[论文解读] Understanding artificial intelligence ethics and safety

David Leslie|arXiv (Cornell University)|Jun 11, 2019

Ethics and Social Impacts of AI参考文献 276被引用 136

一句话总结

本文提出一份指南，识别公共部门中人工智能的潜在危害，并提出用于治理、负责任创新以及以人为本、可解释的人工智能的可操作措施。

ABSTRACT

A remarkable time of human promise has been ushered in by the convergence of the ever-expanding availability of big data, the soaring speed and stretch of cloud computing platforms, and the advancement of increasingly sophisticated machine learning algorithms. Innovations in AI are already leaving a mark on government by improving the provision of essential social goods and services from healthcare, education, and transportation to food supply, energy, and environmental management. These bounties are likely just the start. The prospect that progress in AI will help government to confront some of its most urgent challenges is exciting, but legitimate worries abound. As with any new and rapidly evolving technology, a steep learning curve means that mistakes and miscalculations will be made and that both unanticipated and harmful impacts will occur. This guide, written for department and delivery leads in the UK public sector and adopted by the British Government in its publication, 'Using AI in the Public Sector,' identifies the potential harms caused by AI systems and proposes concrete, operationalisable measures to counteract them. It stresses that public sector organisations can anticipate and prevent these potential harms by stewarding a culture of responsible innovation and by putting in place governance processes that support the design and implementation of ethical, fair, and safe AI systems. It also highlights the need for algorithmically supported outcomes to be interpretable by their users and made understandable to decision subjects in clear, non-technical, and accessible ways. Finally, it builds out a vision of human-centred and context-sensitive implementation that gives a central role to communication, evidence-based reasoning, situational awareness, and moral justifiability.

研究动机与目标

• 识别公共部门AI系统可能造成的潜在危害。
• 提出具体、可操作的措施以对冲这些危害。
• 推动治理流程与负责任创新文化。
• 倡导向决策主体提供可解释的、非技术性的AI结果解释。
• 构建以人为本、情境敏感的AI实施愿景。

提出的方法

• 在公共部门情境中对AI危害及治理需求的全景审视。
• 提出具体、可操作的治理措施和负责任创新实践。
• 强调需要让用户可理解算法支持的结果。
• 倡导在AI部署中进行沟通、以证据为基础的推理、情境感知和道德可辩性。

实验结果

研究问题

• RQ1 公共部门环境下，AI系统可能带来哪些潜在危害？
• RQ2 哪些治理流程和实践可以预见并防止这些危害？
• RQ3 如何使AI结果对非技术决策者和主体易于理解和解释？
• RQ4 公共部门中以人为本、情境敏感的AI实现有哪些特征？

主要发现

• AI创新可以改善政府提供社会性福利，但也存在合法风险和潜在危害。
• 治理与负责任创新文化对预测和防范危害至关重要。
• 算法结果应以清晰、非技术性语言向用户可解释和可说明。
• 实施应以人为本、情境敏感，并以沟通、以证据为基础的推理以及情境感知为基础。
• 在政府情境中的AI系统设计与部署应以道德可辩性为核心。