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Science writer; lecturer, Copenhagen; author, The Generous Man: How Helping Others Is the Sexiest Thing You Can Do
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Making machines that think will be like putting a man on the moon: The effect will be the exact opposite of what everyone expected. The Apollo program didn’t launch humanity into a Space Age of cosmic exploration. It led to something much more important: the Earth Age. We left home to explore the universe and discovered for the first time the place we came from. The image of our planet rising on the sky of the moon became the iconic symbol of ecology, fragility, and globalization.
Thinking machines will mean a huge change in the way we understand something much more subtle and alien than machines—ourselves. Teaching machines to think will teach us who we are and how we think. We don’t think the way we think we do. Most of what we do in terms of advanced information processing we don’t think about at all. We just do it. A child is threatened and we act, immediately. Only afterward do we start thinking about it. A thought appears in our mind—a beautiful, luminescent, and breathtaking thought. It’s just there. We didn’t think of it before it was a thought.
We aren’t consciously aware of most of the information we process when we think. It all happens unconsciously, in our mind, in our body. Right away. We’re not even rational in the sense of being logical and explicitly deductive. We’re fast, intuitive, and emotional.
Economists believe we are Homo economicus—selfish and rational, acting with reason in our own self-interest. But most economic and social interactions deal with fairness, trust, sharing, and long-term relationships. Experimental economics shows us that when we act directly and without hesitation, we’re social and cooperative. Only when we start thinking for some seconds do we choose to be selfish.
Unless we deal with computers. When we play economic games with machine counterparts, we tend to be cold and egoistic. You can even measure the difference in our blood flow in the brain and in the hormones in our bloodstream. We think of machines the way economists think about us—as rational, cold-blooded, and selfish. Therefore we treat them as such.
By instinct, we know that humans are more human than when we think of ourselves in the theoretical terms of economics (or other social sciences). We act according to this instinct, but when we think about it we’re still under the false impression that we’re Homo economicus. Building thinking machines will show us that there was a deep evolutionary wisdom in our social instincts: In the long run, it pays much more to be unselfish. It’s not truly selfish for you to be selfish, since being unselfish leads to better results for you.
The strategic lesson we’ll have to teach machines is all about love.
Robot scientist Hans Moravec has described different biological and technological systems according to their ability to process and store information. At one end: simple, rule-based, and stereotypical creatures, like viruses, worms, and computers. At the other: the truly powerful information processors, like whales, elephants, and human beings. All the creatures with huge capacity are mammals. Their offspring aren’t born with the full program for functioning. They go through many years of upbringing before they can act on their own. Their skills aren’t specified as rules but as lessons learned from experience. You bang your head on a table until you learn not to. Learning by trial and error. Exploring. This is possible only because the young mammals are taken care of by older mammals. Parenting. Nursing. Love.
Love creates the trust that gives young mammals confidence enough to go out and collect Big Data about the world. And digest it. And heal the wounds.
Love is the recipe for how to grow a human intelligence, a human set of skills, and a human ability to think. To make machines think, we’ll have to give them love. It will be more like a kindergarten than a high-tech lab. We’ll have to let machines explore all by themselves, do weird things, not just act according to our wants. They’ll have to be not tame but wild, acting from their own will.
The challenge is for us to love wild machines that think. We have to get past the ideas of machines that think and of artificial life. Because when something is alive—and therefore able to self-reproduce and to change—it’s no longer artificial. When it thinks on its own, it’s no longer a machine but a thinking creature. It will be illogical, intuitive, and benevolent. We’ll wonder how it became that way. Until we understand that it was created in our own image.
