To investigate ethical, applied affect recognition, this workshop will leverage multimodal data that includes, but is not limited to, 2D, 3D, thermal, brain, physiological, and mobile sensor signals. This workshop aims to expose current use cases for affective computing and emerging applications of affective computing to spark future work. Along with this, this workshop has a specific focus on the ethical considerations of such work, including how to mitigate ethical concerns. Considering this, topics of the workshop will focus on questions including, but not limited to:

What inter-correlations exist between facial affect (e.g. expression) and other modalities (e.g. EEG)?
How can multimodal data be leveraged to create real-world applications of affect recognition such as prediction of stress, real-time ubiquitous emotion recognition, and impact of mood on ubiquitous subject identification?
How can we facilitate the collection of multimodal data for applied affect recognition?
What are the ethical implications of working on such questions?
How can we mitigate the ethical concerns that such work produces?
Can we positively address public fears and misconceptions regarding applied affective computing?
To address these questions, AMAR2021 targets researchers in BCI, affective computing, biometrics, computer vision, human-computer interaction, behavioral sciences, social sciences, and policy makers who are interested in leveraging multimodal data for ethical, applied affect recognition.
Topics of interest include, but are not limited to, ethical applications of the following:
Health applications with a focus on multimodal affect
Multimodal affective computing for cybersecurity applications (e.g., biometrics and IoT security)
Inter-correlations and fusion of ubiquitous multimodal data as it relates to applied emotion recognition (e.g. face and EEG data)
Leveraging ubiquitous devices to create reliable multimodal applications for emotion recognition
Applications of in-the-wild data vs. lab controlled
Facilitation and collection of multimodal data (e.g. ubiquitous data) for applied emotion recognition
Engineering applications of multimodal affect (e.g., robotics, social engineering, domain inspired hardware / sensing technologies, etc.)
Privacy and security
Institutionalized bias
Trustworthy applications of affective computing
Equal access to ethical applications of affective computing (e.g. medical applications inaccessible due to wealth inequality)
NOTE: Topics that do not demonstrate an existing or potential application of affective computing / emotion recognition are not topics of interest for this workshop.

Workshop candidates are invited to submit papers up to 4 pages plus one for references in the ACII format. Submissions to AMAR 2021 should have no substantial overlap with any other paper submitted to ACII2021 or already published. All persons who have made any substantial contribution to the work should be listed as authors, and all listed authors should have made some substantial contribution to the work. Papers presented at AMAR 2021 will appear in the IEEE Xplore digital library. Papers should follow the ACII conference format (anonymous). The paper submission portal is available through EasyChair - https://www.acii-conf.net/2021/submission/