The same also extends to surgical interventions, where a programmed robot may be able to outperform a human when it comes to conducting certain procedures. This analysis comes from Dr. Jörg Goldhahn, who works at the Institute for Translational Medicine at ETH Zurich, Switzerland. Goldhahn has made his points in an article in the British Medical Journal.
The reason that Goldhahn is making these points is because development with intelligent machines and their “near unlimited capacity” for data processing and subsequent learning, mean they can achieve things at speeds that humans cannot match.
Furthermore, greater amounts of data are being gathered, increasing rapidly the amount of collected knowledge and machines are adept at shifting through this and developing best practices. Much of this data is being drawn from health apps, personal monitoring devices, and electronic medical records.
In fact, there’s so much information emerging that no person could read and review everything pertaining to their area of interest. To this Goldhahn writes: “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.”
He also argues that machine learning is also not subject to the same types of bias that occurs with human learning, such as cultural influences. However, there are scores of research papers that point out the biases inherent in machine learning and artificial intelligence. Bias can arise from the mathematical property of an algorithm or the way a machine has been taught, such as echoing the stereotypes or prejudices of the programmer.
The greater use of machines is often countered by the importance of the patient-doctor relationship. While Goldhahn acknowledges this he remarks that machines and systems can be more trustworthy than humans. He also notes that many of the younger generation are used to, or even prefer, interacting with machines. Others would challenge that the relationship between doctor and patient cannot be replicated, such as medical doctor Ann Robinson who wrote about this subject in The Guardian recently.
Goldhahn further notes that machines can assist with medical training and have the potential to improve results and the quality of medical practice.
The article in the British Medical Journal is titled “Could artificial intelligence make doctors obsolete?”
