Artificial Intelligence-powered tools, such as ChatGPT, have the potential to revolutionize the efficiency, effectiveness, and speed of the work humans do. And this is true in financial markets as much as in sectors like health care, manufacturing, and almost every other aspect of our lives. I’ve been researching financial markets and algorithmic trading for 14 years. While AI offers many benefits, the growing use of these technologies in financial markets also points to potential perils. A look at Wall Street’s past efforts to speed up trading by embracing computers and AI offers important lessons on the implications of using them for decision-making. Program trading fuels Black Monday In the early 1980s, fueled by advancements in technology and financial innovations such as derivatives, institutional investors began using computer programs to execute trades based on predefined rules and algorithms. This helped them complete large trades quickly and efficiently. Back then, these algorithms were relatively simple and were primarily used for so-called index arbitrage, which involves trying to profit from discrepancies between the price of a stock index – like the S&P 500 – and that of the stocks it’s composed of. As technology advanced and more data became available, this kind of program trading became increasingly sophisticated, with algorithms able to analyze complex market data and execute trades based on a wide range of factors. These program traders continued to grow in number on the largely unregulated trading freeways – on which over a trillion dollars worth of assets change hands every day – causing market volatility to increase dramatically. Eventually, this resulted in…ChatGPT AI traders: Too fast, too furious, too risky?