AI was overestimated in the 1960s and the 1980s, and Brooks believes it is being overestimated again in 2017.

This is partly a judgement about history and partly an opinion about 2017. Judge it as of 7 September 2017 on three parts: (a) AI was widely overestimated or overhyped in the 1960s; (b) the same happened in the 1980s; (c) in 2017 AI expectations were inflated relative to what AI could do. True: historians or the AI literature generally describe both the 1960s and the 1980s as periods of overoptimism or hype (for example, failed predictions followed by funding cuts or 'AI winters'), and in 2017 there was credible, contemporaneous commentary that expectations or predictions about AI were outrunning its capabilities. Mostly true: (a) and (b) are well supported and (c) is a reasonable but disputed view in 2017. Mixed: only one of the two historical periods is generally seen as a time of overestimation, or the 2017 part has no contemporaneous support. Mostly false: the historical record does not generally describe either decade as a time of overestimation, but there was some isolated hype. False: the record shows AI was not overestimated in those decades.

Set before the research began.

1. E1 History of artificial intelligence Wikipedia (mirror hosted at static.hlt.bme.hu) · 15 April 2012

   “Many of them predicted that a machine as intelligent as a human being would exist in no more than a generation and they were given millions of dollars to make this vision come true.”

2. E2 History of artificial intelligence Wikipedia (mirror hosted at static.hlt.bme.hu) · 15 April 2012

   “The business community's fascination with AI rose and fell in the 1980s in the classic pattern of an economic bubble.”

3. E3 AI winter - Wikipedia Wikipedia

   “warned the business community that enthusiasm for AI had spiraled out of control in the 1980s and that disappointment could certainly follow”

4. E4 Gartner Hype Cycle for Artificial Intelligence, 2017. Gartner (slide deck presented by Yunus Özdemir) · August 2017

   “By 2020, the average person will have more conversations with bots than with their spouse.”

E1 describes early AI researchers predicting human-level machine intelligence within a generation and receiving millions in funding, consistent with overoptimism in the early era. E2 and E3 describe 1980s business enthusiasm for AI as a bubble that 'spiraled out of control', supporting the 1980s part. For 2017, E4 (Gartner's 2017 AI Hype Cycle) shows ambitious contemporaneous forecasts but is not itself direct commentary that expectations exceeded capabilities, so the 2017 part is a reasonable but disputed view with limited support in the evidence.