Micah Carroll

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Anca D DraganAssistant Professor at UC Berkeley // Director, AI Safety and Alignment, Google DeepMindVerified email at berkeley.edu
Rohin ShahResearch Scientist, Google DeepMindVerified email at deepmind.com
Mark HoAssistant ProfessorVerified email at stevens.edu
Pieter AbbeelUC Berkeley | CovariantVerified email at cs.berkeley.edu
Stuart RussellProfessor of Computer Science, University of California, BerkeleyVerified email at cs.berkeley.edu
Sam DevlinMicrosoft Research CambridgeVerified email at microsoft.com
Katja HofmannMicrosoft ResearchVerified email at microsoft.com
Dylan Hadfield-MenellMassachusetts Institute of TechnologyVerified email at csail.mit.edu
David Scott KruegerUniversity Assistant Professor, University of CambridgeVerified email at cam.ac.uk
Alan ChanCentre for the Governance of AI; Mila, Université de MontréalVerified email at mila.quebec
Smitha MilliCornell TechVerified email at berkeley.edu
Stephanie MilaniCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Jessy LinUC BerkeleyVerified email at berkeley.edu
Matthew HausknechtLatitude AIVerified email at microsoft.com
Orr ParadiseUC BerkeleyVerified email at eecs.berkeley.edu

Micah Carroll

PhD student, UC Berkeley

Verified email at berkeley.edu - Homepage

Human-AI systems Preference Change Human Modelling Recommender systems


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
On the Utility of Learning About Humans for Human-AI Coordination M Carroll, R Shah, MK Ho, T Griffiths, S Seshia, P Abbeel, A Dragan Advances in Neural Information Processing Systems, 2019, 5174-5185, 2019	320	2019
Open problems and fundamental limitations of reinforcement learning from human feedback S Casper, X Davies, C Shi, TK Gilbert, J Scheurer, J Rando, R Freedman, ... arXiv preprint arXiv:2307.15217, 2023	147	2023
Estimating and Penalizing Induced Preference Shifts in Recommender Systems M Carroll, A Dragan, S Russell, D Hadfield-Menell International Conference on Machine Learning, 2022 (Spotlight), 2686-2708, 2022	51*	2022
Harms from Increasingly Agentic Algorithmic Systems A Chan, R Salganik, A Markelius, C Pang, N Rajkumar, D Krasheninnikov, ... Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023	37*	2023
Evaluating the Robustness of Collaborative Agents P Knott, M Carroll, S Devlin, K Ciosek, K Hofmann, AD Dragan, R Shah AAMAS 2021 (Extended Abstract), 2021	25	2021
Uni[MASK]: Unified inference in sequential decision problems M Carroll, O Paradise, J Lin, R Georgescu, M Sun, D Bignell, S Milani, ... NeurIPS 2022 (Oral), 2022	24*	2022
Characterizing Manipulation from AI Systems M Carroll, A Chan, H Ashton, D Krueger EEAMO 2023, 2023	20	2023
Engagement, user satisfaction, and the amplification of divisive content on social media S Milli, M Carroll, S Pandey, Y Wang, AD Dragan Preprint at arXiv https://doi. org/10.48550/arXiv 2305, 2023	16*	2023
Time-Efficient Reward Learning via Visually Assisted Cluster Ranking D Zhang, M Carroll, A Bobu, A Dragan NeurIPS 2022 Human in the Loop Learning (HiLL) Workshop, 2022	4	2022
Optimal Behavior Prior: Data-Efficient Human Models for Improved Human-AI Collaboration M Yang, M Carroll, A Dragan NeurIPS 2022 Human in the Loop Learning (HiLL) Workshop, 2022	4	2022
Who Needs to Know? Minimal Knowledge for Optimal Coordination N Lauffer, A Shah, M Carroll, MD Dennis, S Russell International Conference on Machine Learning 2023, 18599-18613, 2023	3	2023
Overview of current AI alignment approaches M Carroll	3	2018

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