Authors
Don Howard
University of Notre Dame
Ioan Muntean
University of North Carolina, Asheville
Abstract
This paper proposes a model for an artificial autonomous moral agent (AAMA), which is parsimonious in its ontology and minimal in its ethical assumptions. Starting from a set of moral data, this AAMA is able to learn and develop a form of moral competency. It resembles an “optimizing predictive mind,” which uses moral data (describing typical behavior of humans) and a set of dispositional traits to learn how to classify different actions (given a given background knowledge) as morally right, wrong, or neutral. When confronted with a new situation, this AAMA is supposedly able to predict a behavior consistent with the training set. This paper argues that a promising computational tool that fits our model is “neuroevolution,” i.e. evolving artificial neural networks.
Keywords Artificial morality  Moral Functionalism  Machine Ethics  Autonomous Moral Agents
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