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Alrich’s blog” on Blogspot. I’m now publishing my posts in this Substack blog, named
“Tom Alrich’s blog, too”. I’m posting for free on Substack now, but after
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of good posts to come!
My latest post,
which was based mostly on last Saturday’s column by Greg Ip of the Wall
Street Journal, described three negative societal impacts of the massive AI
buildout that is going on:
1.
Investment in other tech areas besides AI is
being squeezed because of the huge amounts that companies like Microsoft and
Meta are spending on the AI rollout (Microsoft alone is likely to spend $80 Bn
this year, mostly on new data centers. I’ve been told they’re opening a new
data center almost every day).
2.
The huge amounts of cash being spent on the AI
buildout are starting to raise interest rates. Given the miniscule revenues
that are now coming in to the big AI players, they need to borrow a lot of the
money to finance the buildout, whether from a bank, the bond market or just
other revenue streams (e.g., I’m sure revenue from Facebook finances at least
some of Meta’s AI buildout). If anything, this trend will accelerate; for
example, Microsoft is likely to spend over $100 billion on AI next year.
What’s the third negative societal impact? While Greg didn’t
mention this in his column, I wrote in a blog
post last year that the huge power needs of AI data centers are causing
more and more electric utilities to postpone retirement of coal plants. Of
course, this will damage our (i.e., humanity’s) ability to combat climate
change.
However, I noted at the end of my latest post that my next
post would talk about the benefits of AI. That goal has been aided by two new newspaper
articles, one
in the Wall Street Journal (this time not by Greg Ip) and the other in
the Washington
Post. Both articles discuss huge economic benefits that are
accruing to the US today, due to the current AI boom.
The fact that these are accruing today is important, since Greg
Ip’s column had spoken of AI’s benefits as coming far in the future. This isn’t
a contradiction, because Greg discusses capital markets; his big concern in
this article is whether the stock market is justified in its apparent belief
that the huge AI buildouts will return concomitant benefits in a reasonable
time frame (say, 5-10 years). He is clearly skeptical that this will happen; he
thinks the full benefits to the companies doing the buildouts won’t arrive for 10-15
years.
On the other hand, both the WaPo article and the new WSJ
article point out that just about half of the growth projected for the US
economy this year will be due to the AI buildout, since most of that money
stays in the US. For example, lots of people are employed in that buildout (at decent
wages, hopefully); those people eat at restaurants, buy clothes for their kids,
buy new TVs, etc. I don’t know how often in the past a single industry has
accounted for half of GDP - other than in World War II, when I’m sure the
military was the dominant industry (for example, a lot of factories that made
cars, planes, etc. were converted to wartime production).
Of course, a lot of the chips, motherboards, and pieces of furniture
those people are installing are manufactured overseas. Will these expenditures result
in an overstatement of the GDP benefits of the buildout? No. In fact, the
result will be just the opposite. Imports are subtracted from GDP. This
means that what’s being spent on domestic labor and products in the AI rollout will
be equal to or larger than the sum of the cost of the imported products (but with
a positive sign) and the yearly increase in all other domestic activity that
falls under GDP. This makes the fact that the AI buildout will account for half
of GDP even more impressive.
To quote the article,
“The AI complex seems to be carrying the economy on its
back now,” said Callie Cox, a market strategist with investment firm Ritholtz
Wealth Management. “In a healthy economy, consumers and businesses from all
backgrounds and industries should be participating meaningfully. That’s not the
case right now.”
“AI executives argue the spending boom will create more
jobs and bring about scientific breakthroughs with advancements in the
technology. OpenAI has said that
once its AI data centers are built, the resulting economic boom will create
“hundreds of thousands of American jobs.”[i]
The WSJ becomes Mr. Softee
The Wall Street Journal usually focuses on hard
numbers that can be easily verified – closing stock prices, trade statistics,
etc. True to form, this
WSJ article starts by focusing on a hard economic number: productivity.
This is defined as the rate of output per unit of input – that is, the amount
by which output varies from one period to another if changes in the “factors of
production”, usually grouped into labor and capital, are accounted for.
For example, suppose a plant has 100 workers in period 1 and
200 in period 2. The plant also has $1,000 of capital (machinery, buildings, cash
on hand, etc.) in period 1, which increases to $2,000 in period 2. If output increases
from 300 widgets in 1 to 600 in 2, that means both inputs and output have
doubled; thus, the ratio of quantity output to quantity of input doesn’t
change. Thus, productivity stays the same.
On the other hand, if the inputs doubled, output only
increased from 300 to 450, this means productivity fell, since the same inputs
produced a lower output. Of course, this isn’t a good thing. Conversely, if inputs
doubled but output increased from 300 widgets to 750, this means output more
than doubled and productivity increased, which is a good thing. There is
thus more money for raises for workers and bonuses for management, as well as
for investment.
When you look at an entire economy, productivity needs to
grow at a certain amount every year, just to keep up with growth of the
population. Let’s assume population grows at 2% per year. This means that productivity
will also need to grow at 2%, just to allow the population to maintain their
current standard of living. If productivity grows at more than 2%, the standard
of living can increase. Conversely, if it grows at less than 2%, the standard
of living will decrease, unless the government increases its borrowing to
maintain living standards. But as the US is learning now, there are limits to
the borrowing strategy.
The best way to increase productivity in the short term is
to grow the amount and/or quality of capital that is used for production (it
takes much longer to “grow” workers). For example, if productive capital grows by
10% but the labor force only grows by 2%, then output per worker will grow
enough that the standard of living can increase.
But the increased capital needs to be the kind that will allow
more output to be produced. For example, suppose there are two types of capital:
Type A machines that produce clothes and food, and Type B machines that produce
pencils. Obviously, if the entire capital investment is in B machines, the
increase in output will consist entirely of pencils; meanwhile, the workers
will all be naked and starve to death.
As Greg IP pointed out, the AI buildout isn’t designed to
raise economic output much in the near term; therefore, it’s much more like Type
B investment than Type A. What keeps valuations of the AI companies high is
that it’s well known there will be a huge increase in economic output (due to
productivity gains brought on by AI) at some point in the future – but that
point is currently not known. Therefore, traditional economic analysis, which
assumes that productivity is the key to prosperity, finds the AI buildout to be
a colossal waste.
However, the authors of the second WSJ article point
out that there’s another economic measure that paints a completely different
picture of the AI buildout. This measure can’t be quantified exactly but can be
estimated through surveys. It’s called “consumer surplus”; it’s the difference between
the price a consumer would be willing to pay for a product or service and its
actual price. Of course, this quantity varies by the consumer, the product, and
even the time of day, so it can never be directly measured. However, the
authors (both academics) have conducted surveys that allow them to estimate the
consumer surplus from AI products at $97 billion (here, “consumers” means
individuals and organizations).
Of course, AI products today are mostly free, or at least
free enhancements to existing for-charge products (e.g., Microsoft’s CoPilot
add-on to its Office 365 suite). The authors point out that free AI products are
almost never included in GDP, which is based almost entirely on sales data. However,
they definitely produce benefits for consumers, just like for-pay products do:
“When a consumer takes advantage of a free-tier chatbot
or image generator, no market transaction occurs, so the benefits that users
derive—saving an hour drafting a brief, automating a birthday-party invitation,
tutoring a child in algebra—don’t get tallied. That mismeasurement grows when
people replace a costly service like stock photos with a free alternative like
Bing Image Creator or Google’s ImageFX.”
In other words, the consumer surplus can be considered a
quantity that should be maximized just like GDP should be maximized, even though
it will probably never be possible to include it in GDP. They describe how they
arrived at the $97 billion estimate in this passage:
“Rather than asking what people pay for a good, we ask
what they would need to be paid to give it up. In late 2024, a nationally representative survey of U.S. adults
revealed that 40% were regular users of generative AI. Our own survey found
that their average valuation to forgo these tools for one month is $98.
Multiply that by 82 million users and 12 months, and the $97 billion surplus
surfaces.”
They continue,
“William Nordhaus calculated that, in the 20th
century, 97% of welfare gains from major innovations accrued to
consumers, not firms. Our early AI estimates fit that pattern. While the
consumer benefits are already piling up, we believe that measured GDP and
productivity will improve as well. History shows that once complementary
infrastructure matures, the numbers climb.
“Tyler Cowen forecasts a
0.5% annual boost to U.S. productivity, while a report by the National Academies puts the figure at
more than 1% and Goldman Sachs at 1.5%. Even if the skeptics prove
right and the officially measured GDP gains top out under 1%, we would be wrong
to call AI a disappointment. Life may improve far faster than the spreadsheets
imply, especially for lower-income households, which gain most,
relative to their baseline earnings, from free tools.”
To paraphrase these two paragraphs, the authors estimate
there will eventually be a big boost in GDP due to AI use, even though today the
boost is mostly outside of GDP. Of course, they are talking about an increase
in GDP due to use of AI, whereas the earlier estimate that half of GDP growth
this year will be due to AI is referring to the massive spending for
infrastructure rollout going on now.
In other words, AI will produce two big boosts to GDP: due
to the rollout (starting this year, but certainly not ending anytime soon) and
due to the productivity gains caused by widespread use of AI products. The
latter gains can’t be measured today, but they will in the future.
The authors conclude,
“As more digital goods become available free, measuring
benefits as well as costs will become increasingly important. The absence of
evidence in GDP isn’t evidence of absence in real life. AI’s value proposition
already sits in millions of browser tabs and smartphone keyboards. Our
statistical mirrors haven’t caught the reflection. The productivity revolution
is brewing beneath the surface, but the welfare revolution is already on tap.”
If you would like to comment on what you have read here, I would love to hear from you. Please email me at tom@tomalrich.com, or even better, sign up as a free subscriber to the Substack community chat for my subscribers and make your comment there.
[i] The
WaPo article points out that a large portion of the growth due to AI is
simply Nvidia’s profits. But it is certainly not the lion’s share of that
growth.
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