Great Intellectual Fraud

I was unsettled when Mandelbrot boldly declared normality as the "great intellectual fraud." He did not mince words in criticizing the revered Carl Gauss, whose work on normality dominated 19th-century mathematics. Mandelbrot's dissent stemmed from a fundamental observation: since the 1920s, J C Willis' work and later discoveries revealed another pervasive pattern in nature—non-normality. This was evident in language (J B Estoup 1916), aristocracy (Bienaymé 1845), wealth distribution, genetics, species populations, brightness and power, polymers, and more. Mandelbrot, focused on understanding nature, saw preferential attachment (another name for non-normality) as a universal law and dismissed normality with disdain.

The Information Age is built on the foundation of preferential attachment. Not nine algorithms, but one algorithm, underpins our era: the "rich get richer" principle. Search engines, neural networks, large language models (LLMs)—all echo this law. Even $50T passive investing and market-cap-based indexing reflect the same winner-takes-all dynamic. Capitalism itself is deeply rooted in this principle.

We’ve applied this natural law to create transformative tools. A language model passes the Turing test, capturing the world’s imagination. Indexing information by popularity powers trillion-dollar search engines. Neural networks, reframed as richer nodes in a system, revolutionize image recognition under the banner of artificial intelligence. To support this generative information boom, we’ve leaned on ever-stronger computation, fueling the computational revolution.

But this translation of nature's behavior into statistical law is where the problem begins. Mandelbrot wasn’t alone in struggling to explain preferential attachment; physicists, too, have been critiqued for their cyclical rediscovery of the "rich get richer" phenomenon. To this day, there’s no definitive explanation for why the law works—or how nature occasionally defies it. Schr?dinger famously asked this in What is Life?, invoking Maxwell’s demon. How does nature escape its own rule?

Why are these questions urgent now? The Information Age has created extraordinary complexity, mirroring evolution itself. But unlike nature, which adapts around complexity, humanity finds itself building better mousetraps while the mice vanish. We’ve exploited the algorithm, churning out more information than we can ever process, reaching a dead end that we mistakenly label as intelligence.

What’s the way forward? Here’s the beautiful twist: the rich don’t always get richer, and first-mover advantages don’t last forever. After a century of preferential attachment, we find ourselves burdened by escalating complexity. The challenge for modern science is to transcend it. When that happens, LLMs and neural networks will likely be relics of the past, replaced by something fundamentally different. The world will have moved beyond the computational age. Imagine that—Clarkian magic transforming us into a truly intelligent world, far removed from today's constraints, beyond the spin of fraud.

Bibliography

1. Mandelbrot, Benoit. The Fractal Geometry of Nature. W.H. Freeman and Company, 1982.
2. Mandelbrot, Benoit B., and Richard L. Hudson. The (Mis)Behavior of Markets: A Fractal View of Risk, Ruin, and Reward. Basic Books, 2004.
3. Gauss, Carl Friedrich. Disquisitiones Generales Circa Superficies Curvas. 1827.
4. Willis, J. C. Age and Area: A Study in Geographical Distribution and Origin of Species. Cambridge University Press, 1922.
5. Simkin, M.V. Roychowdhury, V.P., Re-inventing Willis, 2006
6. Schr?dinger, Erwin. What is Life? The Physical Aspect of the Living Cell. Cambridge University Press, 1944.
7. Newman, M.E.J. "The Structure and Function of Complex Networks." SIAM Review, vol. 45, no. 2, 2003, pp. 167–256.
8. Pal, M. "The Snowball Effect", SSRN, 2022