Letter to the Congressional A.I. Caucus

May 23, 2021

Re: Anticompetitive Practices in the Market for A.I. Software

Dear Members of Congress,

I’m currently an entrepreneur looking to raise funding to market and lease my A.I. software, though before that, I worked in financial services, for eight years, most recently at BlackRock, and McDermott Will & Emery before that. I received my J.D. from New York University School of Law, and B.A. in computer science from The City University of New York. I published articles in refereed mathematics journals as an undergraduate, won national research contests in computer science, again as an undergraduate, and wrote for many years in The Atlantic as a young professional, about finance and economics, in my free time.

I’m emailing you because I believe there are very serious and extremely obvious anticompetitive practices in the market for A.I. software, that I’ve explained below.

Background

The most basic prediction algorithm in A.I., known as the, “nearest neighbor algorithm”, which I did not develop, is actually the best algorithm for many real world problems in A.I. (see attached, “Analyzing Dataset Consistency”).

This is not a matter of pride –

I did not come up with this algorithm, and I don’t know who did. It has been around for decades, and in any case, it is certainly widely known, and even has a Wikipedia page:

https://en.wikipedia.org/wiki/Nearest_neighbor_search

This is also not a subject of debate –

The math is absolute, but even if you don’t understand the theory, you can simply download and run the software to see that it works (see Section 1.1., example, “MNIST Numerical Dataset” of, “Vectorized Deep Learning”, attached).

The intuition for the nearest neighbor algorithm is straightforward: if A and B are the most similar items in scope, and you know what A is, then you should be able to predict what B is. For example, if A is a picture of a cat, and picture B is most similar to A, out of all other pictures in scope, then B should also be a picture of a cat. Of course, implementation is not quite this simple, but it’s not that complicated either, and this really is the basic idea.

The nearest neighbor algorithm reduces many real world problems in A.I. to something that some high school students would have no problem understanding and coding. Yet, this algorithm is never discussed, in my experience, let alone used. In fact, I’ve never even seen it discussed in an A.I. tutorial, despite the fact that it is not only incredibly simple, but also incredibly powerful.

So the natural question is, why isn’t the industry making use of what is often the best approach to many basic problems in A.I.?

I believe the answer is not so good.

It is my belief that the tech sector is profoundly corrupt, and recent events in the sector should convince you that this is the case, with espionage, anticompetitive behavior, and probably worse, all common practice in the sector. But even so, why would a market of this scale, that is ostensibly sophisticated, make use of inferior techniques?

I believe the answer is that firms in the market profit from the amount of time it takes to perform a task on their servers –

They are therefore economically disincentivized to allow for efficiency.

Said otherwise, the longer a program takes to run, the more they get paid. So they don’t want the best solution to a problem, they want the worst one, because that’s the one that takes the longest time to run, generating the most revenue, and the biggest bills for their clients.

The next question is, why do clients put up with it? Because they don’t have a choice, and that’s what an oligopoly is –

A market so small, dominated by so few firms, that the market stops making economic sense, with price and term fixing, and all the rest. This is precisely why this type of conduct is a criminal offense in the United States, because it stifles competition and innovation.

To be perfectly clear, it is my opinion that firms in the tech sector are actively suppressing the most efficient software in A.I. (which includes but is not limited to the nearest neighbor algorithm), because they profit more from the least efficient software. This must be the case, because the simplest software in all of A.I. (i.e., the nearest neighbor algorithm) cannot be beat in terms of accuracy for many real world problems, yet it’s never discussed, let alone used, to my knowledge and in my experience.

Conclusion

Again, it is public knowledge that the tech sector is an oligopoly, and this fact is now the subject of multiple enforcement actions at the state and federal level. Common sense suggests that this is exactly the type of economic environment where an otherwise unthinkable anticompetitive ruse would be possible. Moreover, these are gigantic companies that plainly run an oligopoly, so the idea that they wouldn’t suppress innovation for commercial gain is beyond naive, and is just not how economies, markets, or people function.

It is my honest opinion that the market for A.I. is promoting nonsense solutions in one of the most important sectors to the future of this country, A.I., so that a handful of firms can maintain market share and revenues. This is obviously bad for the American economy, as innovation will be effectively cut off domestically, and flourish abroad, which at some point, will create national security risks, and probably already has, given that as I noted above, this basic technique has been around for decades.

This type of otherwise unbelievable outcome regrettably has recent precedent in the U.S. –

Bernie Madoff ran a multi-billion dollar, imaginary business, that somehow avoided regulatory scrutiny, despite reportedly never executing a single trade. This is something that even the most basic regulatory inquiry would have uncovered. I’ll also note that the SEC ignored a mathematician that told them that it was mathematically impossible for Bernie Madoff to be making the returns he claimed to be making. It turns out, this was correct.

I am telling you, as a mathematician, that it is mathematically impossible to beat the nearest neighbor algorithm for many real world problems. This implies quite plainly that the market for A.I. software is distorted by collusion and oppression, likely doing harm to the American economy on a massive scale, and no one’s doing anything about it.

For a neutral introduction to A.I., I’d recommend this video from MIT, which discusses early advances in A.I., from 1961, that will give you a sense of how advanced A.I. really is, now that we’re sixty years from this already astonishing technology:

The fact that these ideas have been around for decades raises other issues:

It turns out that the nearest neighbor algorithm, again the most basic prediction algorithm, theoretically has perfect accuracy on certain datasets, which often translates into nearly perfect accuracy in practice. So now imagine what the truly most efficient solutions in A.I. are capable of; Think about how much data these companies have about basically every American, including children, regarding their interests, their relationships, their personal conversations, and therefore their most intimate experiences, and even their health; What are they doing with all of that data and predictive power? I’m betting it’s nothing good, given what I’ve outlined above.