Affective Computing Has Changed: The Foundation Model Disruption
This work highlights the potential of Foundation Models to transform Affective Computing, an incremental step in leveraging AI for human psychology-related tasks.
The paper explores the application of Foundation Models to Affective Computing by generating and analyzing multimodal affective data across vision, linguistics, and speech, while addressing ethical and regulatory challenges.
The dawn of Foundation Models has on the one hand revolutionised a wide range of research problems, and, on the other hand, democratised the access and use of AI-based tools by the general public. We even observe an incursion of these models into disciplines related to human psychology, such as the Affective Computing domain, suggesting their affective, emerging capabilities. In this work, we aim to raise awareness of the power of Foundation Models in the field of Affective Computing by synthetically generating and analysing multimodal affective data, focusing on vision, linguistics, and speech (acoustics). We also discuss some fundamental problems, such as ethical issues and regulatory aspects, related to the use of Foundation Models in this research area.