Agents often exert influence when interacting with humans and non-human agents. However, the ethical status of such influence is often unclear. In this paper, we present the SHAPE framework, which lists reasons why influence may be unethical. We draw on literature from descriptive and moral philosophy and connect it to machine learning to help guide ethical considerations when developing algorithms with potential influence. Lastly, we explore mechanisms for governing algorithmic systems that influence people, inspired by mechanisms used in journalism, human subject research, and advertising.

翻译：智能体在与人类及非人类智能体交互时常常施加影响力，然而此类影响力的伦理性通常不明确。本文提出SHAPE框架，系统列举了影响力可能违背伦理的具体原因。通过融合描述性与道德哲学文献，并将其与机器学习领域相关联，我们旨在指导具有潜在影响力的算法开发过程中的伦理考量。最后，受新闻业、人类受试者研究及广告业中现有机制的启发，我们探索了治理具有影响力算法的系统可能采用的机制。