[Colloquium] [CDAC] Kate Crawford - "Atlas of AI: Mapping the Politics and Ethics of How Artificial Intelligence is Made"

[Rob Mitchum]

*Kate Crawford*
*Visiting Chair of AI and Justice, École Normale Supérieure*
*Senior Principal Researcher, Microsoft Research*

*Monday, March 15th*
*5:00 p.m. - 6:00 p.m.*
*Zoom (RSVP for login
<https://www.eventbrite.com/e/cdac-distinguished-speaker-series-kate-crawford-tickets-129950857513>)
or YouTube <https://youtu.be/YhqYt7b8sFY> (no registration required)*


*Atlas of AI: Mapping the Politics and Ethics of How Artificial
Intelligence is Made*
Machine learning systems are already playing a significant role in many of
our social institutions, including healthcare, education, hiring and
criminal justice. But despite the patina of objectivity and neutrality,
many scholars have shown how these systems can reproduce and intensify
forms of structural bias and discrimination. In this talk, Dr. Kate
Crawford shares insights from her new book Atlas of AI to show the
historical origins, labor practices, infrastructures, and epistemological
assumptions that underlie the production of artificial intelligence. The
classificatory logics and predictive approaches raise challenges that
extend well beyond the current bias debate. By focusing on the role of data
in creating “ground truth”, we see the ethical and political consequences
of how AI systems are currently trained. Crawford offers new paths for
thinking through the research ethics and policy implications of the turn to
machine learning, which are increasingly urgent in a time of a pandemic and
growing inequality in the United States.

*Bio*:

Dr. Kate Crawford is a leading scholar of science, technology and society,
and the author of *Atlas of AI: Power, Politics, and the Planetary Costs of
Artificial Intelligence* (Yale, 2021). Over a 20-year career, her work has
focused on understanding large scale data systems and AI in the wider
contexts of history, politics, labor, and the environment. Kate has held
academic positions around the world, including MIT, NYU and the University
of Sydney. She is the inaugural Visiting Chair of AI and Justice at the
École Normale Supérieure, a Senior Principal Researcher at Microsoft
Research and the cofounder of the AI Now Institute at NYU. Her
collaborative projects *Anatomy of an AI System* and *Excavating AI* have
won international awards including the Ayrton Prize, and she has
contributed to policy discussions across the US, EU, UK and Australia. Her
research has been published in journals such as *Nature*, *New Media &
Society*, *Science*, *Technology & Human Values*, and her writing has
appeared in venues such as *The New York Times*, *Harpers’ Magazine*, and *The
Wall Street Journal*.


*Part of the CDAC Winter 2021 Distinguished Speaker Series:*
*Bias Correction: Solutions for Socially Responsible Data Science
<https://cdac.uchicago.edu/news/announcing-the-cdac-winter-2021-distinguished-speaker-series/>*

Security, privacy and bias in the context of machine learning are often
treated as binary issues, where an algorithm is either biased or fair,
ethical or unjust. In reality, there is a tradeoff between using technology
and opening up new privacy and security risks. Researchers are developing
innovative tools that navigate these tradeoffs by applying advances in
machine learning to societal issues without exacerbating bias or
endangering privacy and security. The CDAC Winter 2021 Distinguished
Speaker Series will host interdisciplinary researchers and thinkers
exploring methods and applications that protect user privacy, prevent
malicious use, and avoid deepening societal inequities — while diving into
the human values and decisions that underpin these approaches.


-- 
*Rob Mitchum*

*Associate Director of Communications for Data Science and Computing*
*University of Chicago*
*rmitchum at uchicago.edu <rmitchum at ci.uchicago.edu>*
*773-484-9890*
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