1. Your extensive background spans psychology, business, government, non-profits, academia, and entrepreneurship. How do you see these diverse experiences informing your perspective on the application of AI in healthcare? How can interdisciplinary thinking enhance AI's role in improving global health outcomes? Perhaps it’s a matter of perspective. I see AI as being best conceptualized as a tool, more so that a panacea or solution or easy button. When I first started out in clinical practice, I was very fearful of misdiagnosing someone as having a psychiatric condition rather than an endocrine disorder that presented with psychiatric symptoms. As a former math/computer science undergrad, I wrote a very, very basic program that would probabilistically “consider” the symptom presentation and suggest various non-psychiatric diagnoses to consider for referral to a specialist and/or lab test that could help point in a better diagnostic direction. It was more algorithmic than heuristic, and it was a tool, not an easy-button. As the question concerns the very broad “healthcare” ecosystem, and knowing that prediction is difficult especially about the future (a la Niels Bohr), and that what I write today stands a more than fair chance to be seen as naïve (at best) or wrong (at worst). What all of I think should be take with a grain of salt. So, having said that, I think AI will be a helpful accelerator in drug discovery. There is nascent work afoot as I write this, in the area for treating individuals with schizophrenia. There are a number of ChatBots already being used, but they are not without their bugs. GPT-2, and other natural-language algorithms like it, are known to embed deeply racist, sexist, and homophobic ideas. More than one chatbot has been led disastrously astray this way, the most
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