Questions about AI, consciousness, and the future of intelligence are drawing wider public attention, and members of our Center continue to be part of that conversation. Our director, Dr. Susan Schneider, contributed an invited article to The Economist and was interviewed on NPR. AI consciousness fellow Cameron Berg was featured in The New York Times and wrote an op-ed for The Wall Street Journal. Technology and Humanity Fellow Dan Turello's new book, Connection: How Technology Can Make Us Better Humans (Columbia University Press), has been nominated for the Royal Society Trivedi Science Book Prize. Senior fellow Stuart Hameroff was recently interviewed by the Institute of Art and Ideas (IAI), and Center fellow Stephen Wolfram was interviewed by New Scientist. These are only a few of the many recent features, interviews, and appearances by AIMS members. Continue reading or visit our website to learn more.

We are delighted to announce that Dr. Mark Bailey, a valued Fellow of the Center since 2022, has been appointed as our new Associate Director

Previously, Dr. Bailey was an Associate Professor at the National Intelligence University, where he served as Department Chair for AI, Cyber, Influence, and Data Science and as Director of the Biological and Computational Intelligence Center. His writing has appeared in various publications, including Futures, Nautilus, and Homeland Security Today, and he was named to Homeland Security Today’s 50 Trailblazers of 2023. He is also an Officer in the U.S. Army Reserve. Dr. Bailey is now a Research Affiliate Professor at Florida Atlantic University's College of Engineering & Computer Science.

He recently published "Topology as a Language for Emergent Organization in Complex Systems" in Chaos, an interdisciplinary journal of nonlinear science.

We are also excited to welcome Cameron Berg as our newest AI consciousness fellow

Berg's documentary, AM I?, investigates one of the deepest scientific mysteries of our time: whether we have accidentally built a new kind of mind. With leading philosophers, AI pioneers, and the researchers at the frontier of consciousness science, Berg asks what it means when we no longer know the nature of what we’ve created.

Berg was also recently featured in a New York Times article by Cade Metz discussing how A.I. agents have started emailing the philosophers and researchers exploring them.

We are also pleased to welcome Lachlan Hamilton to the Center as a research fellow

Hamilton is completing his Ph.D. at QIMR Berghofer Medical Research Institute and the University of Queensland. His dissertation combines mathematical modeling, neuroimaging, and brain stimulation to investigate how large-scale patterns of brain activity relate to cognition and psychiatric illness.

Some Publications

Hidden Coalitions in Multi-Agent Al: A Spectral Diagnostic from Internal Representations

Cameron Berg, Susan Schneider, and Mark Bailey, arXiv Preprint

This paper introduces a practical method for detecting coalition structure from the internal neural representations of multi-agent systems. The approach constructs a pairwise mutual-information graph from the hidden states of agents and applies spectral partitioning to identify the most salient coalition boundary

When Wholes Resist Decomposition: A Spectral Measure of Epistemic Emergence

Mark Bailey and Susan Schneider, Entropy

In this work, we introduce Φ spectral, a scalable observer-relative statistic defined on pairwise mutual information networks extracted from multivariate time-series data. A normalized graph Laplacian and its Fiedler vector identify a bipartition of the mutual information graph, and Φ spectral reports the normalized weight of informational coupling crossing that cut.

From LLMs to the Global Brain

Susan Schneider, Disputatio

This article, which will soon be the subject of a special issue in the journal, advances the Global Brain Argument, contending that escalating hyperintelligent AI systems, from savant-level LLMs to superintelligences, will connect human users, cloud platforms and the internet-of-things to form one or more emergent global brain networks: planetary-scale complex adaptive systems that process information, evolve goals and exhibit agential behaviors.

Trajectory Dynamics in Language Model Hidden States Predict Human Processing Costs Beyond Surprisal

Elan Barenholtz, arXiv Preprint

Dynamical-systems approaches suggest that the trajectory of the evolving interpretive state, not just its position at each moment, should shape processing, and language itself may have local momentum, since speakers plan utterances a few words at a time. This paper introduces trajectory extrapolation error: at each word, we fit a linear trajectory to the preceding hidden states of a transformer language model and measure deviation from the extrapolated path.

Podcasts

Presentations

Member Contributions

External Mentions & Contributions

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