Skip to content
Hallway
0:00 / 0:00

#lighthillreport#johnmccarthy#aiwinter

The Lighthill Debate (1973) - part 1 of 6

bilkable

188 subscribers • 1 video on Hallway

YouTube
  • Recommended by 2 people: 2 on Hacker News.
  • May be out of date. Uploaded 16 years ago, in an area where tools change fast.
  • An opinion. It argues one side of a question engineers disagree on.

Intermediate. Assumes working knowledge.

12K views16 years ago2 recommendations

AI and machine learningHistory and cultureHistory of computingComputation and complexityAI safety and impact

The historic 1973 BBC debate between Sir James Lighthill and AI pioneers including John McCarthy over the future of AI research.

In 1973, professor Sir James Lighthill was asked by Parliament to evaluate the state of AI research in the United Kingdom. His report, now called the Lighthill report, criticized the utter failure of AI to achieve its "grandiose objectives." He concluded that nothing being done in AI couldn't be done in other sciences. He specifically mentioned the problem of "combinatorial explosion" or "intractability", which implied that many of AI's most successful algorithms would grind to a halt on real world problems and were only suitable for solving "toy" versions. The report was contested in a debate broadcast in the BBC "Controversy" series in 1973. The debate "The general purpose robot is a mirage" from the Royal Institute was Lighthill versus the team of Michie, McCarthy and Gregory. The report led to the near-complete dismantling of AI research in England. Starring: James Lighthill, Donald Michie, Richard Gregory and John McCarthy. en.wikipedia.org/wiki/Lighthill_report en.wikipedia.org/wiki/AI_winter#The_Lighthill_report

Why it's here

2 people recommend this

What people say. Pointed to as a crucial historical document illustrating the arguments that led to the first AI winter.

AndrewOMartinon Hacker News • Recommends

On “Computing machinery and intelligence (1950)”

…ugh do read the conference proposal, posted on HN recently [link ]; then you have the Lighthill report where the UK Government essentially lost interest in the project, the conclusions are debatable, but clearly and entertainingly argued, a video of the presentation of the report, with McCarthy present and responding, is available online also [video ]. Finally I'd cite the 1970s era book What Computers Can't Do, and its 90s reprint, What Computers Still Can't Do as all you need to know about the current state of AI, its ultimate aims and the fatal flaws in its fundamental assumptions. The fact that it was written in the 70s and applies to today's discussions on AI should be enough to i…
View on Hacker News

sgt101on Hacker News • Recommends

On “A rising sentiment that IBM’s Watson can’t deliver on its promises”

…existed because of Don's drive to commercialise Expert Systems. Don was a driver in the Alvey project which was a grand project to solve issues around Expert Systems in response to the Japanese Fifth Generation project. A man called Lighthill then rumbled the Expert System movement. If you want to watch a demolition of it see the following video : link to this video and the other 5 of them (you will find them in the sidebar!) Fun fact. In video 6 you can watch Christopher Strachey have a pop at AI. Christopher didn't work at Bletchley, he was too young, but he did work at Manchester with Alan Turing and they created computer music and love poetry in collaboration before Turing killed himself. Strachey…
View on Hacker News

YeGoblynQueenneon Hacker News • Mentions

On “Deep reinforcement learning is a waste of time (2019)”

Why do you have to start your comment by accusing me of moving the goal posts? I don't even like ball games. Why is it so hard to have a decent conversation on the internet? It's a serious concern and I stand by it. It's perfectly possible -it's even easy- to make algorithms, systems, programs, what have you, that can solve one problem, perform one task, and do nothing else. Hell, you can train a dog to perform one task. Sit boy! Boy sits. And that's all it knows to do. 80% of AI research output, ever since Dartmouth, has been like that. 99% of AI research output in the last ten years is like that. My entire phylum of AI research (I'm a PhD student studying Inductive Logic Programming and ev…
View on Hacker News