Embodied intelligence: Recent advances and future perspectives
Institute of AI for Industries, Chinese Academy of Sciences, Nanjing 211135, China
Sense-making reconsidered: large language models and the blind spot of embodied cognition
Large Language Models (LLMs) demonstrate a kind of linguistic competence that theories of embodied and enactive cognition have long deemed impossible for systems lacking the meaningful perspective of a living being, i.e., the capacity for sense-making. Facing up to this unexpected technological development requires confronting what I propose to call the “AI dilemma”: either frontier LLMs are capable of sense-making despite lacking biological embodiment, or the kind of linguistic competence they exhibit does not necessarily require sense-making. In their chapter on cognition, Frank, Thompson, and Gleiser (2024) maintain that no AI system comes close to realizing relevance, a position that derives much of its motivation from past practical failures. However, frontier LLMs have effectively overcome Dreyfus’ commonsense knowledge problem, such that their dismissal as categorically mindless risks undermining Frank et al.’s central claim that human cognition is deeply intertwined with lived experience. I therefore argue in favor of the alternative side of the AI dilemma: human-level linguistic competence of LLMs should be recognized as a novel non‑biological form of sense‑making, based on a technologically‑mediated embodiment whose enabling properties are in need of further theoretical analysis. This reorientation invites enactive theory to clarify which aspects of sense-making may be universal and which aspects are specifically contingent on organic life, thereby advancing its conceptual framework in dialogue with contemporary AI.
Embodied AI: China’s Big Bet on Smart Robots
Beijing believes that true AI dominance will come from systems capable of autonomous operation in the physical world—AI-powered robotics, or embodied AI.
Embodied AI: China’s Big Bet on Smart Robots
Beijing believes that true AI dominance will come from systems capable of autonomous operation in the physical world—AI-powered robotics, or embodied AI.
On working machines
In part one, on thinking machines, I explored two facets of the philosophy of artificial intelligence: “intelligence”, and consciousness. That left an important topic to consider for this post: the...
AI experienced through AI co-created tools
AI co-created tools and social spaces as a new medium
AI is not superhuman
What metaphor should drive the field of AI research?
AI, Ethics, and Society — Home
The Octotypic Mind
Carcinization, Cognitive Prosthetics, and the Shape of Intelligence After AI
Anthropomorphism Is Breaking Our Ability to Judge AI
Tech Policy Press fellow James Ball asks, how should we interact with a technology designed to ‘speak’ with us on what appear to be human terms?
Stuck in the middle: Being an engineer & artist in the AI era | Annie Sexton | Offprint
I'm an AI skeptic, through and through. But I also voluntarily use AI nearly every day. So naturally, you might be asking: what the heck?
What Does 'Human-Centred AI' Mean?
While it seems sensible that human-centred artificial intelligence (AI) means centring "human behaviour and experience," it cannot be any other way. AI, I argue, is usefully seen as a relationship between technology and humans where it appears that artifacts can perform, to a greater or lesser extent, human cognitive labour. This is evinced using examples that juxtapose technology with cognition, inter alia: abacus versus mental arithmetic; alarm clock versus knocker-upper; camera versus vision; and sweatshop versus tailor. Using novel definitions and analyses, sociotechnical relationships can be analysed into varying types of: displacement (harmful), enhancement (beneficial), and/or replacement (neutral) of human cognitive labour. Ultimately, all AI implicates human cognition; no matter what. Obfuscation of cognition in the AI context -- from clocks to artificial neural networks -- results in distortion, in slowing critical engagement, perverting cognitive science, and indeed in limiting our ability to truly centre humans and humanity in the engineering of AI systems. To even begin to de-fetishise AI, we must look the human-in-the-loop in the eyes.
What Does 'Human-Centred AI' Mean?
While it seems sensible that human-centred artificial intelligence (AI) means centring "human behaviour and experience," it cannot be any other way. AI, I argue, is usefully seen as a relationship between technology and humans where it appears that artifacts can perform, to a greater or lesser extent, human cognitive labour. This is evinced using examples that juxtapose technology with cognition, inter alia: abacus versus mental arithmetic; alarm clock versus knocker-upper; camera versus vision; and sweatshop versus tailor. Using novel definitions and analyses, sociotechnical relationships can be analysed into varying types of: displacement (harmful), enhancement (beneficial), and/or replacement (neutral) of human cognitive labour. Ultimately, all AI implicates human cognition; no matter what. Obfuscation of cognition in the AI context -- from clocks to artificial neural networks -- results in distortion, in slowing critical engagement, perverting cognitive science, and indeed in limiting our ability to truly centre humans and humanity in the engineering of AI systems. To even begin to de-fetishise AI, we must look the human-in-the-loop in the eyes.
233. "The Illusion of Thinking" — Thoughts on This Important Paper
This is a fantastic paper. I just love it. tl;dr AI is not human. Anthropomorphization has been bad for AI, LLMs, and Chat. Clippy walked so today's AI could run.
Study: Sycophantic AI can undermine human judgment
Subjects who interacted with AI tools were more likely to think they were right, less likely to resolve conflicts.
