[论文解读] Responsible AI by Design in Practice

Richard Benjamins, Alberto Barbado+1 more|arXiv (Cornell University)|Sep 27, 2019

Ethics and Social Impacts of AI参考文献 35被引用 36

一句话总结

这篇论文展示了在一家大型组织中实施公司级方法以最小化不良AI后果的实际案例，强调技术和组织步骤。

ABSTRACT

Recently, a lot of attention has been given to undesired consequences of Artificial Intelligence (AI), such as unfair bias leading to discrimination, or the lack of explanations of the results of AI systems. There are several important questions to answer before AI can be deployed at scale in our businesses and societies. Most of these issues are being discussed by experts and the wider communities, and it seems there is broad consensus on where they come from. There is, however, less consensus on, and experience with how to practically deal with those issues in organizations that develop and use AI, both from a technical and organizational perspective. In this paper, we discuss the practical case of a large organization that is putting in place a company-wide methodology to minimize the risk of undesired consequences of AI. We hope that other organizations can learn from this and that our experience contributes to making the best of AI while minimizing its risks.

研究动机与目标

• 激发在 AI 部署中解决偏见、歧视和可解释性需求的必要性。
• 描述一个大型组织如何构建并执行面向全公司的一体化负责任 AI 方法论。
• 分享在真实世界情境中应用负责任 AI 实践的经验教训。

提出的方法

• 呈现一个大型组织采用负责任 AI 设计方法论的实际案例研究。
• 讨论将技术与组织方法相结合以最小化AI风险。
• 突出用于使负责任 AI 落地的治理结构、流程与工作流。
• 提供来自 AAAI 秋季研讨会中‘以人为本的 AI：可信度轨道’经验的见解。

实验结果

研究问题

• RQ1 组织在现实世界部署中可以采取哪些实际步骤来最小化 AI 的不良后果？
• RQ2 如何将技术与组织实践结合起来，以大规模设计值得信赖的 AI？
• RQ3 在组织中哪些治理、风险管理和衡量方法对负责任 AI 最为有效？

主要发现

• 一个真实案例展示了大型组织如何实施面向全公司的负责任 AI 方法论。
• 对将负责任 AI 落地的组织挑战与推动因素的见解。
• 关于在实践中最小化 AI 风险所需的治理、流程和工作流的讨论。
• 来自参与 AAAI 秋季研讨会‘可信任 AI 模型与数据’ HAi 专题的证据。