Webs We Weave Looks like SEC Chair Gary Gensler has been harboring some serious — as in, destroy-the-economy-level serious — AI apprehensions for some time now. As Axios reports, back in 2020, Gensler — still a professor at MIT at the time — penned a paper arguing that embedding an array of too-similar deep learning programs into our economic structures could stand to undermine those systems to the tune of a crisis-level crash. Coauthored alongside MIT engineer and computer scientist Lily Bailey, the paper contends that the “broad adoption” of AI could push economic systems to the point of deeply fragile uniformity and interconnectedness, which would leave our financial systems vulnerable to, say, a disastrous mass sell-off triggered by machine predictions. Our “existing financial sector regulatory regimes,” meanwhile, designed to manage now-outdated human-speed fintech and analytics, wouldn’t be able to keep up, leading to similarly consequential regulatory gaps. As AI “moves to a mature stage of broad adoption,” the authors wrote, “it may lead to financial system fragility and economy-wide risks.” Big gulp. Data Hegemony The paper is expansive, and among other reasons to fear model hegemony, Gensler and Bailey warn of the risk of data “crowding” and “herding,” or the reality that “models built on the same datasets are likely to generate highly correlated predictions that proceed in lockstep.” So, basically: if you train two models on the same data, those models can be expected to draw the same or similar conclusions. And if too many advanced models come…SEC Head Fears AI Could Cause a Financial Crash