In a 1987 article in the Times Book Review, Robert Solow, a Nobel-winning economist at M.I.T., commented, “You can see the computer age everywhere but in the productivity statistics.” Despite massive increases in computing power and the rising popularity of personal computers, government figures showed that over-all output per worker, a key determinant of wages and living standards, had stagnated for more than a decade.
The “productivity paradox,” as it came to be known, persisted into the nineteen-nineties and beyond, generating a huge and inconclusive body of literature. Some economists blamed mismanagement of the new technology; others argued that computers paled in economic importance compared to older inventions such as the steam engine and electricity; still others blamed measurement errors in the data and argued that once these were corrected the paradox disappeared.
Nearly forty years after Solow’s article, and almost three years since OpenAI released its ChatGPT chatbot, we may be facing a new economic paradox, this one involving generative artificial intelligence.
According to a recent survey carried out by economists at Stanford, Clemson, and the World Bank, in June and July of this year, almost half of all workers—45.6 per cent, to be precise—were using A.I. tools. And yet, a new study, from a team of researchers associated with M.I.T.’s Media Lab, reports, “Despite $30 - $40 billion in enterprise investment into GenAI, this report uncovers a surprising result in that 95% of organizations are getting zero return.”
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