人工智能管理

Scott J. Shackelford, Rachel Dockery
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引用次数: 2

摘要

人工智能(AI)在日常生活中日益普及和必不可少,使应用程序和各种智能设备能够自动驾驶汽车和医疗设备。然而,随着万物互联的日益紧密和反应迅速,人工智能也带来了一系列法律、社会、经济和文化方面的挑战。涉及的各种利益相关者——跨越世界各地的政府、行业和用户——为如何最好地促进安全、公平地开发、部署和使用创新的人工智能应用提供了独特的机会和治理问题。世界各地的州、国家和国际层面的监管机构都在积极考虑监管这一系列技术的下一步措施,但他们对如何相互促进和加强努力知之甚少。这种情况表明,需要采用新的方法来实现嵌套式治理,尤其是在包括美国、欧盟和中国在内的主要人工智能大国之间。本文概述了人工智能及其带来的众多挑战,并特别关注自动驾驶汽车,同时探讨了从多中心治理框架中吸取的教训,以及如何将这些社会科学结构应用于人工智能世界。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Governing AI
Artificial intelligence (AI) is increasingly pervasive and essential to everyday life, enabling apps and various smart devices to autonomous vehicles and medical devices. Yet along with the promise of an increasingly interconnected and responsive Internet of Everything, AI is ushering in a host of legal, social, economic, and cultural challenges. The variety of stakeholders involved – spanning governments, industries, and users around the world – presents unique opportunities and governance questions for how best to facilitate the safe and equitable development, deployment, and use of innovative AI applications. Regulators around the world at the state, national, and international levels are actively considering next steps in regulating this suite of technologies, but with little sense of how their efforts can build on and reinforce one another. This state of affairs points to the need for novel approaches to nested governance, particularly among leading AI powers including the United States, European Union, and China. This Article provides an overview of AI and the numerous challenges it presents with special attention being paid to autonomous vehicles, along with exploring the lessons to be learned from polycentric governance frameworks and how to apply such social science constructs to the world of AI.
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