Could generative AI could turn out to be the tech industry’s Vietnam? And could public backlash lead AI to a better place?
We live in interesting times
As I am sure you have heard by now, the backlash against AI i keep nattering on about is growing fast. At least three commencement speakers, include Google’s one time CEO Eric Schmidt were booed over the last few days simply for mentioning AI.
This lead Jason Calacanis (of All In) to draw a parallel
But I think the analogy might run deeper. And Jason may be underrating the student’s chances here (see later part of this essay).
In the Vietnam war, the US invested massively in a huge, disastrous campaign that drained resources and achieved nothing, fueled by arrogance. The war moved forward for years despite evidence that it wasn’t working as planned. It was also ridiculously expensive, about a trillion in today’s dollars.
Could the multitrillion dollar investment in AI, burning money at unprecedented rates, and still struggling with hallucinations, unreliability and misalignment – even after truly massive investments, turn out to be another epic arrogance-fueled mistake?
Every time I think about the numbers and lack of RoI for most pilot studies and the reliability problems I think so. (Discussion in the comments below would be welcome.)
But here’s something else interesting. In my Politico “Black Swan” prediction for 2026 year, from January I made the seemingly wild prediction that,“By the end of 2026, President Trump will have begun to distance himself from the aggressively pro-AI industry policies that characterized his AI strategy in 2025”
Suddenly that notion looks like it has legs, far sooner than I expected.
As you may have seen, in a total turnaround, and perhaps prompted by fears over Mythos, Trump is now actively considering the kind of AI preflight check that Michelle Rempel Garner and I recommended here three years ago. (We urged that “applications of AI could be governed similarly to [FDA], with authorities set up to evaluate and regulate the release of new major applications based on carefully-delineated evidence of safety.”, which is pretty much what is under consideration now).
The great Trump AI repositioning that I forecast may have begun!
Things are changing fast.
And if the backlash has enough force behind it, Trump may move further away from last year’s anti-regulatory policies.
As I argued at the end of Taming Silicon Valley, which I hope you will read or reread now that is so directly relevant, if the people unite, we might actually be able to get AI to a better place.
The Vietnam analogy is more structurally precise than Calacanis intended. Vietnam's specific failure mode was a metrics problem. The US measured progress with body counts and territory captured while the actual situation deteriorated underneath. The numbers told a story of winning while the ground truth was losing.
AI is running the same divergence right now. Benchmarks keep climbing. Leaderboard scores improve quarterly. But enterprise pilot ROI keeps failing to materialise and the political coalition that funded the buildout is fracturing in real time. The industry is measuring capability while the market needs reliability, and those two metrics diverged about two years ago. Thats the gap where backlashes form.
The students are not confused. They are looking at a society willing to spend effectively unlimited sums of money, energy, land, water & political will to build data centers so machines can produce simulations of human-produced works of art, while that same society tells them affordable housing, stable work, and a decent life are somehow unrealistic demands.
This is why Silicon Valley and its broader ethos is the least innovative social force in history.