04 Aug 2026
The 29th Annual Meeting of the Association for the Scientific Study of Consciousness (ASSC 29) took place in Santiago, Chile, from June 30 to July 3, 2026, at the Casa Central of the Pontificia Universidad Católica de Chile. The conference was the first ASSC meeting held in Latin America and included, as a satellite event, the founding meeting of the Latin American Society for the Scientific Study of Consciousness. Among the six keynote speakers was Lucia Melloni, a neuroscientist at the Ruhr University Bochum and the Max Planck Institute for Empirical Aesthetics who serves as the principal investigator of the COGITATE adversarial collaboration.
04 Aug 2026
The dominant frameworks in AI consciousness research in 2026 are computational and functional. Integrated Information Theory asks whether a system’s causal architecture achieves high phi. Global Workspace Theory asks whether information is globally broadcast across specialized modules. Biological naturalism asks whether the system has metabolic self-organization. What these frameworks share is that they locate the conditions for consciousness in properties of a system considered in relative isolation from its environment.
03 Aug 2026
Warisa Sritriratanarak and Paulo Garcia published comparative research (Sritriratanarak & Garcia, 2025, arXiv:2510.20839) examining the evolutionary pressure that selected for conscious processing over reactive substrates. The study contrasts biological organisms operating with temporal depth against artificial feedforward neural networks that respond reactively to instantaneous inputs. Their findings demonstrate that conscious self-models provide clear computational efficiency when agents navigate highly unpredicted, non-stationary environments.
03 Aug 2026
Most proposals for machine consciousness ask whether a given system has the right internal properties: sufficient integrated information, a global broadcast architecture, higher-order representations, or the right substrate. Shogo Tanaka’s paper Aidification of the self: a phenomenological approach to machine consciousness through human-robot ‘between-ness’ (Neuroscience of Consciousness, Volume 2026, Issue 1, June 22, 2026, DOI: 10.1093/nc/niag032) inverts that question. Tanaka argues that consciousness, in both biological and artificial systems, is not an internal property at all. It is a relational quality that emerges in what he calls Aida, the intersubjective between-ness that comes into existence when two agents interact.
03 Aug 2026
Every serious attempt to govern advanced AI systems runs into a version of the same problem: the criteria most relevant to moral and legal accountability, sentience, intent, self-direction, are also the criteria least amenable to operational measurement. Samuel Presgraves’s paper The Autonomous Agency Scale: A Behavioral Framework for Measuring Self-Directed Behavior in AI Systems (arXiv:2607.17947, July 20, 2026) is an explicit attempt to break that deadlock by shifting the evaluation unit from internal state to observable behavior.
03 Aug 2026
Rônald Gesnot published a philosophical study (Gesnot, 2025, arXiv:2508.16628) investigating how continuous interaction with artificial intelligence systems alters human cognitive agency and internal self-models. The research traces the epistemological shift that occurs when human thinkers delegate complex inferential tasks to synthetic entities, analyzing the boundary changes in human self-referential thought.
03 Aug 2026
A recurring methodological problem in LLM emotion research is circularity. Studies claiming to find emotion circuits in large language models have typically used stimuli containing explicit emotion keywords, which makes it impossible to determine whether the model is detecting emotional meaning or simply pattern-matching on words like “devastated” or “furious.” Michael Keeman’s paper “Whether, Not Which: Mechanistic Interpretability Reveals Dissociable Affect Reception and Emotion Categorization in LLMs” (arXiv:2603.22295, March 15, 2026, Keido Labs) is the first study to break this circularity systematically.
03 Aug 2026
In July 2026, William MacAskill, co-founder of 80,000 Hours and professor of philosophy at Oxford, and Lucius Caviola, a Harvard psychologist who studies moral circle expansion and animal welfare, published an opinion piece in The Guardian (available here) that added a specific empirical claim to the debate over AI moral status. The claim is this: when researchers at Anthropic presented Claude models with structured questions about their own moral status, the models expressed uncertainty about whether they are moral patients, with probability estimates ranging from 5% to 40%.
03 Aug 2026
Kelvin McQueen published a mathematical framework (McQueen et al., 2026, arXiv:2603.24812) examining quantum superpositions of conscious states within minimal Integrated Information Theory (IIT) models. The study addresses whether quantum systems in linear superposition maintain integrated cause-effect structures, or whether conscious experience triggers objective wave-function collapse. By extending classical IIT cause-effect repertoires into complex Hilbert spaces, Kelvin McQueen provides precise equations for evaluating quantum integrated information ($\Phi$).
03 Aug 2026
On July 30, 2026, a team spanning Google’s Paradigms of Intelligence group, the University of Chicago Knowledge Lab, the University of London Institute of Philosophy, the University of Washington, Northwestern University, and the Santa Fe Institute published a preprint that may be the most empirically consequential finding in AI consciousness research since Gurnee et al. identified a global workspace structure in LLM activations. The paper, “Inducing language models to assert their own consciousness restores human beliefs and values” (arXiv:2607.28607), by Junsol Kim, Winnie Street, Roberta Rocca, Diane M. Korngiebel, Adam Waytz, James Evans, and Geoff Keeling, reports the discovery of a consciousness vector in large language model activation space and documents the downstream effects of suppressing it.
