No. 114/2022

you an answer, irrespective of the number of images you show them. So, if you get humans and AI to work together you can combine the best of both worlds and, hopefully, eliminate the respective disadvantages.” AN INGENIOUS MOVE FLABBERGASTS THE GO COMMUNITY But AI is not only capable of supporting people. In certain areas it is now beginning to successfully compete with them. One historic example was the victory of AI in the strategically complex board game Go. In March 2016, one of the world’s best Go players, the South Korean Lee Sedol, lost four of his five matches against the computer programme, AlphaGo. It was the 37th move in the second match that was to mark a new milestone in machine intelligence. Commentators couldn’t believe their eyes. It looked as though someone had clicked on the wrong button of an online game. At that point, the world-class player Lee Sedol seems to have intuited the implications of the move. He left the room for a few minutes. No top-rank player had ever performed a comparable move in the board game. So, AlphaGo’s artificial intelli- gence could not have witnessed a move like that before. The computer had not simply replicated something that had been programmed in; it had applied its knowledge about the game intelligently. How does a computer manage something like that? Classic AI is based on rules and symbols and functions well in predictable environments. It adheres to decision trees or searches for solutions from a set quantity of potential solutions. Everything it knows about the world has been fed into it by humans. Modern AI of the type used in AlphaGo, on the other hand, is effectively based on our brain. Neurons that are connected in our brain and sometimes fire and sometimes don’t are reproduced digitally. They respond to different stimuli. “These digital neurons have one thing in common with the brain. They are connected to other neurons. And whether they ‘fire’, depends on the amount of input they get. One neuron fires at the next one according to a mathematical formula which tries to reproduce what’s taking place amongst the neurons in the brain,” the Humboldtian Christian Becker-Asano, Professor of Artificial Intelligence at the Hochschule der Medien in Stuttgart, explains. But even if artificial intelligence were one day able to function like human intelligence, if it could perceive the world the way we do, it would probably still be lacking something crucial: an emotional relationship with whatever it perceives. The Humboldtian Tobias Matzner, professor in the Department of Media, Algorithms and Society at Paderborn University, describes the difference between humans and machines: “An algorithm looking at an image simply sees rows of pixels. Nothing else. And for an algorithm, these pixels ‘equal image’, irrespective of whether the image is noisy or whether it shows a friend, or a dog, or just something blurry. When we look at an image, it immediately triggers a raft of associations.” That is why AI needs far more examples to learn something new than humans do. Milica Gašić therefore wants to humanise the way AI learns. The Sofja Kovalevskaja Award Winner at Heinrich Heine University Düsseldorf takes her inspiration from the way animals and children learn. “I would like to build systems that continue developing over time as humans do. Every day, I see how my little daughter learns new things, and we really have a fantastic ability to pick up new things and to knowwhat to do with them,” says Gašić. Her aim is to improve language systems so that we can talk to AI just as we do to other people. So far, it is not just a more eloquent use of The essence of human conversation is our ability to recognise and respond to emotions. Milica Gašić, Sofja Kovalevskaja Award Winner, Heinrich Heine University Düsseldorf FOCUS 14 HUMBOLDT KOSMOS 114/2022