Siobhan Hanna is helping AI companies protect one of the most important parts of model development: the human data layer. As a leader at WeLo Data, she works with foundational LLM builders and enterprise technology companies to provide high quality multilingual human data. WeLo Data's NEMO framework recently won an AI Excellence Award for helping detect fraud, misrepresentation, and data integrity risks in AI training pipelines.
In this episode, Russ and Siobhan explore why high quality human data is essential to building better AI models and dive into NEMO, WeLo Data's fraud mitigation and misrepresentation detection framework using continuous monitoring, behavioral analytics, and organizational psychology.