Meet the Authors: The Equality Machine: Harnessing Digital Technology for a Brighter, More Inclusive Future
At a time when AI and digital platforms are under fire, Orly Lobel, a renowned tech policy scholar, defends technology as a powerful tool we can harness to achieve equality and a better future. Much has been written about the challenges tech presents to equality and democracy. But we can either criticize big data and automation or steer it to do better. Lobel makes a compelling argument that while we cannot stop technological development, we can direct its course according to our most fundamental values. With provocative insights in every chapter, Lobel masterfully shows that digital technology frequently has a comparative advantage over humans in detecting discrimination, correcting historical exclusions, subverting long-standing stereotypes, and addressing the world’s thorniest problems: climate, poverty, injustice, literacy, accessibility, speech, health, and safety.
Presenters
Orly Lobel is the Warren Distinguished Professor of Law at the University of San Diego and the Director of the Center for Employment and Labor Law (CELP). She is the award-winning author several books and a leading scholar in behavioral law and policy. Lobel regularly advises government and private industry on competition law and tech. A graduate of Tel-Aviv University and Harvard Law School, Lobel clerked on the Israeli Supreme Court and is a member of the American Law Institute. She is consistently ranked among the most cited legal scholars in the United States. Her books You Don’t Own Me: How Mattel v. MGA Entertainment Exposed Barbie’s Dark Side (Norton) and Talent Wants to Be Free: Why We Should Learn to Love Leaks, Raids and Free Riding (Yale University Press) have been received glowing reviews by top media including The New Yorker, the Financial Times, the Wall Street Journal, Slate, NPR and more. Her new book The Equality Machine: Harnessing Digital Technology for a Brighter, More Inclusive Future (PublicAffairs 2022) is a contrarian constructive response to debates on AI, automation, and datafication.
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