How to avoid unethical practices like bias, manipulation, causing harm, and instead building ethical machines has been a topic of investigation and discussion within the Artificial Intelligence (AI) field for more than two decades. If there were clear rules to follow, AI would have long ago demonstrated how to avoid unethical practices. We suggest that such moral norms could perhaps emerge from experience by ethical reasoning about particular situations in different domains, and evolve over time.
In this work, we review the field of machine ethics in the last two decades or so, discussing the challenges and outlining possible future directions and potential developments. Building on these insights, we propose a modular framework for deriving practical ethical rules for AI systems from experience, enabling a more transparent and adaptive approach to moral decision making in AI. The potential of the framework is illustrated by means of a couple of case studies in the medical domain.
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