I am the Bonnie and Marty (1964) Tenenbaum Career Development Assistant Professor of EECS at MIT. I run the Algorithmic Alignment Group in the Computer Science and Artificial Intelligence Laboratory (CSAIL) and I'm also a Schmidt Sciences AI2050 Early Career Fellow. My research develops methods to ensure that AI systems behavior aligns with the goals and values of their human users and society as a whole, a concept known as 'AI alignment'. My group and I work to address alignment challenges in multi-agent systems, human-AI teams, and societal oversight of machine learning. Our goal is to enable the safe, beneficial, and trustworthy deployment of AI in real-world settings.
Dylan Hadfield-Menell
dhm at csail.mit.edu
Bonnie and Marty (1964) Tenenbaum Career Development Assistant Professor of EECS
Faculty of Artificial Intelligence and Decision-Making
Computer Science and Artificial Intelligence Laboratory
Dept. of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
44 Vassar St., 45-701D
Cambridge, MA 02139
United States
Publications
Journal Publications- Spurious Normativity Enhances Learning of Compliance and Enforcement Behavior in Artificial Agents. Raphael Koster, Dylan Hadfield-Menell, Richard Everett, Laura Weidinger, Gillian K. Hadfield, and Joel Z. Leibo. Proceedings of the National Academy of Sciences of the United States (PNAS). 2022.
- When Curation Becomes Creation: Algorithms, microcontent, and the vanishing distinction between platforms and creators. Liu Leqi, Dylan Hadfield-Menell, Zachary C. Liption. Communications of the ACM. 2021.
- Guided Imitation of Task and Motion Planning. Michael J. McDonald, Dylan Hadfield-Menell. Proceedings of the 5th Conference on Robot Learning (CoRL). 2021.
- Consequences of Misaligned AI. Simon Zhuang, Dylan Hadfield-Menell. Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS). 2020.
- Conservative Agency via Attainable Utility Preservation. Alexander M. Turner, Dylan Hadfield-Menell, Prasad Tadepalli. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (AIES). 2020.
- The Assistive Multi-Armed Bandit. Lawrence Chan, Dylan Hadfield-Menell, Siddartha S. Srinivasa, Anca D. Dragan. Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction (HRI). 2019.
- Human-AI Learning Performance in Multi-Armed Bandits. Ravi Pandya, Sandy H. Huang, Dylan Hadfield-Menell, Anca D. Dragan. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (AIES). 2019.
- Legible Normativity for AI Alignment: The Value of Silly Rules. Dylan Hadfield-Menell, McKane Andrus, Gillian K. Hadfield. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (AIES). 2019.
- Incomplete Contracting and AI Alignment. Dylan Hadfield-Menell, Gillian K. Hadfield. Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society (AIES). 2019.
- An Efficient, Generalized Bellman Update for Cooperative Inverse Reinforcement Learning. Dhruv Malik, Malayandi Palaniappan, Jaime F. Fisac, Dylan Hadfield-Menell, Stuart J. Russell, Anca D. Dragan. Proceedings of the International Conference on Machine Learning Research (ICML). 2018.
- Simplifying Reward Design through Divide-and-Conquer. Ellis Ratner, Dylan Hadfield-Menell, Anca D. Dragan. Proceedings of Robotics: Science and Systems (RSS). 2018.
- Pragmatic-Pedagogic Value Alignment. Jaime F. Fisac, Monica A. Gates, Jessica B. Hamrick, Chang Liu, Dylan Hadfield-Menell, Malayandi Palaniappan, Dhruv Malik, S. Shankar Sastry, Thomas L. Griffiths, Anca D. Dragan. Proceedings of the International Symposium on Robotics Research (ISRR). 2017.
- Inverse Reward Design. Dylan Hadfield-Menell, Smitha Milli, Pieter Abbeel, Stuart J. Russell, Anca D. Dragan. Proceedings of the 31st Conference on Neural Information Processing Systems (NeurIPS). 2017.
- The Off-Switch Game. Dylan Hadfield-Menell, Anca D. Dragan, Pieter Abbeel, Stuart J. Russell. Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI). 2017.
- Should Robots be Obedient? Smitha Milli, Dylan Hadfield-Menell, Anca D. Dragan, Stuart J. Russell. Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI), 2017.
- Expressive Robot Motion Timing. Allan Zhou, Dylan Hadfield-Menell, and Anca D. Dragan. Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction. 2017.
- Cooperative Inverse Reinforcement Learning. Dylan Hadfield-Menell, Anca D. Dragan, Pieter Abbeel, Stuart J. Russell. Proceedings of the 30th Conference on Neural Information Processing Systems (NeurIPS), 2016.
- Sequential Quadratic Programming for Task Plan Optimization. Dylan Hadfield-Menell, Chris Lin, Rohan Chitnis, Pieter Abbeel, Stuart J. Russell. Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS). 2016.
- Guided Search for Task and Motion Plans Using Learned Heuristics. Rohan Chitnis, Dylan Hadfield-Menell, Abhishek Gupta, Siddharth Srivastava, Edward Groshev, Christopher Lin, Pieter Abbeel. Proceedings of the IEEE Conference on Robotics and Automation (ICRA). 2016.
- Modular Task and Motion Planning in Belief Space. Dylan Hadfield-Menell, Edward Groshev, Rohan Chitnis, and Pieter Abbeel. Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems (IROS). 2015.
- Multitasking: Efficient Optimal Planning for Bandit Superprocesses. Dylan Hadfield-Menell, Stuart J. Russell. Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence (UAI). 2015. Supplementary Materials.
- Beyond Lowest-Warping Cost Action Selection in Trajectory Transfer. Dylan Hadfield-Menell, Alex X. Lee, Chelsea Finn, Eric Tzeng, Sandy Huang, and Pieter Abbeel. Proceedings of the IEEE Conference on Robotics and Automation (ICRA). 2015.
- Unifying Scene Registration and Trajectory Optimization for Learning from Demonstrations with Application to Manipulation of Deformable Objects. Alex X. Lee, Sandy H. Huang, Dylan Hadfield-Menell, Eric Tzeng, Pieter Abbeel. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 2014.
- Optimization in the Now: Dynamic Peephole Optimization for Hierarchical Planning Dylan Hadfield-Menell, Leslie Pack Kaelbling, and Tomás Lozano-Pérez. Proceedings of the IEEE Conference on Robotics and Automation (ICRA). 2013.
- Estimating and Penalizing Induced Preference Shifts in Recommender Systems. Micah Carroll, Dylan Hadfield-Menell, Stuart Russell, Anca Dragan. RecSys LBR Track, FAccTRec Workshop. 2021.
- What are you optimizing for? Aligning Recommender Systems with Human Values. Jonathan Stray, Ivan Vendrov, Jeremy Nixon, Steven Adler, Dylan Hadfield-Menell. ICML Workshop on Participatory Approaches to Machine Learning. 2020.
- Multi-Principal Assistance Games: Definition and Collegial Mechanisms. Arnaud Fickinger, Simon Zhuang, Andrew Critch, Dylan Hadfield-Menell, Stuart Russell. NeurIPS Workshop on Cooperative AI. 2020.
- An Extensible Interactive Interface for Agent Design. Matthew Rahtz, James Fang, Anca D. Dragan, Dylan Hadfield-Menell. 2019.
- Adversarial Training with Voronoi Constraints. Marc Khoury, Dylan Hadfield-Menell. 2019.
- The
Principal-Agent Value Alignment Problem in
Artificial Intelligence. Ph.D. Thesis.
Advisors: Anca D. Dragan, Pieter Abbeel, Stuart J. Russell - Execution
Cost Optimization for Hierarchical Planning in the
Now. M.Eng. Thesis.
Advisors: Tomas Lozano-Perez, Leslie Pack Kaelbling