Humans evolved to communicate with other humans, not with algorithms. So, to create algorithms that are better at doing what we want, we need to understand how humans communicate. Alan Cowen, CEO and Chief Scientist at Hume AI, discusses how algorithms can better understand human communication and the role this will play in the future. Cowen covers semantic space theory, a new data-driven way of thinking about emotions and how we express them. Hume runs experiments all over the world to see how humans express themselves, and measures nuances of expression in voice, language, face, and body movements. Hume then leverages this data to fine-tune models, such as GPT-3 to create a model that controls the emotional tone of a response. The goal is to create more responsive assistive technology and to enhance training tools for healthcare professionals and others.
He also discusses what new datasets and models are teaching us about the vocabulary of human expression and some of Hume’s findings, and how expressive communication and empathy can be built into modern technology. Cowen is an applied mathematician and computational emotion scientist. Prior to founding Hume AI, he was a researcher at Google AI, where he helped establish affective computing research efforts.