How to train your robot: Can we teach robots right from wrong?

English: The imitation game, as described by Alan Turing in “Computing Machinery and Intelligence”. Player C, through a series of written questions, attempts to determine which of the two players is a man, and which of the two is the woman. Player A – the man – tires to trick player C into making the wrong decision, while player B tries to help player C. Turing uses this game as the basis for his test for intelligence. (Photo credit: Wikipedia)

From performing surgery and flying planes to babysitting kids and driving cars, today’s robots can do it all.

With chatbots such as Eugene Goostman recently being hailed as “passing” the Turing test, it appears robots are becoming increasingly adept at posing as humans. While machines are becoming ever more integrated into human lives, the need to imbue them with a sense of morality becomes increasingly urgent. But can we really teach robots how to be good?

An innovative piece of research recently published in the Journal of Experimental & Theoretical Artificial Intelligence looks into the matter of machine morality, and questions whether it is “evil” for robots to masquerade as humans.

Drawing on Luciano Floridi’s theories of Information Ethics and artificial evil, the team leading the research explore the ethical implications regarding the development of machines in disguise. ‘Masquerading refers to a person in a given context being unable to tell whether the machine is human’, explain the researchers – this is the very essence of the Turing Test. This type of deception increases “metaphysical entropy”, meaning any corruption of entities and impoverishment of being; since this leads to a lack of good in the environment – or infosphere – it is regarded as the fundamental evil by Floridi.  Following this premise, the team set out to ascertain where ‘the locus of moral responsibility and moral accountability’ lie in relationships with masquerading machines, and try to establish whether it is ethical to develop robots that can pass a Turing test.

Six significant actor-patient relationships yielding key insights on the matter are identified and analysed in the study. Looking at associations between developers, robots, users and owners, and integrating in the research notable examples, such as Nanis’ Twitter bot and Apple’s Siri, the team identify where ethical accountabilities lie – with machines, humans, or somewhere in between?

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