Moral AI has been studied in the fields of philosophy and artificial intelligence. Although most existing studies are only theoretical, recent developments in AI have made it increasingly necessary to implement AI with morality. On the other hand, humans are under the moral uncertainty of not knowing what is morally right. In this paper, we implement the Maximizing Expected Choiceworthiness (MEC) algorithm, which aggregates outputs of models based on three normative theories of normative ethics to generate the most appropriate output. MEC is a method for making appropriate moral judgments under moral uncertainty. Our experimental results suggest that the output of MEC correlates to some extent with commonsense morality and that MEC can produce equally or more appropriate output than existing methods.

In the early 20th century, the psychoanalyst Carl Jung came up with the concept of the shadow--the human personality's darker, repressed side, which can burst out in unexpected ways. Surprisingly, this theme recurs in the field of artificial intelligence in the form of the Waluigi Effect, a curiously named phenomenon referring to the dark alter-ego of the helpful plumber Luigi, from Nintendo's Mario universe. Luigi plays by the rules; Waluigi cheats and causes chaos. An AI was designed to find drugs for curing human diseases; an inverted version, its Waluigi, suggested molecules for over 40,000 chemical weapons. All the researchers had to do, as lead author Fabio Urbina explained in an interview, was give a high reward score to toxicity instead of penalizing it.

Smart assistants could come with a'moral AI' to decide whether to report their owners for breaking the law. That's the suggestion by academics at the University of Bergen, Norway, who touted the idea at the ACM conference on Artificial Intelligence, Ethics and Society in Hawaii. They suggest that domestic bots such as Amazon Echo and Google Home should be enhanced with moral AI. This would enable them to weigh-up whether to report illegal activity to the police, effectively putting millions of people under constant surveillance. Marija Slavkovik, Associate Professor the Department of Information Science and Media Studies, led the research behind the idea.

With every advance in technology comes a wave of warnings about how it will impact society. Artificial intelligence (AI) is no different and has met a number of sceptics along the way. One of the greatest criticisms has been around ethics and how an AI can learn the right behaviours. As humans, our own principles of right and wrong are derived our experiences. Lessons that we are taught – either formally or informally – throughout our lives.

The warnings are exaggerated, of course, and are rooted in science fiction (SkyNet isn't coming, guys, c'mon). But it doesn't hurt to be prepared, or at least to influence the direction AI research can or should take. A new enterprise rises to the challenge in the form of the Ethics and Governance of Artificial Intelligence Fund. Backed by eBay founder Pierre Omidyar and LinkedIn co-founder Reid Hoffman, together with the Knight Foundation, the fund's goal is "to support work around the world that advances the development of ethical AI in the public interest, with an emphasis on applied research and eduction." At its launch last January 10, the fund already received an initial investment of $27 million -- with Hoffman and Omidyar each committing $10 million through their respective foundations, and the Knight Foundation's $5 million contribution.

"A reasoned, even cournterempathic analysis of moral obligation and likely consequences is a better guide to planning for the future than the gut wrench of empathy." This is the argument presented by Paul Bloom in his latest book, Against Empathy. He argues that a more fair and reliable guide for one's morality is rational compassion; a morality based on facts, cost/benefit analysis and rational thinking. For the most part, I agree with him. I think back to all of the conflicts that I have witnessed or been engaged in, whether with friends, colleagues or family.