Podcast appearances and mentions of hanna wallach

Dr Blodgett is a senior researcher in the Fairness, Accountability, Transparency, and Ethics in AI (FATE) group at Microsoft Research Montréal. She's broadly interested in examining the social and ethical implications of natural language processing technologies; she developed approaches for anticipating, measuring, and mitigating harms arising from language technologies, focusing on the complexities of language and language technologies in their social contexts, and on supporting NLP practitioners in their ethical work. Dr. Blodgett has also worked on using NLP approaches to examine language variation and change (computational sociolinguistics), for example developing models to identify language variation on social media. Dr. Blodgett completed a Ph.D. in computer science at the University of Massachusetts Amherst working in the Statistical Social Language Analysis Lab under the guidance of Brendan O'Connor, where they were also supported by the NSF Graduate Research Fellowship. Dr. Blodgett received a B.A. in mathematics from Wellesley College. She interned at Microsoft Research New York in summer 2019, where she had the fortune of working with Solon Barocas, Hal Daumé III, and Hanna Wallach. Ready to explore the research we discuss on this week's episode? https://www.youtube.com/watch?v=lLlj2LZGfQc https://www.researchgate.net/publication/371924250_Taxonomizing_and_Measuring_Representational_Harms_A_Look_at_Image_Tagging ------------------------------------------------------- Join Kathleen and Tricia at CEESA's conference in Malta this March Learn more: https://www.ceesaconference.com/2024/ ---------------------------------------------------------- For a transcript of this episode head to  https://unhingedcollaboration.com/  

Powerful large-scale AI models like GPT-4 are showing dramatic improvements in reasoning, problem-solving, and language capabilities. This marks a phase change for artificial intelligence—and a signal of accelerating progress to come.In this Microsoft Research Podcast series, AI scientist and engineer Ashley Llorens hosts conversations with his collaborators and colleagues about what these models—and the models that will come next—mean for our approach to creating, understanding, and deploying AI, its applications in areas such as healthcare and education, and its potential to benefit humanity.This episode features Partner Research Manager Hanna Wallach, whose research into fairness, accountability, transparency, and ethics in AI and machine learning has helped inform the use of AI in Microsoft products and services for years. Wallach describes how she and a team of applied scientists expanded their tools for measuring fairness-related harms in AI systems to address harmful content more broadly during their involvement in the deployment of Bing Chat; her interest in filtering, a technique for mitigating harms that she describes as widely used but not often talked about; and the cross-company collaboration that brings policy, engineering, and research together to evolve and execute the Microsoft approach to developing and deploying AI responsibly.Learn more: Microsoft AI: Responsible AI Principles and Approach  AI and Microsoft Research 

The transition to remote work, while having its challenges, has also brought unexpected positive changes to the new way that we work. Now more than ever, workers from different locations around the world, who may have found it difficult to connect remotely before, are able to connect fairly throughout remote space. In this episode, host Doug Thomas speaks with Hanna Wallach, Senior Researcher at Microsoft. In addition to her work in artificial intelligence and machine learning, Hanna also leads a group of summer interns in Microsoft’s Research program. In this episode, Hanna describes the unique ways she has connected with interns through virtual social events including yoga, painting classes, and even a cocktail making lesson. Additionally, Hanna explains how the full shift to remote work has propelled a more inclusive effort in scheduling meetings, video conferencing, and even large-scale virtual conferences. Resources:Hanna Wallach – MSR Bio | LinkedInFATE: Fairness, Accountability, Transparency, and Ethics in AI See acast.com/privacy for privacy and opt-out information.

Today we’re joined by Hanna Wallach, a Principal Researcher at Microsoft Research. Hanna and I really dig into how bias and a lack of interpretability and transparency show up across machine learning. We discuss the role that human biases, even those that are inadvertent, play in tainting data, and whether deployment of “fair” ML models can actually be achieved in practice, and much more. Along the way, Hanna points us to a TON of papers and resources to further explore the topic of fairness in ML. You’ll definitely want to check out the notes page for this episode, which you’ll find at twimlai.com/talk/232. We’d like to thank Microsoft for their support and their sponsorship of this series. Microsoft is committed to ensuring the responsible development and use of AI and is empowering people around the world with intelligent technology to help solve previously intractable societal challenges spanning sustainability, accessibility and humanitarian action. Learn more at Microsoft.ai.

In episode one of season two, we celebrate the 10th anniversary of Women in Machine Learning (WiML) with its co-founder (and our guest host for this episode) Hanna Wallach of Microsoft Research. Hanna and Jenn Wortman Vaughan, who also helped to found the event, tell us how about how the 2015 event went. Lillian Lee (Cornell), Raia Hadsell (Google Deepmind), Been Kim (AI2/University of Washington), and Corinna Cortes (Google Research) gave invited talks at the 2015 event. WiML also released a directory of women in machine learning, if you’d like to listed, want to find a collaborator, or are looking for an expert to take part in an event, it’s an excellent resource. Plus, we talk with Jenn Wortman Vaughan, about the research she is doing at Microsoft Research which examines the assumptions we make about how humans actually act and using that to inform thinking about our interactions with computers.  Want to learn more about the talks at WiML 2015? Here are the slides from each speaker. Lillian LeeCorinna CortesRaia Hadsell Been Kim

This week we're looking at how powerful computers and massive data sets are changing the we study each other, scientifically and socially. We're joined by machine learning researcher Hanna Wallach, to talk about the definition of "big data," and social science research techniques that use data about individual people to model patterns in human behavior. And we'll speak to Christian Rudder, co-founder of OkCupid and author of the OkTrends blog, about his book "Dataclysm: Who We Are (When We Think No One's Looking)."

In episode four we talk with Hanna Wallach, of Microsoft Research. She's also a professor in the Department of Computer Science, University of Massachusetts Amherst and one of the founders of Women in Machine Learning (better known as WiML). We take a listener question about scalability and the size of data sets. And Ryan takes us through topic modeling using Latent Dirichlet allocation (say that five times fast).

In the first episode of Talking Machines we meet our hosts, Katherine Gorman (nerd, journalist) and Ryan Adams (nerd, Harvard computer science professor), and explore some of the interviews you'll be able to hear this season. Today we hear some short clips on big issues, we'll get technical, but today is all about introductions.We start with Kevin Murphy of Google talking about his textbook that has become a standard in the field. Then we turn to Hanna Wallach of Microsoft Research NYC and UMass Amherst and hear about the founding of WiML (Women in Machine Learning). Next we discuss academia's relationship with business with Max Welling from the University of Amsterdam, program co-chair of  the 2013 NIPS conference (Neural Information Processing Systems). Finally, we sit down with three pillars of the field Yann LeCun, Yoshua Bengio, and Geoff Hinton to hear about where the field has been and where it might be headed.