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The Algorithmic Alignment Group is a research program at MIT CSAIL (Computer Science and Artificial Intelligence Laboratory), established when Dylan Hadfield-Menell joined MIT as an Assistant Professor in 2021. Hadfield-Menell, who holds the Bonnie and Marty Tenenbaum Career Development Professorship and was promoted to Associate Professor in 2024, directs the group within CSAIL's Embodied Intelligence cluster.

The group's mission is to develop better conceptual understanding, algorithmic techniques, and policies to make AI more safe and socially beneficial. Their work is interdisciplinary and centers on how humans and AI systems interact across the contexts of value learning, incentives, recommendation systems, debugging, and policy. Core research areas include: AI safety and robustness (adversarial attacks, unlearning methods, latent adversarial training); AI alignment and preference learning (reinforcement learning from human feedback, assistance games, goal inference); interpretability and transparency (neural network diagnostics, feature analysis, internal representations of language models); responsible AI development (auditing, open-weight model risk, deepfake harms); and…

The group believes that rigorous technical research on AI alignment · covering value learning, robustness, interpretability, and human-AI interaction · will produce concrete algorithmic techniques that can be adopted by AI developers to build safer systems. By identifying failure modes in current approaches (such as reward misspecification and feedback manipulation), developing better evaluation and auditing methods, and contributing to evidence-based AI governance, the group aims to shift how AI systems are designed and deployed. The causal chain runs from foundational research to improved alignment methods to safer AI systems in production, with policy work providing a parallel path to reducing systemic risk from advanced AI.