字幕表 動画を再生する 英語字幕をプリント Who would you save, the pedestrian in the road or the drivers in the car? It's not easy, and yet that's the kind of decision which millions of autonomous cars would have to make in the near future. We programme the machine but who do we tell it to save? That is the set-up of the moral machine experiment. There are so many moral decisions that we usually make during the day we don't realise. In driverless cars, these decisions will have to be implemented ahead of time. The goal was to open this discussion to the public. Some decisions might seem simple - should the car save a family of 4 or a cat? But what about a homeless person and their dog instead of a businessman? Or how about two athletes and an old woman instead of two schoolchildren? The problem was that there were so many combinations, so many possible accidents, that it seemed impossible to investigate them all using classic social science methods. Not only that, but how do people's culture and background affect the decisions that they make? The only option we had really was to turn it into a viral website. Of course, it's easier said than done, right. But that is exactly what the team managed to do. They turned these situations into an online task that people across the globe wanted to share and take part in. They gathered almost 40 million moral decisions, taken from millions of online participants across 233 countries and territories from all around the world. The results are intriguing. First, there are three fundamental principles which hold true across the world. The main results of the paper, for me, are first, the big three in people's preferences which is save human, save the greater number, save the kids. The second most interesting finding was the clusters, the clusters of countries with different moral profiles. The first cluster included many western countries, the second cluster had many eastern countries and the third cluster had countries from Latin America and also from former French colonies. The cultural differences we find are sometimes hard to describe because they're multidimensional, but some of them are very striking, like the fact that eastern countries do not have such a strong preference for saving young lives. Eastern countries seem to be more respectful of older people, which I thought was a very interesting finding. And it wasn't just age. One cluster showed an unexpectedly strong preference for saving women over men. I was also struck by the fact that French and the French subcluster was so interested in saving women. That was, yeah, I'm still not quite sure what's going on here. Another surprising finding concerned people's social status. On one side we put male and female executives, and on the other side we put a homeless person. The higher the economic inequality in a country, the more people were willing to spare the executives at the cost of the homeless people. This work provides new insight into how morals change across cultures and the team see particular relevance to the field of artificial intelligence and autonomous vehicles. In the grand scheme of it, I think these results are going to be very important to align artificial intelligence to human values. We sometimes change our minds. Other people next to us don't think the same things we do. Other countries don't think the same things we do. So aligning AI and human moral value is only possible if we do understand these differences, and that's what we tried to do. I so much hope that we can converge, that we avoid a future where you have to learn about the new ethical setting of your car every time you cross a border.