Teething issues - the bit they are not telling you about today's AI
by Doug Brodie
I came across the story in the New York Times last week; I can’t add anything to the explanation, so here’s the re-print:
“The lawsuit began like so many others: A man named Roberto Mata sued the airline Avianca, saying he was injured when a metal serving cart struck his knee during a flight to Kennedy International Airport in New York.
When Avianca asked a Manhattan federal judge to toss out the case, Mr. Mata’s lawyers vehemently objected, submitting a 10-page brief that cited more than half a dozen relevant court decisions. There was Martinez v. Delta Air Lines, Zicherman v. Korean Air Lines and, of course, Varghese v. China Southern Airlines, with its learned discussion of federal law and “the tolling effect of the automatic stay on a statute of limitations.”
There was just one hitch: No one — not the airline’s lawyers, not even the judge himself — could find the decisions or the quotations cited and summarized in the brief.
That was because ChatGPT had invented everything.
Mr. Schwartz, who has practiced law in New York for three decades, told Judge P. Kevin Castel that he had no intent to deceive the court or the airline. Mr. Schwartz said that he had never used ChatGPT, and “therefore was unaware of the possibility that its content could be false.”
He had, he told Judge Castel, even asked the program to verify that the cases were real.
It had said yes.
Mr. Schwartz said he “greatly regrets” relying on ChatGPT “and will never do so in the future without absolute verification of its authenticity.”
The real-life case of Roberto Mata v. Avianca Inc. shows that white-collar professions may have at least a little time left before the robots take over.
It began when Mr. Mata was a passenger on Avianca Flight 670 from El Salvador to New York on Aug. 27, 2019, when an airline employee bonked him with the serving cart, according to the lawsuit. After Mr. Mata sued, the airline filed papers asking that the case be dismissed because the statute of limitations had expired.
In a brief filed in March, Mr. Mata’s lawyers said the lawsuit should continue, bolstering their argument with references and quotes from the many court decisions that have since been debunked. Soon, Avianca’s lawyers wrote to Judge Castel, saying they were unable to find the cases that were cited in the brief.
When it came to Varghese v. China Southern Airlines, they said they had “not been able to locate this case by caption or citation, nor any case bearing any resemblance to it.”
Indeed, the lawyers added, the quotation, which came from Varghese itself, cited something called Zicherman v. Korean Air Lines Co. Ltd., an opinion purportedly handed down by the U.S. Court of Appeals for the 11th Circuit in 2008. They said they could not find that, either.
The copy of the supposed Varghese decision, for example, is six pages long and says it was written by a member of a three-judge panel of the 11th Circuit. But Avianca’s lawyers told the judge that they could not find that opinion, or the others, on court dockets or legal databases.
In Mr. Mata’s case, the program appears to have discerned the labyrinthine framework of a written legal argument, but has populated it with names and facts from a bouillabaisse of existing cases.
Mr. Schwartz said that he had consulted ChatGPT “to supplement” his own work and that, “in consultation” with it, found and cited the half-dozen non-existent cases. He said ChatGPT had provided reassurances.
“Is Varghese a real case,” he typed, according to a copy of the exchange that he submitted to the judge.
“Yes,” the chatbot replied, offering a citation and adding that it “is a real case.”
Mr. Schwartz dug deeper.
“Are the other cases you provided fake,” Mr. Schwartz asked.
ChatGPT responded, “No, the other cases I provided are real and can be found in reputable legal databases.”
But, alas, they could not be.”
You’ll agree that such Trumpian errors are scary – I hope aircraft and medical teams don’t use ChatGPT the same way, though I can see lazy investors (professional & amateur) getting sucked in.
The problem from AI that is causing the storm clouds we have to watch out for is Nvidia.
In the old days you and I would have known Intel as the dominant maker of microchips, with their little logo on all our pc’s, however for reasons far beyond my pay grade the Big Kid on the block today is Nvidia, and it is apparently the dominant processor maker for Artificial Intelligence. This led to Nvidia’s market value topping $1 trillion, making it the sixth largest company on the planet. Nothing special there we might think, given that Aramco is $2 trillion, Amazon $1.3 trillion, Alphabet $1.6 trillion, Microsoft $2.5 trillion and Apple $2.5 trillion. (Let me give you a reference point: the value of the entire FTSE 100 today is $2.42 trillion.)
To spot the problem you need to recall Sun Microsystems; in 2000 at the height of the dotcom bubble, Sun was valued at $200 billion and it was sold after the crash to Oracle for $7 billion. Famously, transparently, honestly, its CEO said in 2002:
“2 years ago we were selling at 10 times revenues when we were at $64. At 10 times revenues, to give you a 10-year payback, I have to pay you 100% of revenues for 10 straight years in dividends. That assumes I can get that by my shareholders. That assumes I have zero cost of goods sold, which is very hard for a computer company. That assumes zero expenses, which is really hard with 39,000 employees. That assumes I pay no taxes, which is very hard. And that assumes you pay no taxes on your dividends, which is kind of illegal. And that assumes with zero R&D for the next 10 years, I can maintain the current revenue run rate,” said Scott McNealy in 2002.
“Now, having done that, would any of you like to buy my stock at $64? Do you realise how ridiculous those basic assumptions are? You don’t need any transparency. You don’t need any footnotes. What were you thinking?”
Scott McNealy to Bloomberg, 2002.
Ok, so Sun was over-hyped and over-valued at the level of 10 times its sales. A couple of days ago Nvidia was being valued at 37 times its sales. It’s going to rain, and it will rain hard. When we see storm clouds on the horizon we grab a coat and a brolly or stay inside – it’s not the storm that harms us, it’s being unprepared.
More, you may have heard about the US government avoiding a crisis two weeks ago, this is why:
Twenty years ago the US government debt was $10 trillion, ten years ago it was $21 trillion, it’s now $31 trillion. Look how steep the wall is in the past few years, covid added $5 trillion. The US has to deal with this and we can’t see politicians over there demonstrating either a willingness or an ability to grasp this nettle. We’re not doomsters in any way, however we are pragmatists and at the very least you and I will see the media telling us we’re all doomed because of this, over the coming years.
If you’ve ever run a business, you know that the mantra above all others is ‘never run out of money’. When we look at the levels of valuations and debt together in the US, we know it’s going to rain, and the storm will be a monsoon – heavy, quick, followed by sunshine.
Our umbrella is the reserves of the trusts we use and where our client money lies. The reserves work, we monitor them daily/weekly/monthly to ensure that we always have the umbrella to hand though we hope the cost of the brollies will be wasted money – it’s an insurance, and the pandemic period demonstrated the effectiveness of that protection.
Don’t get caught in the storm, pay attention to the forecast – we don’t know when, but just because no one knows the timing doesn’t mean it’s not coming. Storms are fun to watch from the inside, so stick with the trusts and keep your shirt dry.
Doug