A.I. Predictions Failing To Come True

· Reason

Right/wrong: "A year ago, the message from many business leaders was that AI was going to wipe out jobs. For the past month or so, tech CEOs have been striking a more optimistic tone," reports The Wall Street Journal's Katherine Bindley, citing OpenAI CEO Sam Altman's comments several months ago that "we've been roughly right on technological predictions and pretty wrong on the social and economic implications."

It's not clear whether Altman, and his rival/counterpart Dario Amodei at Anthropic (who recently went from warning that half of entry-level jobs could be demolished to citing how firms can "do the same thing with less resources"), are toning down their predictions because they're trying not to alarm people, because they were in fact somewhat wrong, or because, a year-plus ago, they were trying to build additional hype in the arms race. Maybe all of the above.

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Of course, all of this will be hard to untangle in the future. Tech CEOs love blaming layoffs on A.I., when sometimes that's not the case at all.

"This isn't just about efficiency," Jack Dorsey told shareholders in February, announcing that he was cutting his workforce over at Block by half. "Intelligence tools have changed what it means to build and run a company….A significantly smaller team, using the tools we're building, can do more and do it better." Maybe that's true, or maybe a bunch of people just didn't seem to be creating much value. When Brian Armstrong cut his workforce at Coinbase down, he explained it like this:

As for the A.I. CEOs, "they may have noticed that the labor market is genuinely not changing (i.e., imploding) as rapidly as they expected," the MIT economist David Autor told the Journal. "They may have realized it was simply bad business to say that your great new product will destroy the economy." And CEOs of other firms that have deployed A.I. tools but are not developing A.I. models seem to, in many cases, be having a hard time figuring out which deployments are actually reaping rewards vs. which are wastes of time. Figuring out which jobs can be successfully automated and which can't involves some amount of trial and error, pedaling and backpedaling. It's not necessarily as obvious as some initially made it out to be.

So far, some of the biggest transformations have been for coders. Becoming a computer programmer/developer/software engineer had long been a wise route if you had the technical skills to handle it. Some coders are profoundly helped by A.I. advances, and some amateurs are brought up to a higher level by A.I.-assisted coding. Even a wordcel like me can vibecode (badly) nowadays. To some degree, this industry is going to be made way better and more efficient, brought up to a higher level, by A.I. assistance. But some number of coding jobs may be lopped off, and a sector that once was thought of as safe and high-paying may plagued by instability. (I, for one, am afraid of that future, not because of high levels of disruptions in the economy but rather because I fear many developers happen to be libertarians, and that the spicy comments section on each Reason Roundup might explode. Lord help us.)

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