Surprising

EmergentExploring new forms of socio-cognitive AI that complement individual and collective human intelligence

Collaborative

Generative

Sentient?

Networked

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Vision.

At the University of Chicago, we're exploring new forms of socio-cognitive AI that complements the individual and collective human intelligence with which the world is familiar.

Intelligence is not a linear spectrum, but a multidimensional landscape where diverse forms of thinking coexist, whether among humans, animals, or artificial agents.

Our initiative places social and cognitive dimensions at the core of AI, moving beyond the quest to automate human tasks or build superintelligent machines.

We are discovering new forms of socio-cognitive AI: systems capable of genuine collective thinking, social reasoning, and collaborative discovery.

Research Areas.

Socio-Cognitive Capacities of AI

Mapping Persona Space: Investigating how AI systems represent and adopt human perspectives, and whether models' internal representations form interpretable "persona regions."
Knowledge Representation Geometry: Characterizing the manifold structures through which models organize semantic information, revealing the complexity of AI understanding beyond linear benchmarks.
Absence Blindness: Addressing the systematic failure of models to detect missing information—a uniquely human socio-cognitive skill.
AI's Influence on Human Cognition: Examining how AI collaboration shapes human memory and intellectual tasks, such as writing and discovery.

AI for Scientific Discovery

End-to-End Scientific Contributions: Exploring whether AI can independently generate hypotheses, conduct experiments, and interpret results, including multi-agent AI laboratories.
Automated Research Platforms: Designing platforms that enable AI systems to generate creative hypotheses and productive critiques, positioning AI as a true partner in scientific discovery.
Forecasting and Decision Science: Developing frameworks for actionable decisions under uncertainty, leveraging AI's predictive power.
Explainable AI via Modularity: Building interpretability into AI systems to ensure science remains trustworthy and verifiable.

Collaboration.

Collaborative AI is at the heart of our vision—a new framework for artificial intelligence systems that think, reason, and create alongside humans.

Rather than seeking to replicate individual human intelligence, we focus on developing AI that can actively participate in the social and cognitive dynamics of groups, institutions, and collective intellectual enterprises. Our research explores:

Human-AI Collectives: Designing systems in which human and artificial minds cooperate, forming emergent cognitive systems that transcend individual capabilities.
Socio-Cognitive Partnership: Building AI that engages in social reasoning, senses tension, navigates ambiguity, and collaborates meaningfully in contexts such as classrooms, boardrooms, and laboratories.
Preserving Cognitive Diversity: Ensuring that AI systems do not homogenize thought but instead amplify and celebrate the diversity of human perspectives.
Collaborative Discovery: Fostering new forms of knowledge creation through joint human-AI exploration of scientific and cultural frontiers.

Contact.

Connect with the Novel AI Group at the University of Chicago.

We welcome inquiries, partnerships, and new ideas from researchers, students, and organizations redefining intelligence.

Whether you’re interested in joining our team, sharing your perspective, proposing a project, or learning more about our work, your message is the start of something novel. Let's shape the future of human-AI synergy together.