Challenges of Generative Artificial Intelligence in Building Accessible Computational Systems
Abstract
In recent times, advancements in the field of Artificial Intelligence (AI) have shown promising adoption in various sectors of society and led to numerous studies on their implications. This systematic mapping explores the intersection of accessibility and Generative AI, examining contributions from the literature and their potential consequences for users with disabilities or reduced mobility by investigating how these AI techniques can improve their digital inclusion. As result, it was observed that there is a greater predominance of the use of the ChatGPT tool for accessibility-related issues. The contributions of this mapping corroborate the guidance for the development of accessible computational systems through Generative Artificial Intelligence.
Keywords:
accessibility, generative artificial intelligence
References
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Perdigão, L., Monteiro, F., Peixotto, B., Bianco, V. L., and Fernandes, E. (2023). Inteligência artificial para audiodescrição de imagens: uma análise da pessoa com deficiência visual. In Anais do VIII Congresso sobre Tecnologias na Educação, pages 182–191, Porto Alegre, RS, Brasil. SBC.
Tseng, C.-E., Jung, S. H., Elglaly, Y. N., Liu, Y., and Ludi, S. (2022). Exploration on integrating accessibility into an ai course. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education Volume 1, SIGCSE 2022, page 864–870, New York, NY, USA. Association for Computing Machinery.
Chowdhary, K. (2020). Fundamentals of artificial intelligence. Springer.
Freire, A. P., Cardoso, P. C. F., and Salgado, A. d. L. (2023). May we consult chatgpt in our human-computer interaction written exam? an experience report after a professor answered yes. In Proceedings of the XXII Brazilian Symposium on Human Factors in Computing Systems, pages 1–11.
Gadiraju, V., Kane, S., Dev, S., Taylor, A., Wang, D., Denton, E., and Brewer, R. (2023). "i wouldn’t say offensive but...": Disability-centered perspectives on large language models. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, FAccT ’23, page 205–216, New York, NY, USA. Association for Computing Machinery.
Gumina, S., Dalton, T., and Gerdes, J. (2023). Teaching it software fundamentals: Strategies and techniques for inclusion of large language models: Strategies and techniques for inclusion of large language models. In Proceedings of the 24th Annual Conference on Information Technology Education, SIGITE ’23, page 60–65, New York, NY, USA. Association for Computing Machinery.
Jandrey, A., Ruiz, D., and Silveira, M. (2023). Imagery contents descriptions for people with visual impairments. In Anais do XXII Simpósio Brasileiro sobre Fatores Humanos em Sistemas Computacionais, Porto Alegre, RS, Brasil. SBC.
Kitchenham, B. and Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. 2.
Lima, J., Jacaúna, R., Müller, M., and Menezes, C. (2023). Sistemas complexos com apoio do chatgpt na interpretação de gráficos para estudantes com deficiência visual. In Anais do XXXIV Simpósio Brasileiro de Informática na Educação, pages 1040–1049, Porto Alegre, RS, Brasil. SBC.
Morris, M. R. (2020). Ai and accessibility. Commun. ACM, 63(6):35–37.
Othman, A., Dhouib, A., and Nasser Al Jabor, A. (2023). Fostering websites accessibility: A case study on the use of the large language models chatgpt for automatic remediation. In Proceedings of the 16th International Conference on PErvasive Technologies Related to Assistive Environments, PETRA ’23, page 707–713, New York, NY, USA. Association for Computing Machinery.
Perdigão, L., Monteiro, F., Peixotto, B., Bianco, V. L., and Fernandes, E. (2023). Inteligência artificial para audiodescrição de imagens: uma análise da pessoa com deficiência visual. In Anais do VIII Congresso sobre Tecnologias na Educação, pages 182–191, Porto Alegre, RS, Brasil. SBC.
Tseng, C.-E., Jung, S. H., Elglaly, Y. N., Liu, Y., and Ludi, S. (2022). Exploration on integrating accessibility into an ai course. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education Volume 1, SIGCSE 2022, page 864–870, New York, NY, USA. Association for Computing Machinery.
Published
2024-10-07
How to Cite
DA SILVA, Ingrid M. Miranda; PEREIRA SILVA, Marcelo Henrique; ARRUDA TERAN, Luciano; PEREIRA MOTA, Marcelle.
Challenges of Generative Artificial Intelligence in Building Accessible Computational Systems. In: WORKSHOP ON ASPECTS OF HUMAN-COMPUTER INTERACTION FOR THE SOCIAL WEB (WAIHCWS), 15. , 2024, Brasília/DF.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 19-28.
ISSN 2596-0296.
DOI: https://doi.org/10.5753/waihcws.2024.244024.
