Abstract
Ethics evaluations of companies that function with AI at their core are increasingly required by regulation and law in Europe and the US. Investors in artificial intelligence (AI)-intensive companies also seek ethics evaluations as part of the nonfinancial information they gather about corporate performance, especially as it relates to privacy and algorithmic fairness. The result is an increasing demand for the evaluations. The costs and time necessary to perform an AI ethics audit, however, are high, even prohibitive. To solve the problem, natural language processing (NLP) and machine learning (ML) can be employed to automate the process. The proposal is that much of the work of AI evaluating can be accomplished more efficiently by machines than by humans. To show how automated ethics reporting may work, this paper describes a project currently underway at Pace University in New York and the University of Trento in Italy. The project endeavours to apply AI to the task of producing AI ethics evaluations.
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