Zhao, J ORCID: https://orcid.org/0000-0001-6430-2356, 2022. Artificial intelligence and corporate decisions: fantasy, reality or destiny. Catholic University Law Review, 71 (4): 6. ISSN 0008-8390
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Abstract
Fueled by the ever-growing significance of big data and advances in AI, tasks in relation to decision-making in contemporary societies have been increasingly delegated to AI at different levels. While there is massive investment all over the world related to one side of AI, namely engineering, it is also important to create rules and competence related to humanistic AI and its effects on people and societies. This article aims to examine AI’s role in the boardroom and associated legal challenges, by exploring the interplay between AI and corporate law and governance. We observe that the delegation of board tasks to AI may tackle situations where urgent decisions need to be made on the basis of a large quantity of data. AI will also ease the tension between plausible hypotheses for the formal analysis of business judgments and a lack of capability to understand and subsequently choose among the options available to directors. As a powerful tool to radicalize and change decision makers’ habits and rationales, AI can assist or advise directors in using big data more effectively and efficiently for more informed and higher-quality decisions, which will result in higher perceived legitimacy. Therefore, we propose the imposition of a duty to use AI to suggest options and disclose the responses of the board to these suggestions, in order to satisfy the standard of care for rational decision making by prudent and diligent directors, and to promote the fair, accountable, and transparent application of AI in the boardroom.
Item Type: | Journal article |
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Publication Title: | Catholic University Law Review |
Creators: | Zhao, J. |
Date: | 2 December 2022 |
Volume: | 71 |
Number: | 4 |
ISSN: | 0008-8390 |
Identifiers: | Number Type 1441151 Other |
Divisions: | Schools > Nottingham Law School |
Record created by: | Laura Ward |
Date Added: | 25 May 2021 14:40 |
Last Modified: | 15 May 2024 08:09 |
URI: | https://irep.ntu.ac.uk/id/eprint/42914 |
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