The Public Interest in Predictive Algorithms with Anne L. Washington

**Event moved to zoom only**

Join us for a talk by Anne L. Washington.

Abstract: Predictive algorithms transform daily life but will they ever serve the public interest? The ability to differentiate people through digital representations often advantages powerful interests. Algorithms that resist domination, link communities, or center the vulnerable, are more rare than algorithms that divide opinions or encourage spending. Distributing social resources, especially through algorithms, is inherently political. For a more inclusive digital society, data scientists will need to blend computational expertise and critical thinking. Illustrated with successful and cautionary tales, this talk unpacks the moral aspects of seemingly technical choices in a typical data science workflow. This talk is based on Anne’s new book Ethical Data Science (Oxford University Press, 2023) that empowers technologists to build predictive algorithms that unleash human potential.

About: Anne L. Washington, PhD is a computer scientist and an Assistant Professor of Data Policy at New York University. Through the lens of socio-technical infrastructure, her writing asks questions about the non-technical interests that influence computer science practice. She served on the ACM programming committees for EAMMO, JCDL, and FAACT and was co-chair for the 2020 ACM/AAAI AI, Ethics, and Society Conference (AIES). In addition to generous international and domestic funding, the National Science Foundation has recognized her work multiple times including a NSF CAREER award. With her team at the the Digital Interests Lab, she currently is leading research on NLP benchmarks, automated decision systems, and blockchain. She has advised the White House, the Treasury, and the United Nations in addition to testifying before Congress on the ethics of artificial intelligence in financial services. Before completing her doctorate at The George Washington University School of Business, she had extensive work experience in industry and government including the Library of Congress, Barclays Global Investors, and Apple Computers. She holds a master’s degree in library and information science from Rutgers University and an undergraduate degree in computer science from Brown University. She will be a 2024-2025 CASBS fellow at Stanford University.

To attend via zoom, please register here

Tuesday, May 21 at 3:30pm to 4:45pm

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