No. 114/2022

I f you thought you were showing signs of depression, would you rather contact a person or a machine? The start-up clare&me comes down firmly in favour of the latter. If you call their hotline, you will reach Clare, a phonebot like those used by customer services or help- desks. The bot contains an AI algorithm and responds to key words: if the caller talks about their anxiety, Clare sug- gests coping strategies. Currently, the app is being tested in the UK and is due to be marketed in the autumn. Clare is designed to help in an emergency, as a support to cover the time spent waiting for therapy – which is get- ting ever longer. During the Corona pandemic in 2021, the German Association of Psychotherapists (DPtV) registered an increase of more than 40 percent in demand for ther- apy; amongst children and young people even more than 60 percent. That same year, the association warned about the mental health impact of continued climate change. Now, there is also anxiety caused by Russia’s war against Ukraine. “People are overwhelmed,” explains Enno Maaß, National Vice Chairman of DPtV. In towns, he estimates it takes two to three months to get into therapy. “In the coun- try, you have to reckon on six to nine months.” The waiting times and growing demand have trig- gered a wave of new, digital mental health offers. Many are even available on prescription. They have names like HelloBetter, moodgym, deprexis and Selfapy and offer online courses in the form of apps on how to deal with stress, burnout, depression and panic attacks. With the IN PRACTICE “SORRY YOU’RE GOING THROUGH THIS” People who suffer from depression or other mental health issues could soon seek help from an artificial intelligence. Will AI one day obviate the need for psychotherapists? by MIRKO HEINEMANN themes like the evil AI striving for world domination make people uneasy. In order to build trust, it would be helpful to understand how AI thinks, how it makes assessments and decisions. But that is not so easy. Most modern AI systems are black box models. They receive input und deliver output. They recognise a dog or a cat, a stop sign or a speed limit, a tumour or a rare disease. But how they do it is their own well-kept secret. “Neural networks are impenetrable,” says Daniel Rückert. “If we want to automate measuring procedures, we can use the measurements on the screen to show the radiologist how the computer has calculated the volume of the tumour. The radiologist sees it all, too, and can judge whether it’s right or not. We don’t need to explain exactly how we delin- eated the tumour. Where it starts to get tricky, however, is when you want to use the results of your AI model to for- mulate hypotheses on how a disease will develop, for exam- ple, or what the origins of the disease were.” Christian Becker-Asano sometimes worries that some scientists are perfectly satisfied when something works without understanding what is going on in the back- ground. This leads to AIs that do normally work, but in some situations suddenly don’t. “We have great achieve- › We don’t understand why mysterious mistakes keep occurring because we don’t know what the algorithm really is doing inside. Christian Becker-Asano, Professor of Artificial Intelligence at the Hochschule der Medien in Stuttgart FOCUS 16 HUMBOLDT KOSMOS 114/2022