需要开展有关人类与人工智能关系规范的实证研究计划

Madeline G. Reinecke, Andreas Kappes, Sebastian Porsdam Mann, Julian Savulescu, Brian D. Earp
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摘要

随着人工智能(AI)系统开始承担传统上由人类承担的社会角色,了解这如何影响人们的合作期望将是至关重要的。在人与人二人组的情况下,不同的关系受不同的规范支配:例如,面对类似的协调问题时,两个陌生人(而不是两个朋友或同事)应该如何互动,往往是不同的。“社交”人工智能(以及最终的超级智能人工智能)的兴起将如何使人们对应该管理不同类型关系(无论是人与人还是人与人工智能)的合作规范的期望复杂化?在给定的社会角色中,人们是否期望人工智能与人类一样坚持相同的合作动力?相反,他们会开始期望人类在某些类型的关系中表现得更像人工智能吗?在这里,我们考虑了人们的合作期望如何在人与人之间和人与人工智能之间的关系中分离,详细介绍了在关系类型中映射这些差异的经验建议。我们认为,从我们的提议中得出的数据与理解人们在社交人工智能时代对特定关系的合作期望有关,这也可能预测人工智能系统占据某些社会角色的潜在阻力。最后,这些数据可以构成道德评估的基础:我们应该为人类与人工智能的互动采用什么样的特定关系的合作规范,或者通过负责任的人工智能设计来加强这种合作规范,这在一定程度上取决于人们认为这种互动的直觉规范(以及维持这些规范的成本和收益)。在论文的最后,我们讨论了这些关系规范如何随着时间的推移而变化,并考虑了这对拟议的研究计划的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The need for an empirical research program regarding human–AI relational norms

As artificial intelligence (AI) systems begin to take on social roles traditionally filled by humans, it will be crucial to understand how this affects people’s cooperative expectations. In the case of human–human dyads, different relationships are governed by different norms: For example, how two strangers—versus two friends or colleagues—should interact when faced with a similar coordination problem often differs. How will the rise of ‘social’ artificial intelligence (and ultimately, superintelligent AI) complicate people’s expectations about the cooperative norms that should govern different types of relationships, whether human–human or human–AI? Do people expect AI to adhere to the same cooperative dynamics as humans when in a given social role? Conversely, will they begin to expect humans in certain types of relationships to act more like AI? Here, we consider how people’s cooperative expectations may pull apart between human–human and human–AI relationships, detailing an empirical proposal for mapping these distinctions across relationship types. We see the data resulting from our proposal as relevant for understanding people’s relationship–specific cooperative expectations in an age of social AI, which may also forecast potential resistance towards AI systems occupying certain social roles. Finally, these data can form the basis for ethical evaluations: What relationship–specific cooperative norms we should adopt for human–AI interactions, or reinforce through responsible AI design, depends partly on empirical facts about what norms people find intuitive for such interactions (along with the costs and benefits of maintaining these). Toward the end of the paper, we discuss how these relational norms may change over time and consider the implications of this for the proposed research program.

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