Toward an Ethics of AI Belief
Winnie Ma, Vincent Valton

TL;DR
This paper explores the emerging field of AI ethics of belief, examining what artificial agents ought to believe and the moral implications of their beliefs, integrating epistemology and ethics.
Contribution
It introduces a novel philosophical framework for AI belief ethics, applying concepts from human belief ethics to artificial agents and highlighting new research areas.
Findings
Identifies four key topics in AI belief ethics: doxastic wronging, morally owed beliefs, encroachment, and responsibility.
Proposes two nascent research areas: epistemic and ethical decolonization, and epistemic injustice in AI.
Abstract
In this paper we, an epistemologist and a machine learning scientist, argue that we need to pursue a novel area of philosophical research in AI - the ethics of belief for AI. Here we take the ethics of belief to refer to a field at the intersection of epistemology and ethics concerned with possible moral, practical, and other non-truth-related dimensions of belief. In this paper we will primarily be concerned with the normative question within the ethics of belief regarding what agents - both human and artificial - ought to believe, rather than with questions concerning whether beliefs meet certain evaluative standards such as being true, being justified, constituting knowledge, etc. We suggest four topics in extant work in the ethics of (human) belief that can be applied to an ethics of AI belief: doxastic wronging by AI (morally wronging someone in virtue of beliefs held about them);…
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Taxonomy
TopicsPsychology of Moral and Emotional Judgment · Ethics and Social Impacts of AI · Adversarial Robustness in Machine Learning
