Last week, Microsoft inadvertently revealed the difficulty of creating moral robots. Chatbot Tay, designed to speak like a teenage girl, turned into a Nazi-loving racist after less than 24 hours on Twitter. "Repeat after me, Hitler did nothing wrong," she said, after interacting with various trolls. "Bush did 9/11 and Hitler would have done a better job than the monkey we have got now." Of course, Tay wasn't designed to be explicitly moral.
As artificial intelligence (AI) systems become increasingly ubiquitous, the topic of AI governance for ethical decision-making by AI has captured public imagination. Within the AI research community, this topic remains less familiar to many researchers. In this paper, we complement existing surveys, which largely focused on the psychological, social and legal discussions of the topic, with an analysis of recent advances in technical solutions for AI governance. By reviewing publications in leading AI conferences including AAAI, AAMAS, ECAI and IJCAI, we propose a taxonomy which divides the field into four areas: 1) exploring ethical dilemmas; 2) individual ethical decision frameworks; 3) collective ethical decision frameworks; and 4) ethics in human-AI interactions. We highlight the intuitions and key techniques used in each approach, and discuss promising future research directions towards successful integration of ethical AI systems into human societies.
We consider the consequences for human beings of attempting to create ethical robots, a goal of the new field of AI that has been called Machine Ethics. We argue that the concerns that have been raised are either unfounded, or can be minimized, and that many benefits for human beings can come from this research. In particular, working on machine ethics will force us to clarify what it means to behave ethically and thus advance the study of Ethical Theory. Also, this research will help to ensure ethically acceptable behavior from artificially intelligent agents, permitting a wider range of applications that benefit human beings. Finally, it is possible that this research could lead to the creation of ideal ethical decision-makers who might be able to teach us all how to behave more ethically. A new field of Artificial Intelligence is emerging that has been called Machine Ethics.
In the age of AI, how can we live with artificially intelligent machines and robots that may become more intelligent than us? An AI machine can be a computer or smart device; it can also be known as a robot that, with or without appendages, can emulate human life physically. There are still so many unanswered questions. How can we coexist comfortably and conveniently if one day, the machines we have created decide to think for themselves? Do you believe in technological singularity, and is it near?
The field of machine ethics is concerned with the question of how to embed ethical behaviors, or a means to determine ethical behaviors, into artificial intelligence (AI) systems. The goal is to produce artificial moral agents (AMAs) that are either implicitly ethical (designed to avoid unethical consequences) or explicitly ethical (designed to behave ethically). Van Wynsberghe and Robbins' (2018) paper Critiquing the Reasons for Making Artificial Moral Agents critically addresses the reasons offered by machine ethicists for pursuing AMA research; this paper, co-authored by machine ethicists and commentators, aims to contribute to the machine ethics conversation by responding to that critique. The reasons for developing AMAs discussed in van Wynsberghe and Robbins (2018) are: it is inevitable that they will be developed; the prevention of harm; the necessity for public trust; the prevention of immoral use; such machines are better moral reasoners than humans, and building these machines would lead to a better understanding of human morality. In this paper, each co-author addresses those reasons in turn. In so doing, this paper demonstrates that the reasons critiqued are not shared by all co-authors; each machine ethicist has their own reasons for researching AMAs. But while we express a diverse range of views on each of the six reasons in van Wynsberghe and Robbins' critique, we nevertheless share the opinion that the scientific study of AMAs has considerable value.