Bennett is a partner in the Washington DC office of DLA Piper and a data scientist who has made significant contributions to the field of AI governance and algorithmic bias testing. 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 has helped numerous clients monitor and test their AI and automated decision-making systems for unintended bias. 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. Bennett's contributions to the field have earned him the distinction of being named a Chambers ranked lawyer annually since 2015. 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. Bennett is a Scientific Advisor to NIST and a member of the National Conference of Lawyers and Scientists (NCLS) of the American Academy for the Advancement of Science.