循环中的社会：规划职业社会契约
Society-in-the-Loop: Programming the Algorithmic Social Contract
摘要：
人工智能（AI）和机器学习的快速发展引发了许多关于自主机器监管和治理机制的问题。许多评论家、学者和政策制定者现在呼吁确保管理我们生活的算法是透明、公平和负责任的。在这里，我提出了一个监管AI和算法系统的概念框架。我认为，我们需要工具来编程，调试和维护算法社会契约，这是由机器调解的各种人类利益相关者之间的契约。为了实现这一点，我们可以从建模和仿真以及交互式机器学习领域中采用人在回路（HITL）的概念。特别是，我提出了一个我称之为社会在环（SITL）的议程，它将HITL控制范式与受人工智能系统影响的各种利益相关者的价值观谈判机制相结合，并监督协议的遵守情况。简言之，`SITL = HITL +社会契约。'
英文摘要：
Recent rapid advances in Artificial Intelligence (AI) and Machine Learning have raised many questions about the regulatory and governance mechanisms for autonomous machines. Many commentators, scholars, and policy-makers now call for ensuring that algorithms governing our lives are transparent, fair, and accountable. Here, I propose a conceptual framework for the regulation of AI and algorithmic systems. I argue that we need tools to program, debug and maintain an algorithmic social contract, a pact between various human stakeholders, mediated by machines. To achieve this, we can adapt the concept of human-in-the-loop (HITL) from the fields of modeling and simulation, and interactive machine learning. In particular, I propose an agenda I call society-in-the-loop (SITL), which combines the HITL control paradigm with mechanisms for negotiating the values of various stakeholders affected by AI systems, and monitoring compliance with the agreement. In short, `SITL = HITL + Social Contract.'
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。
