Global Courant
NEW YORK – Microsoft has added about $1.5 trillion to its market cap this year after launching ChatGPT. Nvidia added about $640 billion. Overall, the market value of generative AI models has increased by several trillion dollars. What would justify such an appreciation?
Market research firms claim that the market for generative AI will reach $126.5 billion by 2031. That’s not a lot of sales compared to market value. Microsoft now sells at about 12 times its revenue, which is a natural monopoly.
Even if that estimate were correct, market valuations are three to five times higher than $126 billion in revenue would warrant. And I don’t see how generative AI can lower that revenue level, not by an order of magnitude.
What exactly should generative AI do? Supposedly, it can answer customer questions, replace low-ranking programmers, and provide better online search results. But how much revenue can that generate?
Let’s do some back-of-envelope calculations.
Suppose chatbots replace every employee of every help desk in the United States. There are 38,808 help desk employees who earn an average of $43,275 per year. Replace them all and you’ll save $1.68 billion a year. Of course, you can’t replace them all, and chatbots cost something, so I estimate the potential savings are $1 billion a year, provided the gadget actually works.
Markets inflate chatbot valuations based on erroneous projections. Photo: Twitter/Getty Images
Then there are computer programmers. ChatGPT can write basic code. There are 132,740 programmers in the US, so let’s estimate that generative AI could replace the bottom quarter of them, or 33,185 programmers. The bottom quartile of programmers earn $34.84 per hour, according to the Bureau of Labor Statistics. That would save $2.312 billion, minus the cost of the AI program.
So far, we’ve wiped out two key jobs and saved just over $3 billion in salary. I don’t know where the marketing surveys came up with a figure of $125 billion, but they seem to be off by an order of magnitude.
There are plenty of other generative AI applications, for example for medical diagnostics. But we’ve heard that story before. AI could read X-rays faster and more accurately than a human radiologist, but that turned out to be a failure.
“Radiologists have more reason than most to be disappointed because CAD (computer-aided detection) in medical imaging was more than an unrealized promise. Almost unique in the world of technology, medical or otherwise, the hype and optimism surrounding second era AI led to the widespread use of CAD in clinical imaging. This use was most evident in screening mammography, where it is estimated in 2010 that more than 74% of mammograms in the United States were read with CAD assistance. Unfortunately, the benefit of CAD was questionable. Several large studies concluded that CAD has at best shown no benefit and at worst reduced radiologist accuracy, resulting in higher recall and biopsy rates,” according to a study.
This isn’t the first case of AI hype driving stock valuations up.
Do you remember autonomous vehicles? Ford put $1 billion into an AV startup called Argo AI, worth $12.4 billion in 2021, and to zero in October 2022, when it shut down. Self-driving cars are the technology of a future that won’t come anytime soon, at least not in the United States.
The dirty little secret of AVs is that they require a huge amount of data with a very short transmission time (low latency). America’s so-called 5G network doesn’t have the low latency required for AVs. It’s just a hyped 4G with a slow response time.
China already has autonomous taxi services in some cities. China’s 5G network is not only the largest in the world, but also offers near-instantaneous response times made possible by the new technology. AVs are a great idea if you have wide and straight roads (like in some Chinese cities), but not the jumble of American urban landscapes.
Mark Zuckerberg’s Meta poured $100 billion into a virtual reality world that couldn’t find enough visitors willing to wear heavy and expensive headsets. Meta’s stock price crashed after the metaverse fiasco, but rose along with other tech companies in the AI bubble.
The hypothetical calculations above really make no sense. Chat GPT does not work well with real people. By the standards of a human 10-year-old, it’s really, really stupid. It can’t make the kind of mental connections that humor makes possible. In a recent essay for Law&Liberty, I reported some less than satisfactory exchanges with OpenAI’s chatbot over self-referential humor.
Joking aside, generative AI just can’t fathom how humans think and talk. Mental associations that people naturally have are incomprehensible to generative AI models, unless the models have been trained on an identical case in the past.
Better images by AI / Alan Warburton / CC BY-SA Creative Commons
Helpdesk employees aren’t going to replace them any time soon, let alone radiologists. And the trillions of stock market valuations that mushroomed in anticipation of generative AI will disappear, just like the other AI bubbles of recent years.
Of course, AI works wonders when applied to routine tasks, such as picking up faulty items from a conveyor belt or manipulating autonomous cranes and trucks in a port. America’s largest port in Long Beach, California, is one of the least efficient in the world (it’s ranked No. 300 on the World Bank’s list). It takes about 48 hours to unload a large container ship.
At China’s most modern port, Tianjin, a 5G network using Huawei-designed AI systems can unload the same ship in 15 minutes. Smart cranes find barcodes on containers, move them to autonomous trucks and move on to the next.
AI is there to free people from mechanical tasks, not to let machines imitate people. That is where AI will add economic value.
Follow David P Goldman on Twitter at @davidpgoldman
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