31 citations · 60 across the 13 of their papers we have counts for
13 papers
Hidden Coalitions in Multi-Agent AI: A Spectral Diagnostic from Internal Representations
Cameron Berg, Susan L. Schneider, Mark M. Bailey
Collections of interacting AI agents can form coalitions, creating emergent group-level organization that is critical for AI safety and alignment. However, observing agent behavior…
Targeted Disruption of Hypernetworks via Spectral Partitioning
Mark M. Bailey, Matthew J. Hasenjager, Nina H. Fefferman
We study hyperedge-removal strategies for suppressing contagion on synthetic hypergraphs. Hypergraphs are generated from Erdős--Rényi, Barabási--Albert, and Watts--Strogatz seed gr…
Topology as a Language for Emergent Organization in Complex Systems: Multiscale Structure, Higher-Order Interactions, and Early Warning Signals
Mark M. Bailey
Complex systems are difficult to study not only because they are nonlinear, multiscale, and often nonstationary, but because their scientifically relevant organization is often inv…
Quotient Geometry and Persistence-Stable Metrics for Swarm Configurations
Mark M. Bailey
Can temporal information recover geometry lost by a persistence diagram? For points on the unit sphere evolving under known homogeneous complete consensus, we prove generic…
CONSENT: A Negotiation Framework for Leveraging User Flexibility in Vehicle-to-Building Charging under Uncertainty
Rishav Sen, Fangqi Liu, Jose Paolo Talusan +5
The growth of Electric Vehicles (EVs) creates a conflict in vehicle-to-building (V2B) settings between building operators, who face high energy costs from uncoordinated charging, a…
Detecting Narrative Shifts through Persistent Structures: A Topological Analysis of Media Discourse
Mark M. Bailey, Mark I. Heiligman
How can we detect when global events fundamentally reshape public discourse? This study introduces a topological framework for identifying structural change in media narratives usi…
Rethinking Technological Readiness in the Era of AI Uncertainty
S. Tucker Browne, Mark M. Bailey
Artificial intelligence (AI) is poised to revolutionize military combat systems, but ensuring these AI-enabled capabilities are truly mission-ready presents new challenges. We argu…
The Necessity of AI Audit Standards Boards
David Manheim, Sammy Martin, Mark Bailey +2
Auditing of AI systems is a promising way to understand and manage ethical problems and societal risks associated with contemporary AI systems, as well as some anticipated future r…
An International Consortium for Evaluations of Societal-Scale Risks from Advanced AI
Ross Gruetzemacher, Alan Chan, Kevin Frazier +11
Given rapid progress toward advanced AI and risks from frontier AI systems (advanced AI systems pushing the boundaries of the AI capabilities frontier), the creation and implementa…
Could AI be the Great Filter? What Astrobiology can Teach the Intelligence Community about Anthropogenic Risks
Mark M. Bailey
Where is everybody? This phrase distills the foreboding of what has come to be known as the Fermi Paradox - the disquieting idea that, if extraterrestrial life is probable in the U…
A Hypergraph-Based Machine Learning Ensemble Network Intrusion Detection System
Zong-Zhi Lin, Thomas D. Pike, Mark M. Bailey +1
Network intrusion detection systems (NIDS) to detect malicious attacks continue to meet challenges. NIDS are often developed offline while they face auto-generated port scan infilt…
Examining the Differential Risk from High-level Artificial Intelligence and the Question of Control
Kyle A. Kilian, Christopher J. Ventura, Mark M. Bailey
Artificial Intelligence (AI) is one of the most transformative technologies of the 21st century. The extent and scope of future AI capabilities remain a key uncertainty, with wides…
Social Networks as a Collective Intelligence: An Examination of the Python Ecosystem
Thomas Pike, Robert Colter, Mark Bailey +2
The Python ecosystem represents a global, data rich, technology-enabled network. By analyzing Python's dependency network, its top 14 most imported libraries and cPython (or core P…