Shared Wisdom summary

Stories are the basis of human advancement. That’s why, throughout history, humanity's greatest leaps forward came after technologies improving how we share stories. Three major innovations have transformed our trajectory in this regard.

First, regular gatherings created spaces for communities to exchange experiences daily. While it may seem intuitive now, hunter-gatherer bands sitting around campfires at day's end to swap information wasn't instinctive behavior but a learned social practice. Yet it dramatically accelerated how quickly useful knowledge spread through a group.

Think about how your country is governed. If you live in a Western democracy, you probably elect representatives who make decisions on your behalf, right? Even though that seems progressive on the surface, here's an uncomfortable truth about these systems: they still function remarkably like the elite-run systems of ancient Rome. We've just gotten better at hiding it.

When Japan opened up to the West in the late 1870s, the Japanese rulers were dismayed that the Europeans considered their feudal system to be “barbarian”. They also recognized that British and American democracies were essentially run by wealthy families too. So they devised an elegant workaround by simply changing the vocabulary of their governance, turning “fiefdoms” into “companies” and “serfs” into “lifetime employees”. Suddenly, Japan could present itself as a modern democracy that fit right in with the Western world–without actually changing who was in charge.

There’s plenty of room to imagine how new technologies like modern AI could solve society's problems. But if we actually want to make it happen, it’s just as important to look at how past technologies have exacerbated our problems. 

Since the 1950s, we've seen three major AI booms, each following a troubling pattern. The technology worked brilliantly for specific tasks—optimizing delivery routes, automating loan decisions, personalizing search results. Yet beneath these successes, they began to slowly erode the social fabric.

AI bears as many risks as it promises rewards. And as we’ve seen, our democracies and bureaucracies weren't built for the digital age. They're stuck using ancient organizational models to solve twenty-first-century problems—and it shows. Trust in government has collapsed from 80 percent in 1960 to under 20 percent today. Communities feel powerless, managed by distant professionals who don't understand local needs.

But even the most rigid institutions can transform when they embrace distributed decision-making. Take the US Army in 2003 Iraq. Facing nimble guerrilla forces, the traditional command-and-control structure simply couldn't keep up. General Stanley McChrystal made a radical move: he created "teams of teams", empowering frontline units to make their own decisions based on the commander's overall intent, not rigid orders. Using digital networks to share information instantly, the Army became genuinely agile.

When world leaders gathered at the Club de Madrid two years ago, a fascinating split emerged. Senior EU regulators pushed for rigid, top-down control of AI–new laws and bureaucracies tailored to each technology type. But the former presidents and prime ministers saw things differently. They advocated for something simpler: audit trails and liability rules. Let companies innovate, but hold them accountable when things go wrong.

This disagreement captures our fundamental challenge with AI regulation. We're tempted to predict and prevent every possible harm before it happens. But AI evolves too rapidly and comes in too many forms for this approach to work. The instinct for control can override practical wisdom.