@inproceedings{mitrevska2024physiological,
	title = {Physiological Signals as Implicit Multimodal Input in Human-AI Interactions During Creative Tasks},
	author = {Teodora Mitrevska and Sven Mayer},
	year = {2024},
	booktitle = {GenAICHI: CHI 2024 Workshop on Generative AI and HCI},
	pages = {3},
	url = {https://sven-mayer.com/wp-content/uploads/2024/07/mitrevska2024physiological.pdf},
	date = {2024-01-01},
	abstract = {Recent experiments have explored AI's role in creative collaboration, producing promising outcomes. While AI excels in generating text and visual art, human-AI collaboration lacks rich feedback compared to human-human interaction. So far, textual feedback is the dominant communication between systems and humans, which is in strong contrast to feedback in human-human conversations with many nonverbal cues. For creative individuals, their mental state, especially emotions, play a big role in creating art. They project their feelings on canvas or translate them into music. However, not being able to express them verbally puts a strain on the feedback and impacts the output of the collaboration. Using methods for emotion recognition can provide insights into humans' emotional states, which can be used to improve human-AI collaborations in creative scenarios. In this work, we present the concept of factoring in human physiological signals in co-creative scenarios with Generative AI as a multimodal input. We underscore this vision by presenting three applications utilizing an emotional-aware input.},
	keywords = {physiological signals, human-AI interaction, creative tasks, multimodal input, emotion recognition, co-creative collaboration, generative AI, nonverbal cues, emotional awareness, implicit feedback}
}