Everything from the cloud and the Internet of Things (IoT) to social media has fueled massive, global data stores and a regulatory tsunami, increasing the tension between the freedom to use information and the need to govern it. For the typical enterprise, things are just getting more and more complicated.
Consider the EU’s General Data Protection Regulation (GDPR). Despite more than two years of warnings, education, nail biting and “enterprise initiatives,” a DemandBase survey issued in the months following the GDPR deadline found that only 32 percent of respondents self-reported as fully GDPR compliant, while 20 percent were completely unaware of the regulation! Similarly, a Deloitte survey found only 35 percent of respondents felt they could demonstrate a “defensible position” on GDPR compliance. And the new California Consumer Privacy Act (CaCPA) reflects that we’re really just getting started in confronting new privacy regulations.
The Impact of Machine Learning
Ironically, one of the most complex technologies gaining traction, machine learning (ML), has the potential to make life a lot simpler for legal and compliance teams. So says Jake Frazier, a Senior Managing Director at FTI Consulting and head of the Information Governance, Privacy & Security practice within the Technology segment. He’s also the Chair of the distinguished CGOC Faculty. Jake explored the topic of machine learning and governance at our recent CGOC New York event where he discussed using ML to classify email “where it lives.”
I recently had a chance to talk more to Jake about ML and shared highlights of our conversation on my Information Management blog. In the post, Jake elaborates on how ML is powering Technology Assisted Review (TAR), enabling legal eDiscovery teams to review massive data collections faster and more accurately at a dramatically lower cost. He also discusses what companies are doing right and wrong when it comes to ML, as well as some of the legal and compliance concerns of ML projects.
I also took up the topic of ML in a recently published Forbes article. I think that the most important point is that while legal and governance professionals are increasingly being invited to assess ML projects for their compliance with applicable regulations, I see the huge potential of ML to support a variety of governance tasks, including classifying data, tracking changing regulatory obligations and control requirements, monitoring specific compliance requirements, facilitating faster and more accurate legal research, and estimating lawsuit outcomes.
Join the Conversation
Unified governance, privacy, artificial intelligence, cybersecurity, interacting with global authorities…the list of topics covered by the CGOC is ever-growing and increasingly vital to legal and compliance teams. Please join the conversation by becoming a CGOC member.
Not a member? Join the community
Already a member? Sign in
Become a CGOC Member and have access to resources, white papers, surveys, proceedings, and practice tools such as the Information Economic Process Assessment Kit. CGOC Members receive first priority to regional CGOC executive meetings around the world.
Asterisks (*) indicate fields required for registration