Podcasts about automating inequality

When is a cancer scare, a rejected mortgage loan, a false arrest, or predictive grading, more than a glitch in A.I.? That's today's big question, and my guest is Meredith Broussard. Meredith is a data journalist and associate professor at the Arthur L. Carter Journalism Institute of New York University, Research Director at the NYU Alliance for Public Interest Technology and the author of several books I loved, including More Than a Glitch: Confronting Race, Gender and Ability Bias in Tech, and Artificial Unintelligence: How Computers Misunderstand the World. Her academic research focuses on A.I. in investigative reporting and ethical A.I., with a particular interest in using data analysis for social good. She's a former features editor at the Philadelphia Inquirer. She's also worked as a software developer at AT&T Bell Labs and at the MIT Media Lab. Meredith's features and essays have appeared in The Atlantic, The New York Times, Slate, and other outlets. If you have ever turned on a computer or used the internet in some way to apply for something, or literally anything, this one is for you.-----------Have feedback or questions? Tweet us, or send a message to questions@importantnotimportant.comNew here? Get started with our fan favorite episodes at podcast.importantnotimportant.com.-----------INI Book Club:Chain Gang All Stars by Nana Kwame Adjei-BrenyahFind all of our guest recommendations at the INI Book Club: https://bookshop.org/lists/important-not-important-book-clubLinks:Read Meredith's books: More Than A Glitch and Artificial UnintelligenceCheck out Meredith's website and follow her on social mediaGet up to speed on A.I. ethics by reading: Weapons of Math Destruction, Algorithms of Oppression, Automating Inequality, Race After Technology, Black SoftwareFollow algorithm and bias influencers Avriel Epps and Joel BervellCheck out the Blueprint for an...

AI & The Human Alignment Problem here II We chat with Professor Richard Dazeley from Deakin University's School of Information Technology.Automating Inequality here II Virginia Eubanks' book Automating Inequality: How hi-tech tools profile, punish & police the poor is a spring board to this talk that highlights the embedded bias in AI tools.This is the Week here II Kevin Healy slices and dices the week with satire.Curbing Big Tech here II We go to the Seattle Townhall on "Digital Trade", put on by Trade Justice Education Fund, to hear from Democrat Rep. Pramila Jayapal about the fight to curb the power of big tech.

This episode features a conversation between Lane Rasberry, Wikimedia-in-Residence at the University of Virginia School of Data Science, and Virginia Eubanks, author, journalist, and associate professor of political science at the University at Albany. The conversation was recorded in 2019 but the topics are still relevant today. Eubanks looks toward the future, warning of the unintended—or at times intended—consequences of emerging technologies. The discussion focuses on the effects of algorithmic automation, as well as the practice, policies, and implementation of these algorithms. Although she critiques the tech world, Eubanks also provides many reasons for optimism.Virginia Eubanks authored the 2018 book Automating Inequality, which is a detailed investigation into data-based discrimination. She is also the author of Digital Dead End: Fighting for Social Justice in the Information Age and the co-editor, with Alethia Jones, of Ain't Gonna Let Nobody Turn Me Around: Forty Years of Movement Building with Barbara Smith. She also writes for various outlets, including the Guardian, American Scientist, and the New York Times. Recently, Virginia began the PTSD Bookclub, an ongoing project that explores books about trauma and its aftermath. You can find this project and Virginia Eubank's other projects at virginia-eubanks.com.

Iason Gabriel is a research scientist at DeepMind and was previously a lecturer in political and moral philosophy at Oxford University. His work focuses on the moral questions raised by artificial intelligence. In this conversation we discuss how and why AI is different from other technologies; the problem of value alignment in AI; what political philosophy can tell us about how to build ethical AI systems; and much more. Iason's paper on value alignment that we discuss is here. In the paper, he also recommends this paper on decolonial AI; the book Superintelligence by Nick Bostrom; and the book Automating Inequality by Virginia Eubanks.-----------------Thanks to Cofruition for consulting on and producing the show. You can learn more about Entrepreneur First at www.joinef.com and subscribe to my weekly newsletter at tib.matthewclifford.com

Diversity, Equity, and Inclusion (DEI) have been the buzz phrase in the last few years. Today, my guest addresses how this concept plays out in product development and management. Dr. Dédé Tetsubayashi, Founder & CEO of incluu, is an Ethical Technologist and Social Scientist. She synergizes her lived experience as a Black queer woman with an invisible disability with her over 20 years of experience in ethical tech, product equity & inclusion as a catalyst for creating brave spaces and products for all. Her work empowers individuals and organizations committed to investing in equitable and accessible product development and design processes, unlocking their full potential in their products, people, and practices.In our conversation, Dédé pulls back the curtain on what building products for equitable outcomes and non-discrimination means and why she founded her business, incluu. We dive into some fascinating topics such as:How straddling multiple identities played a role in shaping Dédé's future and ultimate career choices.Why relationship building and intentional curiosity are crucial in building a culture of inclusivity.How the Incluu team helps companies and their teams understand their circles of influence and why it's essential to increase those circles.Bridging the gap between technology, justice, and ethics.The biggest challenge facing leaders today is fear and functioning from a place of fear of the unknown.Why a leader needs to hold strong beliefs loosely that will enable them to have a transparent dialogue. Why do leaders need to be aware of their knowledge gaps and understand when it's time to ask for help.Dédé recommends two books that offer a deeper dive into how high tech tools profile, police, and punish the poor and reinforce the inequality in our society: Automating Inequality by Virginia Eubanks and Weapons of Math Destruction by Cathy O'Neil.Connect with Dédé at www.incluu.us and tune into her podcast Brave Spaces Roundtable to learn more about the work that Dédé and her team do.If you found the conversation helpful, subscribe to the podcast, so you don't miss any future episodes.Connect with your host, Kele:Instagram: https://www.instagram.com/thetailoredapproach/Website: https://thetailoredapproach.com 

Systems used by the government to automate social services may create injustice. Virginia talked to Kunumi about the impact of these systems on people's lives. She also focuses her work on trauma: social, physical, and mental.

In this episode: Big news from Nazareth College. We've formed the Institute for Technology, Artificial Intelligence, and Society (ITAS), a pioneering initiative in higher education to train future professionals to guide and develop technology toward equitable and just ends. Guests: Dianne Oliver, Ph.D., is co-director of the Nazareth College Institute for Technology, AI, and Society (ITAS), and since 2015 has been dean of the College of Arts & Sciences. Her background includes degrees in both computer science and in religion and ethics, deeply connecting her experience and work to this initiative at Naz. Yousuf George, Ph.D., is the other ITAS co-director and associate to the president for strategy and momentum. He joined the College in 2008 as a faculty member in the Mathematics Department and later served as the associate dean of the College of Arts and Sciences. Wendy Norris, Ph.D., is an assistant professor and founding faculty member for ITAS. Wendy's doctorate is in information science from the University of Colorado Boulder. She brings expertise in the design of humanitarian crisis response technologies to her teaching and research. She joined the Mathematics Department in 2020 to help launch Nazareth's new ethical data science major.  Chelsea Wahl, Ph.D. — another founding faculty member for ITAS — joined Nazareth's Sociology & Anthropology Department as an assistant professor of sociology in 2020. She earned her bachelor's degree in sociology from Hamilton College and her doctorate from University of Pennsylvania. She specializes in technology, inequality, work, and organizations. Student Nate Ancona ‘21 is a senior majoring in business management and a four-year member of the swim team. He is currently taking several ITAS courses that explore programming, AI, and the ethical and societal impacts of technology and is looking at graduate schools. Book mentioned in the podcast: Automating Inequality by Virginia Eubanks

Welcome to another episode of Decoding 40 in the middle of a pandemic and racial injustice. The guys check in with L.O. about to tackle another home construction project and a new book he's reading: Automating Inequality by Virginia Eubanks. Vin shares a funeral crashing story about him going to a funeral parlor to get a program just for an excuse to play hookie from work. It is more Seinfield than Seinfeld. Alaric talks about a myriad of emotions sparked from the death of Justice Ruth Bader Ginsburg and the Brianna Taylor grand jury verdict. Mack is more optimistic and believes our humanity will prevail. You'll hear all of this and more on this episode of Decoding 40. If you haven't already registered to vote, please do so by visiting www.vote.org. Don't let all those who dedicated their entire life to fighting for these rights die in vain.  The 2020 Census is more than a population count. It's an opportunity to shape your community's future. Please complete the Census for 2020.  Be sure to catch us every Monday night at 11pm EST for Decoding 40 After Dark on FB Live and YouTube. Want to be our Whiskey Warrior of the Week? Or, do you have an event or product that you would like us to attend, sample and promote? Then, please send us an email to Decoding40@gmail.com to start the discussion.

Welcome to another episode of Decoding 40 in the middle of a pandemic and racial injustice. The guys check in with L.O. about to tackle another home construction project and a new book he’s reading: Automating Inequality by Virginia Eubanks. Vin shares a funeral crashing story about him going to a funeral parlor to get a program just for an excuse to play hookie from work. It is more Seinfield than Seinfeld. Alaric talks about a myriad of emotions sparked from the death of Justice Ruth Bader Ginsburg and the Brianna Taylor grand jury verdict. Mack is more optimistic and believes our humanity will prevail. You’ll hear all of this and more on this episode of Decoding 40. If you haven't already registered to vote, please do so by visiting www.vote.org. Don't let all those who dedicated their entire life to fighting for these rights die in vain.  The 2020 Census is more than a population count. It's an opportunity to shape your community's future. Please complete the Census for 2020.  Be sure to catch us every Monday night at 11pm EST for Decoding 40 After Dark on FB Live and YouTube. Want to be our Whiskey Warrior of the Week? Or, do you have an event or product that you would like us to attend, sample and promote? Then, please send us an email to Decoding40@gmail.com to start the discussion.

Virginia Eubanks examines the relationship between technology and society in her book Automating Inequality: How High-Tech tools Profile, Police, and Punish the Poor and joins us this week for a discussion about who matters in a democracy and the empathy gap between the people who develop the technology for social systems and the people who use those systems.Eubanks is an Associate Professor of Political Science at the University at Albany, SUNY. She is also the author of Digital Dead End: Fighting for Social Justice in the Information Age; and co-editor, with Alethia Jones, of Ain't Gonna Let Nobody Turn Me Around: Forty Years of Movement Building with Barbara Smith. Her writing about technology and social justice has appeared in Scientific American, The Nation, Harper's, and Wired. She was a founding member of the Our Data Bodies Project and a 2016-2017 Fellow at New America.Additional InformationAutomating Inequality: How High-Tech tools Profile, Police, and Punish the PoorEubanks will present a lecture on her work for Penn State's Rock Ethics Institute on October 1, 2020 at 6:00 p.m. The event is free and open to anyone. Register here.Related EpisodesA roadmap to a more equitable democracyWill AI destroy democracy?Facebook is not a democracy

În episodul 125 al podcastului “Un român în Londra” am vorbit despre tirania algoritmului pentru liceeni britanici (Automating Inequality de Virginia Eubanks), covidro.info făcut de Alex Mihăileanu.   Show notes: manuelcheta.com

The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years―because a new computer system interprets any mistake as “failure to cooperate.” In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems―rather than humans―control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. In Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (St. Martin's, 2018), Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values. This deeply researched and passionate book could not be more timely. John Danaher is a lecturer the National University of Ireland, Galway. He is also the host of the wonderful podcast Philosophical Disquisitions. You can find it here on Apple Podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices

The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years―because a new computer system interprets any mistake as “failure to cooperate.” In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems―rather than humans―control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. In Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (St. Martin's, 2018), Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values. This deeply researched and passionate book could not be more timely. John Danaher is a lecturer the National University of Ireland, Galway. He is also the host of the wonderful podcast Philosophical Disquisitions. You can find it here on Apple Podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices

The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years―because a new computer system interprets any mistake as “failure to cooperate.” In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems―rather than humans―control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. In Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (St. Martin's, 2018), Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values. This deeply researched and passionate book could not be more timely. John Danaher is a lecturer the National University of Ireland, Galway. He is also the host of the wonderful podcast Philosophical Disquisitions. You can find it here on Apple Podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices

"In Automating Inequality, Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile."In April, the Penn State Rock Ethics Institute is hosting Eubanks to talk about her book Automating Inequality. Prior to that, on March 26, Brady Clemens, our district library consultant, will lead a nonfiction book club in Schlow's Sun Room to discuss the book. We chat with Brady about Automating Inequality and some of the sobering and alarming information Eubanks discovered in her research and investigation.

The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years―because a new computer system interprets any mistake as “failure to cooperate.” In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems―rather than humans―control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. In Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (St. Martin's, 2018), Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values. This deeply researched and passionate book could not be more timely. John Danaher is a lecturer the National University of Ireland, Galway. He is also the host of the wonderful podcast Philosophical Disquisitions. You can find it here on Apple Podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices

The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years―because a new computer system interprets any mistake as “failure to cooperate.” In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems―rather than humans―control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. In Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (St. Martin's, 2018), Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values. This deeply researched and passionate book could not be more timely. John Danaher is a lecturer the National University of Ireland, Galway. He is also the host of the wonderful podcast Philosophical Disquisitions. You can find it here on Apple Podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices

The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years―because a new computer system interprets any mistake as “failure to cooperate.” In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems―rather than humans―control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. In Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (St. Martin's, 2018), Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values. This deeply researched and passionate book could not be more timely. John Danaher is a lecturer the National University of Ireland, Galway. He is also the host of the wonderful podcast Philosophical Disquisitions. You can find it here on Apple Podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices

The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years―because a new computer system interprets any mistake as “failure to cooperate.” In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems―rather than humans―control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. In Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (St. Martin's, 2018), Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values. This deeply researched and passionate book could not be more timely. John Danaher is a lecturer the National University of Ireland, Galway. He is also the host of the wonderful podcast Philosophical Disquisitions. You can find it here on Apple Podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices

The State of Indiana denies one million applications for healthcare, foodstamps and cash benefits in three years―because a new computer system interprets any mistake as “failure to cooperate.” In Los Angeles, an algorithm calculates the comparative vulnerability of tens of thousands of homeless people in order to prioritize them for an inadequate pool of housing resources. In Pittsburgh, a child welfare agency uses a statistical model to try to predict which children might be future victims of abuse or neglect. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems―rather than humans―control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. In Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor (St. Martin's, 2018), Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhumane choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values. This deeply researched and passionate book could not be more timely. John Danaher is a lecturer the National University of Ireland, Galway. He is also the host of the wonderful podcast Philosophical Disquisitions. You can find it here on Apple Podcasts. Learn more about your ad choices. Visit megaphone.fm/adchoices

In Automating Inequality, Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. In this talk, Eubanks explores some of her book's heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. “This book is downright scary,” says Naomi Klein, “but with its striking research and moving, indelible portraits of life in the ‘digital poorhouse,' you will emerge smarter and more empowered to demand justice.”

Dot Citizen is back, and this week is a special Book Chat episode! We're discussing Virginia Eubank's book: Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. A book that is as much a work of searing investigative journalism as it is brilliant political analysis, Automating Inequality examines how our attempts to engineer away human biases are creating a new "digital poorhouse." Zach and Chrisella talk about the points from the book that stuck with them, the questions it raised, and the ethics of technology automation in a world of systemic inequalities. We want to hear your thoughts! Send us your feedback on Twitter or join our community on Flick Chat!

Today in part 2 of my deeply insightful interview with author Kris Shaffer, we discuss how marketers and foreign powers have been capturing our attention and even manipulating our responses. We'll discuss how these techniques were used in the 2016 US presidential election and in other critical voting situations. In many cases, it's sufficient to make people stay home or to sow doubt in the election results. But we'll also discuss whether some of these sames tools and techniques can be used to expose manipulation and tip the scales back in our favor. Kris Shaffer, PhD (Yale University, 2011), is a data scientist and Senior Computational Disinformation Analyst for Yonder. He co-authored "The Tactics and Tropes of the Internet Research Agency", a report prepared for the United States Senate Select Committee on Intelligence about Russian interference in the 2016 U.S. presidential election. Kris has consulted for multiple U.S. government agencies, non-profits, and universities on matters related to digital disinformation, data ethics, and digital pedagogy. Kris is the author of Data versus Democracy: How Big Data Algorithms Shape Opinions and Alter the Course of History, published July 2019 by Apress. Further Info Data versus Democracy: https://www.apress.com/us/book/9781484245392 Kris Shaffer’s website: https://pushpullfork.com Weapons of Math Destruction: https://weaponsofmathdestructionbook.com/ Automating Inequality: https://virginia-eubanks.com/ The Great Hack: https://www.thegreathack.com/ Give Thanks and Donate: https://firewallsdontstopdragons.com/give-thanks-donate/

Tess Posner, CEO of AI4ALL, gives an overview of the field of AI and discusses representation in AI careers, the ramifications of not having diversity in tech, the role of allies, and the future of work. AI4ALL AI4ALL Summer Programs "Decoding Diversity"- Intel study on the financial and economic returns to diversity in tech "Tech Leavers Study"- from Kapor Center for Social Impact "There is a diversity crisis in AI, but together we can fix it."- Tess Posner Algorithms of Oppression- Safiya Umoja Noble Automating Inequality- Virginia Eubanks The Gender Shades Project AOC on Automation (SxSW 2019) Opportunity@Work Open Learning Tess on Twitter See open positions at thoughtbot! Become a Sponsor of Giant Robots!

Virginia Eubanks is an associate professor of political science at UAlbany's Rockefeller College of Public Affairs & Policy. On this episode of the UAlbany News Podcast, Eubanks shares about her book, 'Automating Inequality: How High-Tech Tools Profile, Police and Punish the Poor.' In the book, she details three examples of technology failing to streamline welfare programs: • an effort to automate eligibility processes for public assistance programs in Indiana •an electronic registry of the homeless in California •a statistical model in Pennsylvania that attempts to predict child maltreatment These automated public service systems are designed to serve some of the country’s most vulnerable populations, such as those living in poverty or contending with poor health, while at the same time saving the government time and money. But these technologies can leave poor families feeling tracked, targeted and trapped. Eubanks explains how these systems fail to remove human bias, exacerbate inequality and perpetuate a "Digital Poorhouse" for working-class people in America. The UAlbany News Podcast is hosted and produced by Sarah O'Carroll, a Communications Specialist at the University at Albany, State University of New York, with production assistance by Patrick Dodson and Scott Freedman. Have a comment or question about one of our episodes? You can email us at mediarelations@albany.edu, and you can find us on Twitter @UAlbanyNews.

Venezuela Update II Joe Montero a MEAA member went with a three person delegation of local supporters of the Boliva Revolution to see for themselves what is going on in Venezuela.LNP & Labor Report Card on Social Security policy II Abigail Lewis from PerCapita goes through what the LNP and Labor are taking to the Federal Election when it comes to social security policyThis is the Week that wasAutomating Inequality follow up II We follow up last weeks rivetting speech by Virginia Eubank, author of Automating Inequality with some of the answers from the panel after her speech.

Automating Inequality II Virginia Eubank's book Automating Inequality: How hi-tech tools profile, punish & police the poor is a heart stopper. Listen and learn.So you want to be a candidate? II we speak to Jerome Small, socialist candidate in the upcoming Federal election about why and what it is like to put your hat in the ringThis is the week that wasWest Papuan flood update

Virginia Eubanks, Automating Inequality: How High-Tech Tools Profile, Police and Punish the Poor by Centre for Ethics, University of Toronto

Juhan Sonin, designer, researcher, and MIT lecturer. Juhan specialized in software design and system engineering. He has worked at Apple, National Center for Supercomputing Applications, Massachusetts Institute of Technology (MIT), and MITRE. I had the opportunity to record this episode in Juhan’s GoInvo studio office, where he is the company’s Creative Director. Website: https://www.goinvo.com/ WE MUST SET HEALTHCARE FREE: Opensourcehealthcare.org Udemy Blockchain/Healthcare Course ($125 off with HEALTHUNCHAINED coupon): https://www.udemy.com/blockchain-and-healthcare/?couponCOde=HEALTHUNCHAINED Show Notes •Software Design and System Engineering •Asynchronous telemedicine •People don’t really care about their health until we are unwell •Blockchain use case to access medical records and proxy it from anywhere with internet •Location of conception will be part of your life (health) data •Ownership and co-ownership models for health data •Data Use Agreements •Open Genome Project •You’ve put your data out on the internet and your genetic data is open-sourced. Have you had any unexpected consequences from that decision? •Health Data Standards •Open-source Standard Health Record: http://standardhealthrecord.org/ •Data exchange problems are not only business and technology issues but generally human issues •Determinants of Health •Robot doctors and the future of healthcare •Black-box healthcare algorithms should be •Open source is the only way for Medicine https://medium.com/@marcus_baw/open-source-is-the-only-way-for-medicine-9e698de0447e •Primary Care Manifesto •Patients’ interests in owning their own health •Favorite books: The Elements of Style by William Strunk Jr; Automating Inequality by Virginia Eubanks; Democracy in Chains by Nancy MacLean; The Color of Law by Richard Rothstein News Corner: https://hitinfrastructure.com/news/aetna-ascension-sign-on-to-healthcare-blockchain-alliance On Dec 3rd, two new organizations announced that they will be joining the Alliance to be part of it’s first pilot project which seeks to determine if applying blockchain technology can help ensure the most current information about healthcare providers is available in the provider directories maintained by health insurers. The two organizations are Aetna, one of the top 3 health insurance companies in the US with $60 billion in revenue in 2017 AND Ascension, the largest Catholic health system in the world and the largest non-profit health system in the US. To me this is really exciting news because Aetna recently merged with CVS Health making the combined provider directory information from these organizations huge.

Virginia Eubanks joins us for a rousing conversation about her timely and provocative book, Automating Inequality. In Automating Inequality, Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. "This book is downright scary,” says Naomi Klein, “but with its striking research and moving, indelible portraits of life in the ‘digital poorhouse,’ you will emerge smarter and more empowered to demand justice.” More info on this event here: https://cyber.harvard.edu/events/2018-10-23/automating-inequality

In this episode I talk to Virginia Eubanks. Virginia is an Associate Professor of Political Science at the University at Albany, SUNY. She is the author of several books, including Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor and Digital Dead End: Fighting for Social Justice in the Information Age. Her writing … More Episode #47 – Eubanks on Automating Inequality

 In this episode I talk to Virginia Eubanks. Virginia is an Associate Professor of Political Science at the University at Albany, SUNY. She is the author of several books, including Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor and Digital Dead End: Fighting for Social Justice in the Information Age. Her writing about technology and social justice has appeared in The American Prospect, The Nation, Harper’s and Wired. She has worked for two decades in community technology and economic justice movements. We talk about the history of poverty management in the US and how it is now being infiltrated and affected by tools for algorithmic governance. You can download the episode here or listen below. You can also subscribe to the show on iTunes or Stitcher (the RSS feed is here). Show Notes0:00 - Introduction1:39 - The future is unevenly distributed but not in the way you might think7:05 - Virginia's personal encounter with the tools for automating inequality12:33 - Automated helplessness?14:11 - The history of poverty management: denial and moralisation22:40 - Technology doesn't disrupt our ideology of poverty; it amplifies it24:16 - The problem of poverty myths: it's not just something that happens to other people28:23 - The Indiana Case Study: Automating the system for claiming benefits33:15 - The problem of automated defaults in the Indiana Case37:32 - What happened in the end?41:38 - The L.A. Case Study: A "match.com" for the homeless45:40 - The Allegheny County Case Study: Managing At-Risk Children52:46 - Doing the right things but still getting it wrong?58:44 - The need to design an automated system that addresses institutional bias1:07:45 - The problem of technological solutions in search of a problem1:10:46 - The key features of the digital poorhouse  Relevant LinksVirginia's HomepageVirginia on TwitterAutomating Inequality'A Child Abuse Prediction Model Fails Poor Families' by Virginia in WiredThe Allegheny County Family Screening Tool (official webpage - includes a critical response to Virginia's Wired article)'Can an Algorithm Tell when Kids Are in Danger?' by Dan Hurley (generally positive story about the family screening tool in the New York Times).'A Response to Allegheny County DHS' by Virginia (a response to Allegheny County's defence of the family screening tool)Episode 41 with Reuben Binns on Fairness in Algorithmic Decision-MakingEpisode 19 with Andrew Ferguson about Predictive Policing  #mc_embed_signup{background:#fff; clear:left; font:14px Helvetica,Arial,sans-serif; } /* Add your own MailChimp form style overrides in your site stylesheet or in this style block. We recommend moving this block and the preceding CSS link to the HEAD of your HTML file. */ Subscribe to the newsletter

The rise of artificial intelligence has as many anxious as it does excited, with people concerned that autonomous technologies could automate them out of a job. But as technology continues to make huge leaps forward, there's very little in the way of policy to ensure these innovations don't disrupt people's working lives and contribute to a more unequal society.Featuring:Nicholas Davis - Head of Society and Innovation, Member of the Executive Committee, World Economic Forum.Nik Dawson - PhD Student in the Faculty of Engineering and Information Technologies at the University of Technology Sydney.

The rise of artificial intelligence has as many anxious as it does excited, with people concerned that autonomous technologies could automate them out of a job. But as technology continues to make huge leaps forward, there’s very little in the way of policy to ensure these innovations don’t disrupt people's working lives and contribute to a more unequal society. Producer Cheyne Anderson teams up with Think: Sustainability's Jake Morcom to offer two perspectives on the possible impacts of growing automation. Cheyne chats to Nicholas Davis, Head of Society and Innovation at the World Economic Forum, while Jake meets with Nik Dawson, PhD student in the Faculty of Engineering and Information Technologies at the University of Technology Sydney.

Often the algorithms that shape our lives feel invisible, but every now and then you really notice them. Your credit card might get declined when you’re on vacation because a system decides the behavior seems suspicious. You might buy a quirky gift for your cousin, and then have ads for that product pop up everywhere you go online. In education, schools and colleges even use big data to nudge students to stay on track. As we create this data layer around us, there’s more and more chance for systems to misfire, or to be set up in a way that consistently disadvantages one group over another. That potential for systemic unfairness is the concern of this week’s podcast guest, Virginia Eubanks. She’s an associate professor of political science at SUNY Albany and a longtime advocate for underprivileged communities as well as an expert on tech. She’s the author of Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor, which The New York Times called “riveting” and noted that that’s an unusual accomplishment for a book about policy and tech. EdSurge connected with Eubanks this month to ask her about her explorations of technology’s unintended consequences, and about what people in education should consider as they leverage big data systems.

Virginia Eubanks, Associate Professor of Political Science at the University at Albany, SUNY, discusses her new book. Since the dawn of the digital age, decision-making in finance, employment, politics, health and human services has undergone revolutionary change. Today, automated systems—rather than humans—control which neighborhoods get policed, which families attain needed resources, and who is investigated for fraud. While we all live under this new regime of data, the most invasive and punitive systems are aimed at the poor. Automating Inequality systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile.

In this weeks episode we interviewed Virginia Eubanks and talked about her newest book, "Automating Inequality." Enjoy the enlightening discussion along with some less enlightening tech news about garlic bread and Amazon.

Virginia Eubanks systematically investigates the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. Virginia Eubanks is an associate professor of Political Science at the University at Albany, SUNY. For two decades, she has worked in community technology and economic justice movements. And she is also a founding member of the Our Data Bodies Project and a fellow at New America.

Will AI just wind up automating inequality?, a Policy Options podcast. Proponents of automation say the developments will create a more efficient and advanced society, but there are concerns that the changes will not affect all citizens equally. According to Virginia Eubanks, the automation of social and welfare services in the United States is creating a "digital poorhouse,” deepening class divides and diverting poor and working-class people from accessing public resources. Eubanks joined the podcast to discuss her new book Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. She is an associate professor of political science at the University at Albany, SUNY. Download for free. New episodes every second Tuesday. Tweet your questions and comments to @IRPP. Read the Policy Options feature series on the Ethical and Social Dimensions of AI.

CONSENT IN THE AGE OF #METOO with Sarah Barmak MATCHMAKING with Sophie Papamarko INTERSECTIONAL DATING with Claire Ah Vass is reading Automating Inequality by Virginia Eubanks Guest host Sophie is reading All the Anxious Girls on Earth by Zsuszi Gartner TUNES: Scott Pilgrim by Plumtree The Pricillas Song by Lily Frost Hard Not to Quit by Jason Bejada

Virginia Eubanks speaks about her most recent book Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. Eubanks systematically shows the impacts of data mining, policy algorithms, and predictive risk models on poor and working-class people in America. The book is full of heart-wrenching and eye-opening stories, from a woman in Indiana whose benefits are literally cut off as she lays dying to a family in Pennsylvania in daily fear of losing their daughter because they fit a certain statistical profile. The U.S. has always used its most cutting-edge science and technology to contain, investigate, discipline and punish the destitute. Like the county poorhouse and scientific charity before them, digital tracking and automated decision-making hide poverty from the middle-class public and give the nation the ethical distance it needs to make inhuman choices: which families get food and which starve, who has housing and who remains homeless, and which families are broken up by the state. In the process, they weaken democracy and betray our most cherished national values.