A great summary of AI cross currents. You touch on it towards the end but I think AI progress may be slower for the simple reason many people DO NOT WANT IT. You note job satisfaction going down among scientists using it, and also that scheming is going up. Suppose a new technology is A. a direct threat to your job, B. a direct threat to your sense of meaning, and C. possibly a direct threat to your life (until scheming is fixed-and I've heard of no way to address that any more than they've fixed hallucinations). That's a trifecta of powerful motivations not fully appreciated by the tech bros building AI. IMO, the more they push to get it everywhere, the more quiet anti-AI backlash will gain steam. A large majority of US people are already suspicious of AI-with good cause. If AI progress is measured by benchmarks in labs (which are routinely gamed, and a great reason not to take AI labs at their word), then AI progress is accelerating. If you measure it by how many AI integrations actually work in businesses that try them, the success rate is dismal. And I'd argue the trifecta of strongly opposing motivations plays a significant part in those failures. https://www.cio.com/article/3617614/cios-lack-of-success-metrics-dooms-many-ai-projects.html
A great summary of AI cross currents. You touch on it towards the end but I think AI progress may be slower for the simple reason many people DO NOT WANT IT. You note job satisfaction going down among scientists using it, and also that scheming is going up. Suppose a new technology is A. a direct threat to your job, B. a direct threat to your sense of meaning, and C. possibly a direct threat to your life (until scheming is fixed-and I've heard of no way to address that any more than they've fixed hallucinations). That's a trifecta of powerful motivations not fully appreciated by the tech bros building AI. IMO, the more they push to get it everywhere, the more quiet anti-AI backlash will gain steam. A large majority of US people are already suspicious of AI-with good cause. If AI progress is measured by benchmarks in labs (which are routinely gamed, and a great reason not to take AI labs at their word), then AI progress is accelerating. If you measure it by how many AI integrations actually work in businesses that try them, the success rate is dismal. And I'd argue the trifecta of strongly opposing motivations plays a significant part in those failures. https://www.cio.com/article/3617614/cios-lack-of-success-metrics-dooms-many-ai-projects.html