BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//UM ESC - ECPv6.18.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:UM ESC
X-ORIGINAL-URL:https://esc.umich.edu
X-WR-CALDESC:Events for UM ESC
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Detroit
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20250309T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20251102T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T060000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20270314T070000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20271107T060000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20261103T150000
DTEND;TZID=America/Detroit:20261103T160000
DTSTAMP:20261014T201218Z
CREATED:20261013T181246Z
LAST-MODIFIED:20261014T201218Z
UID:4081-1793718000-1793721600@esc.umich.edu
SUMMARY:Book Launch: Algorithmic Realism with Assistant Professor and Author Ben Green
DESCRIPTION:   ESC will be hosting a book launch with UMSI Professor Ben Green to talk about his new book\, Algorithmic Realism: Data Science Practices to Promote Social Justice on Tuesday\, November 3rd from 3 – 4:00 pm in the Leinweber Building’s Dow Room 4320 (or Online via Zoom). Join us to hear Prof. Green in conversation with UMSI Professor Abigail Jacobs and CSE Professor Benjamin Kuipers. Light snacks and refreshments will be provided. Please register for in-person attendance here\, or register here if you plan to attend online. This book launch is co-sponsored by The Center for Ethics\, Society\, and Computing (ESC)\, and the Michigan Institute for Data & AI in Society (MIDAS).  Book Description for Algorithmic Realism A bold new vision for data science—and a practical\, step-by-step guide for how data scientists can contribute to social justice. The field of data science faces a moral crisis. Despite the desires of data scientists to develop algorithms for good\, algorithms regularly produce injustice in practice. Given these persistent harms\, the field must reflect on difficult questions about its identity and future. Can data science be a force for promoting social justice in the world? What practices should data scientists follow to achieve this goal? In Algorithmic Realism\, Ben Green presents a bold and interdisciplinary approach to data science. Drawing on his experience practicing data science in the public interest\, he argues that improving society with algorithms requires transforming data science from a formalist methodology focused on mathematical models into a practical methodology focused on addressing real-world problems. By providing an expanded framework for the “data science workflow”—the steps that characterize the algorithm-development process—he offers a practical\, step-by-step guide describing how data scientists can apply their skills in service of social justice. Through these contributions\, the book reveals a vision for a renewed\, but realistic\, optimism about data science’s potential to foster a more equitable world. Author Bio Ben Green is an Assistant Professor of Information and Public Policy at the University of Michigan and a Faculty Associate at the Berkman Klein Center for Internet & Society at Harvard. Through his research\, writing\, and advocacy\, Ben contributes practical lessons for achieving a world in which AI improves society rather than exacerbating inequality and oppression. He has published op-eds in outlets including The New York Times\, The Wall Street Journal\, and The Hill\, and has been quoted in newspapers such as The New York Times\, The Washington Post\, and the Los Angeles Times. He is the author of two books from the MIT Press: Algorithmic Realism: Data Science Practices to Promote Social Justice (2026) and The Smart Enough City: Putting Technology in Its Place to Reclaim Our Urban Future (2019).
URL:https://esc.umich.edu/event/book-launch-algorithmic-realism-with-assistant-professor-and-author-ben-green/
LOCATION:Leinweber Building\, Dow Room 4320\, 2200 Hayward Street\, Ann Arbor\, MI\, 48109\, United States
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20261109T160000
DTEND;TZID=America/Detroit:20261109T190000
DTSTAMP:20260828T171944Z
CREATED:20260828T152831Z
LAST-MODIFIED:20260828T171944Z
UID:3999-1794240000-1794250800@esc.umich.edu
SUMMARY:Book Launch Event | Auditing AI
DESCRIPTION:Celebrate the book launch of Auditing AI with authors Christian Sandvig\, Ellery Biddle\, and Danae Metaxa! Stay tuned for more details! Time: Nov. 9\, 4 pm – 5 pm (book launch)\, 5 pm -7 pm (mixer) Location: Cahoots Event Space (206 E Huron St)   About the book: How tech companies\, journalists\, and policymakers can prevent AI decision-making from going wrong. Our lives are increasingly governed by automated systems influencing everything from medical care to policing to employment opportunities\, but researchers and investigative journalists have proven that AI systems regularly get things wrong. Auditing AI is a first-of-its-kind exploration of why and how to audit artificial intelligence systems. It offers a simple roadmap for using AI audits to make product and policy changes that benefit companies and the public alike. The book aims to convince readers that AI systems should be subject to robust audits to protect all of us from the dangers of these systems. Readers will come away with an understanding of what an AI audit is\, why AI audits are important\, key components of an audit that follows best practices\, how to interpret an audit\, and the available choices to act on an audit’s results. The book is organized around canonical examples: from AI-powered drones mistakenly targeting civilians in conflict areas to false arrests triggered by facial recognition systems that misidentified people with dark skin tones to HR hiring software that prefers men. It explains these definitive cases of AI decision-making gone wrong and then highlights specific audits that have led to concrete changes in government policy and corporate practice.
URL:https://esc.umich.edu/event/book-launch-event-auditing-ai/
LOCATION:MI
END:VEVENT
END:VCALENDAR