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A Bayesian Analysis of Moral Norm Malleability during Clarification Dialogues

Abstract

One of the principle tenets of modern behavioral ethics is thathuman morality is dynamic and malleable. Recent work intechnology ethics has highlighted the role technologies canplay in this process. As such, it is the responsibility oftechnology designers to actively identify and address possi-ble negative consequences of such technological mediation. Inthis work, we examine dialogue systems employed by currentrobotic agents, arguing that they can have deleterious effectson both the human moral ecosystem and human perception ofthe robots, regardless of the robots’ actual ethical competence.We present a preliminary Bayesian analysis of empirical datasuggesting that the architectural status quo of clarification re-quest generation systems may (1) cause robots to unintention-ally miscommunicate their ethical intentions (our two tests forthis yielded Bayes factors of 1319 and 1099) and (2) weakenhumans’ contextual application of moral norms (Bayes fac-tor of 1069).

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