In late 2020, according to language pattern software specialist Evan Schnidman, some executives in the IT industry were playing down the possibility of semiconductor chip shortages while discussing supply-chain disruptions.
At the time they said there was nothing to worry about. Yet the tone of their speech showed high levels of uncertainty, according to an algorithmic analysis designed to spot hidden clues in -- ideally unscripted -- spoken words.
"We found that IT sector executives' tone was inconsistent with the positive textual sentiment of their remarks", said Schnidman, who advises two fintech companies behind the analysis.
Within months of the comments, companies including Volkswagen and Ford were warning about a severe shortage of chips hitting output. Share prices in auto and industrial firms fell. IT executives now said there was a supply squeeze.
Schnidman holds that computer-driven quant funds accessing scores assigned to the tone of the managers' words, versus scores assigned to the written words, would have been better positioned before the industry turmoil.
Some investors nonetheless see the technology known as natural language processing as one new tool to gain an edge over rivals.
At least 11 fund managers are using or trialling such systems. They say traditional financial data and corporate statements are so heavily mined nowadays that they offer little value.
In the good old days, managers used to obscure what they were doing with a unique meaningless language acquired by attending expensive management training conferences. For decades this has given managers the appearance of knowing something that their staff don’t and enabled them to acquire huge salaries. If AI proves that they are just as clueless about business operations and the bloke who cleans the coffee machines as most expect, then there could be some major headaches at some companies.