论文标题
蒙特利尔AI伦理研究所对欧盟委员会的白皮书的回应
Response by the Montreal AI Ethics Institute to the European Commission's Whitepaper on AI
论文作者
论文摘要
2020年2月，欧洲委员会（EC）发表了一份题为《人工智能 - 欧洲卓越和信任的方法》的白皮书。本文概述了欧盟在欧盟促进和采用人工智能（AI）的政策选择。蒙特利尔AI伦理研究所（MAIEI）审查了本文，并发表了一份答复，介绍了EC建立“卓越生态系统”和“信任生态系统”的计划，以及AI，物联网（IoT）（IoT）和机器人技术的安全和责任含义。 Maiei就上述部分提供了15个建议，包括：1）专注于研究和创新社区，成员国和私营部门； 2）在交易伙伴的政策和欧盟政策之间建立一致； 3）分析理论框架与建立可信赖AI的方法之间的生态系统差距； 4）专注于协调和政策一致； 5）专注于促进私人和安全共享数据的机制； 6）建立一个卓越的AI研究网络以加强研究和创新社区； 7）通过数字创新枢纽促进知识转移并发展AI专业知识； 8）加上有关AI系统不透明度的讨论的细微差别； 9）为个人创建一个过程，以对AI系统的决策或产出提出上诉； 10）执行新规则并加强现有法规； 11）禁止使用面部识别技术； 12）将所有AI系统符合类似的标准和强制要求； 13）确保生物识别系统实现其实施的目的； 14）针对不被视为高风险的系统实施自愿标签系统； 15）任命个人对AI系统了解并能够传达潜在风险的个人。
In February 2020, the European Commission (EC) published a white paper entitled, On Artificial Intelligence - A European approach to excellence and trust. This paper outlines the EC's policy options for the promotion and adoption of artificial intelligence (AI) in the European Union. The Montreal AI Ethics Institute (MAIEI) reviewed this paper and published a response addressing the EC's plans to build an "ecosystem of excellence" and an "ecosystem of trust," as well as the safety and liability implications of AI, the internet of things (IoT), and robotics. MAIEI provides 15 recommendations in relation to the sections outlined above, including: 1) focus efforts on the research and innovation community, member states, and the private sector; 2) create alignment between trading partners' policies and EU policies; 3) analyze the gaps in the ecosystem between theoretical frameworks and approaches to building trustworthy AI; 4) focus on coordination and policy alignment; 5) focus on mechanisms that promote private and secure sharing of data; 6) create a network of AI research excellence centres to strengthen the research and innovation community; 7) promote knowledge transfer and develop AI expertise through Digital Innovation Hubs; 8) add nuance to the discussion regarding the opacity of AI systems; 9) create a process for individuals to appeal an AI system's decision or output; 10) implement new rules and strengthen existing regulations; 11) ban the use of facial recognition technology; 12) hold all AI systems to similar standards and compulsory requirements; 13) ensure biometric identification systems fulfill the purpose for which they are implemented; 14) implement a voluntary labelling system for systems that are not considered high-risk; 15) appoint individuals to the oversight process who understand AI systems well and are able to communicate potential risks.
