人-机器人协作中的不犯错而做正确的事
Doing Right by Not Doing Wrong in Human-Robot Collaboration
摘要：
随着机器人系统越来越能够在日常生活中帮助人类，我们必须考虑这些人工智能体使人类合作者感到不安全或不公平对待他们的机会。机器人可以表现出对人类造成身体伤害的反社会行为，或者复制不公平的行为，复制甚至放大历史和社会偏见，这对与它们互动的人类有害。在本文中，我们讨论这些问题，考虑社会机器人操作和公平的机器人决策。我们提出了一种学习公平和社交行为的新方法，不是通过复制积极的行为，而是通过避免消极的行为。在这项研究中，我们强调了在机器人操作中融入社会性的重要性，以及在人机交互中考虑公平性的必要性。
英文摘要：
As robotic systems become more and more capable of assisting humans in their everyday lives, we must consider the opportunities for these artificial agents to make their human collaborators feel unsafe or to treat them unfairly. Robots can exhibit antisocial behavior causing physical harm to people or reproduce unfair behavior replicating and even amplifying historical and societal biases which are detrimental to humans they interact with. In this paper, we discuss these issues considering sociable robotic manipulation and fair robotic decision making. We propose a novel approach to learning fair and sociable behavior, not by reproducing positive behavior, but rather by avoiding negative behavior. In this study, we highlight the importance of incorporating sociability in robot manipulation, as well as the need to consider fairness in human-robot interactions.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
