BOSTON COLLOQUIUM FOR PHILOSOPHY OF SCIENCE

DATE: DATE: Sunday, March 22nd, 2020 Monday, March 23rd, 2020 LOCATION: LOCATION: Kilachand Center Hariri Institute for Computing 610 Commonwealth Ave, 111 Cummington Mall, Room 101, Boston, MA Rooms B39 & B24, Boston, MA

OVERVIEW TALK TITLES With the increased dependence of our society and The Ethical Algorithm Michael Kearns, Computer & Information Science, economy on algorithmic processes that adapt to the U of Pennsylvania data they consume, there is mounting evidence that A Topography of Bias these processes are susceptible to producing biased Deborah Hellman, School of Law, University of Virginia results. AI bias may be introduced by system Lessons from Archives: Strategies for Collecting designers with conscious or unconscious preferences Sociocultural Data in Machine Learning or it may be simply the result of relying on data with Timnit Gebru, Ethical AI Team, Brain pre-existing biases. These biases are of particular Soft Ethics: From AI’s Ethical Principles to Practices concern when used in (AI) Luciano Floridi, Philosophy and Digital Ethics Lab, systems with decision-making capacities in contexts Oxford University of social importance. Taming the Machine: How do we Recognize and Address This two-day conference, co-organized by the BU Bias in Medical AI Ravi B. Parikh, Perelman School of Medicine, U of Penn Center for Philosophy & History of Science, the BU Hariri Institute for Computing, and the BU AI in Medicine: Uncertainty, Association and Intervention Alex John London, Philosophy, Carnegie Mellon Responsible Conduct of Research Program, will bring together computer scientists, philosophers, lawyers, Fairness and Machine Learning: Limitations and Opportunities medical doctors, and more to discuss topics ranging Moritz Hardt, Electrical Engineering & Computer Science, from the design of ethical algorithms to the UC Berkeley topography of bias, with the aim of exploring how to Technology’s Unpaid Debt: AI and the Promise of a More promote more transparent, just, and ethical AI Humane Future algorithms. Shannon Vallor, Edinburgh Futures Institute (EFI), University of Edinburgh

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