Organizations with seemingly mature TPRM programs still experience failures because privacy accountability can lag behind the ...

The U.S. Department of Defense's designation of Anthropic's AI model Claude as a national security supply-chain risk could have broad implications for companies.

As organizations expand their deployment of artificial intelligence, many are looking to implement the technology for internal use including in human resource systems. While employers often view AI ...

CET As privacy incidents increasingly lead to regulatory scrutiny and class action litigation, organizations are under growing pressure to quickly and defensibly identify what sensitive information ...

As the growth of AI and other technologies speed up workplace change, credentials play an important role, signaling a professional's expertise and commanding greater compensation.

When you visit our website, the site asks your browser to store a small piece of data (text file) called a cookie on your device in order to remember information about you, such as your language ...

A new academic study offers a comprehensive attempt to map the gap between the confidentiality consumer chatbot users expect and the confidentiality they actually receive. Consumer chatbots have ...

As with seemingly every aspect of AI, legislative activity related to potential AI risks and harms has moved with unprecedented speed. Often it can take decades for policymakers to begin responding to ...

Join hundreds of AI governance professionals in Dublin to connect with peers and learn from experts how to navigate AI governance challenges, solutions, emerging trends, best practices and upcoming ...

This guide provides an overview of the main provisions of the Gramm–Leach–Bliley Act. The GLBA is a federal law that became effective in the United States In 1999 ...

Meet your colleagues in Singapore for the region’s top event. IAPP Asia Forum 2026: Privacy | AI governance | Cybersecurity law brings professionals from around the ...

High-quality, diverse and extensive datasets are fundamental for improving machine learning model performance, and web scraping helps gather the necessary data to develop more robust and generalizable ...