Abstract
Universal access in human-machine cooperation has gained significant attention with the emergence of affective computing technologies. This paper presents a comprehensive review of the current state of the field, focusing on how affective computing is shaping the landscape of universal access. We explore the key concepts, challenges, and opportunities at the intersection of affective computing and universal access, emphasizing its impact on individuals with disabilities and diverse cultural backgrounds. Additionally, we delve into ethical considerations and potential future directions for research and development. The paper delves into the realm of accessibility and affective computing, illuminating the potential of affective computing technologies to ameliorate accessibility barriers faced by individuals with disabilities. Through a comprehensive investigation, the paper assesses how emotion recognition and response systems can augment the user experience for individuals with diverse physical and cognitive impairments, thereby facilitating universal access to cutting-edge technology. Also, the European Union (EU) is currently developing an AI Act, which would establish a comprehensive regulatory framework for AI products and services within the bloc. This legislation would classify AI systems based on their risk level and impose specific requirements for each category. For example, high-risk AI systems would require mandatory conformity assessments and transparency reports. During the paper, a critical analysis about the implications of the new EU AI regulation (Act AI) will be performed, particularly in the affective computing applied to accessibility.
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Sousa, J., Santos, S., André, L., Ferreira, J. (2024). Converging Affective Computing and Ethical Challenges: The Quest for Universal Access in Human-Machine Cooperation. In: Antona, M., Stephanidis, C. (eds) Universal Access in Human-Computer Interaction. HCII 2024. Lecture Notes in Computer Science, vol 14696. Springer, Cham. https://doi.org/10.1007/978-3-031-60875-9_8
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