What's Your Problem?

Catherine Nakalembe is an assistant professor at the University of Maryland and the head of the Africa program at NASA Harvest, which uses satellite images to track agriculture around the world. Catherine’s problem is this: How do you predict when a famine is coming – and how do you convince leaders to act in time? In this episode, Catherine explains:  How satellite data can predict crop failure months in advance Why phots can convince decision-makers faster than maps or statistics Why imaging systems developed for US farmland often don’t work in Africa Why a half-page memo moves food trucks faster than a scientific paper Connect with us: Follow Jacob Goldstein on LinkedIn, X and Instagram  Email us at [email protected]  Follow Pushkin on Instagram, LinkedIn or X  Listen to Jacob’s other show, Business History  To listen to the show early and ad free, sign up for Pushkin+ See omnystudio.com/listener for privacy information.

Nir Barzilai is a physician and a researcher at the Albert Einstein College of Medicine in New York, where he runs the Institute for Geroscience. Nir’s problem is this: How can we use lifestyle changes and drugs to slow the process of aging? In this episode, Nir explains:  The search for biological markers of aging The existing drugs that might reduce the risk of diseases associated with aging The four key lifestyle factors that every researcher in the field agrees on What he learned by studying the genes of people who lived to 100 What “geroscience” means, and why it doesn’t have a Wikipedia page  Connect with us: Follow Jacob Goldstein on LinkedIn, X and Instagram  Email us at [email protected]  Follow Pushkin on Instagram, LinkedIn or X  Listen to Jacob’s other show, Business History To listen to the show early and ad free, sign up for Pushkin+ See omnystudio.com/listener for privacy information.

In 2016, Geoffrey Hinton, one of the inventors of modern AI, predicted that AI would replace radiologists within years. Ten years later, we have a shortage of radiologists. AI has yet to revolutionize the field. What happened, and what does the story of AI and radiology tell us about AI and the future of work? Saurabh Jha is a radiologist at the University of Pennsylvania. He's written about how he uses AI in his practice, and why radiologists have been slow to adopt AI. Saurabh has also traveled to India and Nepal to understand the very different ways AI is being adopted for radiology in the developing world. In this episode, Saurabh explains:  Why AI still hasn't made radiologists faster or more productive The risks of novice radiologists using AI versus the benefits to experts Why a successful AI model would need to be nearly perfect  How AI is being used to spot tuberculosis in India Why diagnosing a normal scan is harder than diagnosing disease Connect with us: Follow Jacob Goldstein on LinkedIn, X and Instagram  Email us at [email protected]  Follow Pushkin on Instagram, LinkedIn or X  Listen to Jacob’s other show, Business History  To listen to the show early and ad free, sign up for Pushkin+ See omnystudio.com/listener for privacy information.