New Neural Framework Could Make LLMs More Empathetic

As more people turn to large-language models (LLMs) during personal crises, the companies behind them are engineering these AI-powered models to be more personal, empathetic, and understanding when prompts indicate a user is in emotional distress.

The trend is raising concern about how well prepared ChatGPT, Claude, Gemini, and other popular LLMs are to provide appropriate emotional support.

To address this concern, Georgia Tech researchers have developed a new neural framework that examines how different training sources influence empathy and social reasoning within these AI-powered models.

“A lot of people are using LLMs to help process the death of a loved one, or maybe their girlfriend broke up with them, or their boyfriend cheated on them,” said Glenn Matlin, a Ph.D. student in the School of Interactive Computing.

Matlin said the new framework he and a Georgia Tech-led research team have developed audits neural networks with an LLM and estimates the influence documents, transcripts, and other data sources have on a model’s output.