Jörg Goldhahn, MD, MAS, deputy head of the Institute for Translational Medicine at ETH Zurich, Switzerland says that artificial intelligence systems simulate human intelligence by learning, reasoning, and self correction. This technology has the potential to be more accurate than doctors at making diagnoses and performing surgical interventions. It has a “near unlimited capacity” for data processing and subsequent learning, and can do this at a speed that humans cannot match.Increasing amounts of health data, from apps, personal monitoring devices, electronic medical records, and social media platforms are being brought together to give machines as much information as possible about people and their diseases. At the same time machines are “reading” and taking account of the rapidly expanding scientific literature.”The notion that today’s physicians could approximate this knowledge by keeping abreast of current medical research while maintaining close contacts with their patients is an illusion not least because of the sheer volume of data,” says Goldhahn.Machine learning is also not subject to the same level of potential bias seen in human learning that reflects cultural influences and links with particular institutions, for example.
“Computers aren’t able to care for patients in the sense of showing devotion or concern for the other as a person, because they are not people and do not care about anything. Sophisticated robots might show empathy as a matter of form, just as humans might behave nicely in social situations yet remain emotionally disengaged because they are only performing a social role.”
“Patients need to be cared for by people, especially when we are ill and at our most vulnerable. A machine will never be able to show us true comfort,” they say.