I keep seeing the "Productivity Paradox" highlighted over an over again. I think one thing people are missing with this specific technology is that unlike many of the comparisons (computers, internet, broadband, etc), AI in particular doesn't have a high requirement at the consumer side. Everyone already has everything they need to use it.

There will be a period like we are in now where dramatic capability gain (like recent coding gains) take a while for people to adapt to, however, I think the change will be much faster. Even the speed of uptake in coding tools over the last 3 months has been faster than I predicted. I think we'll see other shifts like this in different sectors where it changes almost over a series of a few months.

I would argue that the leadership and financial support behind AI (in its current form) does not have the patience or level-headedness to treat it as a long-term change, and is very much trying an all-or-nothing approach to making a long shift happen in a few years instead, or burn through nation-level budgets trying.

To my eyes, the problem is not the productivity gain arriving slowly, but the immediate draining of funding from virtually all other areas of innovation.

This isn't new.

"The Productivity Paradox" is what they called it when people were skeptical that computer would end up finding a place in the office. There are articles from the 90s complaining about how much people are spending on buying computers for no real impact on productivity https://dl.acm.org/doi/10.1145/163298.163309

Even the source article in the first link, https://www.nber.org/papers/w34836

the same firms "predict sizable impacts" over the next three years

late 2025 was an inflection point for a lot of companies

Seems like it’s an ever shifting goalpost when we are told that tons of layoffs etc are already happening due to the tech and yet when quantified it’s debatable if there’s been any gains at all

I'll take it over seemingly endless deluge of FUD-slop from the past 4 years that claims you better get ready for the AI takeover coming for all the jobs in just-long-enough of a timeline that nobody will remember to hold the author accountable when their prediction is woefully incorrect, where the "advice" in the article is conveniently to pay for more AI tools.

All of the technologies mentioned eventually made things better. In order to work, gen AI requires a general acceptance of widely spread mostly mediocre outcomes. I don’t see how the comparison stands.

How to reconcile this with all the narratives of how powerful AI is, how it can perform right now at the same level of engineers and so on?

Once confronted with reality we have a "productivity paradox"?