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We review practical challenges in building and deploying ethical AI at thescale of contemporary industrial and societal uses. Apart from the purelytechnical concerns that are the usual focus of academic research, theoperational challenges of inconsistent regulatory pressures, conflictingbusiness goals, data quality issues, development processes, systems integrationpractices, and the scale of deployment all conspire to create new ethicalrisks. Such ethical concerns arising from these practical considerations arenot adequately addressed by existing research results. We argue that a holisticconsideration of ethics in the development and deployment of AI systems isnecessary for building ethical AI in practice, and exhort researchers toconsider the full operational contexts of AI systems when assessing ethicalrisks.

Beyond Fairness Metrics: Roadblocks and Challenges for Ethical AI in Practice