The end of AI winter?

An AI Winter is a collapse in the perception of artificial intelligence research. The term was coined by analogy with the relentless spiral of a nuclear winter: a chain reaction of pessimism in the AI community, followed by pessimism in the press, followed by a severe cutback in funding, followed by the end of serious research. It first appeared in 1984 as the topic of a public debate at the annual meeting of AAAI (then called the "American Association of Artificial Intelligence"). Two leading AI researchers, Roger Schank and Marvin Minsky, warned the business community that enthusiasm for AI had spiraled out of control and that disappointment would certainly follow. They were right. Just three years later, the billion-dollar AI industry began to collapse.

The process of hype, disappointment and funding cuts are common in many advancing technologies (consider the dot-com bubble and the software crisis), but the problem has been particularly acute for AI. The pattern has occurred many times:

• 1966: the failure of machine translation,
• 1970: the abandonment of connectionism,
• 1971-75: DARPA's frustration with the Speech Understanding Research program at CMU,
• 1973: the end of AI research in England in response to the Lighthill Report,
• 1973-74: DARPA's cutbacks to academic AI research in general,
• 1987: the collapse of the LISP machine market,
• 1993: expert systems slowly reaching the bottom,
• 1990 or so: the quiet disappearance of the fifth-generation computer project's original goals and the generally bad reputation AI has had since.

The worst times for AI have been 1974-1980 and 1987 to the present. Sometimes one or the other of these periods (or some part of them) is referred to as the AI winter.

The historical episodes known as AI winters are collapses only in the perception of AI by government bureacrats and venture capitalists. Despite the rise and fall of AI's reputation, it has continued to develop new and successful technologies. AI researcher Rodney Brooks would complain in 2002 that "there's this stupid myth out there that AI has failed, but AI is around you every second of the day." Ray Kurzweil agrees: "Many observers still think that the AI winter was the end of the story and that nothing since come of the AI field. Yet today many thousands of AI applications are deeply embedded in the infrastructure of every industry." He adds unequivocally: "the AI winter is long since over."

Machine translation and the ALPAC report of 1966

During the Cold War, the US government was particularly interested in the automatic, instant translation of Russian documents and scientific reports. The government aggressively supported efforts at machine translation starting in 1954. At the outset, the researchers were optimistic. Noam Chomsky's new work in grammar was streamlining the translation process and there were "many predictions of imminent 'breakthroughs'".

However, researchers had underestimated the profound difficulty of disambiguation. In order to translate a sentence, a machine needed to have some idea what the sentence was about, otherwise it made ludicrous mistakes. A famous example was "the spirit is willing but the flesh is weak." Translated back and forth with Russian, it became "the vodka is good but the meat is rotten." Later researchers would call this the commonsense knowledge problem.

By 1964, National Research Council had become concerned about the lack progress and formed the Automatic Language Processing Advisory Committee (ALPAC) to look into the problem. They concluded, in a famous 1966 report, that machine translation was more expensive, less accurate and slower than human translation. After spending some 20 million dollars, the NRC ended all support. Careers were destroyed and research ended.