Keywords: Machine learning, Ethics, Fairness, Diversification, Inclusion
TL;DR: An AI ethics paper on the operationalization of fairness and diversity in AI
Abstract: We investigate the preconditions of an operationalization of ethics on the example algorithmization, i.e. the mathematical implementation, of the concepts of fairness and diversity in AI.
From a non-technical point of view in ethics, this implementation entails two major drawbacks, (1) as it narrows down big concepts to a single model that is deemed manageable, and (2) as it hides unsolved problems of humanity in a system that could be mistaken as the `solution' to these problems. We encourage extra caution when dealing with such issues and vote for human oversight.
Permission: pdf
Submission Number: 57
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