# Mark Nitzberg

Mark Jay Nitzberg is an American computer scientist, inventor, entrepreneur, and academic who has worked on the societal and economic impacts of artificial intelligence (AI) and its governance. Nitzberg is the executive director of the Center for Human-Compatible Artificial Intelligence at UC Berkeley, interim executive director of the International Association for Safe and Ethical Artificial Intelligence, and Director of Technology Research at the Berkeley Roundtable on the International Economy (BRIE).

## Background and education

Nitzberg earned a B.A. in Mathematics and Music Composition from the University of Oregon. He pursued his doctoral studies in Computer Science at Harvard, where he worked under the supervision of David Mumford, Ken Nakayama, Takahiro Shiota, and Alan Yuille.

## Career

Nitzberg has held roles in academia, industry, and technology development. As of 2025, he serves as the executive director of the Center for Human-Compatible Artificial Intelligence at UC Berkeley, and as an advisor to the Berkeley AI Research Lab (BAIR). He is the director of technology research at the Berkeley Roundtable on the International Economy (BRIE).
In a 2020 interview as part of the Future of Work Series at UC Davis, Nitzberg reflected on his career in artificial intelligence and shared insights into his educational background, professional experiences, and thoughts on the societal impacts of technology. He credited early mentorship from Marvin Minsky and Joseph Weizenbaum for shaping his perspectives on AI. Nitzberg emphasized the importance of cultivating adaptability and lifelong learning. He advocated for a broad-based education in liberal arts and sciences. He discussed his career decisions.
In July 2024, Nitzberg delivered a keynote address titled "US' Approach to AI Governance," in which he outlined the challenges and principles surrounding the regulation of artificial intelligence in the United States. Speaking as the executive director of the Center for Human-Compatible Artificial Intelligence at UC Berkeley, Nitzberg spoke about the complexities of regulating AI due to its black-box nature and general-purpose applications and the interplay between federal, state, and international regulatory efforts. He discussed ongoing initiatives such as the Schumer AI roadmap, California's SP 1047 bill, and existing sectoral laws. Nitzberg also advocated for global collaboration in AI governance and described his center's work on long-term strategies for ensuring AI safety.

## Selected publications
### Selected articles

* Nitzberg, M.; Shiota, T. (Aug 1992). "Nonlinear image filtering with edge and corner enhancement". IEEE Transactions on Pattern Analysis and Machine Intelligence. 14 (8): 826–833. doi:10.1109/34.149593.
* Nitzberg, Mark; Zysman, John (2022-11-02). "Algorithms, data, and platforms: the diverse challenges of governing AI". Journal of European Public Policy. 29 (11): 1753–1778. doi:10.1080/13501763.2022.2096668. ISSN 1350-1763.
* Judge, Brian; Nitzberg, Mark; Russell, Stuart (2024-05-29). "When code isn't law: rethinking regulation for artificial intelligence". Policy and Society. doi:10.1093/polsoc/puae020. ISSN 1449-4035.
* Zysman, John; Nitzberg, Mark (2024). "Generative AI and the Future of Work: Augmentation or Automation?". SSRN Electronic Journal. doi:10.2139/ssrn.4811728. ISSN 1556-5068.

## Patents

* Powell, R.D. and Nitzberg, M.J., Corbis Corp, 1998. Method and system for digital image signatures.
* Powell, R.D. and Nitzberg, M.J. (1998) Method for encoding auxiliary data within a source signal.
* Powell, R.D. and Nitzberg, M.J., Digimarc Corp, 1999. Method for image encoding.
* Sheehan, D.M., Nitzberg, M.J. and Fitzgerald, P.J., 2001. Prescription-controlled data collection system and method.