It’s interesting that people claimed the exact same thing when computers were being introduced to the work place int the 80s and 90s. Lots of papers showing how productivity didn’t go up at all and using a paper and pen seems to be just as efficient as using a PC.
Even in the 19th century, when electricity became widely available, there was no productivity gain for 30 years at least. This is a well understood phenomenon.
Ah you must be referring to this off the cuff comment by Robert Solow in a book review: "You can see the computer age everywhere but in the productivity statistics" (1987)
It's an interesting question and very much not resolved. It indeed led to a flurry of studies in the 1990s, and more recently to several updates and meta-analyses.
The problem of "does computer technology investment causes increased productivity" is an interesting issue in economics and statistics. It is far from clear that the (immense) investment in computers over the past several decades has caused a corresponding excess growth in productivity.
Some of the literature published after 2015 that I have read on this topic:
"Information technology (IT) productivity paradox in the 21st century"
> Thus we are still unable to confirm or reject the existence of an IT
productivity paradox
"Benchmarking the IT productivity paradox: Recent evidence from the manufacturing sector"
(This one was published in 2006 but I find it relevant because it does a very well scoped analysis in manufacturing firms thus addressing the oft-mentioned argument that computer technology may leverage task productivity in a way that is hard to measure in aggregate)
> However, many scholars from both sides of the IT paradox debate agree that difficulty still exists in specifying how to assess the IT contribution, and the availability of reliable data sets
> Regardless of the final decision to differentiate or conform, our results make a compelling argument that more spending does not necessarily mean better IT productivity.
"Lessons from three decades of IT productivity research: towards a better understanding of IT‑induced productivity effects"
(This is one of the most inclined to disagree with the existence of the paradox, and still very cautious in the language used for writing the conclusion, e.g.:)
> But to not at least consider the ongoing technological change as an important determinant of the deceleration in productivity growth seems ill-advised."
(This I'm quoting from the submitted manuscript. I haven't gotten around to reading the published version yet, but:)
> Since the size of the effect helps make the right decision in business-related investments, our result of ICT elasticity being very close to zero with values, about 0.3% for productivity and no effect on profitability, supports the argument that there are better forms of investment to be made
This is just ~2 - 4 years after ChatGPT launched, and despite very shallow adoption (only ~6% of all work hours.) As a sibling comment indicates, it took almost 2 decades for the Computer Revolution to be visible in national level statistics.
Also note this study was originally published in 2024, then revised in 2025, but this preliminary evidence has been around for a while, if people wanted to find it. It's even been posted to HN a couple of times, somehow it just doesn't get the attention you'd think it should get, even if it was just to poke holes in the conclusions.
> Since the release of ChatGPT in late 2022, artificial intelligence (AI) has been widely expected to raise productivity. But aggregate productivity data have so far offered a more muted signal: Utilization-adjusted total factor productivity grew only 0.07% over the four quarters ending with the first quarter of 2026
> When we feed these estimates into a standard aggregate production model, this suggests that generative AI may have increased labor productivity by up to 1.3% since the introduction of ChatGPT. This is consistent with recent estimates of aggregate labor productivity in the U.S. nonfarm business sector. For example, productivity increased at an average rate of 1.43% per year from 2015-2019, before the COVID-19 pandemic. By contrast, from the fourth quarter of 2022 through the second quarter of 2025, aggregate labor productivity increased by 2.16% on an annualized basis. Relative to its prepandemic trend, this corresponds to excess cumulative productivity growth of 1.89 percentage points since ChatGPT was publicly released
These long term data suggest that this "excess" remains bellow historical productivity growth
The analysis bellow, more recent than the one you pointed to, is from May 2026, and an even stronger argument to support your position on the side of "computer technology investment caused a delayed excess growth in productivity". And as you can see at the end of my comment, they still write a very tentative conclusion.
To be clear: I do not take a position. I think this is an open question, a very important one, and I am not fully convinced that the exponential growth in the investment on computer technology over the past 50 years has led to a corresponding gain in productivity, nor that it is entirely a drag and a mechanism for increasing firm size and driving asymmetric profitability concentrated in ever fewer firms as the increased concentration in the capitalization of American stock market index composition would indicate.
That said, the strongest case I have seen for the position that we are beginning to see these delayed gains is the letter I linked above, and it still takes care to conclude:
> As more data become available, it will be important to continue to monitor whether current patterns represent the early stages of a new era of booming productivity or merely a temporary uptick in an otherwise slow-growth environment.
> These long term data suggest that this "excess" remains bellow historical productivity growth.
That's partly because we are discussing productivity growth. Today's productivity growth is on top of the substantial productivity improvements that have been compounding due to past booms like the Computer and Internet one. So in relative terms the growth looks modest, but in absolute terms this is substantial.
Also that BLS chart is a bit unhelpful because it shows time periods covering multiple years and does not isolate the years after ChatGPT launched, which is what the St. Lous Fed looks at and finds interesting indications. Like currently productivity growth is 1.3 percentage points above what was forecasted just before ChatGPT was released. This discrepancy is not fully explained by other factors and lines up with other data sources related to the effects of AI.
The letter you linked is relevant, but it is trying to make a much broader point than I am. Note that:
1) it's asking whether we have entered a "high-growth regime" meaning a period of sustained productivity growth, and itself points out that it necessarily requires years to play out; and
2) its point of reference is the 90s when the computer revolution had truly kicked in after almost two decades of adoption starting in the mid/late-80's, during which any impact was famously hard to find: https://en.wikipedia.org/wiki/Productivity_paradox
So what is astounding is that the effects of the AI revolution may be visible in national-level economics data after only 2 - 4 years since the technology was introduced, and we're already wondering if we have shifted into a "high productivity growth era"!
I'm sorry I don't understand what you mean when you discriminate productivity growth from productivity improvement.
> So what is astounding is that the effects of the AI revolution may be visible in national-level economics data after only 2 - 4 years since the technology was introduced, and we're already wondering if we have shifted into a "high productivity growth era"!
I feel compelled to repeat the conclusion from the letter I linked. I used it as an example of how much of an open contention the productivity-from-computer-technology issue remains
> As more data become available, it will be important to continue to monitor whether current patterns represent the early stages of a new era of booming productivity or merely a temporary uptick in an otherwise slow-growth environment.
I wasn't trying to differentiate between growth and improvement, I meant to use them interchangeably, apologies for the confusion. What I meant is the relative amounts in the BLS chart are prone to being misinterpreted because that growth is compounding and the time periods depicted don't correspond to the time period we are interested in.
I realize the findings from these studies are tentative; in such a short timeframe such conclusions have to be. But I don't really see much open contention regarding the key question here, which I think is "Has AI had an impact on national level labor statistics?"
E.g. the conclusion you quoted simply says that it is not clear if this is a temporary uptick or a sustained boom. But it agrees that there has been a significant positive impact on labor productivity already, even if the impact on TFP is more modest. Which is what the St. Louis study looking at survey data, and corroborated by various other data sources, finds too.
If the question is whether this is a sustained "productivity boom", I agree that we don't know that yet. But if the question is whether there has been any productivity impact at all, I would say there are multiple indications of that.
You are focusing too much on an informal letter. There are lots - I am talking dozens - of peer-reviewed papers discussing the so-called "productivity paradox"
There is a lot more to this discussion than one time series from the BLS, I have linked just 4 that are worth skimming elsewhere in this thread.
I am not trying to prove a point one way or the other. The topic interests me and there is a lot of analysis available on the problem of finding the productivity growth in economic data corresponding to the ever increasing investment in computer technology.
To me it is clear that it is an open problem, and the literature available is a great reflection on statistical methodology in economics.
> But if the question is whether there has been any productivity impact at all, I would say there are multiple indications of that.
That is indeed the question, and I have not found one paper that conclusively states that there is clear evidence or clear absence of a measured statistical effect.
Once the previous goalpost gets demolished on HN, there's always someone new to put a new one. We aren't quite there yet but eventually the goalpost moves to something that is just impossible to even measure. That'll be the end game surely
1. the metrics you mention are hard to measure and usually lag
2. the metrics might not be moving yet, because AI accelerates everything a little bit, and most of the hype is still the promise rather than the actuality
3. people are using the gained productivity to speed up secondary tasks / do different work, because applying it to their main work is still complex or not of sufficient quality
Considering the amount of literature I have found and read on this topic so far, covering 30 years of analysis specifically in the context of productivity driven by investments in computer technology, and using data covering 130 years of economical statistics, its methodology and limitations, I am deeply skeptical of any 3 point dismissal of this problem as being easy to explain away such as your own.
I said elsewhere, I don't have any beliefs about this problem, I am deeply fascinated by the difficulty involved in productivity analyses and especially by the question of missing productivity that we should expect to be driven by the huge investments in computer technology that have been observed over the past half century - and quickly accelerating of late.
It's a fascinating topic and I intended merely to point out that quantifying computer technology driven productivity growth is a hard problem. Any facile conclusions one way or the other are suspicious in my view.
It is not clear to me at all that building and buying more computer and data centers and software is an obviously good investment that should only be increased because it raises productivity. That is the discourse, but there is a very conspicuous lack of hard data to support that claim, and lots of pages going back and forth and proclaiming at the 'conclusions' sessions of papers and chapters that the problem is indeed hard and the work done so far is at best inconclusive.
more code faster is competing against some of the largest tax hikes of the last ~70 years, economic uncertainty on what the taxes tomorrow will look like, combined with an energy crisis.
Are you claiming productivity should be growing much more slowly then it is over the past few months or years? Can you show me any analysis that supports that claim?
Because I have seen plenty of analysis published in the past 30 years that puzzle over the productivity growth stagnation in the face of an exponential growth in capital expenditure in computer technology.
So by all means share with me some of the groundbreaking results showing that we can finally see more productivity growth than would be otherwise expected by the conjecture.
There's a difference between task-level productivity, which AI has been shown to increase, and effects on the macro. You're talking about the latter while most people here are engineers considering the former.
It's still unclear if task-level productivity gains bubble up, but it's also still early and I'm not sure we should expect to see immediate results there.
Where is the net benefit people keep talking about when they claim productivity gains are obvious because "more code faster, can't you see?"