Can we expect an artificially intelligent machine to behave ethically? There is a field of research that addresses this question, namely machine ethics. This field focuses on designing artificial moral agents (AMAs), robots, or artificially intelligent computers that behave morally. This thrust is not new. More than sixty years ago, Isaac Asimov considered the issue in his collection of nine science-fiction stories, published as I, Robot in 1950. In this book, at the insistence of his editor, John W. Campbell Jr., Asimov proposed his now famous three laws of robotics.

1. A robot may not injure a human being or through inaction allow a human being to come to harm.
2. A robot must obey the orders given to it by human beings, except in cases where such orders would conflict with the first law.
3. A robot must protect its own existence as long as such protection does not conflict with the first or second law.

Asimov, however, expressed doubts that the three laws would be sufficient to govern the morality of artificially intelligent systems. In fact he spent much of his time testing the boundaries of the three laws to detect where they might break down or create paradoxical or unanticipated behavior. He concluded that no set of laws could anticipate all circumstances. It turns out Asimov was correct.

To understand just how correct he was, let us discuss a 2009 experiment performed by the Laboratory of Intelligent Systems in the Swiss Federal Institute of Technology in Lausanne. The experiment involved robots programmed to cooperate with one another in searching out a beneficial resource and avoiding a poisonous one. Surprisingly the robots learned to lie to one another in an attempt to hoard the beneficial resource (“Evolving Robots Learn to Lie to Each Other,” Popular Science, August 18, 2009). Does this experiment suggest the human emotion (or mind-set) of greed is a learned behavior? If intelligent machines can learn greed, what else can they learn? Wouldn’t self-preservation be even more important to an intelligent machine?

Where would robots learn self-preservation? An obvious answer is on the battlefield. That is one reason some AI researchers question the use of robots in military operations, especially when the robots are programmed with some degree of autonomous functions. If this seems farfetched, consider that a US Navy–funded study recommends that as military robots become more complex, greater attention should be paid to their ability to make autonomous decisions (Joseph L. Flatley, “Navy Report Warns of Robot Uprising, Suggests a Strong Moral Compass,” www.engadget.com). Could we end up with a Terminator scenario (one in which machines attempt to exterminate the human race)? This issue is real, and researchers are addressing it to a limited extent. Some examples include:

• In 2008 the president of the Association for the Advancement of Artificial Intelligence commissioned a study titled “AAAI Presidential Panel on Long-Term AI Futures.” Its main purpose was to address the aforementioned issue. AAAI’s interim report can be accessed at http://research.microsoft.com/en-us/um/people/horvitz/AAAI_Presidential_Panel_2008-2009.htm.
• Popular science-fiction author Vernor Vinge suggests in his writings that the scenario of some computers becoming smarter than humans may be somewhat or possibly extremely dangerous for humans (Vernor Vinge, “The Coming Technological Singularity: How to Survive in the Post-Human Era,” Department of Mathematical Sciences, San Diego State University, 1993).
• In 2009 academics and technical experts held a conference to discuss the hypothetical possibility that intelligent machines could become self-sufficient and able to make their own decisions (John Markoff, “Scientists Worry Machines May Outsmart Man,” The New York Times, July 26, 2009). They noted: 1)Some machines have acquired various forms of semiautonomy, including being able to find power sources and independently choose targets to attack with weapons. 2)Some computer viruses can evade elimination and have achieved “cockroach intelligence.”
• The Singularity Institute for Artificial Intelligence stresses the need to build “friendly AI” (i.e., AI that is intrinsically friendly and humane). In this regard Ni ck Bostrom, a Swedish philosopher at St. Cross College at the University of Oxford, and Eliezer Yudkowsky, an American blogger, writer, and advocate for friendly artificial intelligence, have argued for decision trees over neural networks and genetic algorithms. They argue that decision trees obey modern social norms of transparency and predictability. Bostrom also published a paper, “Existential Risks,” in the Journal of Evolution and Technology that states artificial intelligence has the capability to bring about human extinction.
• In 2009 authors Wendell Wallach and Colin Allen addressed the question of machine ethics in Moral Machines: Teaching Robots Right from Wrong (New York: Oxford University Press). In this book they brought greater attention to the controversial issue of which specific learning algorithms to use in machines.

While the above discussion indicates there is an awareness that SAMs may become hostile toward humans, no legislation or regulation has resulted. AI remains an unregulated branch of engineering, and the computer you buy eighteen months from now will be twice as capable as the one you can buy today.

Where does this leave us? We will address the key questions in the next post.

Source: The Artificial Intelligence Revolution (2014), Louis A. Del Monte