Subscribe to enjoy similar stories. Almost two years have passed since OpenAI released GPT-3.5 to great fanfare. Bill Gates, co-founder of Microsoft, compared the technology’s arrival to his first encounter with the graphical user interface—a breakthrough that reshaped personal computing—in the 1980s.
Others predicted that generative artificial intelligence (AI) would rapidly transform economies around the world, leaving many millions unemployed. Yet despite the hype and the worries, ai’s impact has been muted thus far. According to America’s Census Bureau, only 6% of businesses use AI to produce goods and services.
Output and labour-productivity growth, meanwhile, remain far below the soaring heights of the computer age in the 1990s. Why has AI so far failed to live up to its promise? Lessons from the computer age can shed light on the question. As with AI today, the early years of the computer age were marked by predictions of economic transformation.
In 1965 Herbert Simon, a giant of computer science, declared that “machines will be capable within 20 years of doing any work that a man can do." Two decades after Simon’s prediction, the promised productivity revolution remained elusive. In 1987 Robert Solow, a Nobel laureate, famously quipped that “you can see the computer age everywhere but in the productivity statistics." Only in the late 1990s did the economic transformation at last materialise, leading Solow to acknowledge—three decades after the initial exuberance—that computers had begun to reshape the economy. Three main factors contributed to the eventual arrival of a computer-age productivity boom: companies ramped up investment in information technology, computer and software prices fell rapidly (see chart),
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