Toward an Ethics of AI Belief
- URL: http://arxiv.org/abs/2304.14577v7
- Date: Sat, 13 Apr 2024 00:12:16 GMT
- Title: Toward an Ethics of AI Belief
- Authors: Winnie Ma, Vincent Valton,
- Abstract summary: We argue that we need to pursue a novel area of philosophical research in AI - the ethics of belief for AI.
We suggest four topics in extant work in the ethics of (human) belief that can be applied to an ethics of AI belief.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- 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); morally owed beliefs (beliefs that agents are morally obligated to hold); pragmatic and moral encroachment (cases where the practical or moral features of a belief is relevant to its epistemic status, and in our case specifically to whether an agent ought to hold the belief); and moral responsibility for AI beliefs. We also indicate two relatively nascent areas of philosophical research that haven't yet been generally recognized as ethics of AI belief research, but that do fall within this field of research in virtue of investigating various moral and practical dimensions of belief: the epistemic and ethical decolonization of AI; and epistemic injustice in AI.
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