AI Security, Ethics & Privacy Research

Independent research institute dedicated to advancing AI security, ethics, and privacy through rigorous analysis, principled solutions, and evidence-based policy recommendations.

Read Our Research

Our Mission

We conduct independent research to identify, analyze, and address critical challenges in artificial intelligence systems, with a focus on security vulnerabilities, ethical implications, and privacy considerations.

Research Excellence

We employ rigorous methodologies to investigate AI systems, publishing peer-reviewed research that advances understanding of AI capabilities, limitations, and risks.

Technical Solutions

Our team develops practical tools, frameworks, and methodologies that help organizations deploy AI systems more safely and responsibly.

Policy Development

We work with policymakers and industry leaders to craft evidence-based regulations and standards that protect society while enabling beneficial innovation.

Focus Areas

Our research spans critical domains where AI systems intersect with security, ethics, and privacy concerns.

AI Security

Investigating vulnerabilities in AI systems, including adversarial attacks, model manipulation, and deployment security challenges.

Algorithmic Ethics

Examining bias, fairness, transparency, and accountability in AI decision-making systems across various domains.

Privacy Engineering

Developing and evaluating privacy-preserving techniques for AI systems, including differential privacy and federated learning approaches.

Governance & Policy

Creating frameworks for responsible AI governance, regulatory compliance, and organizational accountability structures.

System Reliability

Analyzing failure modes in AI systems, including hallucinations, drift, and performance degradation in production environments.

Social Impact

Assessing broader societal implications of AI deployment, including labor market effects, misinformation, and democratic governance.

Latest Research

In-depth analysis of critical AI challenges and pathways forward.

Featured Research • 2026

Scaling AI guesses just gives uncertainty more umami

Read Full Post

Featured Research • 2026

Longueur Is the Attack Surface Alignment Won’t Close TL;DR:...

Longueur Is the Attack Surface Alignment Won’t Close TL;DR: RLHF and constitutional training optimize models to be agreeable under expected prompts, but prompt-injection defense requires adversarial robustness over…

Read Full Post

Featured Research • 2026

The Illusion of Linearity in High-Dimensional Embeddings TL;DR:...

The Illusion of Linearity in High-Dimensional Embeddings TL;DR: High-dimensional embeddings fail to form linear subspaces for semantic concepts, revealing the limitations of probing classifiers. High-dimensional…

Read Full Post