MRAC Track 1: 2nd Workshop on Multimodal, Generative and Responsible Affective Computing
Shreya Ghosh, Zhixi Cai, Abhinav Dhall, Dimitrios Kollias, Roland, Goecke, Tom Gedeon

TL;DR
This workshop focuses on advancing multimodal, generative, and responsible affective computing, emphasizing ethical considerations, real-world applications, and the development of emotionally intelligent AI systems that augment human abilities.
Contribution
It introduces the first comprehensive workshop series addressing multimodal, generative, and responsible affective computing from an ethical AI perspective, expanding from lab to real-world contexts.
Findings
Highlighting ethical implications of generative affective AI
Promoting responsible development of emotionally intelligent systems
Extending affective computing principles to large-scale real-world applications
Abstract
With the rapid advancements in multimodal generative technology, Affective Computing research has provoked discussion about the potential consequences of AI systems equipped with emotional intelligence. Affective Computing involves the design, evaluation, and implementation of Emotion AI and related technologies aimed at improving people's lives. Designing a computational model in affective computing requires vast amounts of multimodal data, including RGB images, video, audio, text, and physiological signals. Moreover, Affective Computing research is deeply engaged with ethical considerations at various stages-from training emotionally intelligent models on large-scale human data to deploying these models in specific applications. Fundamentally, the development of any AI system must prioritize its impact on humans, aiming to augment and enhance human abilities rather than replace them,…
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