Explanation and justification in AI | Absolutely Interdisciplinary 2022 скачать в хорошем качестве

Explanation and justification in AI | Absolutely Interdisciplinary 2022

Modern machine learning systems are often large and complex, making it difficult to understand why they do what they do. This “black box” problem raises challenges when AI systems are used to make or contribute to important decisions such as what medical treatments to adopt, whether to grant bail to someone pending criminal trial, or how to distribute public benefits. The call for AI to be “explainable” has thus been mounting for several years and a “right to explanation” is beginning to appear in proposed legislation governing AI. This call has spurred computer scientists to develop methods to provide accounts of what factors produce or influence an AI decision. But are such accounts the only kinds of explanations we need if AI is to play a significant role in our societies? Do we need explanation, or do we need justification? We look for justification from decision makers such as judges and regulators—an account of the reasons that show that a decision is consistent with governing rules and principles. What insights might we gain about how to build trustworthy and accountable systems from what we know about justification in legal and regulatory domains? Explanation and justification in AI | Absolutely Interdisciplinary 2022 Moderator: Philippe-André Rodriguez Speakers: Boris Babic, Finale Doshi-Velez Boris Babic is an assistant professor in the Department of Statistics and the Department of Philosophy at the University of Toronto, a faculty affiliate at the Schwartz Reisman Institute, and a visiting professor in the Decision Sciences department at INSEAD. Babic’s research interests are in Bayesian inference and decision-making, and normative questions in the implementation of artificial intelligence and machine learning. Babic received a PhD in philosophy and MS in statistics from the University of Michigan, and a JD from Harvard Law School. Finale Doshi-Velez is a Gordon McKay Professor in Computer Science at the Harvard Paulson School of Engineering and Applied Sciences. Doshi-Velez completed her MSc from the University of Cambridge as a Marshall Scholar, her PhD from MIT, and her postdoc at Harvard Medical School. Her interests lie at the intersection of machine learning, healthcare, and interpretability. She has published and lectured widely, is a co-founder, organizer, and past president of the Machine Learning for Healthcare Conference, and a recipient of an NSF Career Award and Sloan Fellowship. Philippe-André Rodriguez is the deputy director of the Center for International Digital Policy at Global Affairs Canada, and a professor of practice at McMaster University. Among other current responsibilities, he acts as the head of the Canadian Delegation on processes related to the global governance of digital technologies at UNESCO, the Council of Europe, and engagement at the UN Secretary General Roadmap for Digital Cooperation and the Freedom Online Coalition. Rodriguez previously served as senior advisor at Canada’s Privy Council Office on issues related to the governance of digital technology, artificial intelligence, and online platforms. Prior to joining the Canadian government, he was a Fellow at Yale Law School, and completed a DPhil at the University of Oxford as a Rhodes Scholar. His research has been published in Cambridge Review of International Affairs, European Review of History, and Human Rights Review, among others. https://absolutelyinterdisciplinary.com/ The Schwartz Reisman Institute for Technology and Society is a research institute at the University of Toronto that explores the ethical and societal implications of technology. Our mission is to deepen knowledge of technologies, societies, and humanity by integrating research across traditional boundaries to build human-centred solutions. Our research community seeks to rethink technology’s role in society, the needs of human communities, and the systems that govern them. We are investigating how best to align technology with human values and deploy it accordingly. Across all our activities, SRI convenes world-class expertise and diverse perspectives from universities, government, industry, and beyond to develop new modes of thinking about powerful technologies and their role in what it means to be human in the 21st century. We are defining what’s possible, determining what’s at stake, and devising implementable solutions to make sure technologies like AI are effective, safe, fair, and beneficial—for everyone. https://srinstitute.utoronto.ca/