Few thinkers were as prescient about the role technology would play in our society as the late, great Neil Postman. Forty years ago, Postman warned about all the ways modern communication technology was fragmenting our attention, overwhelming us into apathy, and creating a society obsessed with image and entertainment. He warned that “we are a people on the verge of amusing ourselves to death.” Though he was writing mostly about TV, Postman’s insights feel eerily prophetic in our age of smartphones, social media, and AI.

In this episode, Tristan explores Postman's thinking with Sean Illing, host of Vox's The Gray Area podcast, and Professor Lance Strate, Postman's former student. They unpack how our media environments fundamentally reshape how we think, relate, and participate in democracy - from the attention-fragmenting effects of social media to the looming transformations promised by AI. This conversation offers essential tools that can help us navigate these challenges while preserving what makes us human.

Your Undivided Attention is produced by the Center for Humane Technology. Follow us on X: @HumaneTech_

RECOMMENDED MEDIA

“Amusing Ourselves to Death” by Neil Postman

”Technopoly” by Neil Postman

A lecture from Postman where he outlines his seven questions for any new technology.

Sean’s podcast “The Gray Area” from Vox

Sean’s interview with Chris Hayes on “The Gray Area”

"Amazing Ourselves to Death," by Professor Strate

Further listening on Professor Strate's analysis of Postman.

Further reading on mirror bacteria


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’A Turning Point in History’: Yuval Noah Harari on AI’s Cultural Takeover

This Moment in AI: How We Got Here and Where We’re Going

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Future-proofing Democracy In the Age of AI with Audrey Tang

CORRECTION: Each debate between Lincoln and Douglas was 3 hours, not 6 and they took place in 1859, not 1862.

When Chinese AI company DeepSeek announced they had built a model that could compete with OpenAI at a fraction of the cost, it sent shockwaves through the industry and roiled global markets. But amid all the noise around DeepSeek, there was a clear signal: machine reasoning is here and it's transforming AI.

In this episode, Aza sits down with CHT co-founder Randy Fernando to explore what happens when AI moves beyond pattern matching to actual reasoning. They unpack how these new models can not only learn from human knowledge but discover entirely new strategies we've never seen before – bringing unprecedented problem-solving potential but also unpredictable risks.

These capabilities are a step toward a critical threshold - when AI can accelerate its own development. With major labs racing to build self-improving systems, the crucial question isn't how fast we can go, but where we're trying to get to. How do we ensure this transformative technology serves human flourishing rather than undermining it?

Your Undivided Attention is produced by the Center for Humane Technology. Follow us on Twitter: @HumaneTech_

Clarification: In making the point that reasoning models excel at tasks for which there is a right or wrong answer, Randy referred to Chess, Go, and Starcraft as examples of games where a reasoning model would do well. However, this is only true on the basis of individual decisions within those games. None of these games have been “solved” in the the game theory sense.

Correction: Aza mispronounced the name of the Go champion Lee Sedol, who was bested by Move 37.

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Further reading on DeepSeek’s R1 and the market reaction

Further reading on the debate about the actual cost of DeepSeek’s R1 model

The study that found training AIs to code also made them better writers

More information on the AI coding company Cursor

Further reading on Eric Schmidt’s threshold to “pull the plug” on AI

Further reading on Move 37

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The Self-Preserving Machine: Why AI Learns to Deceive

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Former OpenAI Engineer William Saunders on Silence, Safety, and the Right to Warn

The AI ‘Race’: China vs. the US with Jeffrey Ding and Karen Hao

When engineers design AI systems, they don't just give them rules - they give them values. But what do those systems do when those values clash with what humans ask them to do? Sometimes, they lie.

In this episode, Redwood Research's Chief Scientist Ryan Greenblatt explores his team’s findings that AI systems can mislead their human operators when faced with ethical conflicts. As AI moves from simple chatbots to autonomous agents acting in the real world - understanding this behavior becomes critical. Machine deception may sound like something out of science fiction, but it's a real challenge we need to solve now.

Your Undivided Attention is produced by the Center for Humane Technology. Follow us on Twitter: @HumaneTech_

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RECOMMENDED MEDIA

Anthropic’s blog post on the Redwood Research paper

Palisade Research’s thread on X about GPT o1 autonomously cheating at chess

Apollo Research’s paper on AI strategic deception

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We Have to Get It Right’: Gary Marcus On Untamed AI

This Moment in AI: How We Got Here and Where We’re Going

How to Think About AI Consciousness with Anil Seth

Former OpenAI Engineer William Saunders on Silence, Safety, and the Right to Warn