Learning from Learning Machines: Optimisation, Rules, and Social Norms
University of California, Irvine（加州大学欧文分校）；Mila (Québec AI Institute / Institut Québécois d’Intelligence Artificielle)（Mila（魁北克人工智能研究所））；Université de Montréal（蒙特利尔大学）
There is an analogy between machine learning systems and economic entities in that they are both adaptive, and their behaviour is specified in a more-or-less explicit way. It appears that the area of AI that is most analogous to the behaviour of economic entities is that of morally good decision-making, but it is an open question as to how precisely moral behaviour can be achieved in an AI system. This paper explores the analogy between these two complex systems, and we suggest that a clearer understanding of this apparent analogy may help us forward in both the socio-economic domain and the AI domain: known results in economics may help inform feasible solutions in AI safety, but also known results in AI may inform economic policy. If this claim is correct, then the recent successes of deep learning for AI suggest that more implicit specifications work better than explicit ones for solving such problems.
Emergence of Social Norms in Generative Agent Societies: Principles and Architecture
School of Mechanical Engineering, Northwestern Polytechnical University（西北工业大学机械工程学院）；School of Cybersecurity, Northwestern Polytechnical University（西北工业大学网络空间安全学院）；School of Artificial Intelligence, OPtics and ElectroNics(iOPEN), Northwestern Polytechnical University（西北工业大学人工智能、光学与电子学院（iOPEN））；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）
AI Ethics and Social Norms: Exploring ChatGPT's Capabilities From What to How
University of Toronto（多伦多大学）；Drexel University（德雷塞尔大学）；University of Siegen（锡根大学）；Westphal College of Media Arts and Design（媒体艺术与设计西弗尔学院）；Digital Media Department（数字媒体系）；Information Systems（信息系统）
