Emotion recognition technology is quickly evolving and comprehends different technologies and processing operations to detect, collect, analyse, categori s e, re act, interact and learn emotions from persons. Such technology is also referred to as ‘affect technology’. Emotion recognition can be used in multiple areas and domains for a wide range of applications146 such as for analysing customer behaviour147 and targeted advertising and neuromarketing ; 148 in the entertainment industry , for example to provide personalised recommendations or to predict reactions to movies ; in medicine and healthcare, for example to detect depression, for suicide prevention or to detect autism, in education, for example to monitor attention or engagement of learners (pupils and students at different ages) ; in employment , for example to accompany the recruitment process, to monitor emotions or boredom of employees, but also well-being applications for ‘making workers happier’149 for law enforcement and public safety, ; for example with lie detectors or emotion screening at big events ; and for many other purposes.
Emotion recognition is frequently doubted as to its effectiveness or as to its accuracy.150 Recital 44 AI Act explains that there are ‘serious concerns about the scientific basis of AI systems aiming to identify or infer emotions, particularly as expression of emotions vary considerably across cultures and situations, and even within a single individual. Among the key shortc omings of such systems are the limited reliability, the lack of specificity and the limited generalisability.’ It further explains that emotion recognition can lead to ‘discriminatory outcomes and can be intrusive to the rights and freedoms of the concerned persons’, in particular the rights to privacy, human dignity and freedom of thought. This plays an important role in asymmetric relationships especially in the context of the workplace and education and training institutions, where both workers and students are in particularly vulnerable position s . At the same time, emotion recognition in specific use contexts, such as for safety and medical care (e.g., health treatment and diagnosis) has benefits.151