Blog

After a political deal had been reached on December 8, 2023, we now have an unofficial draft of the EU AI Act.

In the US, there is, as of yet, no comprehensive federal privacy legislation, but there is a federal agency, the Federal Trade Commission (FTC), that is at the forefront of notable enforcement actions.

The California Consumer Privacy Act (CCPA) has been in effect since January 1, 2020, and it has impacted the way businesses collect, use, and protect consumers’ personal information considerably.

In the contemporary landscape of health information technology, the Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule sets a national standard for the protection of individuals’ medical records and other protected health information (PHI).

The European Union’s recent review of Canada’s data protection adequacy, a follow-up to the initial adequacy decision made in 2001, offers an insightful perspective into Canada’s compliance with evolving international data privacy standards.

Recent updates to Open AI privacy policies, terms of use applicable to individuals, and business terms have sparked the interest of the privacy and business community.

Artificial Intelligence (AI) has infiltrated various sectors of our lives, leading to an urgent need for standardized frameworks to ensure its ethical and responsible use.

OpenAI is an organization known for developing a variety of artificial intelligence (AI) models and tools, which are accessible through various platforms and services. Microsoft Azure is a cloud computing platform that offers a range of services and tools for building, deploying, and managing applications.

Hello, dear community! We are thrilled to announce Private AI’s final release of 2023 with Version 3.6. Let’s explore what’s new and enhanced in this version.

Understanding key tech for data protection regulation compliance

We cover the basics of homomorphic encryption, followed by a brief overview of open source HE libraries and a tutorial on how to use one of those libraries (namely, PALISADE).

A number of people ask us why we should bother creating NLP tools that preserve privacy. Apparently not everyone spends hours thinking about data breaches and privacy infringements.

A very brief overview of privacy-preserving technologies follows for anyone who’s interested in starting out in this area. I cover symmetric encryption, asymmetric encryption, homomorphic encryption, differential privacy, and secure multi-party computation.