Why teaching machine ethics is difficult

We teach machines ethics in the same way we teach them maths or languages: by asking them. A lot of these code-writing minds live in areas where machines are particularly dangerous—or in companies like…

Why teaching machine ethics is difficult

We teach machines ethics in the same way we teach them maths or languages: by asking them. A lot of these code-writing minds live in areas where machines are particularly dangerous—or in companies like Ford, where machines are performing a lot of their low-skill jobs in factories. By giving machines state-of-the-art digital capabilities, these machines are blurring the boundaries between humans and machines, and some people, like Dolores Huber, believe that that kind of blurring has only just begun. Huber is co-creator of Teachable, an emerging technology that aims to teach humans how to write better code. We spoke to Huber to learn more about Teachable’s philosophy. We are curious to know what do we know about nature and how much of our biology we can trust? For me, it’s quite obvious that we have an unfair advantage over nature in the way we think and see the world. Not because of some “cognitive advantage”, but because of course we have got the neurons, even though most of them are in our brain. So, if we just did what nature does, we would have a more egalitarian society. But we are not really lacking in the fact that we think differently from the way nature would want us to. At some point, it’s starting to appear that we have an unfair advantage, even for some calculations or operations. Autonomous vehicles are being tested in a field in Hertfordshire, U.K. Artificial intelligence and robotics are poised to change human lives forever. They have the potential to evolve from something of a power tool into something much more advanced—autonomous weapons systems, search-and-rescue drones, or factories that can hand out their products to us. Autonomous vehicles are being tested in a field in Hertfordshire, U.K. These machines are not made of stone and metal, yet they are developing a mind of their own. In this way, we can understand things about why machines are behaving the way they are and applying this knowledge to each individual example. Why is this the case? There are two things I could say to explain this situation. First, I could say that our capacity is just super-fast enough. Super-fast, that is, a bit faster than the timescale or the length of time that nature uses. But it’s better than nature’s.

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