> we can fairly say that Hinton was wrong because his prediction did not reflect what a radiologist actually does: had Hinton bothered to ask the question, he would have learned that practitioners do much more than interpret diagnostic images.
This has been the crux, for me, of arguments I have had with non-technical people about why, as a software engineer, I am intensely relaxed about AI "taking human jobs". Recently Ford quietly started re-recruiting engineers after they discovered the hard way that their engineers had been doing more than they thought they had, and I sent articles about it to friends I had previously been discussing the matter with. It is still mind-blowing to me that a business historically famous for automating manual labour can have made this mistake, i.e. of literally not knowing what their staff actually do.
Humans aren't machines, who would have guessed? But, perhaps more importantly, machines aren't humans, and the adherence of a lot of domain experts (that should know better) to fairy tale fantasies about the tech they are literally building genuinely makes me wonder if the whole field has just gotten dumber in the 21st century.
> makes me wonder if the whole field has just gotten dumber in the 21st century
it's the finance system. It's affecting everything. We are building not to make money from clients but to please investors, who don't know anything about anything beyond a report every quarter and some random public comments you've never heard of that the press office made. So much money is controlled by stupid algorithms doing stuff like ctrl-f'ing the company quaterly report for mentions of "AI" or "agentic" (not a literal example, irl its thousands of random equally stupid metrics divorced from reality) that its distorting the market
Companies activities all revolving around getting a piece of the investment avalanche, so "we can replace employees" works both for the llm companies and for the companies whose workers are being replaced. Either way, its assumed this makes them more profitable. It probably will, at least in the short term.
And as we all know, there genuinely is a lot of waste and momentum in large companies, so you can cut half your employees, claim you're replacing them with ai, and actually replace them with nothing, and you'll still shuffle onwards for years or more, anything actually important people will keep doing, and the other stuff people will slowly stop. But this is trading off difficult to measure things like tech debt, security, compliance and brand strength that are slowly eroded for short term metrics, which is always a losing game in the long run.
Anyone sensible already knew that the core platform team was all that was needed to maintain the core platform, and the other teams were there for various other reasons, some of which were sensible and some of which were not. The key in business is presumably to identify which is which, but anyone claiming that process is easy or even possible without making costly mistakes is foolish
The key question is of course what happens when this happens all at once, to the whole economy. One company suffering from financialisation or enshittification means customers just go elsewhere. A whole economy doing it all at once results in major loss of trust, normalisation and legitimisation of scams, and collapse of empires.
This has been the crux, for me, of arguments I have had with non-technical people about why, as a software engineer, I am intensely relaxed about AI "taking human jobs". Recently Ford quietly started re-recruiting engineers after they discovered the hard way that their engineers had been doing more than they thought they had, and I sent articles about it to friends I had previously been discussing the matter with. It is still mind-blowing to me that a business historically famous for automating manual labour can have made this mistake, i.e. of literally not knowing what their staff actually do.
Humans aren't machines, who would have guessed? But, perhaps more importantly, machines aren't humans, and the adherence of a lot of domain experts (that should know better) to fairy tale fantasies about the tech they are literally building genuinely makes me wonder if the whole field has just gotten dumber in the 21st century.