Sign In

Communications of the ACM


Federated Learning for Privacy-Preserving AI

keyholes and patterned background, illustration

Credit: Andrij Borys Associates, Shutterstock

There has been remarkable success of machine learning (ML) technologies in empowering practical artificial intelligence (AI) applications, such as automatic speech recognition and computer vision. However, we are facing two major challenges in adopting AI today. One is that data in most industries exist in the form of isolated islands. The other is the ever-increasing demand for privacy-preserving AI. Conventional AI approaches based on centralized data collection cannot meet these challenges. How to solve the problem of data fragmentation and isolation while complying with the privacy-protection laws and regulations is a major challenge for AI researchers and practitioners.

On the legal front, lawmakers and regulatory bodies are coming up with new laws ruling how data shall be managed and used.3 One prominent example is the adoption of the General Data Protection Regulation (GDPR) by the European Union in 2018. In the United States, the California Consumer Privacy Act will be enacted in 2020. China's Cyber Security Law, came into effect in 2017, also imposed strict controls on data collection and transactions.


No entries found

Log in to Read the Full Article

Sign In

Sign in using your ACM Web Account username and password to access premium content if you are an ACM member, Communications subscriber or Digital Library subscriber.

Need Access?

Please select one of the options below for access to premium content and features.

Create a Web Account

If you are already an ACM member, Communications subscriber, or Digital Library subscriber, please set up a web account to access premium content on this site.

Join the ACM

Become a member to take full advantage of ACM's outstanding computing information resources, networking opportunities, and other benefits.

Subscribe to Communications of the ACM Magazine

Get full access to 50+ years of CACM content and receive the print version of the magazine monthly.

Purchase the Article

Non-members can purchase this article or a copy of the magazine in which it appears.
Sign In for Full Access
» Forgot Password? » Create an ACM Web Account