The beauty of writing in public
October 2025
One of my favorite parts of writing publicly is that it acts like a beacon, attracting unexpected and fascinating conversations.
Case in point: a few weeks ago, Dr. Susan Schneider — the philosopher, author, and cognitive scientist — emailed me in response to a recent newsletter I had written. Her message turned into a phone call, which then developed into a deep and unexpected exchange about the real risks of AI.
Susan and I ended up shaping that conversation into a recent Long Game column for Big Think, where Susan introduced me to some of her latest work, focusing on the “megasystem problem”: networks of AI systems colluding in ways we can’t anticipate. Her perspective is fascinating, and it’s exactly the kind of conversation I hope this newsletter continues to spark.
Key quote: “The deeper issue is uniformity of thought. These systems can test your personality with startling accuracy. Combined with your chat history and prompts, the model nudges you into particular ‘basins of attraction.’ You think you’ve had an original idea, but you haven’t. The model blends and regurgitates existing material. Multiply that across millions of users and intellectual diversity collapses. John Stuart Mill argued that diversity of opinion sustains democracy. If AI funnels us all into the same conceptual pathways, we lose that.”
How the Army learned human creativity beats computers
I recently shared my conversation with Angus Fletcher — a brilliant thinker on creativity, storytelling, and why human imagination still matters in an age of machines.
His latest Big Think piece makes the case through an unlikely story from World War II. In the 1940s, the U.S. Army built ENIAC, the world’s first general-purpose computer, believing it could calculate the future. But then they studied Gabby Gabreski, a fighter pilot who became America’s top ace precisely by being unpredictable — breaking rules, improvising, surprising the enemy.
Study of Gabreski led to an understanding of convergent thinkingand divergent thinking, the two pillars of ideation, which can be automated by computers as the basis for generative AI. But, it was discovered, ideation “didn’t work” in the real world of practical creativity.
The bottom line, as revealed by Fletcher and his team, was that “human creativity is driven by mechanical processes that are natural for animal neurons — yet can’t be performed by any known arrangement of electronic transistors.” In other words, the future belongs to human originality, not computation. AI will accelerate, but human creativity remains the decisive advantage.
Key quote: “Perhaps, in time, human engineers will build an artificial brain capable of performing this exercise. (That artificial brain won’t be a computer; it will require the invention of narrative-competent hardware that incorporates the synapse’s nonelectronic architecture.) Until then, however, your best chance at beating your competitors is to learn the lesson of the US Army: computer AI is only partly smart. No matter how quantum, neurosymbolic, or sentient the ENIAC, human creativity remains the future.”
A few more links I enjoyed:
Key quote: “Now, the uncomfortable question this raises is: how many people are being medicated to function in environments fundamentally incompatible with their neurobiology, when restructuring those environments might address the root cause? Sure, not everyone can become self-employed or redesign their career. But asking the question challenges our reflexive reach for the prescription pad.”
Key quote: “Ek presents a provocative and powerful core philosophy: happiness is a trailing indicator of impact. He argues that the pursuit of happiness as a primary goal is often a trap, leading to a state of mere ‘contentment’ rather than true fulfillment… True happiness is not a feeling to be chased but a reward earned through meaningful and impactful work. This reframes ambition from a selfish pursuit to a generous act of creation.”
