Exploring the Impact of Rewards on Developers' Proactive AI Accountability Behavior
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866917850373947392 |
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| author | Nguyen, L. H. Lins, S. Du, G. Sunyaev, A. |
| author_facet | Nguyen, L. H. Lins, S. Du, G. Sunyaev, A. |
| contents | The rapid integration of Artificial Intelligence (AI)-based systems offers benefits for various domains of the economy and society but simultaneously raises concerns due to emerging scandals. These scandals have led to the increasing importance of AI accountability to ensure that actors provide justification and victims receive compensation. However, AI accountability has a negative connotation due to its emphasis on penalizing sanctions, resulting in reactive approaches to emerging concerns. To counteract the prevalent negative view and offer a proactive approach to facilitate the AI accountability behavior of developers, we explore rewards as an alternative mechanism to sanctions. We develop a theoretical model grounded in Self-Determination Theory to uncover the potential impact of rewards and sanctions on AI developers. We further identify typical sanctions and bug bounties as potential reward mechanisms by surveying related research from various domains, including cybersecurity. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_18393 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Exploring the Impact of Rewards on Developers' Proactive AI Accountability Behavior Nguyen, L. H. Lins, S. Du, G. Sunyaev, A. Computers and Society The rapid integration of Artificial Intelligence (AI)-based systems offers benefits for various domains of the economy and society but simultaneously raises concerns due to emerging scandals. These scandals have led to the increasing importance of AI accountability to ensure that actors provide justification and victims receive compensation. However, AI accountability has a negative connotation due to its emphasis on penalizing sanctions, resulting in reactive approaches to emerging concerns. To counteract the prevalent negative view and offer a proactive approach to facilitate the AI accountability behavior of developers, we explore rewards as an alternative mechanism to sanctions. We develop a theoretical model grounded in Self-Determination Theory to uncover the potential impact of rewards and sanctions on AI developers. We further identify typical sanctions and bug bounties as potential reward mechanisms by surveying related research from various domains, including cybersecurity. |
| title | Exploring the Impact of Rewards on Developers' Proactive AI Accountability Behavior |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2411.18393 |