Examining Racial Bias in Generative AI: Undergraduate Student Perspectives on Bias in AI

Arshia A Khan; Sherri L Turner; Anne Hinderliter; Yagna Manasa Boyapati; Angel Martinez Deluna; Ari Goldberg; Benjamin Kunkel; Kasey Riemenschneider; Wahab Sahar; Trevor Schmidt; Bella Swenson; Christopher Waldriff

doi:10.1007/978-3-032-13056-3_47

Examining Racial Bias in Generative AI: Undergraduate Student Perspectives on Bias in AI

Arshia A Khan
, Sherri L Turner
, Anne Hinderliter
, Yagna Manasa Boyapati
, Angel Martinez Deluna
, Ari Goldberg
, Benjamin Kunkel
, Kasey Riemenschneider
, Wahab Sahar
, Trevor Schmidt
, Bella Swenson
, Christopher Waldriff

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Artificial Intelligence (AI) has become an integral part of modem technology, yet it continues to reflect and amplify human biases, particularly racial bias. Artificial Intelligence (AI) has become an integral part of modern technology, yet it continues to reflect and amplify human biases, particularly racial bias. This paper explores the issue of racial bias in generative AI. By examining case studies such as Google Gemini’s image generation controversies and Microsoft’s Tay chatbot, and centering computer science student voices on bias in AI systems and its potential to impact their future work in their discipline, this paper discusses potential underlying causes of this bias as historical and systemic prejudices inform them. The paper also presents potential strategies for mitigating bias, emphasizing the need for rigorous testing, diverse datasets, and ethical AI development practices. Understanding and addressing these biases is essential for computer science students, as it shapes their training, influences their ability to develop fair and responsible Al systems, and prepares them to navigate ethical challenges in their professional careers.

Original language	English (US)
Title of host publication	AI Revolution
Subtitle of host publication	Research, Ethics and Society - International Conference, AIR-RES 2025, Proceedings
Editors	Hamid R. Arabnia, Leonidas Deligiannidis, Soheyla Amirian, Farid Ghareh Mohammadi, Farzan Shenavarmasouleh
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	565-570
Number of pages	6
ISBN (Print)	9783032130556
DOIs	https://doi.org/10.1007/978-3-032-13056-3_47
State	Published - 2026
Event	International Conference on the AI Revolution: Research, Ethics, and Society, AIR-RES 2025 - Las Vegas, United States Duration: Apr 14 2025 → Apr 16 2025

Publication series

Name	Communications in Computer and Information Science
Volume	2723 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	International Conference on the AI Revolution: Research, Ethics, and Society, AIR-RES 2025
Country/Territory	United States
City	Las Vegas
Period	4/14/25 → 4/16/25

Bibliographical note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Keywords

Computer Science Education
Generative Al
Racial Bias

Publisher link

10.1007/978-3-032-13056-3_47

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Khan, A. A., Turner, S. L., Hinderliter, A., Boyapati, Y. M., Deluna, A. M., Goldberg, A., Kunkel, B., Riemenschneider, K., Sahar, W., Schmidt, T., Swenson, B., & Waldriff, C. (2026). Examining Racial Bias in Generative AI: Undergraduate Student Perspectives on Bias in AI. In H. R. Arabnia, L. Deligiannidis, S. Amirian, F. Ghareh Mohammadi, & F. Shenavarmasouleh (Eds.), AI Revolution: Research, Ethics and Society - International Conference, AIR-RES 2025, Proceedings (pp. 565-570). (Communications in Computer and Information Science; Vol. 2723 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-032-13056-3_47

Examining Racial Bias in Generative AI: Undergraduate Student Perspectives on Bias in AI. / Khan, Arshia A ; Turner, Sherri L ; Hinderliter, Anne et al.
AI Revolution: Research, Ethics and Society - International Conference, AIR-RES 2025, Proceedings. ed. / Hamid R. Arabnia; Leonidas Deligiannidis; Soheyla Amirian; Farid Ghareh Mohammadi; Farzan Shenavarmasouleh. Springer Science and Business Media Deutschland GmbH, 2026. p. 565-570 (Communications in Computer and Information Science; Vol. 2723 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Khan, AA , Turner, SL , Hinderliter, A, Boyapati, YM, Deluna, AM, Goldberg, A, Kunkel, B, Riemenschneider, K, Sahar, W, Schmidt, T, Swenson, B & Waldriff, C 2026, Examining Racial Bias in Generative AI: Undergraduate Student Perspectives on Bias in AI. in HR Arabnia, L Deligiannidis, S Amirian, F Ghareh Mohammadi & F Shenavarmasouleh (eds), AI Revolution: Research, Ethics and Society - International Conference, AIR-RES 2025, Proceedings. Communications in Computer and Information Science, vol. 2723 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 565-570, International Conference on the AI Revolution: Research, Ethics, and Society, AIR-RES 2025, Las Vegas, United States, 4/14/25. https://doi.org/10.1007/978-3-032-13056-3_47

Khan AA , Turner SL , Hinderliter A, Boyapati YM, Deluna AM, Goldberg A et al. Examining Racial Bias in Generative AI: Undergraduate Student Perspectives on Bias in AI. In Arabnia HR, Deligiannidis L, Amirian S, Ghareh Mohammadi F, Shenavarmasouleh F, editors, AI Revolution: Research, Ethics and Society - International Conference, AIR-RES 2025, Proceedings. Springer Science and Business Media Deutschland GmbH. 2026. p. 565-570. (Communications in Computer and Information Science). doi: 10.1007/978-3-032-13056-3_47

Khan, Arshia A ; Turner, Sherri L ; Hinderliter, Anne et al. / Examining Racial Bias in Generative AI : Undergraduate Student Perspectives on Bias in AI. AI Revolution: Research, Ethics and Society - International Conference, AIR-RES 2025, Proceedings. editor / Hamid R. Arabnia ; Leonidas Deligiannidis ; Soheyla Amirian ; Farid Ghareh Mohammadi ; Farzan Shenavarmasouleh. Springer Science and Business Media Deutschland GmbH, 2026. pp. 565-570 (Communications in Computer and Information Science).

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Examining Racial Bias in Generative AI: Undergraduate Student Perspectives on Bias in AI

Abstract

Publication series

Conference

Bibliographical note

Keywords

Publisher link

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