i n terviews
Foto: TEDxBerlin, 2019 Sebastian Gabsch
Data For All. Not For Sale Data can exclusively serve big tech companies to increase their profits; it can also accelerate research and strengthen science for the good of us all. Interview with Bart de Witte, a digital health leader, and the founder of HIPPO AI – a NGO focused on open source medical data. AI is already becoming better than a doctor at diagnosing, predicting and preventing diseases. How to convince doctors to create a team with algorithms? Is the conflict between “new, better, datadriven” and “old, traditional, intuitionbased” avoidable?
We should focus on outcome-based care, where AI is the “Intel inside” of most transactions. Combined with a humancentric design, so the doctor sees less data, it would accelerate the adoption of digital health. Doctors could make faster, and hopefully, more accurate deci-
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sions. From my experience, most physicians do not fear AI because the amount of medical knowledge is growing faster then they can handle. Secondly, there is less difference between intuition and mathematics as one might think. Daniel Kahneman wrote in the book “Thinking slow, thinking fast,” that there are two basic systems that doctors use to solve problems. System One is fast and intuitive. In this system, doctors rely on pattern recognition to make quick decisions. Healthcare is full of System One thinking, which includes cognitive biases. For example, one of the bias-
es among physicians is over-confidence, which Kahneman calls “endemic in medicine.” He gives an example of a study that determined physician confidence in their diagnosis. Next, he compared the cause of deaths, as ascertained by autopsy, with the diagnosis the physician had made before the patient died. Clinicians who were utterly sure of the diagnosis antemortem were wrong 40% of the time. There are practically no winning arguments for focussing solely on humans competences. Machines can process information faster, and with the support of the neural networks can detect much more complex patterns. If we allow computers to help doctors to diagnose, they could use the saved time to focus on human factors, such as compassion and kindness. The Stanford University Center for Compassion and Altruism Research and Education ana-
