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I have a lot to say about AI - and why not? Everyone does. Well I will tell you why not. Because I know just enough, to know I do not know enough to tell anyone what, if anything, to do “about” so called AI.
I will note, here, again that OpenAI is either the best company in the world, or they launched the best fake advertisements of this century. If you look back to when they announced OpenAI as a nonprofit and then registered for tax-exempt status - (which was approved by the IRS), and their first Super-Bowl ad: You will find that they were, once a bit more cautious and reticent with their claims. They did not state - at first “we have artificial intelligence.”
The first OpenAI nonprofit announcement discussed “advancing digital intelligence.” A more modest claim, than “owning AI.” But it did not take long before they started drinking their own AI Kool-Aid, and investors sent billions and billions down that rabbit hole of “word calculators” otherwise known as LLMs, or if you don’t know the history of data science “AIs.”
Now there is at least one obvious moral risk here, that has nothing to do with “AI.”
There is a clear moral hazard here (for those unfamiliar with the phrase, it is generally used in finance/economic analysis for situations where one company takes on significantly more risk than they would if it was their money, or their private funds at risk - BECAUSE - the cost of failure - when failure comes - will be paid for by others).
The conventional understanding of capitalism is - or rather was - you buy or build something for one dollar and sell it for two dollars, or if the product is in high demand, maybe 10 or even 1k dollars. Fairly straightforward.
However, there is nothing transparent or straightforward about these “AI” corporations finances.
In other words, they could be airplane companies, or defense companies or car companies - and the same risk would be present. These “AI” companies have become “too big to fail,” because we have invested so much they collectively represent about ¼ of our market and over 50% of our “growth.”
The monopolistic behavior of OpenAI, Google, Microsoft, Anthropic, Meta, is so predictable they no longer seek to hide it. When one of the five companies is facing increasingly grumpy investors - who have not seen a return on investment for word calculators, one of the other five comes to the rescue like a Knight in Shining Armor and suddenly “finds” they need some proprietary something or another from the company in a crunch, and “pays them” tens of billions of dollars for proprietary “things.” Then the spotlight moves to the next company, and “suddenly” it’s time for one of the other four to play the role of a Knight in Shining Armor - and who knew? They suddenly need “some proprietary __” from that company, and tens of billions of dollars “changes” hands.
And just like that the investors of company A, sends billions of dollars to company B, and the shareholders all celebrate the self-dealing monopoly, as though these text predicting algorithms from the 1990’s have invented fire or create the wheel.
If you think I’m being hyperbolic - I wish you were right. This is the precise image these firms have nurtured - check it out, here: https://youtu.be/Z0rZqS_hE3I?is=7cZNQ2iKLaon48aP.
What could possibly go wrong with this model? I’m not an economist, but it seems to me that these types of shell games have not ended well in the past. And when it comes
For readers who had the good fortune of missing the global 2008 financial crisis, take some time and read up on it. Why? Well for the simple reason that our nation does this every 20-30 years:
Step 1. We “forget” our nation’s laws only work when we fund actual oversight of companies by civil servants.
Step 2. The companies take on so much debt and so much risk (knowing they stand to make billions or trillions if and when the crash comes - and that the US taxpayers will foot the bill) that finally…
Step 3. the whole house of cards comes falling down - everyone looks around like deer in the headlights and wonders how this could have possibly happened again.
The government remedy is almost always the same: functioning oversight that can’t be bought off by companies.
Congress passes the legislation, it works for 10-20 years and then lobbyists get it repealed until another crash comes.
If you want to hear better explanations of why and how this is happening again, our nation is blessed with one U.S. Senator who watches this phenomena like a hawk. Senator Elizabeth Warren has the most sophisticated understanding of how capitalism works and what conditions are necessary to keep it working.
I am not sure that his “boom/bust” pattern is actually bad for the economy. It is easy to be cynical and to assume this cycle is destructive. But in researching for this article, it was easy to find articles stating what I just did - but nearly impossible to find one that had a more politically sustainable model to propose.
For those who want to revisit the most articulate defender of open markets, you could do worse than selecting this book by Princeton University Press: “The Infidel and the Professor,” about the friendship between David Hume and Adam Smith. https://press.princeton.edu/books/hardcover/9780691177014/the-infidel-and-the-professor
I spent time in Hong Kong China with Duke Law studying international finance law. One of the case studies we analyzed was the 1996-1997 Asian Financial Crisis (useful summary here: https://unctad.org/system/files/official-document/tdr1998p1ch3_en.pdf, and an even better summary of “causes and cures” by the International Monetary Fund, from 1998 is available here: https://www.imf.org/external/pubs/ft/fandd/1998/06/imfstaff.htm.
The IMF found that financial crash was caused by several factors including:
National safety nets for companies
Massive private capital flows to companies
Insufficient oversight
Weak corporate governance
“connected” lending between the large corporations with very little oversight
And lack of transparency.
Which, if any of these do not apply to Meta/Facebook, XAI, Anthropic, OpenAI, Microsoft and Google? I would suggest they all apply. And I would further suggest that our nations policymakers’ team up with some professors with degrees in finance law, and history and see what needs done to provide meaningful, actionable oversight of these “AI” firms, before the next financial crash. We learned these lessons in 1997, and we learned them again 21 years later in 2008.
Congress needs to act now, to avoid the great financial cliff of 2027-2028.