor as a method of reformation. This is part of a Chinese government policy called hashar and includes many public works projects in Xinjiang. Beyond the simple fact of these slave labor camps, the state also began imposing harsh penalties for violations of birth limits. It also implemented an aggressive campaign of mass sterilization and intrauterine contraceptive device (IUD) implantation programs. Chinese government officials justify this by equating high birth rates with religious extremism. Chinese academics have argued that ethnic minority population growth threatens social stability and national identity.  Leaked government documents show that violations of birth limits are the most common reason Uyghur women are placed in a detention camp. Women have testified to being sterilized without their consent while in detention. Other women have testified that they were threatened with detention if they refused sterilization or IUD implantation procedures. So, in summation, since the 1950s at least the Chinese government has been engaging in forcible assimilation practices. Something that the UN Declaration of the Rights of Indigenous Peoples (a legally non binding resolution passed in 2007) says Indigenous people have a right to not be subjected to. As well as forced sterilization and forced abortions for violating China's family planning laws. And arbitrary detention and forced labor on invented charges of religious extremism and separatist activities. And then also having their children taken away from them and placed into something akin to the residential school system of the US, Canada, and Australia where they are forbidden from even speaking the Uyghur language. Under the UN CPPCG China is guilty of genocide in the form of causing severe bodily or mental harm to the group, imposing measures designed to prevent births within the group, and transferring children of the group to another group. The Uyghur Genocide is one of the more difficult ones to talk about online, especially if you frequent leftist political circles and spaces like I do as anything anti-China is seen often seen as Western propaganda and part of Cold War policies of anticommunism, as if China doesn't have roughly 814 billionaires controlling the majority of their means of production. The wealthiest man in China is Zhong Shanshan. He privately owns a bottled water company and is worth over 60 billion dollars. China isn't a communist country, it's not even socialist. It's just fascist and capitalist. But that's a rant for a different day. The Uyghur Genocide is real and verifiable, although it can be difficult to do so as there is a lot of misinformation and propaganda regarding it on both sides of the discussion. None of that changes the fact of the genocide or of the destruction of Uyghur culture in Xinjiang.  That's it for this week folks. No new reviews, so let's get right into the outro. Have a Day! w/ The History Wizard is brought to you by me, The History Wizard. If you want to see/hear more of me you can find me on Tiktok @thehistorywizard or on Instagram @the_history_wizard. Please remember to rate, review, and subscribe to Have a Day! On your pod catcher of choice. The more you do, the more people will be able to listen and learn along with you. Thank you  for sticking around until the end and, as always, Have a Day, and Free Xinjiang.  

In this episode of The New Quantum Era, Kevin and Sebastian are joined by a special guest, Paul Cadden-Zemansky, Associate Professor of Physics at Bard College and Director of the Physics Program. Paul is also on the Executive Committee for the International Year of Quantum at the American Physical Society and has been actively involved in the UN's recent declaration of 2025 as the International Year of Quantum Science and Technology. With the UN resolution now official, Paul joins us to discuss the significance and plans for this global celebration of quantum mechanics.Listeners can expect an insightful conversation covering the following key points:The Significance of the International Year of Quantum Science and Technology: Paul explains the origins and importance of the UN's declaration, marking the 100th anniversary of quantum mechanics and its impact over the past century.Global Collaboration and Outreach: Discussion on the international cooperation involved in getting the resolution passed, including the involvement of various scientific societies and countries, and the emphasis on public awareness and education.Challenges and Strategies for Quantum Communication: Paul shares his thoughts on the difficulties of communicating complex quantum concepts to the public and the strategies to make quantum mechanics more accessible and engaging.Future Plans and Initiatives: Insights into the plans for 2025, including potential events, educational resources, and how individuals and organizations can get involved in promoting quantum science.Innovations in Quantum Visualization: Paul's work with students on new methods for visualizing complex quantum systems, including the development of tools to help understand two-qubit states.Mentioned in this episode:UN Declaration of 2025 as the International Year of Quantum Science and TechnologyAmerican Physical Society (APS)Quantum 2025 Website: quantum2025.orgPaul's Research Paper on Quantum Visualization on ArxivPaul's web-based visualization toolJoin us as we delve into the exciting world of quantum mechanics and explore the plans for celebrating its centennial year!

An  insightful conversation with Dr. Jennifer Tupper and Dr. Jan Hare as they discuss the significant strides and challenges in Indigenous education. This episode sheds light on the transformative potential of integrating Indigenous knowledge and perspectives into mainstream education to foster inclusive and equitable learning environments for all.Dr. Hare is an Anishinaabe scholar and educator from the M'Chigeeng First Nation, located in northern Ontario. She currently serves as Dean of Education for the Faculty of Education at the University of British ColumbiaDr. Tupper is an award winning scholar and professor of Curriculum Studies. She is currently serving her second term as Dean of the Faculty of Education at the University of Alberta in Treaty 6.Key Takeaways:Importance of Incorporating Indigenous Knowledge in Education: Both Dr. Jennifer Tupper and Dr. Jan Hare underscore the necessity of integrating Indigenous knowledge and perspectives into undergraduate and graduate education programs. This plays a crucial role in not only increasing the presence of Indigenous educators but also in driving systemic change within the educational landscape.Renewing the 2010 Accord to Reflect Modern Contexts: The renewal of the 2010 Accord is essential to support ongoing policy shifts influenced by events such as the Truth and Reconciliation Commission and the incorporation of UNDRIP into provincial legislation. The accord aims to build on foundational work while accommodating the evolving needs and rights of Indigenous communities in education.Provincial and Local Implementation for Broader Impact: Provinces like British Columbia are leading the way in implementing Indigenous-focused educational reforms, such as aligning with the UN Declaration of the Rights of Indigenous Peoples. Successful local adaptations include engaging Indigenous communities in curriculum development and integrating principles of learning that reflect Indigenous values and knowledge systems.

Hello Interactors,Biden's recent reflective quip got me thinking about how European colonial doctrines like the "Doctrine of Discovery" and the "civilizing mission," continue to justify the dominance over Indigenous peoples, including those in Papua New Guinea. These lingering narratives not only influence contemporary struggles for self-determination, they also impact global politics and economic globalism. Join me as I unpack the complex interplay of decolonization, sovereignty, and the roles international actors, and their maps, play(ed) in shaping these dynamics.Let's go…MAPS MARK MYTHSBiden recently suggested his uncle was eaten by "cannibals". Reflecting on World War II war veterans, he said, "He got shot down in New Guinea, and they never found the body because there used to be — there were a lot of cannibals, for real, in that part of New Guinea."Military records show that his uncle's plane crashed off the coast of New Guinea for reasons unknown and his remains were never recovered.Papua New Guinea's (PNG) Prime Minister James Marape didn't take kindly to Biden's remarks, stating that "President Biden's remarks may have been a slip of the tongue; however, my country does not deserve to be labeled as such." Marape reminded Biden that Papua New Guinea was an unwilling participant in World War II. He urged the U.S. to help locate and recover the remains of American servicemen still scattered across the country.President Biden is a victim of depictions of "cannibals" in Papua New Guinea that are part of a deeply problematic colonial and post-colonial narrative still debated among anthropologists. These often exaggerated or fabricated historical portrayals of Indigenous peoples as "savage" or "primitive" were used to justify colonial domination and the imposition of Western control under the guise of bringing "civilization" to these societies.During the age of exploration and colonial expansion, European explorers and colonists frequently labeled various Indigenous groups around the world as “cannibals.” These claims proliferated in PNG by early explorers, missionaries, and colonial administrators to shock audiences and underscore the perceived necessity of the "civilizing mission" — a form of expansionist propaganda.European colonial maps like these served as vital weapons. They defined and controlled space to legitimize territorial claims and the governance of their occupants. In the late 19th century, German commercial interests led by the German New Guinea Company, expanded into the Pacific, annexing northeastern New Guinea and nearby islands as Kaiser-Wilhelmsland. In response, Britain established control over southern New Guinea, later transferring it to Australia. After World War I, Australia captured the remaining German territories, which the League of Nations mandated it to govern as the Territory of New Guinea. Following World War II, the two territories, under UN trusteeship, moved towards unification as the Independent State of Papua New Guinea in 1975.Today, Papua New Guinea is central to Pacific geopolitics, especially with China's growing influence through efforts like the Belt and Road initiative. This is impacting regional dynamics and power relationships involving major nations like Australia, the US, and China resulting in challenges related to debt, environmental concerns, and shifts in power balances. The Porgera gold mine, now managed by a joint venture with majority PNG stakeholders, had been halted in 2020 due to human rights and environmental violations but is resuming under new management. While the extractive industries are largely foreign-owned, the government is trying to shift the revenue balance toward local ownership and lure investors away from exploitative practices. Meanwhile, Indigenous tribes remain critical of the government's complicity in the social, environmental, and economic disruption caused by centuries of capitalism and foreign intrusion.SUPREMACY SUBVERTS SOVEREIGNTYEarly Western explorers used a Christian religious rationale, rooted in the "Doctrine of Discovery" and the "civilizing mission" concept, to justify the subjugation and "taming" of Indigenous peoples in lands like Papua New Guinea. This doctrine deemed non-Christian peoples as lacking rights to their land and sovereignty, positioning European powers as having a divine mandate to take control.The "civilizing mission" substantiated a European moral and religious obligation to convert Indigenous populations to Christianity, underpinned by a profound sense of racial and cultural superiority. Terms like "savages," "beasts," and "cannibals" were used to dehumanize Indigenous peoples and justify their harsh treatment, with the belief that this would elevate them from their perceived primitive state and save their souls, legitimizing the colonization process and stripping them of autonomy.Indigenous peoples around the world continue to fight for their autonomy and right to self-determination. Papua New Guinea's path to self-determination has been fraught with the complexities of defining "peoples" and their rights to form a sovereign state. The concepts of state sovereignty and the rights of Indigenous peoples, particularly in the context of decolonization, were significantly influenced by international leaders like Woodrow Wilson. (for more on how the U.S. was instrumental in drawing the boundaries for Ukraine and other European states, check out my 2022 post on how maps are make to persuade

In this episode we yarn with Dr Sheryl Lightfoot - an Anishinaabe woman, citizen of the Lake Superior Band of Ojibwe, enrolled at the Keweenaw Bay Community.  Dr Lightfoot talks about potential for the UN Declaration on the Rights of Indigenous Peoples to inform a First Nations foreign policy. She also gives an insightful global perspective on the aftermath of Australia's failed referendum on an Indigenous Voice to Parliament. Dr Lightfoot is Chair and North American member on the UN Expert Mechanism on the Rights of Indigenous Peoples (EMRIP). Further reading:  Caring feminist states? Paternalistic feminist foreign policies and the silencing of Indigenous justice claims in Sweden and Canada Publications by Rauna Kuokkanen Credits: Host: ⁠Julie Ballangarry⁠ Guest: ⁠Dr Sheryl Lightfoot Executive Producer and Editor: ⁠Pariya Taherzadeh⁠⁠ Co-producers: ⁠Julie Ballangarry⁠, ⁠Alice Ridge⁠, Carla Kweifio-Okai and Annelise Lecordier Special thanks to Joanna Pradela Artwork: ⁠Humanize Media⁠ Created by the International Women's Development Agency (IWDA) and the Australian Feminist Foreign Policy Coalition.

Content warning for discussion of genocide. Welcome to the first spisode of Have a Day! w/ The History Wizard. This episode will discuss the early days of the field of genocide, the process by which it became a crime undernational law, the life of Raphael Lemkin, in brief, and the first time a country was charged with this crime above all crimes Intro and outro music linked here: https://uppbeat.io/track/paulo-kalazzi/heros-time Episode Transcript to Follow: Hey, Hi, Hello. This is The History Wizard and thank you for joining me for the flagship episode of “Have a Day w/ The History Wizard”. As we embark on this journey together we're going to be talking about History, Politics, Economics, Cartoons, Video Games, Comics, and the points at which all of these topics intersect. Anyone who has been following me one Tiktok or Instagram, @thehistorywizard on Tiktok and @the_history_wizard on Instagram, for any length of time. Literally any length of time at all, will probably be familiar with some, if not all, of the information we're going to learn today. However, I hope that you'll bear with me as it is important to, before we dive into the meat of the matter, make sure we've got some bones to wrap it around… Yes, that is the metaphor I'm going to go with. I wrote it down in my script, read it, decided I liked it, and now you all have to listen to it.  For our first episode we are going to be diving into one of my favorite parts of my field of expertise, meta knowledge concerning the field of genocide studies itself. Yes, that's right. We're going to start with the definition of genocide. The United Nations established the legal definition of genocide in the Convention for the Punishment and Prevention of the Crime of Genocide, which was unanimously adopted by the 51 founding members of the UN in the third meeting of the General Assemble and came into full legal force in 1951 after the 20th nation ratified it. This, by the way, is why none of the Nazis in the Nuremberg Trial were charged with the crime of genocide. The crime didn't exist when they were on trial. But, to return to the matter at hand, the definition of genocide can be found in Article 2 of the Convention for the Punishment and Prevention of the Crime of Genocide and reads as follows: In the present Convention, genocide means any of the following acts committed with intent to destroy, in whole or in part, a national, ethnical, racial or religious group, as such: Killing members of the group; Causing serious bodily or mental harm to members of the group; Deliberately inflicting on the group conditions of life calculated to bring about its physical destruction in whole or in part; Imposing measures intended to prevent births within the group; Forcibly transferring children of the group to another group. It is important to note that definition of genocide that the UN adopted is not exactly the same as the definition that Lemkin first proposed to the UN. His definition included economic classes, as well as political parties. There was, significant, pushback against the inclusion of those two categories from the US and the USSR as both nations feared that their many of their own actions could be considered genocide. Lemkin didn't fight too hard for those categories to stay in the definition, he was more concerned with ethnicity, nationality, race, and religion for, what he called, their cultural carrying capacity. Now, despite Lemkin's concern over the destruction of cultures, there is no strict legal definition of cultural genocide. The inclusion of Article 2, subsection E: Forcibly transferring children of the group to another group, could be seen as a nod to this idea, but it's not nearly enough. There was some effort to rectify this oversight in 2007 with the passage of the UN Declaration of the Rights of Indigenous Peoples, which states that indigenous peoples have a right against forcible assimilation. But even that is barely a step in the right direction as the UN DRIP is a legally non binding resolution making it little better than a suggestion. Now, where did the word genocide come from? Who made it and why? The term genocide was the brain child of a Polish-Jewish lawyer and Holocaust survivor named Raphael Lemkin. Now, despite Lemkin being a Holocaust survivor and term not gaining legal recognition until 1948, Lemkin actually based his work on the Armenian Genocide, what he originally called The Crime of Barbarity. Fun fact about Lemkin, he spoke 9 languages and could read 14. Anyway, after reading about the assassination of Talat Pasha in 1921. Talat was assassinated by Soghomon Telhirian as part of Operation Nemesis (he was put on trial for the assassination and was acquitted) After reading about the assassination Lemkin asked one of his professors at Jan Kazimierz University of Lwów (now the Ivan Franko National University of Lviv) why Talat was unable to be tried for his crimes before a court of law. The professor replied thusly: "Consider the case of a farmer who owns a flock of chickens. He kills them, and this is his business. If you interfere, you are trespassing." Lemkin replied, "But the Armenians are not chickens". His eventual conclusion was that "Sovereignty cannot be conceived as the right to kill millions of innocent people" In 1933 Lemkin made a presentation to the Legal Council of the League of Nations conference on international criminal law in Madrid, for which he prepared an essay on the Crime of Barbarity as a crime against international law. This is where the world would first encounter the word “genocide” a word that Lemkin had created by combining the Greek root ‘genos' meaning race or tribe, with the Latin root ‘cide' meaning killing.  Lemkin was as a private solicitor in Warsaw in 1939 and fled as soon as he could. He managed to escape through Lithuania to Sweden where he taught at the University of Stockholm until he was, with the help of a friend, a Duke University law professor named Malcolm McDermott Lemkin was able to flee to the US. Unfortunately for Lemkin he lost 49 member of his family to the Holocaust. The only family that survived was his brother, Elias and his wife who had both been sent to a Soviet forced labor camp. Lemkin was able to help them both relocate to Montreal in 1948. After publishing his iconic book “Axis Rule in Occupied Europe” with the help of the Carnegie Endowment for International Peace Lemkin became an advisor for chief prosecutor of the Nuremberg Trials, Robert H. Jackson. It was during these trials that he became convinced, more than ever before, that this crime above all crimes needed a name and laws to prevent and punish it. Even after the passage of the Convention for the Punishment of the Crime of Genocide Lemkin didn't consider his work to be over. The UN was brand new and had little in the way of real authority (something that hasn't changed over the past 70 years). So Lemkin traveled around to world trying to get national governments to adopt genocide laws into their own body of laws. He worked with a team of lawyers from Arabic delegations to try and get France tried for genocide for their conduct in Algeria and wrote an article in 1953 on the “Soviet Genocide in Ukraine” what we know as the Holodomor, though Lemkin never used that term in his article. Lemkin lived the last years of his life in poverty in New York city. He died in 1959 of a heart attack, and his funeral, which occurred at Riverside Church in Manhattan, was attended by only a small number of his close friends. Lemkin is buried in Mount Hebron Cemetery in Flushing, Queens. The last thing I want to discuss in our first episode is the first country to be charged with the crime of genocide before the United Nations. As we have already established, despite the Holocaust being the western world's premiere example of genocide, no one at the Nuremberg Trials was tried for the crime of genocide. So who, I can hear you asking from the future, who was the first country charged with genocide? Why, dear listener, it was none other than the U S of A in a 1951 paper titled “We Charge Genocide, which was presented before the United Nations in Paris in 1951. The document pointed out that the United Nations Convention on the Prevention and Punishment of Genocide defined genocide as any acts committed with "intent to destroy" a group, "in whole or in part." To build its case for black genocide, the document cited many instances of lynching in the United States, as well as legal discrimination, disenfranchisement of blacks in the South, a series of incidents of police brutality dating to the present, and systematic inequalities in health and quality of life. The central argument: The U.S. government is both complicit with and responsible for a genocidal situation based on the UN's own definition of genocide. The paper was supported by the American Communist Party and was signed by many famous personages such as:  W. E. B. Du Bois, George W. Crockett, Jr., Benjamin J. Davis, Jr., Ferdinand Smith, Oakley C. Johnson, Aubrey Grossman, Claudia Jones, Rosalie McGee, Josephine Grayson, Amy and Doris Mallard, Paul Washington, Wesley R. Wells, Horace Wilson, James Thorpe, Collis English, Ralph Cooper, Leon Josephson, and William Patterson. It was Patterson who presented the paper and the signatures before the UN in 1951. The UN largely ignored Patterson and never deigned to hear his case against the US government. And upon his return journey Patterson was detained while passing through Britain and had his passport seized once he returned to the US. He was forbade to ever travel out of the country again. The history of the field of genocide studies is long, unfortunately, far longer than the existence of a word with a legal definition and laws to back it up. We'll be going through the history of genocide in future episode, interspersed with other historical events or pressing issues of great import as we take this educational journey together. I'm going to try and put an episode together once a week, and if that needs to change for any reason I will let you know. Next week, on March 26th, we'll be learning about the Gazan genocide and the vast amount of historical context that goes into this, currently occurring, genocide. I've been the History Wizard. You can find me on Tiktok @thehistorywizard. You can find me on Instagram @the_history_wizard. Have a Day w/ The History Wizard can be found anywhere pods are cast. If you cannot find it on your podcatcher or choice, let me know and I will try and do something about it. Tune in next week for more depressing, but very necessary information and remember… Have a Day!

Join host Phil Le-Brun, AWS Director of Enterprise Strategy, and Neerav Kingsland, Head of Global Accounts for Anthropic, in a conversation about Anthropic's journey to create the safest and most capable AI model in the world. Learn about the company's relentless focus on safety, their groundbreaking large language model Claude, and how they ensure ethical outputs through Constitutional AI, which draws from varied sources like the UN Declaration of Human Rights and technology trust and safety documents. Gain insights into the partnership between AWS and Anthropic, and learn exactly what differentiates Claude from other generative AI models.Learn more about Amazon Bedrock, the easiest way to build and scale gen AI applications, and Amazon Q, a gen AI-powered assistant that can be tailored to your business.

British Columbia has become the first jurisdiction to sign the UN Declaration on the Rights of Indigenous People into law. Arno Kopecky explores some of the steps the province is taking to protect both biodiversity and the rights of Indigenous people. From the February 14, 2024, episode.

The Prism of America's Education with Host Karen Schoen – Exploring the tension between the US Constitution and the UN Declaration of Human Rights, I delve into the implications of government control over individual freedoms. I highlight the dangers of globalist agendas, the impact on education, health, and religious freedoms, and the urgent need to preserve American sovereignty and values in the face of growing authoritarianism...

In 2023 we did a few Fundamentals episodes covering Benchmarks 101, Datasets 101, FlashAttention, and Transformers Math, and it turns out those were some of your evergreen favorites! So we are experimenting with more educational/survey content in the mix alongside our regular founder and event coverage. Pls request more!We have a new calendar for events; join to be notified of upcoming things in 2024!Today we visit the shoggoth mask factory: how do transformer models go from trawling a deeply learned latent space for next-token prediction to a helpful, honest, harmless chat assistant? Our guest “lecturer” today is ; you might know him from his prolific online writing on and Twitter, or from his previous work leading RLHF at HuggingFace and now at the Allen Institute for AI (AI2) which recently released the open source GPT3.5-class Tulu 2 model which was trained with DPO. He's widely considered one of the most knowledgeable people on RLHF and RLAIF. He recently gave an “RLHF 201” lecture at Stanford, so we invited him on the show to re-record it for everyone to enjoy! You can find the full slides here, which you can use as reference through this episode. Full video with synced slidesFor audio-only listeners, this episode comes with slide presentation along our discussion. You can find it on our YouTube (like, subscribe, tell a friend, et al).Theoretical foundations of RLHFThe foundation and assumptions that go into RLHF go back all the way to Aristotle (and you can find guidance for further research in the slide below) but there are two key concepts that will be helpful in thinking through this topic and LLMs in general:* Von Neumann–Morgenstern utility theorem: you can dive into the math here, but the TLDR is that when humans make decision there's usually a “maximum utility” function that measures what the best decision would be; the fact that this function exists, makes it possible for RLHF to model human preferences and decision making.* Bradley-Terry model: given two items A and B from a population, you can model the probability that A will be preferred to B (or vice-versa). In our world, A and B are usually two outputs from an LLM (or at the lowest level, the next token). It turns out that from this minimal set of assumptions, you can build up the mathematical foundations supporting the modern RLHF paradigm!The RLHF loopOne important point Nathan makes is that "for many tasks we want to solve, evaluation of outcomes is easier than producing the correct behavior". For example, it might be difficult for you to write a poem, but it's really easy to say if you like or dislike a poem someone else wrote. Going back to the Bradley-Terry Model we mentioned, the core idea behind RLHF is that when given two outputs from a model, you will be able to say which of the two you prefer, and we'll then re-encode that preference into the model.An important point that Nathan mentions is that when you use these preferences to change model behavior "it doesn't mean that the model believes these things. It's just trained to prioritize these things". When you have preference for a model to not return instructions on how to write a computer virus for example, you're not erasing the weights that have that knowledge, but you're simply making it hard for that information to surface by prioritizing answers that don't return it. We'll talk more about this in our future Fine Tuning 101 episode as we break down how information is stored in models and how fine-tuning affects it.At a high level, the loop looks something like this:For many RLHF use cases today, we can assume the model we're training is already instruction-tuned for chat or whatever behavior the model is looking to achieve. In the "Reward Model & Other Infrastructure" we have multiple pieces:Reward + Preference ModelThe reward model is trying to signal to the model how much it should change its behavior based on the human preference, subject to a KL constraint. The preference model itself scores the pairwise preferences from the same prompt (worked better than scalar rewards).One way to think about it is that the reward model tells the model how big of a change this new preference should make in the behavior in absolute terms, while the preference model calculates how big of a difference there is between the two outputs in relative terms. A lot of this derives from John Schulman's work on PPO:We recommend watching him talk about it in the video above, and also Nathan's pseudocode distillation of the process:Feedback InterfacesUnlike the "thumbs up/down" buttons in ChatGPT, data annotation from labelers is much more thorough and has many axis of judgement. At a simple level, the LLM generates two outputs, A and B, for a given human conversation. It then asks the labeler to use a Likert scale to score which one it preferred, and by how much:Through the labeling process, there are many other ways to judge a generation:We then use all of this data to train a model from the preference pairs we have. We start from the base instruction-tuned model, and then run training in which the loss of our gradient descent is the difference between the good and the bad prompt.Constitutional AI (RLAIF, model-as-judge)As these models have gotten more sophisticated, people started asking the question of whether or not humans are actually a better judge of harmfulness, bias, etc, especially at the current price of data labeling. Anthropic's work on the "Constitutional AI" paper is using models to judge models. This is part of a broader "RLAIF" space: Reinforcement Learning from AI Feedback.By using a "constitution" that the model has to follow, you are able to generate fine-tuning data for a new model that will be RLHF'd on this constitution principles. The RLHF model will then be able to judge outputs of models to make sure that they follow its principles:Emerging ResearchRLHF is still a nascent field, and there are a lot of different research directions teams are taking; some of the newest and most promising / hyped ones:* Rejection sampling / Best of N Sampling: the core idea here is that rather than just scoring pairwise generations, you are generating a lot more outputs (= more inference cost), score them all with your reward model and then pick the top N results. LLaMA2 used this approach, amongst many others.* Process reward models: in Chain of Thought generation, scoring each step in the chain and treating it like its own state rather than just scoring the full output. This is most effective in fields like math that inherently require step-by-step reasoning.* Direct Preference Optimization (DPO): We covered DPO in our NeurIPS Best Papers recap, and Nathan has a whole blog post on this; DPO isn't technically RLHF as it doesn't have the RL part, but it's the “GPU Poor” version of it. Mistral-Instruct was a DPO model, as do Intel's Neural Chat and StableLM Zephyr. Expect to see a lot more variants in 2024 given how “easy” this was.* Superalignment: OpenAI launched research on weak-to-strong generalization which we briefly discuss at the 1hr mark.Note: Nathan also followed up this post with RLHF resources from his and peers' work:Show Notes* Full RLHF Slides* Interconnects* Retort (podcast)* von Neumann-Morgenstern utility theorem* Bradley-Terry model (pairwise preferences model)* Constitutional AI* Tamer (2008 paper by Bradley Knox and Peter Stone)* Paul Christiano et al. RLHF paper* InstructGPT* Eureka by Jim Fan* ByteDance / OpenAI lawsuit* AlpacaEval* MTBench* TruthfulQA (evaluation tool)* Self-Instruct Paper* Open Assistant* Louis Castricato* Nazneen Rajani* Tulu (DPO model from the Allen Institute)Timestamps* [00:00:00] Introductions and background on the lecture origins* [00:05:17] History of RL and its applications* [00:10:09] Intellectual history of RLHF* [00:13:47] RLHF for decision-making and pre-deep RL vs deep RL* [00:20:19] Initial papers and intuitions around RLHF* [00:27:57] The three phases of RLHF* [00:31:09] Overfitting issues* [00:34:47] How preferences get defined* [00:40:35] Ballpark on LLaMA2 costs* [00:42:50] Synthetic data for training* [00:47:25] Technical deep dive in the RLHF process* [00:54:34] Projection / best event sampling* [00:57:49] Constitutional AI* [01:04:13] DPO* [01:08:54] What's the Allen Institute for AI?* [01:13:43] Benchmarks and models comparisonsTranscriptAlessio [00:00:00]: Hey everyone, welcome to the Latent Space podcast. This is Alessio, partner and CTO in Residence at Decibel Partners, and I'm joined by my co-host Swyx, founder of Smol AI.Swyx [00:00:15]: Hey, and today we have Dr. Nathan Lambert in the house. Welcome.Nathan [00:00:18]: Thanks guys.Swyx [00:00:19]: You didn't have to come too far. You got your PhD in Berkeley, and it seems like you've lived there most of the time in recent years. You worked on robotics and model-based reinforcement learning on your PhD, and you also interned at FAIR and DeepMind. You bootstrapped the RLHF team at Hugging Face, and you recently joined the Allen Institute as a research scientist. So that's your quick bio. What should people know about you that maybe is not super obvious about you on New LinkedIn?Nathan [00:00:43]: I stay sane in various insane sport and ultra-endurance sport activities that I do.Swyx [00:00:50]: What's an ultra-endurance sport activity?Nathan [00:00:52]: Long-distance trail running or gravel biking. Try to unplug sometimes, although it's harder these days. Yeah.Swyx [00:00:59]: Well, you know, just the Bay Area is just really good for that stuff, right?Nathan [00:01:02]: Oh, yeah. You can't beat it. I have a trailhead like 1.2 miles from my house, which is pretty unmatchable in any other urban area.Swyx [00:01:11]: Pretty excellent. You also have an incredible blog, Interconnects, which I'm a fan of. And I also just recently discovered that you have a new podcast, Retort.Nathan [00:01:20]: Yeah, we do. I've been writing for a while, and I feel like I've finally started to write things that are understandable and fun. After a few years lost in the wilderness, if you ask some of my friends that I made read the earlier blogs, they're like, oh, this is yikes, but it's coming along. And the podcast is with my friend Tom, and we just kind of like riff on what's actually happening on AI and not really do news recaps, but just what it all means and have a more critical perspective on the things that really are kind of funny, but still very serious happening in the world of machine learning.Swyx [00:01:52]: Yeah. Awesome. So let's talk about your work. What would you highlight as your greatest hits so far on Interconnects, at least?Nathan [00:01:59]: So the ones that are most popular are timely and or opinion pieces. So the first real breakout piece was when April and I also just wrote down the thing that everyone in AI was feeling, which is we're all feeling stressed, that we're going to get scooped, and that we're overworked, which is behind the curtain, what it feels to work in AI. And then a similar one, which we might touch on later in this, was about my recent job search, which wasn't the first time I wrote a job search post. People always love that stuff. It's so open. I mean, it's easy for me to do in a way that it's very on-brand, and it's very helpful. I understand that until you've done it, it's hard to share this information. And then the other popular ones are various model training techniques or fine tuning. There's an early one on RLHF, which is, this stuff is all just like when I figure it out in my brain. So I wrote an article that's like how RLHF actually works, which is just the intuitions that I had put together in the summer about RLHF, and that was pretty well. And then I opportunistically wrote about QSTAR, which I hate that you have to do it, but it is pretty funny. From a literature perspective, I'm like, open AI publishes on work that is very related to mathematical reasoning. So it's like, oh, you just poke a little around what they've already published, and it seems pretty reasonable. But we don't know. They probably just got like a moderate bump on one of their benchmarks, and then everyone lost their minds. It doesn't really matter.Swyx [00:03:15]: You're like, this is why Sam Altman was fired. I don't know. Anyway, we're here to talk about RLHF 101. You did a presentation, and I think you expressed some desire to rerecord it. And that's why I reached out on Twitter saying, like, why not rerecord it with us, and then we can ask questions and talk about it. Yeah, sounds good.Nathan [00:03:30]: I try to do it every six or 12 months is my estimated cadence, just to refine the ways that I say things. And people will see that we don't know that much more, but we have a bit of better way of saying what we don't know.Swyx [00:03:43]: Awesome. We can dive right in. I don't know if there's any other topics that we want to lay out as groundwork.Alessio [00:03:48]: No, you have some awesome slides. So for people listening on podcast only, we're going to have the slides on our show notes, and then we're going to have a YouTube version where we run through everything together.Nathan [00:03:59]: Sounds good. Yeah. I think to start skipping a lot of the, like, what is a language model stuff, everyone knows that at this point. I think the quote from the Llama 2 paper is a great kind of tidbit on RLHF becoming like a real deal. There was some uncertainty earlier in the year about whether or not RLHF was really going to be important. I think it was not that surprising that it is. I mean, with recent models still using it, the signs were there, but the Llama 2 paper essentially reads like a bunch of NLP researchers that were skeptical and surprised. So the quote from the paper was, meanwhile, reinforcement learning known for its instability seemed a somewhat shadowy field for those in the NLP research community. However, reinforcement learning proved highly effective, particularly given its cost and time effectiveness. So you don't really know exactly what the costs and time that Meta is looking at, because they have a huge team and a pretty good amount of money here to release these Llama models. This is just the kind of thing that we're seeing now. I think any major company that wasn't doing RLHF is now realizing they have to have a team around this. At the same time, we don't have a lot of that in the open and research communities at the same scale. I think seeing that converge would be great, but it's still very early days. And the other thing on the slide is some of Anthropic's work, but everyone knows Anthropic is kind of the masters of this, and they have some of their own techniques that we're going to talk about later on, but that's kind of where we start.Alessio [00:05:17]: Can we do just a one-second RL version? So you come from a robotics background, which RL used to be, or maybe still is, state-of-the-art. And then now you're seeing a lot of LLM plus RL, so you have the gym fans, Eureka, you have MPU, which we had on the podcast when they started with RL. Now they're doing RL plus LLMs. Yeah. Any thoughts there on how we got here? Maybe how the pendulum will keep swinging?Nathan [00:05:46]: I really think RL is about a framing of viewing the world through trial and error learning and feedback, and really just one that's focused on thinking about decision-making and inputs in the world and how inputs have reactions. And in that, a lot of people come from a lot of different backgrounds, whether it's physics, electrical engineering, mechanical engineering. There are obviously computer scientists, but compared to other fields of CS, I do think it's a much more diverse background of people. My background was in electrical engineering and doing robotics and things like that. It really just changes the worldview. I think that reinforcement learning as it was back then, so to say, is really different. You're looking at these toy problems and the numbers are totally different, and everyone went kind of zero to one at scaling these things up, but people like Jim Phan and other people that were... You saw this transition in the decision transformer and papers and when people are trying to use transformers to do decision-making for things like offline RL, and I think that was kind of like the early days. But then once language models were so proven, it's like everyone is using this tool for their research. I think in the long run, it will still settle out, or RL will still be a field that people work on just because of these kind of fundamental things that I talked about. It's just viewing the whole problem formulation different than predicting text, and so there needs to be that separation. And the view of RL in language models is pretty contrived already, so it's not like we're doing real RL. I think the last slide that I have here is a way to make RLHF more like what people would think of with RL, so actually running things over time, but a weird lineage of tools that happen to get us to where we are, so that's why the name takes up so much space, but it could have gone a lot of different ways. Cool.Alessio [00:07:29]: We made it one slide before going on a tangent.Nathan [00:07:31]: Yeah, I mean, it's kind of related. This is a...Swyx [00:07:35]: Yeah, so we have a history of RL.Nathan [00:07:37]: Yeah, so to give the context, this paper really started because I have this more diverse background than some computer scientists, such as trying to understand what the difference of a cost function or a reward function and a preference function would be without going into all of the details. Costs are normally things that control theorists would work with in these kind of closed domains, and then reinforcement learning has always worked with rewards that's central to the formulation that we'll see, and then the idea was like, okay, we now are at preferences, and each step along the way there's kind of different assumptions that you're making. We'll get into these, and those assumptions are built on other fields of work. So that's what this slide is going to say, it's like RLHF, while directly building on tools from RL and language models, is really implicitly impacted and built on theories and philosophies spanning tons of human history. I think we cite Aristotle in this paper, which is fun. It's like going pre-BC, it's like 2,300 years old or something like that. So that's the reason to do this, I think. We kind of list some things in the paper about summarizing what different presumptions of RLHF could be. I think going through these is actually kind of funny. It's fun to talk about these, because they're kind of grab bags of things that you'll see return throughout this podcast that we're talking about it. The core thing of RLHF that, in order to be a believer in this, is that RL actually works. It's like, if you have a reward function, you can optimize it in some way and get a different performance out of it, and you could do this at scale, and you could do this in really complex environments, which is, I don't know how to do that in all the domains. I don't know how to exactly make chat GPT. So it's kind of, we'll overshadow everything. And then there's, go from something kind of obvious like that, and then you read the von Neumann-Morgenstern utility theorem, which is essentially an economic theory that says you can weight different probabilities of different people, which is a theoretical piece of work that is the foundation of utilitarianism, and trying to quantify preferences is crucial to doing any sort of RLHF. And if you look into this, all of these things, there's way more you could go into if you're interested in any of these. So this is kind of like grabbing a few random things, and then kind of similar to that is the Bradley-Terry model, which is the fancy name for the pairwise preferences that everyone is doing. And then all the things that are like, that Anthropic and OpenAI figured out that you can do, which is that you can aggregate preferences from a bunch of different people and different sources. And then when you actually do RLHF, you extract things from that data, and then you train a model that works somehow. And we don't know, there's a lot of complex links there, but if you want to be a believer in doing this at scale, these are the sorts of things that you have to accept as preconditions for doing RLHF. Yeah.Swyx [00:10:09]: You have a nice chart of like the sort of intellectual history of RLHF that we'll send people to refer to either in your paper or in the YouTube video for this podcast. But I like the other slide that you have on like the presumptions that you need to have for RLHF to work. You already mentioned some of those. Which one's underappreciated? Like, this is the first time I've come across the VNM Utility Theorem.Nathan [00:10:29]: Yeah, I know. This is what you get from working with people like to my co-host on the podcast, the rhetoric is that sociologist by training. So he knows all these things and like who the philosophers are that found these different things like utilitarianism. But there's a lot that goes into this. Like essentially there's even economic theories that like there's debate whether or not preferences exist at all. And there's like different types of math you can use with whether or not you actually can model preferences at all. So it's pretty obvious that RLHF is built on the math that thinks that you can actually model any human preference. But this is the sort of thing that's been debated for a long time. So all the work that's here is like, and people hear about in their AI classes. So like Jeremy Bentham, like hedonic calculus and all these things like these are the side of work where people assume that preferences can be measured. And this is like, I don't really know, like, this is what I kind of go on a rant and I say that in RLHF calling things a preference model is a little annoying because there's no inductive bias of what a preference is. It's like if you were to learn a robotic system and you learned a dynamics model, like hopefully that actually mirrors the world in some way of the dynamics. But with a preference model, it's like, Oh my God, I don't know what this model, like I don't know what chat GPT encodes as any sort of preference or what I would want it to be in a fair way. Anthropic has done more work on trying to write these things down. But even like if you look at Claude's constitution, like that doesn't mean the model believes these things. It's just trained to prioritize these things. And that's kind of what the later points I'm looking at, like what RLHF is doing and if it's actually like a repeatable process in the data and in the training, that's just unknown. And we have a long way to go before we understand what this is and the link between preference data and any notion of like writing down a specific value.Alessio [00:12:05]: The disconnect between more sociology work versus computer work already exists, or is it like a recent cross contamination? Because when we had Tri Dao on the podcast, he said FlashAttention came to be because at Hazy they have so much overlap between systems engineer and like deep learning engineers. Is it the same in this field?Nathan [00:12:26]: So I've gone to a couple of workshops for the populations of people who you'd want to include this like R. I think the reason why it's not really talked about is just because the RLHF techniques that people use were built in labs like OpenAI and DeepMind where there are some of these people. These places do a pretty good job of trying to get these people in the door when you compare them to like normal startups. But like they're not bringing in academics from economics, like social choice theory. There's just too much. Like the criticism of this paper that this is based on is like, oh, you're missing these things in RL or at least this decade of RL and it's like it would be literally be bigger than the Sutton and Barto book if you were to include everyone. So it's really hard to include everyone in a principled manner when you're designing this. It's just a good way to understand and improve the communication of what RLHF is and like what is a good reward model for society. It really probably comes down to what an individual wants and it'll probably motivate models to move more in that direction and just be a little bit better about the communication, which is a recurring theme and kind of my work is like I just get frustrated when people say things that don't really make sense, especially when it's going to manipulate individual's values or manipulate the general view of AI or anything like this. So that's kind of why RLHF is so interesting. It's very vague in what it's actually doing while the problem specification is very general.Swyx [00:13:42]: Shall we go to the, I guess, the diagram here on the reinforcement learning basics? Yeah.Nathan [00:13:47]: So reinforcement learning, I kind of mentioned this, it's a trial and error type of system. The diagram and the slides is really this classic thing where you have an agent interacting with an environment. So it's kind of this agent has some input to the environment, which is called the action. The environment returns a state and a reward and that repeats over time and the agent learns based on these states and these rewards that it's seeing and it should learn a policy that makes the rewards go up. That seems pretty simple than if you try to mentally map what this looks like in language, which is that like the language models don't make this easy. I think with the language model, it's very hard to define what an environment is. So if the language model is the policy and it's generating, it's like the environment should be a human, but setting up the infrastructure to take tens of thousands of prompts and generate them and then show them to a human and collect the human responses and then shove that into your training architecture is very far away from working. So we don't really have an environment. We just have a reward model that returns a reward and the state doesn't really exist when you look at it like an RL problem. What happens is the state is a prompt and then you do a completion and then you throw it away and you grab a new prompt. We're really in as an RL researcher, you would think of this as being like you take a state, you get some completion from it and then you look at what that is and you keep kind of iterating on it and all of that isn't here, which is why you'll hear RLHF referred to as bandits problem, which is kind of like you choose one action and then you watch the dynamics play out. There's many more debates that you can have in this. If you get the right RL people in the room, then kind of like this is an RL even when you zoom into what RLHF is doing.Alessio [00:15:22]: Does this change as you think about a chain of thought reasoning and things like that? Like does the state become part of the chain that you're going through?Nathan [00:15:29]: There's work that I've mentioned on one slide called process reward models that essentially rewards each step in the chain of thought reasoning. It doesn't really give the part of interaction, but it does make it a little bit more fine grained where you can think about like calling it at least you have many states from your initial state. That formulation I don't think people have fully settled on. I think there's a bunch of great work out there, like even OpenAI is releasing a lot of this and let's verify step by step is there pretty great paper on the matter. I think in the next year that'll probably get made more concrete by the community on like if you can easily draw out like if chain of thought reasoning is more like RL, we can talk about that more later. That's a kind of a more advanced topic than we probably should spend all the time on.Swyx [00:16:13]: RLHF for decision making. You have a slide here that compares pre-deep RL versus deep RL.Nathan [00:16:19]: This is getting into the history of things, which is showing that the work that people are using now really came from well outside of NLP and it came before deep learning was big. Next up from this paper, Tamer, which is from 2008. Some names that are still really relevant in kind of human centric RL, Bradley Knox and Peter Stone. If you have an agent take an action, you would just have a human give a score from zero to one as a reward rather than having a reward function. And then with that classifier, you can do something with a policy that learns to take actions to maximize that reward. It's a pretty simple setup. It works in simple domains. And then the reason why this is interesting is you compare it to the paper that everyone knows, which is this Paul Christiano et al. Deep Reinforced Learning from Human Preferences paper, which is where they showed that learning from human preferences, you can solve like the basic RL tasks at the time. So various control problems and simulation and this kind of like human preferences approach had higher rewards in some environments than if you just threw RL at the environment that returned a reward. So the preferences thing was you took two trajectories. So in this case, it was like complete trajectories of the agent and the human was labeling which one is better. You can see how this kind of comes to be like the pairwise preferences that are used today that we'll talk about. And there's also a really kind of interesting nugget that is the trajectory that the humans were labeling over has a lot more information than the RL algorithm would see if you just had one state, which is kind of why people think that it's why the performance in this paper was so strong. But I still think that it's surprising that there isn't more RL work of this style happening now. This paper is in 2017. So it's like six years later and I haven't seen things that are exactly similar, but it's a great paper to understand where stuff that's happening now kind of came from.Swyx [00:17:58]: Just on the Christiano paper, you mentioned the performance being strong. I don't remember what results should I have in mind when I think about that paper?Nathan [00:18:04]: It's mostly like if you think about an RL learning curve, which is like on the X axis, you have environment interactions on the Y axis, you have performance. You can think about different like ablation studies of between algorithms. So I think they use like A2C, which I don't even remember what that stands for as their baseline. But if you do the human preference version on a bunch of environments, like the human preference labels, the agent was able to learn faster than if it just learned from the signal from the environment, which means like it's happening because the reward model has more information than the agent would. But like the fact that it can do better, I was like, that's pretty surprising to me because RL algorithms are pretty sensitive. So I was like, okay.Swyx [00:18:41]: It's just one thing I do want to establish as a baseline for our listeners. We are updating all the weights. In some sense, the next token prediction task of training a language model is a form of reinforcement learning. Except that it's not from human feedback. It's just self-supervised learning from a general corpus. There's one distinction which I love, which is that you can actually give negative feedback. Whereas in a general sort of pre-training situation, you cannot. And maybe like the order of magnitude of feedback, like the Likert scale that you're going to talk about, that actually just gives more signal than a typical training process would do in a language model setting. Yeah.Nathan [00:19:15]: I don't think I'm the right person to comment exactly, but like you can make analogies that reinforcement learning is self-supervised learning as well. Like there are a lot of things that will point to that. I don't know whether or not it's a richer signal. I think that could be seen in the results. It's a good thing for people to look into more. As reinforcement learning is so much less compute, like it is a richer signal in terms of its impact. Because if they could do what RLHF is doing at pre-training, they would, but they don't know how to have that effect in like a stable manner. Otherwise everyone would do it.Swyx [00:19:45]: On a practical basis, as someone fine-tuning models, I have often wished for negative fine-tuning, which pretty much doesn't exist in OpenAI land. And it's not the default setup in open-source land.Nathan [00:19:57]: How does this work in like diffusion models and stuff? Because you can give negative prompts to something to like stable diffusion or whatever. It's for guidance.Swyx [00:20:04]: That's for clip guidance.Nathan [00:20:05]: Is that just from like how they prompt it then? I'm just wondering if we could do something similar. It's another tangent.Swyx [00:20:10]: I do want to sort of spell that out for people in case they haven't made the connection between RLHF and the rest of the training process. They might have some familiarity with it.Nathan [00:20:19]: Yeah. The upcoming slides can really dig into this, which is like this in 2018 paper, there was a position paper from a bunch of the same authors from the Christiano paper and from the OpenAI work that everyone knows, which is like, they write a position paper on what a preference reward model could do to solve alignment for agents. That's kind of based on two assumptions. The first assumption is that we can learn user intentions to a sufficiently high accuracy. That doesn't last with me because I don't know what that means. But the second one is pretty telling in the context of RLHF, which is for many tasks we want to solve, evaluation of outcomes is easier than producing the correct behavior. And this is the whole thing. It's like we can compare two poems that the model generates and it can be viewed as liking a positive example, or it could be viewed as really disliking a negative example. And that's what I think a lot of people are doing in like the harm space is like a harmful response to a language model, whether or not you agree with the company's definition of harms is that it's a really bad negative example and they downweight them by preferring something more benign in the RLHF process, among other ways of dealing with safety. So that's a good way of saying it's like this is core, this kind of like comparison and positive or negative example is core to all of the RLHF work that has continued.Swyx [00:21:29]: People often say, I don't know what I want, but I'll know when I see it. This is that expressed in reinforcement learning tools.Nathan [00:21:35]: Yeah, it is. Yeah, it is. That's what everyone's doing in the preference modeling stage that we'll get to. Yeah. Yeah. And you can see there are more papers. This is really just to have all the links for people that go deeper. There's a Ziegler et al. paper in 2019, which shows that you can do this RLHF process on language models. This familiar diagram starts to emerge in 2019, and it's just to show that this goes really far back. I think we can kind of breeze through some of these. And then 2020 is the first open AI experiment that I think caught people's eyes, which is this learning to summarize experiment. It has this three-step process that we'll go to into more when I kind of go into the main concepts. But this is like the first time you see this diagram that they reuse with InstructGPT, they reuse with ChatGPT. And the types of examples that they would have, I don't think I need to read these exactly, but one that I have read a whole bunch of times is like, they took these prompts from Reddit that was like, explain like I'm five or get career advice, and people really pour their heart and soul into these. So these are like multi-paragraph pieces of writing. And then they essentially do comparisons between a vanilla language model, like I think it was either GPT-2 or GPT-3, I don't always get the exact years.Swyx [00:22:42]: 3 was early 2020. So that's about right.Nathan [00:22:45]: Yeah. So this is probably done with GPT-2. It doesn't really matter. But the language model does normal things when you do few shot, which is like it repeats itself. It doesn't have nice text. And what they did is that this was the first time where the language model would generate like pretty nice text from an output. It was restricted to the summarization domain. But I think that I guess this is where I wish I was paying attention more because I would see the paper, but I didn't know to read the language model outputs and kind of understand this qualitative sense of the models very well then. Because you look at the plots in the papers, these Learning to Summarize and Destruct GPT have incredibly pretty plots, just like nicely separated lines with error bars and they're like superfine tuning works, the RL step works. But if you were early to see like how different the language that was written by these models was, I think you could have been early to like things like ChatGPT and knowing RLHF would matter. And now I think the good people know to chat with language models, but not even everyone does this. Like people are still looking at numbers. And I think OpenAI probably figured it out when they were doing this, how important that could be. And then they had years to kind of chisel away at that and that's why they're doing so well now. Yeah.Swyx [00:23:56]: I mean, arguably, you know, it's well known that ChatGPT was kind of an accident that they didn't think it would be that big of a deal. Yeah.Nathan [00:24:02]: So maybe they didn't. Maybe they didn't, but they were getting the proxy that they needed.Swyx [00:24:06]: I've heard off the record from other labs that it was in the air. If OpenAI didn't do it, someone else would have done it. So you've mentioned a couple of other papers that are very seminal to this period. And I love how you say way back when in referring to 2019.Nathan [00:24:19]: It feels like it in my life.Swyx [00:24:21]: So how much should people understand the relationship between RLHF, instruction tuning, PPO, KL divergence, anything like that? Like how would you construct the level of knowledge that people should dive into? What should people know at the high level? And then if people want to dive in deeper, where do they go? Is instruct tuning important here or is that part of the overall process towards modern RLHF?Nathan [00:24:44]: I think for most people, instruction tuning is probably still more important in their day to day life. I think instruction tuning works very well. You can write samples by hand that make sense. You can get the model to learn from them. You could do this with very low compute. It's easy to do almost in like no code solutions at this point. And the loss function is really straightforward. And then if you're interested in RLHF, you can kind of learn from it from a different perspective, which is like how the instruction tuning distribution makes it easier for your RLHF model to learn. There's a lot of details depending on your preference data, if it's close to your instruction model or not, if that matters. But that's really at the RLHF stage. So I think it's nice to segment and just kind of understand what your level of investment and goals are. I think instruction tuning still can do most of what you want to do. And it's like, if you want to think about RLHF, at least before DPO really had taken off at all, it would be like, do you want to have a team of at least like five people if you're really thinking about doing RLHF? I think DPO makes it a little bit easier, but that's still really limited to kind of one data set that everyone's using at this point. Like everyone's using this ultra feedback data set and it boosts AlpacaVal, MTBench, TruthfulQA and like the qualitative model a bit. We don't really know why. It's like, it might just be a data set combined with the method, but you've got to be ready for a bumpy ride if you're wanting to try to do RLHF. I don't really recommend most startups to do it unless it's like going to provide them a clear competitive advantage in their kind of niche, because you're not going to make your model chat GPT like better than OpenAI or anything like that. You've got to accept that there's some exploration there and you might get a vein of benefit in your specific domain, but I'm still like, oh, be careful going into the RLHF can of worms. You probably don't need to.Swyx [00:26:27]: Okay. So there's a bit of a time skip in what you mentioned. DPO is like a couple months old, so we'll leave that towards the end. I think the main result that I think most people talk about at this stage, we're talking about September 2020 and then going into, I guess maybe last year was Vicuña as one of the more interesting applications of instruction tuning that pushed LLAMA1 from, let's say a GPT 3-ish model to a GPT 3.5 model in pure open source with not a lot of resources. I think, I mean, they said something like, you know, they use like under $100 to makeNathan [00:26:58]: this. Yeah. Like instruction tuning can really go a long way. I think the claims of chat GPT level are long overblown in most of the things in open source. I think it's not to say, like Vicuña was a huge step and it's just kind of showing that instruction tuning with the right data will completely change what it feels like to talk with your model. Yeah.Swyx [00:27:19]: From text completion to actually chatting back and forth. Yeah. Yeah.Nathan [00:27:23]: Instruction tuning can be multi-turn. Just having a little bit of data that's like a couple of turns can go a really long way. That was like the story of the whole first part of the year is like people would be surprised by how far you can take instruction tuning on a small model. I think the things that people see now is like the small models don't really handle nuance as well and they could be more repetitive even if they have really good instruction tuning. But if you take that kind of 7 to 70 billion parameter jump, like the instruction tuning at the bigger model is like robustness, little things make more sense. So that's still just with instruction tuning and scale more than anything else.Swyx [00:27:56]: Excellent. Shall we go to technical overview?Nathan [00:27:58]: Yeah. This is kind of where we go through my own version of this like three phase process. You can talk about instruction tuning, which we've talked about a lot. It's funny because all these things, instruction tuning has the fewest slides, even though it's the most practical thing for most people. We could save the debate for like if the big labs still do instruction tuning for later, but that's a coming wave for people. And then like preference data and training and then kind of like what does reinforce learning optimization actually mean? We talk about these sequentially because you really have to be able to do each of them to be able to do the next one. You need to be able to have a model that's chatty or helpful instruction following. Every company has their own word that they like to assign to what instructions mean. And then once you have that, you can collect preference data and do some sort of optimization.Swyx [00:28:39]: When you say word, you mean like angle bracket inst or do you mean something else?Nathan [00:28:42]: Oh, I don't even know what inst means, but just saying like they use their adjective that they like. I think Entropic also like steerable is another one.Swyx [00:28:51]: Just the way they describe it. Yeah.Nathan [00:28:53]: So like instruction tuning, we've covered most of this is really about like you should try to adapt your models to specific needs. It makes models that were only okay, extremely comprehensible. A lot of the times it's where you start to get things like chat templates. So if you want to do system prompts, if you want to ask your model, like act like a pirate, that's one of the ones I always do, which is always funny, but like whatever you like act like a chef, like anything, this is where those types of things that people really know in language models start to get applied. So it's good as a kind of starting point because this chat template is used in our early childhood and all of these things down the line, but it was a basic pointer. It's like, once you see this with instruction tuning, you really know it, which is like you take things like stack overflow where you have a question and an answer. You format that data really nicely. There's much more tricky things that people do, but I still think the vast majority of it is question answer. Please explain this topic to me, generate this thing for me. That hasn't changed that much this year. I think people have just gotten better at scaling up the data that they need. Yeah, this is where this talk will kind of take a whole left turn into more technical detail land. I put a slide with the RLHF objective, which I think is good for people to know. I've started going back to this more, just kind of understand what is trying to happen here and what type of math people could do. I think because of this algorithm, we've mentioned this, it's in the air, direct preference optimization, but everything kind of comes from an equation of trying to learn a policy that maximizes the reward. The reward is some learned metric. A lot can be said about what the reward should be subject to some constraint. The most popular constraint is the KL distraint, which is just a distributional distance. Essentially in language models, that means if you have a completion from your instruction or RLHF model, you can compare that completion to a base model. And looking at the log probs from the model, which are essentially how likely each token is, you can see a rough calculation of the distance between these two models, just as a scalar number. I think what that actually looks like in code, you can look at it. It'd be like a sum of log probs that you get right from the model. It'll look much more simpler than it sounds, but it is just to make the optimization kind of stay on tracks.Make sure it doesn't overfit to the RLHF data. Because we have so little data in RLHF, overfitting is really something that could happen. I think it'll fit to specific features that labelers like to see, that the model likes to generate, punctuation, weird tokens like calculator tokens. It could overfit to anything if it's in the data a lot and it happens to be in a specific format. And the KL constraint prevents that. There's not that much documented work on that, but there's a lot of people that know if you take that away, it just doesn't work at all. I think it's something that people don't focus on too much. But the objective, as I said, it's just kind of, you optimize the reward. The reward is where the human part of this comes in. We'll talk about that next. And then subject to a constraint, don't change the model too much. The real questions are, how do you implement the reward? And then how do you make the reward go up in a meaningful way? So like a preference model, the task is kind of to design a human reward. I think the equation that most of the stuff is based on right now is something called a Bradley-Terry model, which is like a pairwise preference model where you compare two completions and you say which one you like better. I'll show an interface that Anthropic uses here. And the Bradley-Terry model is really a fancy probability between two selections. And what's happening in the math is that you're looking at the probability that the chosen completion, the one you like better, is actually the better completion over the rejected completion. And what these preference models do is they assume this probability is correlated to reward. So if you just sample from this probability, it'll give you a scalar. And then you use that reward later on to signify what piece of text is better. I'm kind of inclined to breeze through the math stuff because otherwise, it's going to be not as good to listen to.Alessio [00:32:49]: I think people want to hear it. I think there's a lot of higher level explanations out there. Yeah.Nathan [00:32:55]: So the real thing is you need to assign a scalar reward of how good a response is. And that's not necessarily that easy to understand. Because if we take back to one of the first works, I mentioned this tamer thing for decision making. People tried that with language models, which is if you have a prompt in a completion and you just have someone rate it from 0 to 10, could you then train a reward model on all of these completions in 0 to 10 ratings and see if you can get chat2BT with that? And the answer is really kind of no. Like a lot of people tried that. It didn't really work. And then that's why they tried this pairwise preference thing. And it happened to work. And this Bradley Terry model comes from the 50s. It's from these fields that I was mentioning earlier. And it's wild how much this happens. I mean, this screenshot I have in the slides is from the DPO paper. I think it might be the appendix. But it's still really around in the literature of what people are doing for RLHF.Alessio [00:33:45]: Yeah.Nathan [00:33:45]: So it's a fun one to know.Swyx [00:33:46]: I'll point out one presumption that this heavily relies on. You mentioned this as part of your six presumptions that we covered earlier, which is that you can aggregate these preferences. This is not exactly true among all humans, right? I have a preference for one thing. You have a preference for a different thing. And actually coming from economics, you mentioned economics earlier. There's a theorem or a name for this called error impossibility, which I'm sure you've come across..Nathan [00:34:07]: It's one of the many kind of things we throw around in the paper.Swyx [00:34:10]: Right. Do we just ignore it?Nathan [00:34:14]: We just, yeah, just aggregate. Yeah. I think the reason this really is done on a deep level is that you're not actually trying to model any contestable preference in this. You're not trying to go into things that are controversial or anything. It's really the notion of preference is trying to stay around correctness and style rather than any meaningful notion of preference. Because otherwise these companies, they don't want to do this at all. I think that's just how it is. And it's like, if you look at what people actually do. So I have a bunch of slides on the feedback interface. And they all publish this.Swyx [00:34:43]: It's always at the appendices of every paper.Nathan [00:34:47]: There's something later on in this talk, which is like, but it's good to mention. And this is when you're doing this preference collection, you write out a very long document of instructions to people that are collecting this data. And it's like, this is the hierarchy of what we want to prioritize. Something amount like factuality, helpfulness, honestness, harmlessness. These are all different things. Every company will rank these in different ways, provide extensive examples. It's like, if you see these two answers, you should select this one and why. And all of this stuff. And then my kind of like head scratching is like, why don't we check if the models actually do these things that we tell the data annotators to collect? But I think it's because it's hard to make that attribution. And it's hard to test if a model is honest and stuff. It would just be nice to understand the kind of causal mechanisms as a researcher or like if our goals are met. But at a simple level, what it boils down to, I have a lot more images than I need. It's like you're having a conversation with an AI, something like type GPT. You get shown two responses or more in some papers, and then you have to choose which one is better. I think something you'll hear a lot in this space is something called a Likert scale. Likert is a name. It's a name for probably some research in economics, decision theory, something. But essentially, it's a type of scale where if you have integers from like one to eight, the middle numbers will represent something close to a tie. And the smallest numbers will represent one model being way better than the other. And the biggest numbers will be like the other models better. So in the case of one to eight, if you're comparing models A to B, if you return a one, if you really liked option A, you return eight if you really like B, and then like a four or five if they were close. There's other ways to collect this data. This one's become really popular. We played with it a bit at Hugging Face. It's hard to use. Filling out this preference data is really hard. You have to read like multiple paragraphs. It's not for me. Some people really like it. I hear I'm like, I can't imagine sitting there and reading AI-generated text and like having to do that for my job. But a lot of these early papers in RLHF have good examples of what was done. The one I have here is from Anthropic's collection demo because it was from slides that I did with Anthropic. But you can look up these in the various papers. It looks like Chat2BT with two responses, and then you have an option to say which one is better. It's nothing crazy. The infrastructure is almost exactly the same, but they just log which one you think is better. I think places like Scale are also really big in this where a lot of the labeler companies will help control like who's doing how many samples. You have multiple people go over the same sample once and like what happens if there's disagreement. I don't really think this disagreement data is used for anything, but it's good to know like what the distribution of prompts is, who's doing it, how many samples you have, controlling the workforce. All of this is very hard. A last thing to add is that a lot of these companies do collect optional metadata. I think the Anthropic example shows a rating of like how good was the prompt or the conversation from good to bad because things matter. Like there's kind of a quadrant of preference data in my mind, which is you're comparing a good answer to a good answer, which is like really interesting signal. And then there's kind of the option of you're comparing a bad answer to a bad answer, which is like you don't want to train your model on two different issues. This is like, we did this at Hugging Base and it was like, our data was like, we don't know if we can use this because a lot of it was just bad answer to bad answer because you're like rushing to try to do this real contract. And then there's also good answer to bad answer, which I think is probably pretty reasonable to include. You just prefer the good one and move on with your life. But those are very different scenarios. I think open AIs of the world are all in good answer, good answer, and have learned to eliminate everything else. But when people try to do this in open source, it's probably like what Open Assistance saw is like, there's just a lot of bad answers in your preference data. And you're like, what do I do with this? Metadata flags can help. I threw in the instruct GPT metadata. You can see how much they collect here. And like everything from the model fails to actually complete the task, hallucinations, different types of offensive or dangerous content, moral judgment, expresses opinion. Like, I don't know exactly if they're doing this now, but you can kind of see why doing RLHF at scale and prioritizing a lot of different endpoints would be hard because these are all things I'd be interested in if I was scaling up a big team to do RLHF and like what is going into the preference data. You do an experiment and you're like, okay, we're going to remove all the data where they said the model hallucinates like just that and then retrain everything. Like, what does that do?Swyx [00:38:59]: Yeah, so hallucination is big, but some of these other metadata categories, and I've seen this in a lot of papers, it's like, does it contain sexual content? Does it express a moral judgment? Does it denigrate a protected class? That kind of stuff, very binary. Should people try to adjust for this at the RLHF layer or should they put it as a pipeline where they have a classifier as a separate model that grades the model output?Nathan [00:39:20]: Do you mean for training or like a deployment? Deployment. I do think that people are doing it at deployment. I think we've seen safety and other things in the RLHF pipeline. Like Lama 2 is famous for kind of having this like helpfulness and safety reward models. Deep in the Gemini report is something that Gemini has like four things, which is like helpfulness, factuality, maybe safety, maybe something else. But places like Anthropic and Chattopadhyay and Bard almost surely have a classifier after, which is like, is this text good? Is this text bad? That's not that surprising, I think, because you could use like a hundred times smaller language model and do much better at filtering than RLHF. But I do think it's still so deeply intertwined with the motivation of RLHF to be for safety that some of these categories still persist. I think that's something I'll kind of settle out, I think.Swyx [00:40:11]: I'm just wondering if it's worth collecting this data for the RLHF purpose, if you're not going to use it in any way, separate model to-Nathan [00:40:18]: Yeah, I don't think OpenAI will collect all of this anymore, but I think for research perspectives, it's very insightful to know, but it's also expensive. So essentially your preference data scales with how many minutes it takes for you to do each task and every button is like, it scales pretty linearly. So it's not cheap stuff.Swyx [00:40:35]: Can we, since you mentioned expensiveness, I think you may have joined one of our spaces back in Lama 2 was released. We had an estimate from you that was something on the order of Lama 2 costs $3 to $6 million to train GPU-wise, and then it was something like $20 to $30 million in preference data. Is that something that's still in the ballpark? I don't need precise numbers.Nathan [00:40:56]: I think it's still a ballpark. I know that the 20 million was off by a factor of four because I was converting from a prompt number to a total data point. So essentially when you do this, if you have multi-turn setting, each turn will be one data point and the Lama 2 paper reports like 1.5 million data points, which could be like 400,000 prompts. So I would say it's still say like 6 to 8 million is safe to say that they're spending, if not more, they're probably also buying other types of data and or throwing out data that they don't like, but it's very comparable to compute costs. But the compute costs listed in the paper always are way lower because all they have to say is like, what does one run cost? But they're running tens or hundreds of runs. So it's like, okay, like... Yeah, it's just kind of a meaningless number. Yeah, the data number would be more interesting.Alessio [00:41:42]: What's the depreciation of this data?Nathan [00:41:46]: It depends on the method. Like some methods, people think that it's more sensitive to the, this is what I was saying. It was like, does the type of instruction tuning you do matter for RLHF? So like, depending on the method, some people are trying to figure out if you need to have like what is called like, this is very confusing. It's called like on policy data, which is like your RLHF data is from your instruction model. I really think people in open source and academics are going to figure out how to use any preference data on any model just because they're scrappy. But there's been an intuition that to do like PPO well and keep improving the model over time and do like what Meta did and what people think that OpenAI does is that you need to collect new preference data to kind of edge the distribution of capabilities forward. So there's a depreciation where like the first batch of data you collect isn't really useful for training the model when you have the fifth batch. We don't really know, but it's a good question. And I do think that if we had all the LLAMA data, we wouldn't know what to do with all of it. Like probably like 20 to 40% would be pretty useful for people, but not the whole data set. Like a lot of it's probably kind of gibberish because they had a lot of data in there.Alessio [00:42:51]: So do you think like the open source community should spend more time figuring out how to reuse the data that we have or like generate more data? I think that's one of the-Nathan [00:43:02]: I think if the people are kind of locked into using synthetic data, people also think that synthetic data is like GPT-4 is more accurate than humans at labeling preferences. So if you look at these diagrams, like humans are about 60 to 70% agreement. And we're like, that's what the models get to. And if humans are about 70% agreement or accuracy, like GPT-4 is like 80%. So it is a bit better, which is like in one way of saying it.Swyx [00:43:24]: Humans don't even agree with humans 50% of the time.Nathan [00:43:27]: Yeah, so like that's the thing. It's like the human disagreement or the lack of accuracy should be like a signal, but how do you incorporate that? It's really tricky to actually do that. I think that people just keep using GPT-4 because it's really cheap. It's one of my like go-to, like I just say this over and over again is like GPT-4 for data generation, all terms and conditions aside because we know OpenAI has this stuff is like very cheap for getting pretty good data compared to compute or salary of any engineer or anything. So it's like tell people to go crazy generating GPT-4 data if you're willing to take the organizational like cloud of should we be doing this? But I think most people have accepted that you kind of do this, especially at individuals. Like they're not gonna come after individuals. I do think more companies should think twice before doing tons of OpenAI outputs. Also just because the data contamination and what it does to your workflow is probably hard to control at scale.Swyx [00:44:21]: And we should just mention at the time of recording, we've seen the first example of OpenAI enforcing their terms of service. ByteDance was caught, reported to be training on GPT-4 data and they got their access to OpenAI revoked. So that was one example.Nathan [00:44:36]: Yeah, I don't expect OpenAI to go too crazy on this cause they're just gonna, there's gonna be so much backlash against them. And like, everyone's gonna do it anyways.Swyx [00:44:46]: And what's at stake here to spell it out is like, okay, that's like cost $10 to collect one data point from a human. It's gonna cost you like a 10th of a cent with OpenAI, right? So like it's just orders of magnitude cheaper. And therefore people-Nathan [00:44:58]: Yeah, and it's like the signal you get from humans is from preferences isn't that high. The signal that you get from humans for instructions is pretty high, but it is also very expensive. So like the human instructions are definitely like by far and away the best ones out there compared to the synthetic data. But I think like the synthetic preferences are just so much easier to get some sort of signal running with and you can work in other, I think people will start working in other goals there between safety and whatever. That's something that's taking off and we'll kind of see that. I think in 2024, at some point, people will start doing things like constitutional AI for preferences, which will be pretty interesting. I think we saw how long it took RLHF to get started in open source. Instruction tuning was like the only thing that was really happening until maybe like August, really. I think Zephyr was the first model that showed success with RLHF in the public, but that's a long time from everyone knowing that it was something that people are interested in to having any like check mark. So I accept that and think the same will happen with constitutional AI. But once people show that you can do it once, they continue to explore.Alessio [00:46:01]: Excellent.Swyx [00:46:01]: Just in the domain of human preference data suppliers, Scale.ai very happily will tell you that they supplied all that data for Lama 2. The other one is probably interesting, LMSYS from Berkeley. What they're running with Chaterina is perhaps a good store of human preference data.Nathan [00:46:17]: Yeah, they released some toxicity data. They, I think, are generally worried about releasing data because they have to process it and make sure everything is safe and they're really lightweight work. I think they're trying to release the preference data. I have, if we make it to evaluation, I'd pretty much say that Chaterina is the best limited evaluation that people have to learn how to use language models. And like, it's very valuable data. They also may share some data with people that they host models from. So like if your model is hosted there and you pay for the hosting, you can get the prompts because you're pointing the endpoint at it and that gets pinged to you and you're any real LLM inference stack saves the prompts tha

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The UN Declaration on the Rights of Indigenous Peoples is of utmost importance and should be respected, rather than being overshadowed by the interests of local communities, says Naw Ei Ei Min. The adverse effects of climate change affect Indigenous Peoples more severely than others, and thus, it is imperative to take action rather than engage in negotiations. We cannot afford to wait for more suffering before taking action. Produced by Dev Kumar Sunuwar (Sunuwar) Interviewee : Naw Ei Ei Min (Karen) "LIBRES Y VIVAS " by MARE ADVETENCIA, used with permission. "Burn your village to the ground", by The Halluci Nation, used with permission

Mary Lawlor, the founder of Front Line Defenders, is currently the UN Special Rapporteur on Human Rights Defenders. This year marked 25 years of the UN Declaration on Human Rights Defenders. Mary shares invaluable insights into the achievements for human rights defenders over the last 25 years, how the landscape has changed and evolved in terms of the protection of HRDs. She also shares her story of how Front Line Defenders came into being, and special moments she has had through her career with HRDs, as well as what it means to be a Special Rapporteur to HRDs.

Second in a four-part series of special Borderlines episodes with UC Berkeley Law guest hosts Professor Roxanna Altholz and Professor Laurel E. Fletcher shining a spotlight on human rights champions—all guest speakers in their Human Rights Practice Workshop course, where leading practitioners working in a variety of institutional settings speak about their struggles against corruption and impunity, the relationship between legal and social justice, and the future of human rights movements. Episode 18 of Borderlines features guest host Professor Roxanna Altholz, Co-Director of Berkeley Law's Clinical Program and its International Human Rights Law Clinic, in discussion with Natali Segovia, Quechua, Legal Director, Water Protector Legal Collective and international human rights lawyer with extensive experience in criminal defense work and Federal Indian Law. Ms. Segovia shares the story about the Water Protector Legal Collective, a legal nonprofit, grew out of the No Dakota Access Pipeline resistance at Standing Rock and works to provide legal support and advocacy for Indigenous peoples and climate justice movements. Listeners will be enriched by powerful first-hand accounts of struggles to stop destruction of the environment and defend the rights of Native people affected by forced displacement, desecration of sacred lands, and human rights violations. Issues covered include leveraging of the UN Declaration of the Rights of Indigenous Peoples with the US framework; SLAPP suits and the criminalization of protest; and protecting cultural and tribal sovereignty against encroachment. For a transcript, please visit the episode page on the Berkeley Law podcast hub. Hosted on Acast. See acast.com/privacy for more information.

Can the law be the same if the language is different? I invited Karen McAuliffe, an expert in multilingual law, to shed some light on this question. Different languages represent reality in different ways. This has an impact on the legal system, too. So how can law be created that will have the same effect across multiple jurisdictions? Especially in the context of the European Court of Justice this is a critical question. Language and storytelling play an important role for law – from the pricing of football jerseys to the UN Declaration of Human Rights. Karen McAuliffe is Professor of Law and Language at the University of Birmingham. Her research focuses on the relationship between law, language and translation in multilingual legal orders, particularly the European Union. She has run a number of large, funded, research projects in the field of law and language, including the Law and Language at the European Court of Justice project and The EU Case Law Corpus project. You can find out more about Karen's research on her website: www.karenmcauliffe.com Here are some links to the things mentioned in this episode: Jessica Whyte (2014) The Fortunes of Natural Man: Robinson Crusoe, Political Economy, and the Universal Declaration of Human Rights, Humanity Vol 5(3), p. 301-321   Karen McAuliffe (2013), The Limitations of a Multilingual Legal System, International Journal for the Semiotics of Law Vol 26(4)   Legal Recognition of Sign Languages Project --- Send in a voice message: https://podcasters.spotify.com/pod/show/michaela-mahlberg/message

In part two of our indigenous law episode with Jeff Nicholls, we speak about British Columbia's free entry mineral tenure regime and the corresponding impacts on the UN Declaration on the Rights of Indigenous Peoples   ✨ Read the full episode transcript HERE ✨ Learn more about the topics/cases on the Lawyered website✨ Help to declutter the law on the Lawyered crowdfunding page

If you believe in people having the opportnity to lead their best lives then you will believe in the power and importance of people - no matter who they are - having a say about how their lives are to be lived. This podcast started with a good mate of mine challenging me on my support of the Australian Voice to Parliament referendum. I say "Vote Yes" - he says "Vote No.." Have a listen and you decide for yourself..  For more resources go to my Facebook page including: The Voice -- UN Declaration on Indigenous People that Australia has committed to.. I draw your attention in particular to Articles 18 to 22.. Exactly what the Voice to Parliament is attempting to do It is the fair, the right, the reasonable, the practical thing to do.. Indigenous People live in two worlds at the same time.. The world of 60,000 years and the world of the past 200 years.. Almost no one in Parliament or the Executive understands the complexities of those two worlds.. Have a look at these Articles 18 to 22.... and make up your own mind.. The choice is yours https://www.ohchr.org/.../Declaration_indigenous_en.pdf     The keyboard discussion on the Voice.. I should be working but a good friend of mine from Melbourne is challenging my position on the Voice.. telling me it is in conflict with Articles 2 and 21 of the UN Charter.... I do appreciate him challenging me as it forces me to dig up the actual facts and data -- so I may as well share it with other 'doubting Thomases..' Without giving away identities.. these are my replies and here are some further resources to help you with your thinking and decision making.. I just read Articles 2 and 21 -- there is no such conflict -- especially Article 21 which talks about the General Assembly -- Article 21 The General Assembly shall adopt its own rules of procedure. It shall elect its President for each session. In talking of the UN -- I draw your attention to the UN Declaration on the rights of Indigenous Peoples (UNDRIP) -- 2007 -- finally endorsed by Australia which had previously abstained when under a Liberal Government.. The Declaration addresses both individual and collective rights; cultural rights and identity; rights to education, health, employment, language, and others. It outlaws discrimination against indigenous peoples and promotes their full and effective participation in all matters that concern them. https://www.ohchr.org/.../un-declaration-rights.... In particular I draw your attention to this UN Declaration -- https://www.ohchr.org/.../Declaration_indigenous_en.pdf --and in particular Article 18 --   This is what Former High Court Chief Justice Robert French said about the Voice to Parliament -- Low Risk - High Return (as reported in The Financial Review)   https://www.afr.com/.../voice-is-low-risk-but-high-return....   The Voice is a big idea but not a complicated one. It is low risk for a high return. The high return is found in the act of recognition, historical fairness and practical benefit to lawmakers, governments, the Australian people and Australia's First peoples.   French goes on to say -- It rests on the historical status of Aboriginal and Torres Strait Islanders as Australia's Indigenous people. It does not rest on race. It accords with the United Nations Declaration on the Rights of Indigenous Peoples, for which Australia voted in 2009. It is consistent with the convention against the elimination of all forms of racial discrimination. Suggestions that it would contravene that convention are wrong.   Robert French AC was chief justice of Australia from 2008-2017. Geoffrey Lindell is Emeritus Professor of Law at the University of Adelaide.   PS: French also made the point that there were loud voices against a referendum for the creation of a Federation of Australia way back in 1898 and 1900 too   PPS: my friend said ATSIC was a disaster and both sides of Parliament said to get rid of it -- here is an analysis from a Professor of Law and Indigenous Studies - https://library.bsl.org.au/.../1/200511_behrendt_atsic.pdf   ATSIC's weaknesses   ATSIC's ability to exercise its functions and meet its aims was impeded by some inherent structural problems. One of the key problems was its lack of executive authority. Under its enabling legislation, ATSIC was given the function to monitor the effectiveness of other agencies, to coordinate the development and implementation of policies and to formulate and implement program proposals. To fulfil this responsibility ATSIC needed the active cooperation and involvement of Commonwealth agencies and State and Territory governments. This in turn required an interface backed by executive authority from the Department of Prime Minister and Cabinet. This authority was never given to ATSIC and the activities of Prime Minister and Cabinet were often to the contrary to ATSIC's stated policies and intentions.   I am glad my friends challenges made me look deeper..   Only to further my resolve that people far smarter and more experienced that I say The Voice to Parliament is a great, historical, empowering move for our First Nations people who need a seat at the table so their voice can be heard on decisions that impact them. #TheVoice #voteyes  

UNDRIP -UNITED NATIONS  Declaration on the Rights of Indigenous Peoples exposed by Alex Newman.All of Sheila's content is completely, 100%, viewer supported and funded. Thank you for your kindness & generosity in keeping this ministry on air.SHEILA WEBSITE: https://sheilazilinsky.comHOW TO GIVE:https://sheilazilinsky.com/donate/Patreon: https://www.patreon.com/sheilazilinskyCash App $SheilaZilinskyVenmo® @SheilaZilinskyZelle® sheila@sheilazilinsky.comPayPal: https://www.paypal.com/paypalme/sheil...Donate by Mail:Sheila ZilinskyBox 28032Kamloops, BCCanada V2C-0C9Donate by phone:CALL 210-209-9238TELL US HOW YOU WOULD LIKE TO SUPPORT SHEILA ZILINSKY MINISTRIESFollow Sheila:Telegram: https://t.me/realsheilazTwitter: https://twitter.com/RealSheilaZFacebook: https://www.facebook.com/realSheilaZInstagram: https://www.instagram.com/sheilazilin...Listen to Sheila's Show: https://sheilazilinsky.com/listen/YouTube:https://www.youtube.com/channel/UCclqMHN8zarvZWKyDOSaP-wPODCAST: https://www.podomatic.com/podcasts/sheilazilinskyhttps://sheilazilinsky.tv (archive of shows)Rumble: https://rumble.com/user/RealSheilaZSHEILAS BOOKS: https://sheilazilinsky.com/books/

Eleanor Roosevelt is undisputedly one of America's most influential First Ladies. She used the office to promote international initiatives that stabilized global peace after the hellish destruction of World War Two, doing such things as securing the passage of the UN Declaration of Human Rights.But one thing few know is that for 10 days the First Lady went missing. In August of 1943, Eleanor was not attending to her domestic duties at the White House, in fact, she was nowhere to be found. Later, Americans would read in newspapers that Eleanor's whereabouts had been discovered—she was on the other side of the world.In an unprecedented mission which only a handful of First Ladies since have ever attempted, Eleanor's assignment was to go undercover into a battle zone and report back, firsthand, what America's servicemen and women were facing... and bring secret information back to the Oval Office. At a time when commercial air travel was unrefined (transcontinental flights took at least 20 hours and involved several fueling stops) and war was still active in the South Pacific, Eleanor faced dangers every day to complete her secret mission and boost troop morale.Today's guest is Shannon McKenna Schmidt, author of The First Lady of World War II: Eleanor Roosevelt's Daring Journey to the Frontlines and Back. She shares the largely untold story of Eleanor's top-secret mission to the Pacific theater that had ripple effects throughout the 20th century.This show is part of the Spreaker Prime Network, if you are interested in advertising on this podcast, contact us at https://www.spreaker.com/show/3101278/advertisement

Democracy and justice cannot exist without freedom of expression and freedom of the press. Today, by and large, the mainstream media is owned and controlled by socially and economically powerful people, resulting in a lack of access, voice, and participation of Indigenous Peoples. On the auspicious day of World's Press Freedom Day, Indigenous broadcasters call attention to the right of Indigenous Media, Article 16 of the UN Declaration on the Rights of Indigenous Peoples (UNDRIP). Land defenders and water protectors are often targeted by violence when there are protests against the development of dams and mines on Indigenous territories. But what is often left out are the threats to journalists covering the aggressions and reporting on grassroots events. Such violence affects them too, yet this is not brought to light as often. Speaking to Cultural Survival, Indigenous journalists around the world reiterate that Indigenous Peoples' rights are also human rights. Produced by Dev Kumar Sunuwar (Sunuwar) Interviewees: Nina Sangma (Garo) David Morales (Wayuu, Iipuana clan) Jenni Monet (Laguna Pueblo) Image: Canva (free use) "Burn your village to the ground", by The Halluci Nation, used with permission

In this Cities@Tufts presentation, we explore Real Estate for Radicals. A near consensus has developed in the US that there is a housing affordability crisis, it has done so while seemingly circumventing a debate about who deserves housing. The UN Declaration on Human Rights is quite clear on this point: housing is a human right and thus all humans deserve housing. This project, Real Estate for Radicals is case study-based research on affordable community-owned housing — co-ops, community land trusts, communes, and squats and their potential to advance housing as a human right. By studying 5 communities and their residents, this presentation will consider the extent to which these urban housing communities advance the principles of equality, liberation, and justice for the residents and the larger community. In addition to this audio, you can watch the video and read the full transcript of their conversation on Shareable.net – while you're there get caught up on past lectures. Cities@Tufts Lectures explores the impact of urban planning on our communities and the opportunities to design for greater equity and justice with professor Julian Agyeman and host Tom Llewellyn.  Cities@Tufts Lectures is produced by Tufts University and Shareable.net with support from The Kresge Foundation, Barr Foundation and SHIFT Foundation. Lectures are moderated by Professor Julian Agyeman and organized in partnership with research assistants Perri Sheinbaum and Caitlin McLennon. Robert Raymond is our audio editor, Zanetta Jones manages communications, Alison Huff manages operations, and the series is produced and hosted by Tom Llewellyn. “Light Without Dark” by Cultivate Beats is our theme song and Caitlin McLennon created this episode's graphic.

Mayan Movement for Media Rights. The host for this show is Joshua Cooper. The guests are Adriana Sunun, Amy B. Van Zyl-Chavarro, Crecencio Ramirez and Rosendo Pablo Ramirez. Mayan peoples of Guatemala demand recognition as Indigenous Peoples and respect to exercise all human rights, including the UN Declaration on the Rights of Indigenous Peoples (UNDRIP). Mayan representatives attend the United Nations Universal Periodic Review in Geneva, Switzerland to share stories of the current situation in communities and enforce decisions of the regional human rights system court decision in Costa Rica. Mayan advocates and media associates discuss the necessity for Indigenous media to freely report and inform responsibilities of the state to uphold United Nations conventions. The ThinkTech YouTube Playlist for this show is https://www.youtube.com/playlist?list=PLQpkwcNJny6lBAcTYfWa3JsYGYjCulQFi Please visit our ThinkTech website at https://thinktechhawaii.com and see our Think Tech Advisories at https://thinktechadvisories.blogspot.com.

Welcome to GLIDE Memorial Church's “Tiny Celebrations,” the mini-podcast highlighting the inspirational words and music from our Sunday Celebration.In this episode Minister of Celebration Marvin K. White shares a writing prompt, and a special prayer from the UN Declaration of Human Rights, and The Glide Ensemble and The Change Band lead our community song for the holiday season, "Angels We Have Heard On High" Please support the music, the art, and the message of GLIDE Memorial Church. Please donate today. https://www.glide.org/igive/

Mi'kmaw people in this province will be tackling some tough subjects in the coming days. They'll be asked about their experiences with racism, discrimination, and prejudice. It's part of a process to develop a National Action Plan for the implementation of he UN Declaration on the Rights of Indigenous Peoples, or UNDRIP. Ottawa passed it into law last year. Keith Cormier is working for the Assembly of First Nations on engagement sessions about UNDRIP.

A Just Transition for Indigenous Peoples is one that centers a human rights approach and the protection of biodiversity and advances Indigenous sovereignty and self-determination in all endeavors relating to the building of green economies. Doing this will require that all stakeholders observe and fully implement the UN Declaration on the Rights of Indigenous Peoples and the right to self-determination and Free, Prior, and Informed Consent in all decision-making. It will surely require a set of solutions including reinforcing and improving existing standards, reforming old mining laws and regulations, mandating circular economy practices, setting standards and meeting targets for minerals' reuse and recycling, reducing demand, and accepting de-growth as a concept and a pathway. We spoke to Pablo Mis. Producer: Shaldon Ferris (Khoisan) Interviewee: Pablo Mis(Maya Q'eqchi') Music: "LIBRES Y VIVAS by MARE ADVETENCIA, used with permission. "Burn your village to the ground", by The Halluci Nation, used with permission.

On July 18th, 2011, Mike Winther gave this lecture on Government as an Apologetic at an IPS Government and Economics Conference hosted for Christian educators of private and home schools. The conference was held in Modesto, California. Mike dives right in and talks about what an apologetic is. Most of you have probably heard of Christian apologetics, which means those in defense of Christianity's claims and truths. Since God has created every type of knowledge, every academic discipline and study should lead us to the Creator. Everything comes down to fundamentals. Mike talks about the fundamental ideas of Government and how it operates. He talks about authority and rights and where authority comes from. Mike explores all aspects of Government as an Apologetic as it applies to authority and biblical principles of truth.    You'll Learn: [01:15] In Christian circles, apologetics means in defense of something. We're making a defense for the claims and truths of Christianity. [02:12] Every academic discipline can lead you to the Creator. God has created every area of knowledge. [03:18] How can the government be an apologetic?  [05:06] It comes down to the fundamental ideas of what government is and how it operates. Were we created or did we evolve? [07:51] The debate needs to be about the same argument. [08:45] To be persuasive with people, you have to actually figure out where the issue lies on the decision tree. [09:05] One of the first forks in the road with the decision tree is creation or evolution. [10:43] One of our apologetics is the creation or evolution debate. [11:01] Authority and rights in the government. Rights are powers that individual citizens in the government have. Authority is the government's power. [13:46] The source of anything determines the use. This is a biblical principle and key concept.  [15:46] We need to know where our rights come from. We can't define a right until we know where it comes from. [21:46] If the government gave us our rights, they could also take them away. [22:22] The UN Declaration of Rights assumes that rights come from the government.  [23:28] Our constitution. If our constitution is modifiable, then can our rights be taken away? [24:47] Secure rights have to come from a non-human source. Our rights come from God. [25:58] Logic is a divine science that will lead you to the Creator. [27:52] Source of rights. Authority and rights. Principal: The Source determines the use. [28:07] If our rights come from God, our authority needs to come from God as well. Rights and authority need to come from the same source.  [30:40] Biblical guidelines: Jesus has all authority. [34:49] Deuteronomy chapter 1. Moses thought that Jethro's advice to appoint judges was good counsel. [37:26] Government systems. When teaching government you need to teach the fundamental systems of government. [37:38] There are five systems of government: 1. Monarchy rule by one. 2.  Oligarchy ruled by a few. 3. Democracy rules by majority. 4. Republic rule by law. 5. Anarchy is the absence of government authority. [39:49] Anarchy is a vacuum and would get filled with chaos and other negative things. [41:04] A monarchy's source of authority is a king or queen.  [42:05] Oligarchies are the most common form of government in the world. The committee agrees to watch each other's backs. [44:28] Democracy is majority rule. The government does what the majority says. People who control information like the educational institutions and media like the idea of majority rule. [45:50] Our founding fathers intended to create a republic which is rule by law. A republic could be the best form of government, but it depends on your laws.  [49:02] If you base your republic on laws with divine origin, then law does not come from man. [52:15] Freedom and slavery are determined by where we get our law.   Your Resources: Books to browse Five Principles By Michael Winther

A Just Transition for Indigenous Peoples is one that centers a human rights approach and the protection of biodiversity and advances Indigenous sovereignty and self-determination in all endeavors relating to the building of green economies. Doing this will require that all stakeholders observe and fully implement the UN Declaration on the Rights of Indigenous Peoples and the right to self-determination and Free, Prior and Informed Consent in all decision-making. It will surely require a set of solutions including reinforcing and improving existing standards, reforming old mining laws and regulations, mandating circular economy practices, setting standards and meeting targets for minerals' reuse and recycling, reducing demand, and accepting de-growth as a concept and a pathway. Cultural Survival spoke to Eileen Mairena Cunningham from CADPI. Producer: Shaldon Ferris (Khoisan) Interviewee: Eileen Mairena Cunningham (Miskito) Music: "LIBRES Y VIVAS by MARE ADVETENCIA, used with permission. "Burn your village to the ground", by The Halluci Nation, used with permission.

Robin celebrates with guest Victoria Tauli-Corpuz, Indigenous Activist Leader (Kankana-ey Igorot) from The Philippines, and one of the original drafters of the UN Declaration on the Rights of Indigenous Peoples, which finally passed in 2007.

The tragic death of Burnaby RCMP Cst. Shaelyn Yang Tom Stamatakis, President of the Canadian Police Association comments on the tragic death of Burnaby RCMP Cst. Shaelyn Yang Will Anjali Appadurai be disqualified from the BC NDP leadership race? Michael Gardiner, President of Strategies 360 and former Provincial Director for the BC NDP discusses whether or not Anjali Appadurai will be disqualified from the BC NDP leadership race, after the BC NDP chief electoral officer recommends Appadurai's disqualification Vancouver's terrible air quality Kyle Howe, Metro Vancouver Air Quality Analyst discusses just how bad Vancouver's smoky skies are Food prices increase despite slowed inflation rate Michael Levy, CKNW Business Analyst discusses why food prices continue to soar, despite a slowed inflation rate Vancouver's UNDRIP Strategy Khelsilem, Squamish Nation Chair discusses the provinces actions to fulfill UN Declaration on the rights of Indigenous Peoples Kevin Bieksa's one-day contract to retire in Vancouver  Al Bieksa, President of United Steelworks Local 2009 and father of Kevin Bieksa discusses the importance of his son retiring as a Vancouver Canuck Shop This City - The app that connects you with local businesses Supporting local businesses has always been an important part of creating and maintaining one's community.. But thanks to a new app, it's even easier to connect with those local businesses! Our show contributor Jawn Jang has more. Learn more about your ad choices. Visit megaphone.fm/adchoices

Khelsilem, Squamish Nation Chair discusses the provinces actions to fulfill UN Declaration on the rights of Indigenous Peoples Learn more about your ad choices. Visit megaphone.fm/adchoices

In 2010, the National Government signed the UN Declaration on the Rights of Indigenous Peoples, joining more than 140 other countries; in 2019 the Labour Government set up a working group tasked with creating a plan to realise that commitment. The result is He Puapua, a discussion document whose title refers to the break between waves and evokes the concept of a disruption to political and legislative norms. Within days, it would become a political football, with some demanding a “national conversation”. So let's talk. Is this an opportunity or a threat for the country? Working group members, writers and lawyers Claire Charters (Ngāti Whakaue, Tūwharetoa, Ngāpuhi, Tainui) and Jacinta Ruru (Raukawa, Ngāti Ranginui, Ngāti Maniapoto) discuss sovereignty, mātauranga Māori and igniting the imagination with Moana Maniapoto (Ngāti Tūwharetoa, Te Arawa). Ara Kē, Ao Kē Series curated by Moana Maniapoto. Supported by Royal Society Te Apārangi. I te tau 2010, ka waitohu te Kāwanatanga Nāhinara i Te Whakapuakitanga a te Rūnanga Whakakotahi i ngā Iwi o te Ao mō ngā Mōtika o ngā Iwi Taketake, pēnei i ētahi whenua 140 neke atu; i te tau 2019 ka whakarite te Kāwanatanga Reipa i tētahi ohu mahi, ko tāna he waihanga i tētahi mahere e tutuki ai taua oati. Ko te hua, ko He Puapua, he tuhinga matapaki, ko tōna taitara e hāngai ana ki te whatinga o te ngaru, me te aha, nāna i pupū ai he whakaaro mō te whakarerekē i ngā āhuatanga ā-tōrangapū, ā-ture anō o te wā. Mea rawa ake, ka whakamahia hei tao tōrangapū, ko ētahi hoki e auē ana mō tētahi "whakawhitinga kōrero ā-motu." Ā kāti, kia kōrero tātou. He ara whai hua rānei, he kapatau rānei tēnei mō te motu? Ko ngā mema o te ohu mahi, ko ngā ringatuhi, ko ngā rōia anō, ko Claire Charters (Ngāti Whakaue, Tūwharetoa, Ngāpuhi, Tainui) rāua ko Jacinta Ruru (Raukawa, Ngāti Ranginui, Ngāti Maniapoto) ka kōrero mō te tino rangatiratanga, mō te mātauranga Māori, mō te hika anō i te kāpura pohewa, me Moana Maniapoto (Ngāti Tūwharetoa, Te Arawa). He mea tautoko nā Te Apārangi. Ara Kē, Ao Kē - Nā Moana Maniapoto tēnei kohinga i rauhī. AUCKLAND WRITERS FESTIVAL, WAITUHI O TĀMAKI SATURDAY 27 AUGUST – 12.30-1.30PM WAITĀKERE ROOM, AOTEA CENTRE

Trigger Warning: In this episode we talk about sexual violence against Native women. If you need help or to talk to someone here are some resources you can call or chat: the StrongHearts Native Helpline at https://strongheartshelpline.org/ 1-844-7NATIVE, National Domestic Violence Hotline at https://www.thehotline.org/ 1-800-799-SAFE or the Rape, Abuse, and Incest National Network (RAINN) at https://www.rainn.org/ 1-800-656-HOPE. 1 in 2 Indigenous women have experienced sexual violence. Even with this staggeringly high statistic, it's near impossible for Indigenous women to access the care and support needed. Juskwa Burnett, Indigenous Advocate, Moccasins of Hope, talks to us about her experience working with Indigenous sexual violence survivors and the ways in which sexual violence impacts her community. In addition, Tarah Demant, Interim National Director of Programs, Advocacy, and Government Affairs with Amnesty International USA, sits down to talk to us about healthcare and judicial barriers faced by Indigenous women as it relates to sexual violence and Amensty International USA's new report detailing the barriers erected by the U.S. government when it comes to Alaska Native and American Indian women's access to healthcare and support after experiencing disproportionate rates of sexual violence.  The United States' response to this epidemic of sexual violence is confusing and maze-like, preventing Indigenous women from being able to access the healthcare they need or get justice for crimes committed. This complex system results in confusion and chaos, and further exacerbates the sexual violence epidemic faced by Indigenous women. The root of this problem is based in the US's erosion of tribal authority, allowing for these extremely unfortunate circumstances to flourish, despite the fact that this country is obligated to protect Indigenous communities under the UN Declaration of the Rights of Indigenous People. Amnesty International USA considers four sectors as related to the sexual violence epidemic experienced by Indigenous women: erosion of tribal authority, jurisdiction, healthcare and support services, and prosecution. Congress has created centuries of contradictory law regarding Indigenous peoples and Indigenous country, leading to an unnavigable system. A massive lack of resources for Indigenous tribal police limit their authority to respond to crimes. This means people's rapes and assaults are not investigated and perpetrators face no repercussions for their crimes. When Indigenous women require healthcare and services after experiencing sexual violence, many simply can't access it. Health centers are located far away from villages and reservations, and Indian Health Services (IHS) is federally underfunded to a point where it is an open question whether or not a rape kit will be available. The justice system in Indian country is also massively federally underfunded and complicated, leading to a lack of prosecution for sexual violence crimes. LinksAmnesty International USA on TwitterAmnesty International USA on FacebookThe never-ending maze: continued failure to protect indigenous women from sexual violence in the USAStrongHearts Native HelplineSupport the show

The summer of 2022 may go down in history as the moment the world woke up to the global water crisis. So I’m thrilled to introduce today’s conversation with Nigel Crawhall, who heads up the local and indigenous knowledge division at UNESCO. What I wanted to learn about is a recent upsurge in demand for indigenous perspectives and solutions in the water space. Nigel recently attended an important UN meeting on water in Tajikistan where he facilitated a first ever forum for indigenous people to have a voice in this political process to reshape how we think about and and act on water in an era of crisis.Nigel explains the nuts and bolts of how to bring indigenous perspectives into fora previously dominated by Western knowledge. We also talk about the new geopolitics of water - why high altitude actors, for example, are now influential players, the role of decolonization in closed-door meetings and everything you need to know about the latest IPBES assessments on wild species and values of nature. Nigel has a fantastic ability to convey vast amounts of knowledge through great storytelling. So if you’ve found this topic challenging in the past, our conversation will definitely open new doors.What we talked about:2.34 The paradigm shift on indigenous knowledge dates back to the 2007 UN Declaration on rights of indigenous peoples. Over time, this converged with global challenges around sustainability - the idea that we need everyone at the table, that exclusion is part of the problem so participation is part of the solution 4.13 The new normal is bringing in multiple streams of evidence including indigenous knowledge into scientufuc assessments and decision making. 6.38 For too long we have been focused on western models & urban living & missed out on the majority of human understanding & knowledge about the world.7.38 Zoom into the politics of water: why did the UN wait nearly half a century to hold a big international conference in water next March in NY? 8.41 Why is it difficult for indigenous people to be involved in water policy ? 9.28 What is the UN water action decade ? UN Decades are major areas of international policy concern -they are a global agenda setting tool. Alongside water currently there are Decades on Ocean Science & Ecosystems Restoration 10.07 one distinctive feature of the Water Action Decade has been the scant public participation - mostly a technical process. Until the Dushanbe conference opened the door. 13.00 From the Arctic to the Kalahari to the Mekong, traditional knowledge holders bring a wealth of insight on water governance. Hearing their stories helps build a bridge between the rights based and the knowledge based approach. 17.05 Why is water so political?One reason is that the state is the main arbiter of the management of water, yet thé living experience of water happens at the ground level. 18.50 high altitude countries with glacial systems have emerged as influential actors in mulltilateral negotiations on water. 20.21 Why the Dushanbe declaration is an extraordinary document, a mini Paris agreement 22.17 what to know about the latest IPBES assessments approved in Bonn? The values assessment gets to the heart of « what matters ». While many want to quantify the value of nature, others say if you put a price on it it means you intend to extract it & turn it into cash value. What the assessment does is look at what is the value of nature from different perspectives. 26.05 Should we talk about decolonization as a context for understanding north/south & east/west stressors in multilateral negotiations? The developing world sees itself as having collective interest about global justice & equity. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit thezeroist.substack.com

Receive the most important news & analysis on Israel/Palestine straight to your inbox! Sign up to our newsletter, Deep Dive Daily: https://bit.ly/3LrCUxE Twitter: @pdeepdive Instagram: @pdeepdivegram   9th October 2020: Learn more about Roger's voyage of discovery on Palestine and hear his thoughts on the most important issues of our time. Roger Waters is one of the most important musicians of our time. A founding member of legendary progressive rock band Pink Floyd, he has also had a prolific solo career since leaving the band in 1985. Roger is a revolutionary musician in every sense, as noted recently by Vijay Prashad, he is “both a person who revolutionised music, but as well, a revolutionary who happens to be a musician.” Having had a lifelong commitment to social and global justice causes, Roger has taken up all the major issues of our time, including the Palestinian cause. Roger is a leading voice in the global solidarity movement for Palestinian human rights, advocating for the civil society Boycott, Divestment & Sanctions movement.

Photo ops, public comment hearings and political appointments are NOT a  seat at the table. "Consultation" is NOT consent. The UN Declaration on the Rights of Indigenous Peoples calls for "free, prior and informed consent" on matters by the state affecting Native people; NOT just checking a box in a rigged process.

JOIN KT THE INTELLECT AND DJ THE FINESSE KID AS THEY EXAMINE THE UNITED NATION'S DECLARATION ON THE RIGHTS OF INDIGENOUS PEOPLE. THIS POPULATION MAINLY CONSISTING OF SO-CALLED BLACK, LATINO, AND NATIVE AMERICANS.

In June 2021 Vice-President Kamala Harris traveled to Guatemala and gave a now infamous speech where she told people in the Central American nation "Do not come".  With little context, explanation or recognition of United States or international law Vice-President Harris comments were seen as more of the same like almost a continuation of Trump era policies and dumbed down rhetoric.  These statements by My two guest, Luis Marco and Carolina Martin Ramos  in Episode 7 are both indigenous people and co-directors of a non-profit with national and international reach for assistance and protection fo Maya people.   On the day that Vice-President made her statement in Guatemala Luis Marcos made the following statement on social media:   "Vice-President Harris' callous words to the people of Guatemala and to the Maya Nation, first ignore that Guatemala as a State is on Maya Territory by virtue of the International Legal Construct known as the Doctrine of Discovery.  Second her words ignore US's obligations under international law as well as its moral obligation to humanity.  This includes its commitment to respect the right of the persecuted to seek asylum as refugees, and Indigenous People's pre-existing rights to migrate as recognized in article 36 of the UN Declaration on the Rights of Indigenous Peoples".   In this episode we discuss: The history of the Maya people and Luis' Mayan Guatemalan roots; Carolina's indigenous roots in Mexico and the United States; The appropriation of traditional native North and South American prints and garb in US and European fashion; The impact of VP Harris' statements in Guatemala and the irony of such statements on Maya territory; Current US immigration and asylum policy and its implications for asylum seekers and indigenous people; The doctrine of discovery and how this fueled crimes against humanity against indigenous people; The international human rights dimensions of indigenous rights; Groundbreaking legal work that Carolina and Luis are doing where the rights of indigenous people (apart from the rights under US law) are being raised in immigration court and United States courts; The important work of their organization and where you can donate or find out more about what they do. A trilingual farewell blessing in Maya, Spanish and English.   Jessica's website: https://www.attorneyjessica.com/    Follow Jessica on Social Media: LinkedIn | Instagram | Facebook | Twitter   LUIS MARCOS BIOGRAPHY Luis Marcos belongs to the Q'anjob'al Maya Nation and serves as Ambassador of the Akateko, Chuj, Popti and Q'anjob'al Maya to the Omaha Nation, Member of the Council of Authorities of the National Council of Indigenous Peoples in Diaspora, Preparatory Budy Member of the Congress of Nations and States.  Furthermore, Luis Marcos is Co-Executive Director of Comunidad Maya Pixan Ixim: Reinforcing our Roots, Living our Maya Heritage (CMPI) a 501c 3 organization of the Q'anjob'al Maya Nation in Nebraska. Luis Marcos works to dismantle the Doctrine of Discovery for the liberation of Indigenous Peoples and Humanity.   To reach Luis Marcos please email him at lmarcos@pixanixim.org.   Carolina Martin Ramos Biography Carolina Martin Ramos (Mexica Mestiza/Chicana/Kinship ties to U.S. Tribes in SE) is Co-Executive Director of Comunidad Maya Pixan Ixim (CMPI) and directs the Maya Human Rights Program and legal services at CMPI. Carolina is an immigration and human rights attorney with years of experience in nonprofit, government, and private practice. She has worked on crimmigration law as a former public defender, represented noncitizen victims of human trafficking and crimes, and asylum seekers. She has received special recognition for her work with Indigenous migrants and LGBTQ asylum seekers. Currently, Carolina focuses her work on the rights of Indigenous Peoples through pre-existing Indigenous traditional laws and governance and international human rights mechanisms while training Indigenous legal advocates to represent Indigenous migrants in immigration proceedings.  Through her work, Carolina has responded to multiple legal and humanitarian crises related to gender violence and the forced displacement of Indigenous Peoples under colonial state policies including environmental destruction through extractive projects and industries. Carolina volunteered at the Red Owl Legal Collective (aka Legal Tent) at Oceti Sakowin, Standing Rock Nation, worked with asylum seekers at the U.S. – Mexico border region during “the surge” in 2014 and subsequent events where caravans of asylum seekers faced human rights violations, family separations, and refoulement under Trump administration Zero Tolerance policies and Migrant Protection Protocols (MPP). In 2018, Carolina traveled to Maya Territory to work directly with families separated at the border and reunited parents and families with their children held in U.S. custody. Carolina's work at CMPI is inherently transnational, cross-jurisdictional, cross border, decolonizing, and anti-colonial. Through the CMPI Maya Human Rights Program, she focuses on providing immigration legal services to Maya and Indigenous migrants, policy and advocacy work in the U.S., and human rights work with Indigenous land and water protectors in Maya Territories.  You can reach Carolina through the Comunidad Maya Pixan Ixim organization at http://www.pixanixim.org and carolina@pixanixim.org.   To donate to Comunidad Maya Pixan Ixim please visit their website or email Luis or Carolina.  All donations are tax deductible as the organization is a 501(c)(3) non-profit and will be devoted to the betterment of indigenous people.