Picture showing a quantified human, image from Quantified Human by Alan Warburton alanwarburton.co.uk
CategoriesArtificial IntelligenceDigital learning

Impact of AI Act on Affective Computing

As we get closer to enacting the #AIAct, I want to share a few thoughts on banning #emotionrecognition on education applications.
 
While certainly moved from a good cause, this ban risks hindering much of the community's progress in affective computing in education. 
As my colleague @deniziren puts it:
"Computational services lacking empathy or emotion-aware capabilities are merely blunt tools. How can we hope to address the human-AI alignment problem without enabling AI to understand human emotions?"
https://www.linkedin.com/pulse/impact-ai-act-affective-computing-deniz-iren-phd-pmp/ 

Technology-assisted emotion recognition is helpful in various contexts, such as supporting people with autism spectrum disorder (ASD) or Asperger syndrome.
Emotion recognition is not the only proxy for users' identity; the same can be done with speech, physiological data, etc. Do we need to ban them all? What will this mean for education research?

There are techniques which we have been using that allow the use of emotion recognition while preserving user privacy (see here: https://link.springer.com/chapter/10.1007/978-3-031-16290-9_4 )

Ultimately, the technology is never the problem per se, but what is more problematic is how it is used and for which intention. So banning a certain technology, such as emotion recognition, also blocks good-intentioned initiatives.

Published by Daniele Di Mitri

Daniele Di Mitri is a research group leader at the DIPF - Leibniz Institute for Research and Information in Education and a lecturer at the Goethe University of Frankfurt, Germany. Daniele received his PhD entitled "The Multimodal Tutor" at the Open University of The Netherlands (2020) in Learning Analytics and wearable sensor support. His research focuses on collecting and analysing multimodal data during physical interactions for automatic feedback and human behaviour analysis. Daniele's current research focuses on designing responsible Artificial Intelligence applications for education and human support. He is a "Johanna Quandt Young Academy" fellow and was elected "AI Newcomer 2021" at the KI Camp by the German Informatics Society. He is a member of the editorial board of Frontiers in Artificial Intelligence journal, a member of the CrossMMLA, a special interest group of the Society of Learning Analytics Research, and chair of the Learning Analytics Hackathon (LAKathon) series.

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