Three separate quotes from different parts of Nikhil Suresh’s “AI Mania Is Eviscerating Global Decision-Making” that work together:
But the broader reality is so much worse: people who have no background in the technology at all actually believe what they are saying. As a general rule you should avoid getting into business with a liar, but if you must, you can at least reason with them even if only in private. A true believer is much more threatening because they are impervious to even inducement by self-interest.
[…]
This is to say that we’re facing a coordination problem around executives being honest around the AI gains they’ve witnessed – if they co-operate, they keep their jobs. If they defect, they will possibly be fired by their embarrassed peers (who have now been implicitly called liars, cowards, or incompetents) and then replaced with someone that will toe the line anyway. If they could all admit the truth at once there might be some hope, but there is no way to coordinate that event.
[…]
The net result of this is that almost every large organisation that I am aware of is no longer able to focus on anything important, unless they are one of the (very) few organisations where AI happens to address their highest priorities. They cannot buy sensible software, hire competent talent, communicate honestly with executives about the state of projects, or undertake any sort of sensible initiative.
The whole thing is very much worth reading. (Those of you who read too many articles on the internet may remember his 2024 gem, “I Will !$%!!$% Piledrive You If You Mention AI Again”)
At least the cryptomania BS a few years ago was unintuitive enough that it was ignored by most businesses despite the desperate pivots and grifting. Adding a useless AI chat feature or calling your platform “AI native” is an easier sales pitch and management obsession than “It’s the same thing…but on the blockchain.”
Most leaders barely understand their own business, let alone the real impact of AI in recent years on their industry, the current contours of AI abilities, or the likelihood of purchased solutions and implementations maturing gracefully in a rapidly changing field. Most people don’t even know if the hard part of the job is generating the answer or verifying it. AI is magical, and yet we’re still firmly in the everyone-is-lying part of the hype cycle.
He writes a cogent summary in the middle of the article:
“Please dear God, do not let it be on earth as it is on LinkedIn.”