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Faster Computers Lead to More Wealth, Right? What Could Go Wrong?

What if fast computers get in the way of carefully considering information before starting trades?

In this week’s podcast, tech philosopher George Gilder and computer engineer Robert J. Marks, our Walter Bradley Center director, continued their discussion of the impact of artificial intelligence (AI).

This time, they focused on the way AI affects the stock market, for better or worse. You can download Gilder’s new book, Gaming AI, for free here. The first part of the discussion between Gilder and Marks is here.

Meanwhile…

From the transcript: (Show Notes, Resources, and a link to the complete transcript follow.)

Robert J. Marks: I had a friend, Jack Marshall, who was a professor of financial engineering. He was approached all the time by people who said, “I have beat the market by artificial intelligence.” And of course doing so would have required ergodicity. Jack said he didn’t even have to look at the program or the results. He simply asked the person who made the claim what kind of car they drove. And if their program had indeed worked, they would be driving a very nice car, but most of these were poor students who had never reduced it to practice.

George Gilder: Yeah. You can calculate various probabilities, and using probabilities does result in very massive, fast, parallel processing. You can trade the market very successfully… One of the chapters of my book Life after Google: The Fall of Big Data and the Rise of the Blockchain Economy tells the story of Renaissance, which is the most successful investment fund in the world, and really in history. And they accomplished something like 40% or more growth for 20 years and profits for 20 years.

And they did it by using computers to trade very rapidly in the market. And what they were doing was essentially front running. They would gauge what participants in the market were doing, and before they could complete their trades, the computer would accomplish the trade, thus they’d front run and scored tremendous, earth-shaking, historic gains. And I believe this kind of computation should not be legal in stock markets, but…

Robert J. Marks: Really?

George Gilder: Yeah. I mean, if front running isn’t legal for humans, it shouldn’t be legal for computers. It’s using the speed of computation to game the markets. And the fact that they can conduct thousands of transactions while a human being is just reaching for the keyboard means that they can out trade human beings. And I don’t think that’s a legitimate technique. It has nothing to do with investment. I mean, now half of all the trades are determined by computers… And they’re fast trades, and they don’t have anything to do with investment. There’s no knowledge about specific technologies and companies and competitive environments and future possibilities. It’s all just identifying trading patterns before they happen. And I don’t think… That’s an abuse of artificial intelligence.

Robert J. Marks (pictured): That’s fascinating. Jack Marshall, the person I talked to you before, was not a believer in forecasting the market.

George Gilder: Yeah. It’s all very short term. It’s thousands of transactions a second or a minute or whatever. I mean, it’s something far beyond what any human trader can dream of accomplishing. So the calculation was that they could do four months of transactions in a second. So they’re not legitimate players in the market. They’re outperforming humans simply by the speed of operations…

Note: Fast computers can result in flash crashes.

For example, “Shortly after 2:30 p.m. EST on May 6, 2010, a flash crash began as the Dow Jones Industrial Average fell more than 1,000 points in 10 minutes, the biggest drop in history at that point. Over one trillion dollars in equity was evaporated, although the market regained 70% by the end of the day. Initial reports claiming that the crash was caused by a mistyped order proved to be erroneous, and the causes of the flash were attributed to Navinder Sarao, a futures trader in the London suburbs, who pled guilty for attempting to “spoof the market” by quickly buying and selling hundreds of E-Mini S&P Futures contracts through the Chicago Mercantile Exchange.” – Investopedia

The whole thing made no sense but no one could do anything about it right away.

Sometimes it’s just not clear why the machine-triggered crashes occur:

“The floor of the New York Stock Exchange stopped trading for three hours and 38 minutes on July 8, 2015. Trading was quickly shifted to the eleven other exchanges, including the NASDAQ, BATS, and many “dark pools.” The NYSE only accounts for 20% total trading, down from about 80% 10 years ago.

The cause of the shutdown is still unknown. It could have been linked to the closure of the Wall Street Journal’s homepage or the grounding of United Airlines’ flights. Both occurred on the same day.” – Kimberly Amadeo, “Flash crash explained with examples,” the balance (July 30, 2020)

George Gilder (pictured): I mean, this has nothing to do with investment. Investment is learning. It’s the growth of knowledge. Wealth is knowledge. Growth is learning. It’s registered in all the learning curves that are the most thoroughly documented phenomenon in economics. And these computers are just learning about transitory patterns in the froth of trading. That has nothing to do with the learning processes that propel capitalist investment.

The road to prosperity doesn’t seem to include getting the machines to do our thinking for us.

Note:Benjamin Franklin is reputed to have said, “An investment in knowledge always pays the best interest.”


Here’s the first part of the interview, including the transcript:

Why is AI a key battleground in philosophy and religion? Tech philosopher George Gilder explains. Spoiler: He thinks humans will win. The belief that AI is superior to human ingenuity, in Gilder’s view, stems from mistaking maps for territory and models for reality.

Show Notes

  • 00:30 | Introducing George Gilder
  • 01:02 | The modeling assumption
  • 06:48 | The big data assumption
  • 09:44 | The ergodicity assumption
  • 11:14 | Artificial intelligence and the stock market

Additional Resources


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Faster Computers Lead to More Wealth, Right? What Could Go Wrong?