Modeling morality with prospective logic

Luís Moniz Pereira, Ari Saptawijaya

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

24 Citations (Scopus)

Abstract

Morality no longer belongs only to the realm of philosophers. Recently, there has been a growing interest in understanding morality from the scientific point of view. This interest comes from various fields, for example, primatology (de Waal 2006), cognitive sciences (Hauser 2007; Mikhail 2007), neuroscience (Tancredi 2005), and other various interdisciplinary perspectives (Joyce 2006; Katz 2002). The study of morality also attracts the artificial intelligence community from the computational perspective and has been known by several names, including machine ethics, machine morality, artificial morality, and computational morality. Research on modeling moral reasoning computationally has been conducted and reported on, for example, at the AAAI 2005 Fall Symposium on Machine Ethics (Guarini 2005; Rzepka and Araki 2005). There are at least two reasons to mention the importance of studying morality from the computational point of view. First, with the current growing interest to understand morality as a science, modeling moral reasoning computationally will assist in better understanding morality. Cognitive scientists, for instance, can greatly benefit in understanding complex interaction of cognitive aspects that build human morality; they may even be able to extract moral principles people normally apply when facing moral dilemmas. Modeling moral reasoning computationally can also be useful for intelligent tutoring systems, for instance, to aid in teaching morality to children. Second, as artificial agents are more and more expected to be fully autonomous and work on our behalf, equipping agents with the capability to compute moral decisions is an indispensable requirement.

Original languageEnglish
Title of host publicationMachine Ethics
PublisherCambridge University Press
Pages398-421
Number of pages24
Volume9780521112352
ISBN (Electronic)9780511978036
ISBN (Print)9780521112352
DOIs
Publication statusPublished - 1 Jan 2011

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