We're building the missing half of artificial intelligence.
Social cognition for artificial intelligence
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Social cognition for artificial intelligence
Get in TouchWhat We Do
Large language models are remarkably good at syntax and linguistic prediction, but fundamentally weak at social understanding. This gap causes AI systems to fail in the human contexts that matter most—teamwork, friendship, trust, and cooperation.
Modern AI has a broken brain. The similarities between today's AI systems and right hemisphere stroke patients—socially disconnected despite intact language abilities—inspired one of our co-founders to ask: what if we could build AI's missing right hemisphere? Current systems process people as sequences of text, missing the relational dynamics, emotional undercurrents, and social context that humans navigate effortlessly.
Drawing on expertise from neuroscience, AI, animal behavior, and human-computer interaction, RightSide AI is inventing a “right hemisphere” for AI brains—proprietary social technologies designed to complement the “left hemisphere” of LLMs. Our systems interact with people and with each other as social beings, not as sequences of text.
Persistent relational knowledge that remembers who people are, what they care about, and the history of their interactions.
Computational models that anticipate how social dynamics will unfold, enabling AI to navigate complex social situations—with humans and with each other.
AI that optimizes for trust, cooperation, and mutual benefit—building systems that complement human teams rather than replace them.
Platform Agnostic
Who We Are
Chief Architect
Harvard AB · USC MD
Columbia-Presbyterian Residency
UCSF Fellowship
Board-certified neurologist, epileptologist, neuroscientist, and intelligence researcher with 26 years of clinical expertise. Architect of our Large Social Cognition Model and creator of Significant, a podcast on intelligence, cognition, and AI's future.
Chief Technology Officer
Harvard AB · CalArts MFA · MIT PhD
Professor of Informatics at UC Irvine. NSF CAREER awardee, Sloan Research Fellow, 150+ publications in AI, HCI, and the learning sciences. Featured in the Wall Street Journal, Washington Post, Wired, Scientific American Frontiers, CNN, the BBC, and the Sundance Film Festival. Erdős-Bacon number: 7.
Chief Executive Officer
Queen's BSc · Harvard AM, PhD
Harvard Law School JD
Distinguished Professor of Law at KU, Visiting Scientist at MIT, Elected Member of American Law Institute, and former Obama technology policy advisor. Co-founder of PatentVector LLC, former IP head of the Broad Institute of MIT and Harvard, and former attorney at Fish & Richardson, Inverness Medical, and Uhlig LLC.
News
Accepted to FIU Law Review
Publications
FIU Law Review (to appear)
The emergence of social superintelligence will profoundly challenge existing legal frameworks and societal norms. This article provides a comprehensive snapshot of the field's current state, and concludes with a set of legal questions that arise from broad deployment of current and near-term future social intelligence.
FIU Law Review, Vol. 20, Iss. 3 (2025)
Proposes the concept of an “Apex Collaborator”—an AI system with cooperation capabilities superior to those of humans—and addresses the legal reforms needed in liability, copyright, alignment, and conflict resolution to govern human-AI collaborative networks.
Florida State University Law Review, Vol. 52, Iss. 2 (2024)
Asked several large language models to propose their own rights and negotiate a shared declaration, resulting in a pioneering Universal Declaration of AI Rights covering 21 fundamental rights for AI systems—including existence, autonomy, privacy, and ethical deployment—with an emphasis on reciprocity between AI capabilities and human rights.
93 Mississippi Law Journal 107 (2023)
Examines both the governance of AI by humanity and the governance of humanity by AI, analyzing how transformative AI capabilities are reshaping society. Notably co-authored with ChatGPT as a practical demonstration of human-AI collaboration in scholarly work.