What does it mean to be an agent?
What does it mean to be an agent?
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DOI：
10.3389/fpsyg.2023.1273470
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发表时间：
2023
影响因子：
3.8
通讯作者：
Naidoo, Meshandren
中科院分区：
文献类型：
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作者：
Naidoo, Meshandren
人工智能（AI）带来了许多法律伦理挑战。这些挑战在处理人工智能时尤为严重，人工智能表现出巨大的计算能力，然后与代理或自主权相关。考虑这个问题的一个常见反应是询问人工智能系统是否“有意识”。如果是，那么它可以构成一个代理人，演员或人。然而，这种框架是无益的，因为关于意识还有许多未解决的问题。相反，提出了一种实用的方法，可以用来更好地监管新的人工智能技术。在这项研究中，实用方法的价值在于：（1）提供了一个包含预测价值的经验可观察、可测试的框架;（2）来自使用语义信息作为标记的数据科学框架;（3）依赖于对代理至关重要的自我参考逻辑;（4）实现AI系统的“分级”或“排名”，这提供了一种替代方法（与当前的风险分层方法相反）和措施来确定AI系统在特定领域（例如，例如社交领域或情感领域）;（5）与其他方法相比，呈现一致，连贯和更高的信息内容;（6）符合信息内容“法律”包含和维护的概念;（7）提出了一种可行的方法来获得“代理”，“代理”和“人格”，这对人工智能技术和社会的当前和未来发展是强大的。
Artificial intelligence (AI) has posed numerous legal–ethical challenges. These challenges are particularly acute when dealing with AI demonstrating substantial computational prowess, which is then correlated with agency or autonomy. A common response to considering this issue is to inquire whether an AI system is “conscious” or not. If it is, then it could constitute an agent, actor, or person. This framing is, however, unhelpful since there are many unresolved questions about consciousness. Instead, a practical approach is proposed, which could be used to better regulate new AI technologies. The value of the practical approach in this study is that it (1) provides an empirically observable, testable framework that contains predictive value; (2) is derived from a data-science framework that uses semantic information as a marker; (3) relies on a self-referential logic which is fundamental to agency; (4) enables the “grading” or “ranking” of AI systems, which provides an alternative method (as opposed to current risk-tiering approaches) and measure to determine the suitability of an AI system within a specific domain (e.g., such as social domains or emotional domains); (5) presents consistent, coherent, and higher informational content as opposed to other approaches; (6) fits within the conception of what informational content “laws” are to contain and maintain; and (7) presents a viable methodology to obtain “agency”, “agent”, and “personhood”, which is robust to current and future developments in AI technologies and society.