Risks Deriving from the Agential Profiles of Modern AI Systems

In Vincent C. Müller, Leonard Dung, Guido Löhr & Aliya Rumana, Philosophy of Artificial Intelligence: The State of the Art. Berlin: SpringerNature (forthcoming)
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Abstract

Modern AI systems based on deep learning are neither traditional tools nor full-blown agents. Rather, they are characterised by idiosyncratic agential profiles, i.e., combinations of agency-relevant properties. Modern AI systems lack superficial features which enable people to recognise agents but possess sophisticated information processing capabilities which can undermine human goals. I argue that systems fitting this description, when they are adversarial with respect to human users, pose particular risks to those users. To explicate my argument, I provide conditions under which agential profiles are explanatorily relevant to harms caused. I then contend that the role of recommender systems in producing harmful outcomes like digital addiction satisfies these conditions.

Author's Profile

Barnaby Crook
Universität Bayreuth

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