Hazel Tang A science writer with data background and an interest in the current affair, culture, and arts; a no-med from an (almost) all-med family. Follow on Twitter.
In the second part of an exclusive interview, Dr. Vimla Patel discusses gender inequality, her influences and the exciting future of AI and healthcare
Dr. Vimla Patel is a Senior Research Scientist and Director of the Center for Cognitive Studies in Medicine and Public Health at the New York Academy of Medicine. She is also an Adjunct Professor of Biomedical Informatics at both Columbia University and the College of Health Solutions at Arizona State University.
A cognitive science PhD graduate of McGill University in Montreal, she was a Professor of Medicine and the director of the Cognitive Science Center. An elected fellow of the Royal Society of Canada, and the American College of Medical Informatics, she was a recipient of the annual Swedish Women of Science award in 1999.
Her current research deals with the impact of technology on human cognition for safe and effective clinical practice. She has over 300 scholarly publications spanning books and journals in biomedical informatics, education, clinical medicine, and cognitive science.
Who’s been the biggest influence on your career?
Walter Kintsch, Professor and Director of Cognitive Science Institute at the University of Colorado in Boulder. He was one of my mentors when I was a graduate student. His insightful critiques of my work on medical text comprehension, using natural language processing, coupled with many hours of discussion, influenced my thinking about data and inferential processes to understand medical problems.
Herbert Simon, a Nobel Laureate for his work on economic game theory, also shaped my ideas in the context of diagnostic problem-solving in complex real-life clinical situations. He taught me never to be afraid of doing studies with small sample size, even n=1 and I never forgot that.
As I began to understand the relationship between my cognitive studies of medical expertise and expert and AI systems, I was influenced by the work of Bill Clancey and his knowledge-based tutoring system, NEOMYCIN and Ted Shortliffe and his work on the expert system, MYCIN.
Besides the academic guidance I received, my career was also built upon the initial support from my parents. My father gave me an opportunity even when he couldn’t afford it, and my mother taught me how to build resiliency through hardship, given all that she had endured as an immigrant in Fiji. These lessons follow me to this day, making me aspire to be the best at what I do and to do it with grace while seeking to be a female academic role model.
What’s the best piece of advice you’ve ever received?
One of my mentors, a well-known psychology professor, told me once that I should “buy low and sell high” when it comes to my research ideas. Don’t always travel the same road as others but take a risk and do something different even though it may conflict with the current thinking. It may be a difficult road in the short run but it will be intellectually rewarding in the long run. Brilliant advice!
What are you most excited about regarding the future of AI and healthcare?
Bringing together multidisciplinary ideas from the best minds in the field to understand what is required to develop AI systems that are not only efficient and effective, but also safer, while addressing the needs of the clinical practitioners in their complex practices.
Does the gender inequality in AI in medicine frustrate you? What can be done to readdress that?
It really frustrates me all the time. I believe the inequality comes at two levels. Generally, it is about the less than adequate representation of women in STEM, including medical AI – although this is changing gradually. There are relatively more women in some facets of science like medicine and biomedical research. There are also more women enrolling in engineering school and others working in cross-disciplinary works like medicine and AI.
Moreover, women are also under-represented in designing intelligent tools. Women are biologically and sociologically different from men. They design and build differently from men too. As such, if medical AI algorithms and models are to be designed and built solely by one gender, this might significantly disadvantage others’ lives, particularly if the developers fail to ask the right questions or attempt to simplify a complex world. Misinformed algorithms will only accentuate gender gaps.
One way we can make sure gender bias does not get amplified is to increase the role of women who participate in the dialogue by increasing the number of women in science and technology. Strong women mentors are needed to take young women under their wings and to assure them that what was traditionally considered a man’s world is no longer so, and they don’t have to think or act like men to belong. My advice for women is always do whatever you do and do it well, capitalizing on your strengths as a woman.
What else would you change in the world of AI and medicine?
The increase in computing power and the availability of large amounts of clinical data have made tremendous advances in the accuracy with which computers can perform medical tasks – including medical decision making, that was once considered to be the territory of human intelligence alone. But while AI technologies do have the potential to transform the practice of medicine, they are currently not all usable and useful.
A significant challenge, which I would like to see addressed, is to make sure that these AI systems can be used easily and effectively, without causing undue frustrations, and also be safe for the end users (doctors or patients) in complex and dynamic clinical practices, capitalizing on human intelligence. Never underestimate the human mind!
Part one of this wide-ranging interview can be read here
Don’t miss Dr Vimla Patel’s keynote address at AIMed’s Global Summit, live and in person in Laguna Beach, CA on January 18-20, 2022.
View the full agenda and book here.
