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arXiv:2104.12871cs.AI

Why AI is Harder Than We Think

Melanie Mitchell

Abstract

Since its beginning in the 1950s, the field of artificial intelligence has cycled several times between periods of optimistic predictions and massive investment ("AI spring") and periods of disappointment, loss of confidence, and reduced funding ("AI winter"). Even with today's seemingly fast pace of AI breakthroughs, the development of long-promised technologies such as self-driving cars, housekeeping robots, and conversational companions has turned out to be much harder than many people expected. One reason for these repeating cycles is our limited understanding of the nature and complexity of intelligence itself. In this paper I describe four fallacies in common assumptions made by AI researchers, which can lead to overconfident predictions about the field. I conclude by discussing the open questions spurred by these fallacies, including the age-old challenge of imbuing machines with humanlike common sense.

arXiv comments
12 pages; typos corrected in newest version
Journal reference
DOI
Subjects
cs.AIArtificial Intelligence

On Hacker News

Linked by 6 identifiable commenters in 6 comments across 6 threads, from Apr 2021 to Sep 2025. Found in 3 HN submissions from Apr 2021 to Aug 2023. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments6 threads

  1. Four Fallacies of Modern AI 1 comment

    • I think this might be the paper being referenced: Melanie Mitchell (2021) "Why AI is Harder Than We Think." https://arxiv.org/abs/2104.12871 That sentence is not from this paper.

      degamadView on HNParent context

  2. Ask HN: I have many PDFs – what is the best local way to leverage AI for search? 1 comment

    • You can use Microlink to turn PDF into HTML, and combine it with other service for processing the text data. Here an example turning a arxiv paper into real text: https://api.microlink.io/?data.html.selector=html&embed=html... It looks like PDF, but it you open devtools you can…

      KikobeatsView on HNParent context

  3. The expanding dark forest and generative AI 1 comment

    • this is a wonderful race: as the machines become more human, the humans are forced to introspect and double down on what it means to be human. One could almost call it the human race. (ba dum tss) I've had my own problems with proving my own humanity[0]. With this AI wave, I…

      swyxView on HNParent context

  4. Why A.I. Moonshots Miss 1 comment

    • This article seems to be a rehash of the paper ‘Why AI is harder than we think’[1]. [1]: https://arxiv.org/pdf/2104.12871.pdf - Related discussion https://news.ycombinator.com/item?id=26964819

      JiocusView on HNParent context

  5. Superintelligence Risk Project: Conclusion 1 comment

    • There was also a good discussion on HN [0] about a new paper by Melanie Mitchell "Why AI is Harder Than We Think" [1] [0] https://news.ycombinator.com/item?id=26964819 [1] https://arxiv.org/abs/2104.12871

      RuffleGordonView on HNParent context

  6. Why AI is harder than we think 1 comment

    • Link to paper: https://arxiv.org/pdf/2104.12871.pdf TLDR: Fallacy 1: Narrow intelligence is on a continuum with general intelligence (solving an easy AI problem doesn't immediately lead to being able to solve a hard AI problem) Fallacy 2: Easy things are easy and hard things are…

      juliangambleView on HNParent context

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