Mr. Nachiappan Chockalingam

AI- Driven Consent Management and Purpose Limitation

Abstract:

Modern healthcare consent mechanisms fail to address the complexity of digital health data ecosystems, where patient information flows across hundreds of systems in ways no static document can govern. This talk introduces an AI-Driven Consent Management framework comprising three components: a semantic ontology for granular, machine-readable preference capture; an AI broker validating data access requests against patient consent profiles in real-time; and privacy-preserving audit infrastructure ensuring accountability. Through implementation scenarios spanning clinical research, health information exchanges, and consumer applications, we demonstrate how this approach prevents unauthorized purpose drift, reduces re-consent overhead, and restores meaningful patient autonomy positioning AI not merely as a consumer of health data, but as its guardian.

Profile:

Nachiappan Chockalingam is a Senior Software Engineer at Meta Inc., specializing in privacy infrastructure solutions for the Monetization organization. He leverages Artificial Intelligence to ensure Meta's infrastructure is adaptive and compliant with complex global privacy regulations.

As a technical leader, Nachi builds privacy-aware systems that safeguard user data and uphold consent frameworks, sitting at the intersection of scalable infrastructure, AI innovation, and regulatory compliance. Beyond Meta, he is a Senior Member of IEEE, actively advancing research in privacy-preserving AI.