Before 1450, books were written out by hand. It was slow and expensive. But Johannes Gutenberg borrowed a ton of money to create a printing press that could crank out Bibles and pamphlets and documents in huge numbers. Science, politics and philosophy were all up-ended. 

For example, the Catholic Church seized on the invention to sell special certificates absolving people of their sins – a move that made money, but caused a permanent schism in Christianity.   

And Gutenberg too found himself in trouble – when a financier sued the inventor to reclaim his loan, plus interest. 

Enjoy this episode from Business History, another Pushkin podcast. 

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Everybody’s worried about the risks of AI. So we called up one of the most insightful writers we know on the subject: Zvi Mowshowitz. Zvi writes about AI and AI risks at his substack, Don’t Worry About the Vase. Zvi’s problem is this: How do we prevent artificial intelligence from killing everyone? 

In this episode, Zvi explains: 

• Why it’s often useful to anthropomorphize AI 
• What this summer’s Hugging Face attack tells us about the nature of AI
•  What increasing AI capability means for cybersecurity risk
•  Whether and when we should pause AI development
• Why powerful pen-weight models may remove the last reliable points of control

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• Follow Jacob Goldstein on LinkedIn, X and Instagram 
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On this bonus episode of What’s Your Problem, Jacob talks to Christine Chase, a Vice President, Financial Consultant at Fidelity Investments. Christine’s problem is this: How do you help clients build a plan to achieve their financial goals? Today’s show is sponsored by Fidelity Investments.

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The fish we eat usually die slowly, suffocating after they’re pulled out of the water. Saif Khawaja is the co-founder and CEO of a company called Shinkei. Saif's problem is this: Can he build a machine to efficiently kill fish in a way that is more humane?

In this episode, Saif explains: 

• How he came to believe that our current fishing practices are inhumane 
• How he adapted the Japanese technique of  ikijime for use at scale 
• Why Shinkei’s process results in better texture and longer shelf life than commodity fish.
• Why Shinkei is doing its own technology development, fish processing, and consumer branding. 

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• Follow Jacob Goldstein on LinkedIn, X and Instagram 
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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

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When Dr. Lara Jehi began treating epilepsy patients in the 2000s, critical surgical decisions were driven more by clinician intuition and expertise than data. Today, she is a leader of IBM and Cleveland Clinic’s Discovery Accelerator, using advanced AI and quantum computing to transform how researchers analyze data, simulate molecules, accelerate drug discovery, and develop more precise treatments. Malcolm Gladwell talks with Dr. Jehi about how quantum computing is changing biomedical research, and what these breakthroughs could mean for the future of healthcare and life sciences.

This is a paid advertisement from IBM. The conversations on this podcast don't necessarily represent IBM's positions, strategies or opinions.

Visit us at https://www.ibm.com/think/podcasts/smart-talks

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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 

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Helen Pearson is the author of the book “Beyond Belief: How Evidence Shows What Really Works.” Helen's problem is this: How do you get people to make important decisions based on high-quality evidence, instead of on hunches or habits?

In this episode, Helen explains: 

• How a doctor's fatal mistake sparked the evidence-based medicine movement
• Why management is so resistant to evidence-based practices
• How systematic reviews changed the way she works as a science journalist
• Why global trust in science remains high – outside the US
• What a randomized trial of pint glasses revealed about preventing violent injuries.

Check out Helen’s book here. 

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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

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After spending decades as marginal players in the global auto industry, Chinese carmakers have become the world’s biggest exporters of cars. Chinese cars are some of the best cars on the planet, and they’re available almost everywhere – except in the US.

Michael Dunne is the CEO of Dunne Insights, a company that consults on the future of cars. Michael has been working with the Chinese auto industry since 1990. I talked with Michael about how China did it. The problem we discussed was: How can the United States catch up with the Chinese auto industry?

In this episode, Michael explains: 

• How China went from making terrible cars in 1990 to dominating global exports today
• Why China bet big on electric vehicles when nobody wanted them
• How Tesla's arrival in China revolutionized their EV industry 
• Why losing the car industry would be a national security problem for the US
• Why the future of a successful American auto industry is on the West Coast

Connect with us:

• Follow Jacob Goldstein on LinkedIn, X and Instagram 
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• Listen to Jacob’s other show, Business History 
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