Margaret Mitchell – Keynote Speaker

Chief Ethics Scientist at Hugging Face

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Specialist Subjects

  • Forecasting the Future of AI From What We Know Today
  • Data and Intentionality in Modern AI
  • Practical AI Ethics
  • Unpacking Data Ethics in AI Systems
  • Diversity and Inclusion (The culture! The math! The glory!)
  • Multi-Task Learning for Mental Health using Social Media Text
  • Operationalizing AI Ethics at Scale
  • AI and ethics and global impact
  • Bias in Vision and Language in AI
  • Seeing AI
  • Unconscious Bias

Categories

Language

  • English

Biography

Margaret Mitchell is a researcher focused on the ins and outs of machine learning and ethics-informed AI development in tech. She has published over 50 papers on natural language generation, assistive technology, computer vision, and AI ethics, and holds multiple patents in the areas of conversation generation and sentiment classification.

Margaret Mitchell currently works at Hugging Face as Chief Ethics Scientist, driving forward work in the ML development ecosystem, ML data governance, AI evaluation, and AI ethics. She previously worked at Google AI as a Staff Research Scientist, where she founded and co-led Google’s Ethical AI group, focused on foundational AI ethics research and operationalizing AI ethics Google-internally. Before joining Google, she was a researcher at Microsoft Research, focused on computer vision-to-language generation; and was a postdoc at Johns Hopkins, focused on Bayesian modeling and information extraction.

Margaret Mitchell holds a PhD in Computer Science from the University of Aberdeen and a Master’s in computational linguistics from the University of Washington. While earning her degrees, she also worked from 2005-2012 on machine learning, neurological disorders, and assistive technology at Oregon Health and Science University. She has spearheaded a number of workshops and initiatives at the intersections of diversity, inclusion, computer science, and ethics.

Her work has received awards from Secretary of Defense Ash Carter and the American Foundation for the Blind, and has been implemented by multiple technology companies.

She likes gardening, dogs, and cats.

Popular Talks by Margaret Mitchell

Forecasting the Future of AI From What We Know Today

By examining how past priorities in AI development shaped the AI of today, we can make some predictions about how what we prioritize today will shape the AI of the future. In this talk, I will work through how AI (machine learning) systems came to be what they are now, the different biases and values at play throughout the AI development lifecycle, what these suggest for how AI will evolve, and what’s worth focusing on now to create beneficial AI in the future.

Data and Intentionality in Modern AI

Data is a fundamental component of machine learning, serving as the foundation for what ML models learn. However, relatively little attention has been paid to how ML datasets can be collected, curated, measured, stored, and shared responsibly. In this talk, I will dig into these issues, covering details on datasets and data governance, and provide some guidance on how we can use human values to shape what (and who) ML data represents.

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