Cognitive architectures for artificial intelligence ethics

& (2023) Cognitive architectures for artificial intelligence ethics. AI and Society, 38(2), pp. 501-519.

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As artificial intelligence (AI) thrives and propagates through modern life, a key question to ask is how to include humans in future AI? Despite human involvement at every stage of the production process from conception and design through to implementation, modern AI is still often criticized for its “black box” characteristics. Sometimes, we do not know what really goes on inside or how and why certain conclusions are met. Future AI will face many dilemmas and ethical issues unforeseen by their creators beyond those commonly discussed (e.g., trolley problems and variants of it) and to which solutions cannot be hard-coded and are often still up for debate. Given the sensitivity of such social and ethical dilemmas and the implications of these for human society at large, when and if our AI make the “wrong” choice we need to understand how they got there in order to make corrections and prevent recurrences. This is particularly true in situations where human livelihoods are at stake (e.g., health, well-being, finance, law) or when major individual or household decisions are taken. Doing so requires opening up the “black box” of AI; especially as they act, interact, and adapt in a human world and how they interact with other AI in this world. In this article, we argue for the application of cognitive architectures for ethical AI. In particular, for their potential contributions to AI transparency, explainability, and accountability. We need to understand how our AI get to the solutions they do, and we should seek to do this on a deeper level in terms of the machine-equivalents of motivations, attitudes, values, and so on. The path to future AI is long and winding but it could arrive faster than we think. In order to harness the positive potential outcomes of AI for humans and society (and avoid the negatives), we need to understand AI more fully in the first place and we expect this will simultaneously contribute towards greater understanding of their human counterparts also.

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ID Code: 235066
Item Type: Contribution to Journal (Journal Article)
Refereed: Yes
ORCID iD:
Bickley, Steve J.orcid.org/0000-0002-9579-4231
Torgler, Bennoorcid.org/0000-0002-9809-963X
Additional Information: Funding Information: Open Access funding enabled and organized by CAUL and its Member Institutions. This research was supported by an Australian Research Training Program (RTP) Scholarship.
Measurements or Duration: 19 pages
Keywords: Artificial intelligence, Cognitive architectures, Ethical AI, Ethics, Intelligent systems, Society
DOI: 10.1007/s00146-022-01452-9
ISSN: 0951-5666
Pure ID: 115007497
Divisions: Current > Research Centres > Centre for Behavioural Economics, Society & Technology
Current > QUT Faculties and Divisions > Faculty of Business & Law
Current > Schools > School of Economics & Finance
Funding Information: Open Access funding enabled and organized by CAUL and its Member Institutions. This research was supported by an Australian Research Training Program (RTP) Scholarship.
Copyright Owner: 2022 The Author(s)
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Deposited On: 05 Sep 2022 05:53
Last Modified: 28 Mar 2024 20:29