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Science & technology December 2018 | Youth Hong Kong

Robots: future decision-makers D

ecision-making by artificial intelligence is a top concern when robotics appears in everything from war to medicine. Who or what will decide what is right and what is wrong? by Chan Pok Fung

What do you look forward to most in the future? When I was small, most if not all of my friends dreamed of having a companion like Doraemon, the robotlike cat. We wanted a Doraemon that could take care of us, just like he took care of Nobi in the story. However, what if Nobi refused to do his homework one day. Is it right for Doraemon to decide to do it for him? Or should he explain to Nobi why he should finish it himself? We probably won’t have a robot with Doraemon’s superpowers for at least 100 years, but we probably can soon develop robots that can accomplish many tasks. Before they start making decisions for us, it is of paramount importance that they know what is right and what is wrong. Ethical considerations like these are one of the most difficult topics in the development of modern artificial intelligence (AI) - even more so than the technology involved. The possibility of spontaneous “wrong” acts committed by AI evokes many fears. One of the most frequently discussed is the self-driving car with two options: crushing a man in the centre of the road or swerving into a wall and killing two passengers. Such a dilemma will only become more frequent as AI develops. Even if the safety record of selfdriving cars far exceeds that of human drivers, the question of responsibility will still remain. Who, or what, decides? I remember one of my classes about machine learning last year where the professor described a similar case and said, “This wouldn’t be a problem if the driver was human. No matter what decision he made, he would be accountable. Society requires that someone is to blame when accidents happen.” In the past, we had a complete understanding of robots’ programmed codes but the results were unsatisfactory and 34

a new approach to machine learning became a rising star in AI development. Machine learning allows AI to “learn” from a sea of data and to self-modify in order to achieve the optimized outcome. But as the performance of AI becomes better and better, the underlying principle becomes more and more opaque. In other words, humans can no longer predict how AI “learns” nor what it may consider the “right” outcome.

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