is intuitively good or morally desirable is not accepted by the virtue of it appearing so. Rather, we look for justifications that can ease the indeterminacy. Ethics is also necessarily intertwined with moral motivation. Behind the normative inquiries in ethics, there is always the assumption that one must aim for moral improvement. Ready-Ethics, on the other hand, treats normativity as a subject of an empirical study because it is only concerned with finding instances of human moral acceptability. No motivation to improve one’s moral conduct is involved. There is only, or at least overwhelmingly, the motivation to make artificial agents comply with current norms. Ready-Ethics is more interested in the practice of morality than the justification behind what is determined as morally acceptable because ethics is only inquired with the purpose of replicating an aspect of human agency. To bring ethics into an implementable form, Ready-Ethics assumes the existence of a useful pattern to be found in the practice of morality and attentively follows what is available based on observable conduct. Therefore, despite dealing with the same subject matter of normativity, Ready-Ethics is not a branch of ethics. Rather, it is a branch of AI research where the technological need for the social acceptance of AI launches an empirical inquiry into the normative. Ready-Ethics is an enframing of ethics’ motivation and how it engages with normativity, which is pushed forward by the need to propagate AI technology. The interested reader may have two questions: First, why should I believe that
Ready-Ethics is indeed the approach that drives the research in replicating ethical decision-making in artificial agents? As Heidegger presented a real-life case with the Rhine to prove his point with enframing, I shall do the same through examining actual cases.
Subsumptivist Generalist Position in Ethical AI First, we summarize global moral preferences. Second, we document individual variations in preferences, based on respondents’ demographics. Third, we report cross-cultural ethical variation, and uncover three major clusters of countries ... We discuss how these preferences can contribute to developing global, socially acceptable principles for machine ethics 14 We consider approaches that query [people] about their judgments in individual examples, and then aggregate these judgments into a general policy. We propose a formal learning-theoretic framework for this setting.”15
One recognizable trend in the recent literature on ethical decision-making replication is the prominence of the Subsumptivist Generalist Position, or SGP. It believes that “the moral status of an act is determined by its falling under a general moral principle,”16 meaning that the moral value of an action “X” is determined by the degree of its compliance to a general moral principle “Y.” One may question what is meant by a “general moral princi-
13 Cambridge, MA: MIT Press, 1993. p.2 14 Awad, E., et al, p.1. 15 Conitzer, V., and Zhang, H.. “A PAC Framework for Aggregating Agents’ Judgments,” AAAI (2019). 16 Strahovnik, V. “Introduction: Challenging Moral Particularism.” Challenging Moral Particularism, edited by Mark Norris, Lance et al., Routledge, 2008, p.1. 120
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