Cognitive Mimetics for AI Ethics: Tacit Knowledge, Action Ontologies and Problem Restructuring

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Abstract

Ethics and ethical information processing are an important problem for AI development. It is important for self-evident reasons, but also challenging in its’ implications and should be welcomed by designers and developers as an interesting technical challenge. This article explores AI ethics as a design problem and lays out how cognitive mimetics could be used a method for its design. AI ethics is conceptualized as a problem of implementation on the one hand, and as a problem of ethical contents on the other. From the viewpoint of human information processing, ethics becomes a special case of ethical information processing - one that has deep implications in terms of AI abilities and information contents. Here we focus on ethical information processing as a property of the system (rather as a general constraint on it). We explore three specific concepts relevant for cognitive mimetics from the perspective of ethics: tacit knowledge, ontologies, and problem restructuring. We close with a general discussion on the difference between abilities and mental contents noted as relevant in previous articles on cognitive mimetics and reiterate its importance in this context as well.

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APA

Karvonen, A. (2020). Cognitive Mimetics for AI Ethics: Tacit Knowledge, Action Ontologies and Problem Restructuring. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12215 LNCS, pp. 95–104). Springer. https://doi.org/10.1007/978-3-030-50267-6_8

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