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iRobot co-founder Rodney Brooks details why humanoid robots won't learn human-level dexterity from current methods, how to make them safe for humans, and more

rodneybrooks.com/why-todays-humanoids- wont-learn-dexterity/  —  In this post I explain why today's humanoid robots will not learn …

Rodney Brooks

Context & Ripple Effects

Brooks’s argument sits within a broader skepticism about near-term general-purpose humanoids: his subsequent discussion of Robust.AI emphasized warehouse-focused robotics and tempered expectations, while later coverage identified human-like robotic hands as a deployment bottleneck.

The safety question is equally central to commercialization. Later work by Nvidia, Neura Robotics and others on systems to reduce humanoid safety risks underscores that capability claims and safe operation are developing as linked, but separate, engineering problems.

First-order effects

  • Humanoid-robot developers relying on current learning approaches face a sharper burden to show that their systems can achieve dependable manipulation, rather than treating scale or training alone as a route to human-level dexterity.
  • Companies placing robots near workers or consumers must treat physical safety as a core design constraint, alongside movement and task performance.

Second-order effects

Third-order effects

  • If these constraints persist, the humanoid market may develop around task-specific deployments and measurable reliability thresholds, rather than a single general-purpose platform arriving first.
  • Safety engineering could become a lasting differentiator and procurement gate: the more robots operate around people, the less credible capability demonstrations alone become.

The trend: Humanoid robotics is moving from headline-level demonstrations toward a harder commercialization test of manipulation reliability, safe human interaction and task-specific economics.

Discussion

  • @rodneyabrooks Rodney Brooks on x
    I have just finished and just published some weekend reading for you. 9,600 words of not easy reading, on why today's humanoid robots won't learn to be dexterous. https://rodneybrooks.com/...
  • @yuxiang_irvl Yu Xiang on x
    The big message I get: most learning-based manipulation methods mainly focus on kinematics, where the sense of touch is not learned from data (critical for dexterity)
  • @techcrunch.com @techcrunch.com on bluesky
    Brooks, who co-founded iRobot and spent decades at MIT, is particularly skeptical of companies like Tesla and Figure trying to teach robots dexterity by showing them videos of humans doing tasks.  In a new essay, he calls this approach “pure fantasy thinking.”
  • @glynmoody Glyn Moody on bluesky
    Famed roboticist says humanoid #robot bubble is doomed to burst - techcrunch.com/2025/09/26/f... “Human hands are incredibly sophisticated, packed with about 17,000 specialized touch receptors that no robot comes close to matching.”
  • @glinden Greg Linden on bluesky
    Good article by an expert in the field.  To summarize, we won't have humanoid robots in the next 15 years, but we will have a lot of defining down what “humanoid robot” means, those still won't work for much, and VCs will lose investors a lot of money.  [embedded post]
  • @mm-jj-nn Mark J. Nelson on bluesky
    Interesting long-form argument from Rodney Brooks that methods similar to the ones from the deep learning era of AI that cracked image recognition, text generation, etc. are unlikely to crack humanoid robot dexterity in the near future.
  • r/technology r on reddit
    Famed roboticist says humanoid robot bubble is doomed to burst