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The newly emerging field of machine ethics (Anderson and Anderson 2006) is concerned with adding an ethical dimension to machines. Unlike computer ethics—which has traditionally focused on ethical issues surrounding humans' use of machines—machine ethics is concerned with ensuring that the behavior of machines toward human users, and perhaps other machines(More)
As part of a larger Machine Ethics Project, we are developing an ethical advisor that provides guidance to health care workers faced with ethical dilemmas. MedEthEx is an implementation of Beauchamp's and Childress' Principles of Biomedical Ethics that harnesses machine learning techniques to abstract decision principles from cases in a particular type of(More)
A paradigm of case-supported principle-based behavior (CPB) is proposed to help ensure ethical behavior of autonomous machines. We argue that ethically significant behavior of autonomous systems should be guided by explicit ethical principles determined through a consensus of ethicists. Such a consensus is likely to emerge in many areas in which autonomous(More)
We describe a neural information retrieval system developed for retrieval of engineering designs. Two-dimensional (2-D) and three-dimensional (3-D) representations of engineering designs are input to adaptive resonance theory (ART-I) neural networks to produce groups or clusters of similar parts. ART-I networks are first trained to cluster designs into(More)
Endowing a computer with an ability to reason with diagrams could be of great benefit in terms of both human-computer interaction and computational efficiency through explicit representation. To date, research in diagrammatic reasoning has dealt with intra-diagrammatic reasoning (reasoning with a single diagram) almost to the exclusion of inter-diagrammatic(More)