人工智能与责任:没有差距,只有丰富

IF 0.7 2区 哲学 Q4 ETHICS Journal of Applied Philosophy Pub Date : 2024-09-13 DOI:10.1111/japp.12765
Maximilian Kiener
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引用次数: 0

摘要

表现最好的人工智能系统,如深度神经网络,往往是最难以控制和理解的系统。为此,学者们担心人工智能的使用会导致所谓的责任缺口,即没有人对人工智能造成的伤害负道德责任,因为没有人满足道德责任的所谓控制条件和认识论条件。在本文中,我承认围绕责任与人工智能存在着巨大的挑战。然而,我并不认为用责任鸿沟来概括这一挑战是最合适的。相反,我主张相反的观点,即存在责任丰裕的情况,即众多代理人对人工智能造成的伤害负有责任,而挑战来自于在实践中处理这种丰裕情况的困难。最后,我认为以这种方式重构挑战具有独特的辩证法和理论优势,有望帮助克服当前围绕 "责任差距 "的辩论中的一些障碍。
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AI and Responsibility: No Gap, but Abundance
The best‐performing AI systems, such as deep neural networks, tend to be the ones that are most difficult to control and understand. For this reason, scholars worry that the use of AI would lead to so‐called responsibility gaps, that is, situations in which no one is morally responsible for the harm caused by AI, because no one satisfies the so‐called control condition and epistemic condition of moral responsibility. In this article, I acknowledge that there is a significant challenge around responsibility and AI. Yet I don't think that this challenge is best captured in terms of a responsibility gap. Instead, I argue for the opposite view, namely that there is responsibility abundance, that is, a situation in which numerous agents are responsible for the harm caused by AI, and that the challenge comes from the difficulties of dealing with such abundance in practice. I conclude by arguing that reframing the challenge in this way offers distinct dialectic and theoretical advantages, promising to help overcome some obstacles in the current debate surrounding ‘responsibility gaps’.
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来源期刊
CiteScore
2.20
自引率
0.00%
发文量
71
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