Do Not Trust AI To Manage Your Investments

Throughout my 60-plus years of investing experience, I have seen numerous attempts to use technology to make successful investment decisions. While all the technology advances were welcome tools, they could never replace the human brain. Why not? Because the relevant areas, necessary ingredients and proper logic for making accurate investing analysis, outlooks and decisions are forever changing.

Bitcoins But AI Knows More And Thinks Faster, Right?

Nope. It does not “know,” nor does it “think.” That is why the many artificial intelligence teams cannot stop their programs from producing hallucinations, meaning wildly incorrect results. The teams are now trying to get those programs to “know” what is right and wrong by slowing down their “thinking.” However, the hallucinating has gotten worse.

(See The New York Times’ May 6 article for a good explanation: “A.I. Is Getting More Powerful, but Its Hallucinations Are Getting Worse – A new wave of ‘reasoning’ systems from companies like OpenAI is producing incorrect information more often. Even the companies don’t know why.”)

While doing analysis for various articles, I have run across AI-created mistakes. Here are three recent examples:

Bitcoins AI Failed To Explain An Aberrant Automobile Production Number

With tariffs starting to affect automobile prices, analyzing the Great Recession pattern of dropping sales and production might offer good investment insight. In 2008, with sales drifting lower, there was an unusually large jump in automobile production. So, to Google with the question, “Why did automobile production increase in July 2008?” The AI answer appeared first, but it only offered suppositions without any supporting information.

However, below the Google AI response was the source of the answer: The New York Times article (August 15, 2008), “Manufacturing Output Topped Forecasts in July.” It provided the accurate, relevant details (underlining is mine):

“Industrial production, a measure of the volume of goods produced in the United States, slightly topped expectations in July, a bit of positive news for an economy buffeted by inflation and higher costs.

“In a report released Friday, the Federal Reserve said that industrial production grew 0.2 percent over the previous month. Economists had expected production to be flat.

“July’s increase was largely driven by a 3.6 percent rise in the production of motor vehicles and parts. The automotive production number has increased in both of the last two months most likely not because of sales, which are at record lows, but because production had been unusually low because of a strike at an auto parts supplier, American Axle. Economists expect that production will slow down again in response to dismal demand.”

As happens in performing analysis, that report led to a search for an article about American Axle’s strike. This NBC News report (May 22, 2008), “American Axle workers vote to end strike,” laid out the relevant facts (underlining is mine):

“Workers at American Axle and Manufacturing Holdings Inc. have voted to end their nearly three-month-old strike, overwhelmingly ratifying a new contract with the company despite steep pay cuts and other concessions.

“The vote, finalized Thursday, means workers likely will return to their jobs next week, ending a walkout that has crippled General Motors Corp.’s production of large sport utility vehicles and pickup trucks.”

Now the 2008 automobile production numbers made sense. Here are the production numbers relative to March 2008, the last normal production month prior to the strike effect:

March – 100.0

April – 88.2

May – 89.9

June – 97.1

July – 117.6 (the aberrant month that required explanation)

August – 102.4

September – 98.9

The strike-affected 5-month production level averaged = 99.0, thereby putting the industry back on track.

Bitcoins AI Failed To Accurately Describe Federal Reserve Interest Rate Management

Originally the Federal Reserve used the discount rate to affect the financial/money situation. Later, it changed to managing the federal funds rate for that purpose. Then, the discount rate was tied to the federal funds rate at a higher level. For an article, I asked this question: “When did the federal reserve discount rise above the federal funds rate?”

However, the Google AI response was both incomplete and incorrect. To get a fulsome, accurate understanding required charting the data and tying it to the Federal Reserve’s actions and reasoning, as follows.

Under Alan Greenspan (1987-2006) the discount rate remained below the federal funds rate until 2003. At that point, he raised the discount rate above to encourage banks to borrow from one another rather than from the Federal Reserve. He also established an automatic 1% difference, thereby removing the necessity of having to set the two rates separately. However, that difference was in place only until 2007, when Ben Bernanke decreased it to about 0.6%. That level prevailed through Janet Yellen’s and Jerome Powell’s terms until the 2020 Covid period, when Powell lowered it to under 0.2%, where it remains today.

Bitcoins AI Lacked Internal Consistency

In a search for stocks that broke their dividend records in 2024, Google AI got this question: “Which U.S. stocks reduced their dividend in 2024 after increasing their dividend each year for at least ten years?” The answer was incomplete and inaccurate. It said there were “several” companies without naming them. Then it gave two false examples: Coca-Cola and Pfizer.

To test whether Google AI really thought those two companies had cut their dividends in 2024, a simple question was asked. “Did __ reduce dividend in 2024?” For both companies, the answer was “No,” adding they had actually increased their lengthy string of dividend increases.”

Those conflicting answers are concerning. If AI’s data and processes are not consistent and interconnected, there is a lack of trust in any answer. Therefore, it means doing some additional analysis to ensure the AI-process answer is accurate.

Bitcoins The Bottom Line: Use AI Answers Gingerly As A Guide To Further Research

All the data in the world and lightening speed does not make for accurate understanding and wise analysis — especially when it comes to investing.

So, use AI as a rudimentary tool that may require additional analysis and confirmation. Moreover, do not expect AI to be an intuitive, decision-making expert.