Severin's Answer to What are the leading theories in moral philosophy and which of them might be technically the easiest to encode into an AI?

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Severin's Answer to What are the leading theories in moral philosophy and which of them might be technically the easiest to encode into an AI?

There are three major approaches to normative ethics (and some approaches to unify two or all of them): Virtue ethics, deontological ethics, and consequentialist ethics.

Virtue ethicists believe that at the core, leading an ethical life means cultivating virtues. In other words: What counts is less what one does moment-to-moment, but that one makes an effort to become the kind of person who habitually acts appropriately in all kinds of different situations. A prominent example for virtue ethics is stoicism.

Deontological ethicists believe that an ethical life is all about following certain behavioral rules, regardless of the consequences. Prominent examples include the ten commandments in Christianity, Kant's "categorical imperative" in philosophy, or Asimov's Three Laws of Robotics in science fiction.

Consequentialist ethicists believe that nor one's character neither the rules one lives by are what makes actions good or bad. Instead, consequentialists believe that only the consequences of an action count, both direct and indirect ones. A prominent example of consequentialist ethics is utilitarianism: The notion that those actions are the most moral that lead to the greatest good for the greatest number of individuals.

The short answer to the question which one of these might be the easiest to encode into an AI is: "We don't know." However, machine learning agents optimize for consequences, not virtues or hard-coded rules. As all the likely roads towards AGI involve machine learning, consequentialism may be the ethical theory to stick closest to.

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Original by: severin (edits by plex)


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