Responsible AI by Design in Practice

作者：Richard Benjamins, Alberto Barbado, Daniel Sierra · 发表于：arXiv (Cornell University) · 年份：2019 · DOI：10.48550/arxiv.1909.12838 · 被引用次数：37 · 研究领域：Ethics and Social Impacts of AI、Adversarial Robustness in Machine Learning、Explainable Artificial Intelligence (XAI)

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.