"Popular accounts of AI history often describe a series of boom-and-bust cycles known as "AI winters"-periods where optimism and funding crashed following overhyped promises of machine intelligence. But according to Thomas Haigh on this week's Intelligent Machines, the reality is more complicated. Haigh's research shows that while elite labs at MIT, Stanford, and Carnegie Mellon faced funding "frost" in the 1970s, the overall field wasn't in crisis internationally or for most working researchers."
"Thomas Haigh traces the origins of the term "artificial intelligence" to John McCarthy at Dartmouth in 1955, where it was first used to draw in research funding. Since then, AI has functioned as a shifting brand-a way for researchers and companies to market their work and attract support. Sometimes, core technologies (like neural networks) fell out of the brand's scope, only to return decades later under new names like "machine learning" or "deep learning.""
Artificial intelligence has operated as a shifting brand used to market research and attract funding since the term's coining at Dartmouth in 1955. Elite laboratories experienced funding "frost" in the 1970s, yet global AI membership, conference participation, and international research presence continued to increase. The popular "AI winter" framing arose primarily from a few privileged labs losing easy government support rather than a universal fieldwide collapse. Technologies such as neural networks moved in and out of the AI brand and later returned under labels like "machine learning" and "deep learning," perpetuating hype-driven cycles and inflated expectations.
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