THE SENSE OF AGENCY IN THE USE OF GENERATIVE AI SYSTEMS IN EDUCATION FROM A SOCIAL IDENTITY THEORY APPROACH

Year 2024, Volume: 26 Issue: 2, 669 - 688, 13.12.2024

Esra Daşcı , Zeynep Uludağ

https://doi.org/10.26468/trakyasobed.1478054

Abstract

Social identity theory is widely accepted to explain intergroup relations for any group. Decisions are influenced by people's social identity which moderates the agent’s sense of agency -one’s feelings of controlling their own actions; therefore, both should be considered while investigating human-generative AI interactions and possible challenges that arise from them. This review starts with discussing human-AI interactions in terms of Social Identity Theory; then, focuses on the sense of agency that plays out in human-AI interactions moderated by social identity; and finally, discusses consequences that would be raised from these correlations. Accountability is one of the concerns related to human-AI interaction. The diversity of the users and the data is another concern. We conclude the review by suggesting a future direction for empirical research on social aspects of the sense of agency in human-AI interactions and provide possible solutions to ethical and social concerns regarding the use of generative AI systems.

Keywords

generative AI, sense of agency, social identitiy theory, educat,on, intergroup relations, diversity

EĞİTİMDE ÜRETKEN YAPAY ZEKANIN KULLANIMINDA KONTROL DUYGUSUNUN SOSYAL KİMLİK KURAMI ÇERÇEVESİNDEN DEĞERLENDİRİLMESİ

Abstract

Sosyal kimlik teorisinin herhangi bir grup için gruplar arası ilişkileri açıkladığı yaygın olarak kabul edilmektedir. Kararlar, kişilerin sosyal kimliklerinden etkilenir; bu da, kişinin kontrol duygusunu -kişinin kendi eylemlerini kontrol etme duygusu etkiler; bu nedenle, insan ve üreten yapay zeka etkileşimleri ve bunlardan kaynaklanan olası zorluklar araştırılırken her ikisi de dikkate alınmalıdır. Bu inceleme, insan-yapay zeka etkileşimlerinin Sosyal Kimlik Kuramı açısından tartışılmasıyla başlıyor; daha sonra sosyal kimliğin gruplar arası etkileşimindeki önemini özellikle insan-yapay zeka etkileşimlerinde ortaya çıkan kontrol duygusuyla bağdaştırarak tartışarak; ve son olarak bu korelasyonlardan ortaya çıkabilecek sonuçları tartışmaktadır. Sorumluluk, insan-yapay zeka etkileşimiyle ilgili endişelerden biridir. Kullanıcıların ve verilerin çeşitliliği başka bir endişe kaynağıdır. İncelemeyi, insan-yapay zeka etkileşimlerinde aracılık duygusunun sosyal yönlerine ilişkin ampirik araştırmalar için gelecekteki bir yön önererek sonlandırıyoruz ve üretken yapay zeka sistemlerinin kullanımına ilişkin etik ve sosyal kaygılara olası çözümler sunuyoruz.

Keywords

üretken yapay zeka, kontrol duygusu, sosyal kimlik kuramı, eğitim, gruplararası ilişkiler, çeşitlilik

References

• Abrams, D., & Hogg, M. A. (1988). Comments on the motivational status of self‐esteem in social identity and intergroup discrimination. European journal of social psychology, 18(4), 317-334.
• Ahmad, S., Rafiq, M., & Ahmad, S. (2018). Gender disparities in the use of internet among graduate students of a developing society: A case of Pakistani universities. Global Knowledge, Memory and Communication, 67(4/5), 226-243.
• Barlas, Z., & Obhi, S. S. (2013). Freedom, choice, and the sense of agency. Frontiers in human neuroscience, 7, 514.
• Berberian, B., Sarrazin, J. C., Le Blaye, P., & Haggard, P. (2012). Automation technology and sense of control: a window on human agency. PloS one, 7(3), e34075.
• Bowskill, N. W. D. (2013). A social identity approach to learning with classroom technologies (Doctoral dissertation, University of Glasgow).
• Celi, L. A., Cellini, J., Charpignon, M. L., Dee, E. C., Dernoncourt, F., Eber, R., ... & Yao, S. (2022). Sources of bias in artificial intelligence that perpetuate healthcare disparities—A global review. PLOS Digital Health, 1(3), e0000022.
• Chan, C. K. Y., & Hu, W. (2023). Students' Voices on Generative AI: Perceptions, Benefits, and Challenges in Higher Education. arXiv preprint arXiv:2305.00290.
• Chauhan, P. S., & Kshetri, N. (2022). The role of data and artificial intelligence in driving diversity, equity, and inclusion. Computer, 55(4), 88-93.
• Cooper, G. (2023). Examining science education in chatgpt: An exploratory study of generative artificial intelligence. Journal of Science Education and Technology, 32(3), 444-452.
• Dele-Ajayi, O., Strachan, R., Anderson, E. V., & Victor, A. M. (2019, October). Technology-enhanced teaching: A technology acceptance model to study teachers’ intentions to use digital games in the classroom. In 2019 IEEE Frontiers in Education Conference (FIE) (pp. 1-8). IEEE.
• Derks, B., Van Laar, C., & Ellemers, N. (2007). The beneficial effects of social identity protection on the performance motivation of members of devalued groups. Social Issues and Policy Review, 1(1), 217-256.
• Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., ... & Wright, R. (2023). “So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642.
• Edwards, B. I., & Cheok, A. D. (2018). Why not robot teachers: artificial intelligence for addressing teacher shortage. Applied Artificial Intelligence, 32(4), 345-360.
• Edwards, C., & Harwood, J. (2003). Social identity in the classroom: An examination of age identification between students and instructors. Communication Education, 52(1), 60-65.
• Edwards, C., Edwards, A., Stoll, B., Lin, X., & Massey, N. (2019). Evaluations of an artificial intelligence instructor's voice: Social Identity Theory in human-robot interactions. Computers in Human Behavior, 90, 357-362.
• Emerson, K. T., & Murphy, M. C. (2014). Identity threat at work: How social identity threat and situational cues contribute to racial and ethnic disparities in the workplace. Cultural Diversity and Ethnic Minority Psychology, 20(4), 508.
• Eom, K., Kim, H. S., & Sherman, D. K. (2018). Social class, control, and action: Socioeconomic status differences in antecedents of support for pro-environmental action. Journal of Experimental Social Psychology, 77, 60-75.
• Esteban, J., & Schneider, G. (2008). Polarization and conflict: Theoretical and empirical issues. Journal of Peace Research, 45(2), 131-141.
• Fosch-Villaronga, E., & Poulsen, A. (2022). Diversity and inclusion in artificial intelligence. Law and Artificial Intelligence: Regulating AI and Applying AI in Legal Practice, 109-134.
• Georgieff, N., & Jeannerod, M. (1998). Beyond consciousness of external reality: a “who” system for consciousness of action and self-consciousness. Consciousness and cognition, 7(3), 465-477.
• Hacker, P., Engel, A., & Mauer, M. (2023, June). Regulating ChatGPT and other large generative AI models. In Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (pp. 1112-1123).
• Haggard, P. (2017). Sense of agency in the human brain. Nature Reviews Neuroscience, 18(4), 196-207.
• Harwood, J. (2006). Communication as social identity. Communication as...: Perspectives on theory, 84-90.
• Hois, J., Theofanou-Fuelbier, D., & Junk, A. J. (2019). How to achieve explainability and transparency in human AI interaction. In HCI International 2019-Posters: 21st International Conference, HCII 2019, Orlando, FL, USA, July 26–31, 2019, Proceedings, Part II 21 (pp. 177-183). Springer International Publishing.
• Hogg, M. A. (2016). Social identity theory (pp. 3-17). Springer International Publishing.
• Karsh, N., & Eitam, B. (2015). I control therefore I do: Judgments of agency influence action selection. Cognition, 138, 122-131.
• Karsh, N., Eitam, B., Mark, I., & Higgins, E. T. (2016). Bootstrapping agency: How control-relevant information affects motivation. Journal of Experimental Psychology: General, 145(10), 1333.
• Kelly, S. (2009). Social identity theories and educational engagement. British Journal of Sociology of Education, 30(4), 449-462.
• King, M. R. (2023). A conversation on artificial intelligence, chatbots, and plagiarism in higher education. Cellular and molecular bioengineering, 16, 1-2. https://doi.org/10.1007/s12195-022-00754-8
• Kleebayoon A. & Wiwanitkit V. (2023) Artifivial Intelligence, chatbots, Plagiarism and Basic Honesty: Comment. Cellular and Mollecular Bioengineering, 16, 173-174. https://doi.org/10.1007/s12195-023-00759-x
• Kong, S., Man-Yin Cheung, W., & Zhang, G. (2020). Evaluation of an artificial intelligence literacy course for university students with diverse study backgrounds. Computers and Education: Artificial Intelligence, 2, 100026. https://doi.org/10.1016/j.caeai.2021.100026
• Leavy, S. (2018). "Gender bias in artificial intelligence: The need for diversity and gender theory in machine learning." In Proceedings of the 1st international workshop on gender equality in software engineering, 14-16. https://doi.org/10.1145/3195570.3195580
• Lee, Y., Lee, J., & Lee, Z. (2006). Social influence on technology acceptance behavior: self-identity theory perspective. ACM SIGMIS Database: The DATABASE for Advances in Information Systems, 37(2-3), 60-75.
• León, G. A., Chiou, E. K., & Wilkins, A. (2021). Accountability increases resource sharing: Effects of accountability on human and AI system performance. International Journal of Human–Computer Interaction, 37(5), 434-444.
• Lewis, A. C., & Sherman, S. J. (2003). Hiring you makes me look bad: Social-identity based reversals of the ingroup favoritism effect. Organizational Behavior and Human Decision Processes, 90(2), 262-276.
• Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. The International Journal of Management Education, 21(2), 100790.
• Liu, Y., & Froese, P. (2020). Faith and agency: The relationships between sense of control, socioeconomic status, and beliefs about god. Journal for the Scientific Study of Religion, 59(2), 311-326.
• Louvet, E., Cambon, L., Milhabet, I., & Rohmer, O. (2019). The relationship between social status and the components of agency. The Journal of social psychology, 159(1), 30-45.
• Mazman Akar, S. G. (2019). Does it matter being innovative: Teachers’ technology acceptance. Education and Information Technologies, 24(6), 3415-3432.
• McLeish, K. N., & Oxoby, R. J. (2011). Social interactions and the salience of social identity. Journal of Economic Psychology, 32(1), 172-178.
• Mealy, M., Stephan, W., & Urrutia, I. C. (2007). The acceptability of lies: A comparison of Ecuadorians and Euro-Americans. International Journal of Intercultural Relations, 31(6), 689-702.
• Meyers, D. T. (2002). Gender in the mirror: Cultural imagery and women's agency. Oxford University Press, USA. Miller, D. R. (1962). The study of social relationships: Situation, identity, and social interaction.
• Moore, J. W. (2016). What is the sense of agency and why does it matter?. Frontiers in psychology, 7, 1272.
• Moretto, G., Walsh, E., & Haggard, P. (2011). Experience of agency and sense of responsibility. Consciousness and cognition, 20(4), 1847-1854.
• Mou, Y., & Xu, K. (2017). The media inequality: Comparing the initial human-human and human-AI social interactions. Computers in Human Behavior, 72, 432-440.
• Neville, F. G., Novelli, D., Drury, J., & Reicher, S. D. (2022). Shared social identity transforms social relations in imaginary crowds. Group Processes & Intergroup Relations, 25(1), 158-173.
• Nobusako, S., Tsujimoto, T., Sakai, A., Shuto, T., Hashimoto, Y., Furukawa, E., ... & Morioka, S. (2020). The time window for sense of agency in school-age children is different from that in young adults. Cognitive Development, 54, 100891.
• Norori, N., Hu, Q., Aellen, F. M., Faraci, F. D., & Tzovara, A. (2021). Addressing bias in big data and AI for health care: A call for open science. Patterns, 2(10).
• Obhi, S. S., & Hall, P. (2011). Sense of agency in joint action: Influence of human and computer co-actors. Experimental brain research, 211, 663-670.
• Ognibene, D., Baldissarri, C., & Manfredi, A. (2023). Does ChatGPT pose a threat to human identity?.
• Pagliari, M., Chambon, V., & Berberian, B. (2022). What is new with Artificial Intelligence? Human–agent interactions through the lens of social agency. Frontiers in Psychology, 13, 954444.
• Parasuraman, R., & Riley, V. (1997). Humans and automation: Use, misuse, disuse, abuse. Human factors, 39(2), 230-253.
• Pitardi, V., Bartikowski, B., Osburg, V. S., & Yoganathan, V. (2023). Effects of gender congruity in human-robot service interactions: The moderating role of masculinity. International Journal of Information Management, 70, 102489.
• Porayska-Pomsta, K., & Rajendran, G. (2019). Accountability in human and artificial intelligence decision-making as the basis for diversity and educational inclusion. Artificial Intelligence and Inclusive Education: Speculative Futures and Emerging Practices, 39-59.
• Prada, R., Raimundo, G., Dimas, J., Martinho, C., Peña, J. F., Baptista, M., ... & Ribeiro, L. L. (2012, June). The role of social identity, rationality and anticipation in believable agents. In AAMAS (pp. 1175-1176).
• Rato, D., & Prada, R. (2021). Towards social identity in socio-cognitive agents. Sustainability, 13(20), 11390.
• Reynolds, K. J., Lee, E., Turner, I., Bromhead, D., & Subasic, E. (2017). How does school climate impact academic achievement? An examination of social identity processes. School Psychology International, 38(1), 78-97.
• Riva, G., & Gaggioli, A. (2015). Positive change and positive technology. Enabling Positive Change, Flow and Complexity in Daily Experience.–Warsaw: De Gruyter Open, 39-49.
• Seaborn, K. From Identified to Self-Identifying: Social Identity Theory for Socially Embodied Artificial Agents. Scheepers, D., & Ellemers, N. (2019). Social identity theory. Social psychology in action: Evidence-based interventions from theory to practice, 129-143.
• Schoon, I., & Cook, R. (2021). Can individual agency compensate for background disadvantage? Predicting tertiary educational attainment among males and females. Journal of youth and adolescence, 50, 408-422.
• Schwarz, G. M., & Watson, B. M. (2005). The influence of perceptions of social identity on information technology-enabled change. Group & Organization Management, 30(3), 289-318.
• Shin, D. (2020). User perceptions of algorithmic decisions in the personalized AI system: Perceptual evaluation of fairness, accountability, transparency, and explainability. Journal of Broadcasting & Electronic Media, 64(4), 541-565.
• Spaccasassi, C., Cenka, K., Petkovic, S., & Avenanti, A. (2023). Sense of agency predicts severity of moral judgments. Frontiers in psychology, 13, 1070742.
• Strait, M., Ramos, A. S., Contreras, V., & Garcia, N. (2018, August). Robots racialized in the likeness of marginalized social identities are subject to greater dehumanization than those racialized as white. In 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN) (pp. 452-457). IEEE. Sundar, S. S. (2020). Rise of machine agency: A framework for studying the psychology of human–AI interaction (HAII). Journal of Computer-Mediated Communication, 25(1), 74-88.
• Tajfel, H., Turner, J. C., Austin, W. G., & Worchel, S. (1979). An integrative theory of intergroup conflict. Organizational identity: A reader, 56(65), 9780203505984-16.
• Thelen, E., Kelso, J. S., & Fogel, A. (1987). Self-organizing systems and infant motor development. Developmental review, 7(1), 39-65.
• Tidwell, M. V. (2005). A social identity model of prosocial behaviors within nonprofit organizations. Nonprofit management and leadership, 15(4), 449-467.
• van der Wel, R. P. (2015). Me and we: Metacognition and performance evaluation of joint actions. Cognition, 140, 49-59.
• Vantrepotte, Q., Berberian, B., Pagliari, M., & Chambon, V. (2022). Leveraging human agency to improve confidence and acceptability in human-machine interactions. Cognition, 222, 105020.
• Veitch, E., & Alsos, O. A. (2022). A systematic review of human-AI interaction in autonomous ship systems. Safety science, 152, 105778.
• Vezzali, L., Stathi, S., Crisp, R. J., Giovannini, D., Capozza, D., & Gaertner, S. L. (2015). Imagined intergroup contact and common ingroup identity: An integrative approach. Social Psychology, 46(5), 265.
• Victor, T. W., Tivesten, E., Gustavsson, P., Johansson, J., Sangberg, F., & Ljung Aust, M. (2018). Automation expectation mismatch: Incorrect prediction despite eyes on threat and hands on wheel. Human factors, 60(8), 1095-1116.
• Vincent, J. (2022). OpenAI’s new chatbot can explain code and write sitcom scripts but is still easily tricked. The Verge.
• Wen, W., & Imamizu, H. (2022). The sense of agency in perception, behaviour and human–machine interactions. Nature Reviews Psychology, 1(4), 211-222.
• Wen, W., & Haggard, P. (2018). Control changes the way we look at the world. Journal of cognitive neuroscience, 30(4), 603-619.
• Wen, W., Yamashita, A., & Asama, H. (2015). The sense of agency during continuous action: performance is more important than action-feedback association. PloS one, 10(4), e0125226.
• Wienrich, C., & Latoschik, M. E. (2021). extended artificial intelligence: New prospects of human-ai interaction research. Frontiers in Virtual Reality, 2, 686783.
• Word, C. O., Zanna, M. P., & Cooper, J. (1974). The nonverbal mediation of self-fulfilling prophecies in interracial interaction. Journal of experimental social psychology, 10(2), 109-120.
• Xia, Q., Chiu, T. K., Lee, M., Sanusi, I. T., Dai, Y., & Chai, C. S. (2022). A self-determination theory (SDT) design approach for inclusive and diverse artificial intelligence (AI) education. Computers & Education, 189, 104582.
• Zanatto, D., Chattington, M., & Noyes, J. (2021). Sense of agency in human-machine interaction. In Advances in Neuroergonomics and Cognitive Engineering: Proceedings of the AHFE 2021 Virtual Conferences on Neuroergonomics and Cognitive Engineering, Industrial Cognitive Ergonomics and Engineering Psychology, and Cognitive Computing and Internet of Things, July 25-29, 2021, USA (pp. 353-360). Springer International Publishing.
• Zhang, Y., Gros, T., & Mao, E. (2021). Gender disparity in students’ choices of information technology majors. Business Systems Research: International journal of the Society for Advancing Innovation and Research in Economy, 12(1), 80-95.
• “OpenAI CEO Sam Altman Says Ai Will Reshape Society, Acknowledges Risks: 'a Little Bit Scared of This'.” ABC News. ABC News Network, March 15, 2023. https://abcnews.go.com/Technology/openai-ceo-sam-altman-ai-reshape-society-acknowledges/story?id=97897122.