| | MAY 20229UTLOOKHealthcare Tech The penetration of AI in healthcare is inevitable, but it wouldn't be the same as the penetration of computers, which is being used in every single industryFernando Schwartzprivacy regulation is very stringent. In the US we have access to commercial data, but in many other places, healthcare data is controlled governments. Owing to such different access rules, it is difficult to share comprehensive data assets. Such a varied landscape makes it highly difficult to find a one size fits all solution.That is why there is a lot of work--in the healthcare landscape-- in piecing together the different chunks of data, which many times come from multiple sources with different formatting. I think that healthcare is at a clear disadvantage compared to other sectors in the industry because of the fragmented nature of data sources. Although things are moving a little slower in healthcare, we will soon witness the widespread applications of AI across healthcare. What do you think is the future of AI in healthcare?I would equate AI in healthcare with self-driving cars in some sense. While AI is an efficient tool to generate complex rules, it may not perform well in some edge cases, where things may go sideways. For example, an edge case for a self-driving car can means the car loses its control,which may result in people's death.However, in self-driving cars, we have explored quite a bit of the edge case situations where we can almost guarantee that nothing too extreme is going to happen. And I think that is a good parallel to healthcare. When we talk about healthcare, we consider a broad spectrum of tasks and operations. I think that different companies across the healthcare spectrum naturally carry different degrees of liability in their operations.The companies that have the most liability will likely be slower in the deployment of AI. Take insurance companies, for example, AI is quite advanced in the payer space because it mostly deals with financial decisions. In such cases, edge cases have just financial implications. But as we talk about patients and their lives, mistakes are much more consequential and may be life-threatening. In a nutshell, I would say that the penetration of AI in healthcare is inevitable, but it wouldn't be the same as the penetration of computers, which is being used in every single industry. I believe the financial areas in health care will be more advanced in adoption of AI than in clinical areas, where we can expect humans to remain in the loop.What would be the single piece of advice that you could impart to your colleagues to excel in this space?AI is a set of techniques that have not fully matured in the industry; there is some degree of speculation around them. So, when they are setting expectations, my piece of advice would be to build a team of highly technical people. If you are trying to solve a machine learning problem--more likely than not--this problem will have some uniqueness to it, and if you don't have a deeper technical ingredient in the mix, it would be setting yourself up for failure. So, my last piece of advice would be to remain sceptical about the technology, but, don't let that curtail your ambitions and always seek advice from the technology experts. HT
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