Bennett B. BordenPartner
Bennett Borden is a lawyer and data scientist who has made significant contributions to the field of AI governance and algorithmic bias testing. With extensive experience in the U.S. intelligence community, he has built a reputation as a trusted AI counsel to major generative AI companies and dozens of Fortune 500 companies. Bennett's deep understanding of AI governance has helped him to establish programs in a variety of industries such as insurance, financial services, labor and employment, manufacturing, retail, health, and life sciences. Bennett is a leading authority on developing insight out of data, whether to help clients monetize and productize data, develop AI systems and algorithmic models in a legal and ethical manner, or conduct discovery and internal investigations. He also advises multinational clients regarding data privacy, security, and related regulatory compliance.
With a strong academic background, including studies at Oxford, Georgetown, and NYU, Bennett has earned a reputation as a highly skilled lawyer with expertise in algorithmic bias testing. He has helped numerous clients monitor and test their AI and automated decision-making systems for unintended bias, and his work in this area has been widely recognized. Bennett's contributions to the field have earned him the distinction of being named a Chambers ranked lawyer annually since 2015.
Bennett's legal expertise extends beyond algorithmic bias testing to include defending companies in the use of AI and automated decision-making systems, including high-profile cases such as a social media MDL case in the Northern District of California. He is a well-known legal expert in the area of AI and is able to provide clients with sound advice and legal representation. Harnessing the power of data is essential for helping clients drive value in their business operations and for telling their side of the story in litigation or regulatory investigations. Bennett advises the firm and its clients on the development and use of analytics models that enable insight, data storytelling, and economic value generation. Bennett’s groundbreaking research into the use of machine-based learning and unstructured data for organizational insight is now being put to work in data-driven early-warning systems for clients to detect and prevent corporate fraud and other misconduct.
In addition to his legal work, Bennett has authored numerous articles and publications on topics related to AI governance, algorithmic bias testing, and legal issues surrounding AI. His work has been widely cited and has helped to shape the conversation around these important issues. Bennett is a Scientific Advisor to NIST, a member of the National Conference of Lawyers and Scientists (NCLS) of the American Academy for the Advancement of Science and is a frequent speaker, author, and guest lecturer at universities and law schools, including, Georgetown University Law Center, the University of Virginia Law School, Temple University Law School, Brigham Young University and the University of Maryland College of Information Studies.
- Developed one of the world's first techniques for testing insurance underwriting and fraud detection algorithms for unintended bias. He employed this technique for more than a dozen leading insurance companies to ensure fair and accurate risk-based pricing.
- Defended a leading social media company in a multidistrict litigation alleging harm to minors from the use of the social media platform. Bennett led the team that analyzed the recommendation engine that determined how content was presented to users and developed a system to classify that content as to potential harm.
- Led the eDiscovery team for a multidistrict litigation for a global retailer facing the DOJ, FDA and OSHA investigations and a simultaneous class action. The volume of potential discovery was immense, and Bennett led the negotiations in developing a reasonable and iterative discovery protocol for the class action while also producing documents to the federal investigators.
- Led the eDiscovery team for a leading defense contractor in litigation concerning the development and manufacturing of military equipment. The volume of electronically stored information was immense and Bennett's fact development team, using advanced classification technology, was able to review more than 20 million documents in eight weeks.
- Led the eDiscovery team for a leading agricultural company in multinational arbitration involving more than 20 parties and third parties and covering ten years' worth of data. Much of this was unstructured data requiring Bennett's team of data scientists to analyze it utilizing a tool developed specifically for this litigation.
- Built and implemented a predictive compliance tool for a Fortune 50 financial services and consumer finance firm that was successfully able to identify and prevent insider threats before they were able to cause damage to the firm or its customers.
- Led a team of lawyers and data scientists in several successful pro bono class actions against police departments for unconstitutional arrest practices. These cases resulted in significant damages awards for the class and forced the police departments to implement new training requirements, tracking of individual officer conduct and new arrest procedures.
- American Sign Language
J.D., Georgetown University Law Center
- M.Sc., New York University
- B.A., George Mason University
Bennett's commitment to promoting constitutional rights and access to justice is also reflected in his pro bono work. Throughout his career, Bennett has fought to protect the civil rights of numerous pro bono clients, especially regarding police misconduct. He has partnered with the ACLU to bring numerous cases against police departments for unconstitutional practices and has used AI to increase access to justice for underserved communities. Bennett has won a Pro Bono Award every year he has been in practice. Bennett is also involved in numerous LGBTQ+ rights groups and is a passionate advocate for equality and justice for all.
Publications and media
- "DLA Piper Audits the Robots as Big Law Digs into AI Work," Bloomberg Law, December 13, 2023
- Speaker with Ashley Carr, AI ChatRoom Video Series, AI + Compliance + Litigation
- Co-author with Danny Tobey and Barclay Blair, "Law Firms of the Future Will Be Different in Three Critical Ways," Bloomberg Law, August 21, 2023
- American Civil Liberties Union
Memberships and Affiliations
- National Conference of Lawyers and Scientists (NCLS) of the American Academy for the Advancement of Science
- The Sedona Conference
- Chair, Cloud Computing Committee, American Bar Association
- Vice Chair, Big Data Committee, American Bar Association
My latest insights
Ensuring ethical AI: Key insights and compliance strategies from the Rite Aid FTC...
12 January 2024 .7 minute read
The role of harmonised standards as tools for AI act compliance
11 January 2024 .11 minute read