Luk Arbuckle
Chief Methodologist
Introduction to Data Privacy
Data privacy, handled responsibly, is your unshakable bedrock for earning trust. That earned trust will allow you to innovate in ways that can benefit everyone.
If you’re wondering how to leverage sensitive data without running afoul of statutory regulations, compromising the trust of your data-sharing partners, or losing the trust of the people your data represents, then this course is for you.
Introduction to Data Privacy gives you a solid overview of data privacy fundamentals, introducing you to the 5 Safes of Risk-Based Anonymization.
Data privacy, handled responsibly, is your unshakable bedrock for earning trust. That earned trust will allow you to innovate in ways that can benefit everyone.
If you’re wondering how to leverage sensitive data without running afoul of statutory regulations, compromising the trust of your data-sharing partners, or losing the trust of the people your data represents, then this course is for you.
Introduction to Data Privacy gives you a solid overview of data privacy fundamentals, introducing you to the 5 Safes of Risk-Based Anonymization.
Luk provides strategic leadership to our clients and to our organization on how to responsibly share and use data. He draws from an extensive background in statistics, data science and anonymization, and from having worked on the regulatory side as Director of Technology Analysis at the Office of the Privacy Commissioner of Canada. Clients rely on Luk to help define the architecture that will enable them to meet their privacy obligations while supporting innovative and scalable uses of their data.
Luk Arbuckle
Chief Methodologist
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 ensure the primary market research process was fully compliant with internal policies and regulations such as GDPR.
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.