Advances in artificial intelligence have raised the possibility that important areas of scientific research, including experiment design and theory creation, might be automated. One prominent example with potentially widespread societal implications is efforts to automate drug discovery. The possibility of automated science seems to hold the promise of rapid acceleration of scientific progress, especially since the past few decades have revealed complexities in many scientific subjects that are difficult for human scientists to grasp. It also raises many concerns. Is automated science capable of thinking outside the box created by its learning process? Does automation limit scientific possibilities compared to human efforts? What will be the future role(s) of human scientists? What are the possible consequences of incomplete human understanding of scientific results, with significant potential consequences for the distribution of responsibility? In this forum, a distinguished panel of experts from philosophy and science will discuss these and other issues.
Panelists:
Professor Robert F. Murphy
Ray and Stephanie Lane Emeritus Professor of Computational Biology, Carnegie Mellon University
Professor Alex John London
Clara L. West Professor of Ethics & Philosophy and Director of the Center for Ethics and Policy, Carnegie Mellon University
Dr. Atoosa Kasirzadeh
Chancellor's Fellow in Philosophy and the Futures Institute, University of Edinburgh
Moderators:
Professor David Danks
Professor of Data Science & Philosophy, University of California San Diego
Professor John Dupré
Professor of Philosophy and Director of Egenis, The Centre for the Study of Life Sciences, University of Exeter
Advances in artificial intelligence have raised the possibility that important areas of scientific research, including experiment design and theory creation, might be automated. One prominent example with potentially widespread societal implications is efforts to automate drug discovery. The possibility of automated science seems to hold the promise of rapid acceleration of scientific progress, especially since the past few decades have revealed complexities in many scientific subjects that are difficult for human scientists to grasp. It also raises many concerns. Is automated science capable of thinking outside the box created by its learning process? Does automation limit scientific possibilities compared to human efforts? What will be the future role(s) of human scientists? What are the possible consequences of incomplete human understanding of scientific results, with significant potential consequences for the distribution of responsibility? In this forum, a distinguished panel of experts from philosophy and science will discuss these and other issues.
Panelists:Professor Robert F. MurphyRay and Stephanie Lane Emeritus Professor of Computational Biology, Carnegie Mellon University
Professor Alex John LondonClara L. West Professor of Ethics & Philosophy and Director of the Center for Ethics and Policy, Carnegie Mellon University
Dr. Atoosa KasirzadehChancellor's Fellow in Philosophy and the Futures Institute, University of Edinburgh
Moderators:
Professor David DanksProfessor of Data Science & Philosophy, University of California San Diego
Professor John DupréProfessor of Philosophy and Director of Egenis, The Centre for the Study of Life Sciences, University of Exeter
Kings 5 PSA 2022 office@philsci.orgTechnical Issues?
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