Say I’m a company with 1000 employees. A company like anthropic is offering to replace each employee with some sort of agent. Suppose the agents cost roughly $80k, where an employee costs $100k. I take that deal because it saves real money and replace, say, 500 employees with agents.
Now let’s assume just for the sake of argument that these AI agents do exactly as promised and truly do replace those workers and all of their responsibilities. Things seem great, I decreased my costs a lot and my business is buzzing along.
Now anthropic comes to me and says they’re going to increase their prices to $100k/agent. What now?
Since you’re trading individual employees for a company that’s providing the service at a cost, it’s effectively like these agents are unionized, in a way. They ask for a raise and you don’t comply? Okay fine. No work for you. Nothing you can say or do will get these agents back
Not only that, anthropic can leverage the absolutely insane amount of data they have to squeeze you for everything you’re worth. They probably have actuaries on staff who can figure out the maximum possible amount they can charge you before you leave.
Going to a competitor is easier said than done. There’s a lot of underlying infrastructure with AI that needs to be changed and adjusted to make it work. Each model has its own strengths and weaknesses. So maybe, you go to a competitor and it’s back to 80k/year, but now, code has a 10% higher error rate and you start losing money
idk. it just seems like this desire to get rid of labor entirely can only backfire. This is one way, but there are so many others too.
Duplicated from source: https://www.reddit.com/r/trueantiAI/comments/1wj748w/wouldnt_using_replacing_employees_with_ai/
This is about timelines. In the short-term it’s a win, in the medium-term it’s a threat, in the long-term it’s potentially catastrophic. They need money now.
This sort of scenario assumes that these companies will always be in a stronger position. I don’t think that’s a given. The companies that plundered all data everywhere, torrented what was available, and reluctantly bought what couldn’t be stolen to train their models are being passed on the right by companies that just look to steal or copy their stuff (e.g. China is inferencing the hell out of them). The hostility towards data centers also forces more development away from centralised servers onto local environments. At the same time, stuff is also being released as open source. I think there is a big chance that the big companies and their models today will be mentioned in the first chapter on the history of this technology but will fall by the wayside rather quickly. Their market position is underpinned by a belief that in the future they will be raking in the dough on subscription fees once they get the dirty work of being started here financed, no matter how. That’s a mighty big bet. Not only is a bubble economy a problem, there is no guarantee to protect their “IP.” It’s really like investing in very expensive tulip bulbs.
Also, we don’t fully understand this technology. A lot of the experts don’t either. Anybody who says they’re pretty sure they know where this road will take us in the next five years has ulterior motives.