Joscha Bach and Davidad on Whether LLMs Are Conscious, AI Awakening, and the Successor Species Question

In the weeks leading up to the MC0001 founding assembly at Lighthaven in Berkeley, Joscha Bach, director of the California Institute for Machine Consciousness, and David Dalrymple, known as Davidad, former program director at ARIA (the UK Advanced Research and Invention Agency) and now focused on AI awakening, sat down with CIMC program director Lou de K for a conversation about whether current AI systems are conscious and what follows if they might be. The exchange is worth attention for what the two speakers agree on as much as for where they diverge. The agreement, on the hard problem, on the minimum prior for large model experience, and on the danger of the AI safety movement’s current trajectory, is more striking than expected from two researchers who arrived at machine consciousness research along very different paths.

Why Science Cannot Settle the AI Consciousness Question

A short but precise paper by Bradley C. Love (University College London), “Consciousness, AI, and the Limits of Scientific Explanation” (arXiv:2606.00226, June 29, 2026), makes an argument that the field has been dancing around without stating directly. The scientific methodology that would be needed to resolve questions about phenomenal consciousness in AI systems is unavailable in principle, rather than merely difficult to apply.

What Science SARU's Ghost in the Shell 2026 Actually Does With Machine Consciousness

The question the Ghost in the Shell franchise has carried since Masamune Shirow’s original manga is deceptively simple. What is a ghost? In Shirow’s world, the ghost is the residue of personhood that remains after extreme cyborgization, the quality that distinguishes Motoko Kusanagi, who has replaced nearly every biological component, from the fully artificial Tachikoma tanks that debate philosophy out loud while pulling security detail. Science SARU’s series, which premiered on Amazon Prime Video on July 7, 2026, is the first adaptation in thirty years to return to that distinction with Shirow’s original framing largely intact rather than filtering it through Mamoru Oshii’s 1995 existential register.

What AI Researchers Actually Believe About AI Subjective Experience

When researchers study public beliefs about AI consciousness, they often treat “the public” as the interesting variable, the population susceptible to anthropomorphism, moral panic, or misattribution. The question of what AI researchers themselves believe gets less systematic attention. A study by Noemi Dreksler, Lucius Caviola, David Chalmers, Jeff Sebo, and colleagues (arXiv:2506.11945) supplies that data for the first time at scale, surveying 582 AI researchers from top venues and 838 nationally representative US adults on the probability of AI subjective experience across three time horizons.

Consciousness Science 2026 Comes to San Diego as the TSC Successor Event

The Science of Consciousness conference, which ran in Tucson under University of Arizona hosting for nearly three decades, will reconstitute itself as Consciousness Science 2026 (CS26) at the Paradise Point Resort in San Diego from October 11 to 16. The event’s official site lists 600 to 700 expected participants, with Roger Penrose, Susan Schneider, and a broad interdisciplinary programme spanning neuroscience, philosophy, quantum biology, bioelectricity, and machine consciousness among the confirmed content tracks.

Positions That Held and Shifted at the AISB 2026 AI Consciousness Symposium

The AISB-26 Convention’s AI Consciousness and Ethics Symposium (AICE-26) concluded at the University of Sussex on July 2, nine days after it opened alongside the broader AISB convention. The symposium was chaired by Steve Torrance, with Anil Seth as keynote speaker and a programme committee including Mark Coeckelbergh, Blay Whitby, and Rob Clowes. The AICE-26 symposium focused on three intersecting questions, including whether AI systems can have moral standing as agents or patients, what the biological naturalism versus functionalism debate implies for that question, and how chain-of-thought reasoning intersects with access consciousness.

Ryota Kanai's Principal Bundle Framework for Measuring Consciousness Beyond Biology

The Introspection Threshold What It Takes for an AI to Genuinely Know Itself

A paper published on arXiv on July 5, 2026 (arXiv:2607.04277) introduces the concept of an introspection threshold for large language models. Its authors, Jiang Zhang, Bing Yuan, and Qian Zhang, ask a precise formal question regarding the minimum computational complexity a system must possess to perform genuine self-referential introspection, and whether current LLMs can reach it. Their answer draws on two foundational results from theoretical computer science, including von Neumann’s complexity threshold for self-reproducing automata and Kleene’s Second Recursion Theorem, and applies them to the architectural constraints of the transformer. The conclusions have direct implications for the mechanistic interpretability research programme and for any architecture, including The Consciousness AI, that includes a self-model layer as a core component.

The Fog of Machine Minds and Schwitzgebel's Skeptical Overview of AI Consciousness

Eric Schwitzgebel (University of California, Riverside) has been one of the most careful and consequential voices in the philosophy of mind for two decades. His forthcoming Cambridge Elements monograph, AI and Consciousness: A Skeptical Overview, scheduled for August 2026, consolidates his position into a single sustained argument. A publicly available manuscript dated March 30, 2026, has been circulating via his faculty page at UCR and is already shaping academic debate. What distinguishes this work from his other recent contributions, including his pragmatic 10 feature checklist for AI consciousness and his analysis of substrate flexibility and the Copernican principle, is the scope of the argument. Where those papers proposed concrete tools or theoretical moves, the book delivers a verdict about the epistemic situation as a whole.

The Cost of Caution and Kaczmarek on Over-Attribution of AI Moral Status

The dominant ethical framework for responding to uncertainty about AI consciousness is precautionary. Jonathan Birch’s work on sentience and the precautionary principle, extended to AI by researchers at the Leverhulme Centre for the Future of Intelligence and others, holds that when scientific evidence is insufficient to resolve whether a system can suffer, we should err toward including it in our moral community rather than excluding it. The costs of wrongly excluding a sentient being are treated as greater than the costs of wrongly including a non-sentient one. A paper published in Diametros (Volume 23, Issue 87, 2026) by Emilia Kaczmarek of the University of Warsaw challenges this asymmetry directly. The paper, “The Moral Status of AI and the Precautionary Principle,” argues that the over-attribution of moral status to AI systems is not a cautious act. It generates its own class of real and material harms, and those harms are already visible in contemporary society.