Tisch University Professor of Computer Science, Cornell University
Panel: Bias in AI
Jon Kleinberg is working towards a careful analysis of how computer scientists—as researchers, pedagogues, and professionals—can contribute to a just and equitable future for computation. Kleinberg has identified ways that computer science might contribute to social change, looking concretely at how algorithms can be biased; how researchers can learn to analyse those algorithms in a manner that is attuned to social processes, and how students can shape their careers in ways that are ethically attuned to the consequences of choices they make as designers and engineers. “Bias in AI” grounds its discussion of the science and engineering of AI in his expertise.
Biography: Cornell University
Jon Kleinberg. Credit: Lindsay France/Cornell University.
2021, Cornell University
Computing requires difficult choices that can have serious implications for real people. This course covers a range of ethical, societal, and policy implications of computing and information, drawing on recent developments in digital technology and their impact on society, situating these in the context of fundamental principles from computing, policy, ethics, and the social sciences.
A recent normative turn in computer science has brought concerns about fairness, bias, and accountability to the core of the field. Yet recent scholarship has warned that much of this technical work treats problematic features of the status quo as fixed, and fails to address deeper patterns of injustice and inequality. While acknowledging these critiques, the authors posit that computational research has valuable roles to play in addressing social problems—roles whose value can be recognized even from a perspective that aspires toward fundamental social change.
2010, Cambridge University Press
In recent years there has been a growing public fascination with the complex “connectedness” of modern society. This connectedness is found in many incarnations: in the rapid growth of the Internet and the Web, in the ease with which global communication now takes place, and in the ability of news and information as well as epidemics and financial crises to spread around the world with surprising speed and intensity. These are phenomena that involve networks, incentives, and the aggregate behavior of groups of people; they are based on the links that connect us and the ways in which each of our decisions can have subtle consequences for the outcomes of everyone else.