Data Privacy

Businesses have identified two types of generative AI: broadly applicable tools that boost personal productivity, and tailored solutions for specific purposes.

The AI Risk Repository, a database of over 700 risks posed by AI, aims to provide a shared framework for monitoring and maintaining AI risk oversight.

Company leaders need to be on top of best practices and legal requirements for data protection, including mandatory incident reporting and bans on ransomware payments.

Cloud misconfigurations, more sophisticated ransomware, and exploitation of vendors are contributing to rising cyberattacks.

A “red light, yellow light, green light” framework can help companies streamline AI governance and decision-making.

A responsible AI framework mitigates the risks from artificial intelligence systems developed outside the company.

Generative artificial intelligence raises novel legal questions about data use and how content will be regulated. A law partner offers guidance.

A roster of artificial intelligence experts calls for an international body to better identify the risks, opportunities, developments, and possible global effects of AI.

How is data used to lead, mislead, manipulate, and inform viewpoints and decisions? The MIT Institute for Data, Systems, and Society investigates.

Blockchain’s permanent record is one of its strengths, but it can cause problems for marketing strategies and consumer privacy.