The Race + Data Science Lecture Series aims to celebrate and advance research in the areas of race and data, engineering, and computational science. With this series of events, our goal is to improve how we as data scientists and data-adjacent researchers speak about race.
Thursday, September 16, 2021 (9:00 AM – 10:00 AM ET) – Virtual
Chair & Moderator
Desmond Upton Patton, Associate Director of Diversity, Equity and Inclusion, The Data Science Institute, Columbia University. Patton is also Associate Professor of Social Work; Associate Dean of Curriculum Innovation and Academic Affairs; and Courtesy Appointment in Department of Sociology, Columbia University School of Social Work.
Abstract & Biography
Sociotechnical Foresight: The value of critical (data) science in shaping emerging technologies
Abstract: Emerging technologies, such as artificial intelligence (AI), are increasingly portrayed as poised to reshape modern society and achieve far-reaching positive change. Yet many of the initial instances of AI real-world systems deployed into society pose significant societal risks, with particularly acute harms to historically marginalized peoples. In response, various stakeholders have sought to propose ethical guidelines and technical mitigations to serve as ethical guardrails for future technology deployment and development.
In this talk, I propose that for ethical frameworks to be effective in re-aligning technology, historical perspectives and their influence on values and power dynamics must be taken into account. Using examples of AI in high-stakes domains such as healthcare and criminal justice, I will discuss how critical evaluations blending insight from data science and STS can lead to dynamic and robust ethical “foresight” to mitigate potential societal harms. I will conclude with a discussion of potential challenges to using foresight in practice and open questions for future research.
Bio: William Isaac is a Staff Research Scientist on DeepMind’s Ethics and Society Team and Research Affiliate at Oxford University Centre for the Governance of AI. My research focuses on the societal impact and governance of AI systems.
Prior to DeepMind, William served as an Open Society Foundations Fellow and Research Advisor for the Human Rights Data Analysis Group. My research has been featured in publications such as Science, New York Times, and the Wall Street Journal.
The Race + Data Science Lecture Series is supported by funding from the MacArthur Foundation and New America.
