As generative AI becomes more thoroughly integrated into many human activities, we may face a systematic credit-blame asymmetry: We may not deserve full credit or praise for the valuable outputs we create with generative AI (i.e., if we do not put in sufficient skill or effort), but we may be entirely blameworthy for harmful outputs (e.g., due to negligence or recklessness). How might patterns of praise and blame change, however, if we use personalised AI that is trained on our own past outputs, created solely by us? In this talk I present recent theory and evidence on this question with data from the US, UK, China, and Singapore.
Brian D. Earp, PhD, is a philosopher, cognitive scientist, and bioethicist based at the University of Oxford. Brian is the Associate Director of the Yale-Hastings Program in Ethics and Health Policy at Yale University and The Hastings Center, Senior Research Fellow in Moral Psychology in the Uehiro Centre for Practical Ethics at the University of Oxford, and Co-Director of the Oxford Experimental Bioethics Lab.
We will run each seminar in a hybrid format, allowing many guests to attend in person and everyone else online.
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