Constructionist Steps Towards an Autonomously Empathetic System
This work addresses the challenge of building more reliable empathetic AI systems for applications like human-computer interaction, though it appears incremental as it builds on existing constructionist theories without claiming major breakthroughs.
The researchers tackled the problem of creating an autonomous system to predict human thoughts or feelings from facial expressions by rejecting outdated emotion models and instead using a constructionist approach that treats emotions as mental constructs dependent on individual users and context. Their system aims to improve accuracy by relying on provable ground truths to avoid inaccurate conclusions common in prior methods.
Prior efforts to create an autonomous computer system capable of predicting what a human being is thinking or feeling from facial expression data have been largely based on outdated, inaccurate models of how emotions work that rely on many scientifically questionable assumptions. In our research, we are creating an empathetic system that incorporates the latest provable scientific understanding of emotions: that they are constructs of the human mind, rather than universal expressions of distinct internal states. Thus, our system uses a user-dependent method of analysis and relies heavily on contextual information to make predictions about what subjects are experiencing. Our system's accuracy and therefore usefulness are built on provable ground truths that prohibit the drawing of inaccurate conclusions that other systems could too easily make.