Lawrence Snapp (TrustScale): Fighting AI Hallucination

Kevin Werbach speaks with Lawrence Snapp, CEO of TrustScale, about why hallucinations remain a stubborn problem and what it takes to verify AI outputs against evidence. Snapp, a CPA by training, compares the current moment to Bill Gates's 2002 Trustworthy Computing memo, which helped launch the modern cybersecurity industry. He argues trustworthy AI is on the same curve, only faster. He is skeptical of labs' self-reported hallucination benchmarks, likening them to a race among mules rather than thoroughbreds, and argues that controls shouldn't be built by the companies being checked. Most questions pose dto AI have no single factual answer, so TrustScale's goal is to give users complete and accurate information, as with the multiple versions of a monthly unemployment figure, rather than declare what's true. That shift, he suggests, means future AI audit reports will look quite different from financial audits built around materiality. Snapp walks through Argus, TrustScale's verification tool, which checks AI claims against outside evidence and flags them red, yellow, or green. Argus deliberately stops short of rewriting outputs, because Snapp wants users to pause and avoid what he calls cognitive surrender. He frames hallucinations as cybersecurity threat vectors, and warns that small errors early in an agentic chain can cascade into the kind of large failures that dominate discussions of catastrophic risk. Lawrence Snapp is CEO of TrustScale, an AI training, evaluation, and assurance company that grew out of e2f, a language data firm founded more than two decades ago. He previously served as CEO of Bryj Technologies, a mobile engagement company; President and CEO of Karmia; Chief Digital Officer and SVP of Corporate Development at National CineMedia; Principal Strategist at Microsoft; and President and COO of Clipper Corporation.