Beyond Fairness Metrics: Roadblocks and Challenges for Ethical AI in
Practice
- URL: http://arxiv.org/abs/2108.06217v1
- Date: Wed, 11 Aug 2021 18:33:17 GMT
- Title: Beyond Fairness Metrics: Roadblocks and Challenges for Ethical AI in
Practice
- Authors: Jiahao Chen and Victor Storchan and Eren Kurshan
- Abstract summary: We review practical challenges in building and deploying ethical AI at the scale of contemporary industrial and societal uses.
We argue that a holistic consideration of ethics in the development and deployment of AI systems is necessary for building ethical AI in practice.
- Score: 2.1485350418225244
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We review practical challenges in building and deploying ethical AI at the
scale of contemporary industrial and societal uses. Apart from the purely
technical concerns that are the usual focus of academic research, the
operational challenges of inconsistent regulatory pressures, conflicting
business goals, data quality issues, development processes, systems integration
practices, and the scale of deployment all conspire to create new ethical
risks. Such ethical concerns arising from these practical considerations are
not adequately addressed by existing research results. We argue that a holistic
consideration of ethics in the development and deployment of AI systems is
necessary for building ethical AI in practice, and exhort researchers to
consider the full operational contexts of AI systems when assessing ethical
risks.
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