About Dr. Rebecca Portnoff

Dr. Rebecca Portnoff has dedicated her career to defending children from sexual abuse. She
holds a B.S.E. from Princeton and a Ph.D. from UC Berkeley, both in Computer Science, and
has been working in the intersection of machine learning (ML)/AI and child safety for over a
decade. She acts as an ecosystem leader to address emerging threats against children via
technology development, novel research, standard setting, policymaking and cross-sector
collaborations, bridging the gap between child safety experts, policymakers and technologists.


She is currently Head of Data Science & AI at Thorn, where the ML/AI and algorithmic solutions
her team builds have global impact: used across hundreds of law enforcement agencies,
hotlines and technology companies. Her policy work was among the first to establish
sociotechnical solutions to prevent generative AI-facilitated child sexual exploitation and abuse.
These solutions have been adopted by major platforms like Google and Anthropic, as well as
integrated into groundbreaking global scientific standards and regulatory tools.


Rebecca is an MIT Tech Review 35 under 35 innovator, and Fast Company AI 20. She serves
on multiple advisory boards, including the Internet Watch Foundation Board, the UNICRI AI for
Safer Children Advisory Board and the National Advisory Committee on the Trafficking of
Children and Youth in the United States. She has presented her work at venues ranging from
AWS:reInvent to the White House, and her work has been recognized and featured by outlets
such as The NYTimes, the WSJ, the AP, Forbes and more.

Rebecca Portnoff – 2024 MIT Innovator of Artificial Intelligence, Director of Data Science at Thorn, UC Berkeley PhD, known for AI research in online child exploitation

Selected Standards

Global standards, recommended practices, and protocols co-authored by Rebecca and informed by Rebecca’s work

NIST AI 100-4: Reducing Risks Posed by Synthetic Content: An Overview of Technical Approaches to Digital Content Transparency

Thorn / UK AISI Safety Protocol: UK AISI / Thorn Recommended
Practice for AI-G CSEA Prevention

IEEE Recommended Practice: Safety by Design in Generative Models to Prioritize Child Safety (publication pending)