All Work Published on Privacy, Safety, Security
Algorithms and the Perceived Legitimacy of Content Moderation
This brief explores people’s views of Facebook’s content moderation processes, providing a pathway for better online speech platforms and improving content moderation processes.
This brief explores people’s views of Facebook’s content moderation processes, providing a pathway for better online speech platforms and improving content moderation processes.
Signal Isn’t Infallible, Despite Being One Of The Most Secure Encrypted Chat Apps
HAI Policy Fellow Riana Pfefferkorn explains the different types of risk protection the private messaging app Signal can and cannot offer its users.
HAI Policy Fellow Riana Pfefferkorn explains the different types of risk protection the private messaging app Signal can and cannot offer its users.
Response to FTC's Advanced Notice of Proposed Rulemaking on Commercial Surveillance and Data Security
Stanford scholars respond to a federal RFC on commercial surveillance and data security, focusing on the intersection of automated decision-making and information privacy.
Stanford scholars respond to a federal RFC on commercial surveillance and data security, focusing on the intersection of automated decision-making and information privacy.
Stanford HAI joined global leaders to discuss the balance between AI innovation and safety and explore future policy paths.
Stanford HAI joined global leaders to discuss the balance between AI innovation and safety and explore future policy paths.
This brief reviews the history of algorithm auditing, describes its current state, and offers best practices for conducting algorithm audits today.
This brief reviews the history of algorithm auditing, describes its current state, and offers best practices for conducting algorithm audits today.
Can AI Hold Consistent Values? Stanford Researchers Probe LLM Consistency and Bias
New research tests large language models for consistency across diverse topics, revealing that while they handle neutral topics reliably, controversial issues lead to varied answers.
New research tests large language models for consistency across diverse topics, revealing that while they handle neutral topics reliably, controversial issues lead to varied answers.
