Learn what steps need to be taken in order to protect private data while limiting risk of re-identification.
Drs. Ann Cavoukian and Khaled El Emam’s white paper outlines the what, why and how of de-identification and present the new research on re-identification.
Ann Cavoukian was formerly the Ontario Privacy and Information Commissioner and currently serves as the Executive Director of the Privacy and Big Data Institute at Ryerson University.
Dr. Khaled El Emam, founder of Privacy Analytics, also headed the Electronic Health Information Laboratory at the Children’s Hospital of Eastern Ontario’s Research Institute.
“Without this technology a lot of research we want to do would grind to a halt.”
– Dr. Mark Walker, Scientific Director and Co-director of the BORN Registry
Situation: California’s Consumer Privacy Act inspired Comcast to evolve the way in which they protect the privacy of customers who consent to share personal information with them.
Situation: Integrate.ai’s AI-powered tech helps clients improve their online experience by sharing signals about website visitor intent. They wanted to ensure privacy remained fully protected within the machine learning / AI context that produces these signals.
Situation: Novartis’ digital transformation in drug R&D drives their need to maximize value from vast stores of clinical study data for critical internal research enabled by their data42 platform.
Situation: CancerLinQ™, a subsidiary of American Society of Clinical Oncology, is a rapid learning healthcare system that helps oncologists aggregate and analyze data on cancer patients to improve care. To achieve this goal, they must de-identify patient data provided by subscribing practices across the U.S.
Situation: Needed to enable AI-driven product innovation with a defensible governance program for the safe and responsible use
of voice-to-text data under Shrems II.
This course runs on the 2nd Wednesday of every month, at 11 a.m. ET (45 mins). Click the button to register and select the date that works best for you.