Toward Responsible AI-Enabled Career Counselling: Ethical Frameworks, Educational Policy Challenges, and Human-Centred Practices
DOI:
https://doi.org/10.63544/ijss.v3i4.320Keywords:
Artificial Intelligence Ethics, Responsible Innovation, Career Counselling, Educational Policy, Algorithmic Fairness, Human-AI Collaboration, Digital Equity, Higher EducationAbstract
Career counselling is one of the most significant events that can happen to students' educational or careers with an impact that affects students' future employability, socioeconomic mobility and personal identity development. Using AI technologies like chatbots, recommendation algorithms, and predictive analytics in career guidance systems provides unprecedented opportunities for personalized, accessible, and data-driven career counselling. This tech integration also poses ethical risks such as algorithmic bias, decision-making transparency issues, privacy concerns, and reliance on automated recommendations that could reduce human decision-making. This systematic conceptual review integrates research across three areas: AI ethics, educational technology, and career development theory and policy to explore the potential of AI in career counselling with an eye to responsible use and practice, accountability and fairness, transparency, privacy protection, and a human-centred approach to decision making. In this paper, the main ethical challenges outlined in 21 peer-reviewed studies and policy documents, an original Responsible AI Career Counselling Framework, which combines four core dimensions of ethical infrastructure, transparent decision system, human counsellor integration and inclusive outcomes, and policy implications for educational institutions and governments, are identified. The report's key findings indicate that responsible deployment of AI tools into career counselling must address data governance and algorithmic fairness; involve human counsellors in key functions across all AI-generated recommendations; embed transparency and explainability in the use of the tools; and adopt culturally responsive practices that address inequities in the digital education system. The paper contributes to the progress of theory seeking to bring AI principles to life in career guidance settings and pinpoints key areas of research needed to better understand the downstream consequences of AI on student outcomes and career progression, then offers practical implications that affect institutional governance, counsellor training and development, ethical procurement guidelines, and student safeguarding policies. Finally, a more human-focused and equitable approach to implementing AI into career counselling requires a shift from tech-based delivery to well-defined ethical and policy frameworks and procedures that prioritize human impact.
References
Akinnagbe, O. B. (2024). Human–AI collaboration: Enhancing productivity and decision-making. International Journal of Education, Management, and Technology, 2(3), 387–417. https://doi.org/10.58578/ijemt.v2i3.4209
Amari, N. (2022). Trust, acceptance, and power: A person-centered client case study. Person-Centered & Experiential Psychotherapies, 21(1), 16–30. https://doi.org/10.1080/14779757.2022.2028662
Arrieta, A. B., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., García, S., Gil-López, S., Molina, D., Benjamins, R., Chatila, R., & Herrera, F. (2020). Explainable artificial intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Information Fusion, 58, 82–115. https://doi.org/10.1016/j.inffus.2019.12.012
Buhăescu-Ciucă, Ş. (2023). Career exploratory intentions and decidedness among students: A career self-management perspective. Journal of Pedagogy (Revista de Pedagogie), 71(1), 29–53. https://doi.org/10.26755/revped/2023.1/29
Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023). Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human Resource Management Review, 33(1), Article 100899. https://doi.org/10.1016/j.hrmr.2022.100899
Folorunso, A., Olanipekun, K., Adewumi, T., & Samuel, B. (2024). A policy framework on AI usage in developing countries and its impact. Global Journal of Engineering and Technology Advances, 21(1), 154–166. https://doi.org/10.30574/gjeta.2024.21.1.0192
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., ... Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, Article 102274. https://doi.org/10.1016/j.lindif.2023.102274
Kolhe, D., & Bhat, A. (2024). Enhancing career guidance with AI in vocational education. In Transforming education with artificial intelligence (pp. 539–550). IGI Global. https://doi.org/10.4018/979-8-3693-7570-9.ch031
Laban, O., Owin, O., & Mugenzi, M. M. (2024). Artificial intelligence, the world's giant: Transformative benefits and impact on modern business in Uganda. International Research Journal of Modernization in Engineering Technology and Science. https://doi.org/10.56726/irjmets59710
Lent, R. W., & Brown, S. D. (1996). Social cognitive approach to career development: An overview. The Career Development Quarterly, 44(4), 310–321. https://doi.org/10.1002/j.2161-0045.1996.tb00448.x
Lu, Q., Zhu, L., Xu, X., Whittle, J., Zowghi, D., & Jacquet, A. (2024). Responsible AI pattern catalogue: A collection of best practices for AI governance and engineering. ACM Computing Surveys, 56(7), 1–35. https://doi.org/10.1145/3626234
Masood, F. (2024). The role of AI in shaping the future of labor markets: A comparative analysis of developed vs. emerging economies. International Journal of Emerging Multidisciplinaries: Social Science, 3(1). https://doi.org/10.54938/ijemdss.2024.03.1.346
Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R. C. W., & Chu, S. K. W. (2023). Teachers' AI digital competencies and twenty-first century skills in the post-pandemic world. Educational Technology Research and Development, 71(1), 137–161. https://doi.org/10.1007/s11423-023-10203-6
Renger, S., & Macaskill, A. (2021). Developing the foundations for a learning-based humanistic therapy. Journal of Humanistic Psychology, 65(5), 1039–1060. https://doi.org/10.1177/00221678211007668
Rossier, J., Cardoso, P. M., & Duarte, M. E. (2020). The narrative turn in career development theories: An integrative perspective. In S. D. Brown & R. W. Lent (Eds.), The Oxford handbook of career development (pp. 169–180). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780190069704.013.13
Schiff, D. S., Kelley, S., & Camacho Ibáñez, J. (2024). The emergence of artificial intelligence ethics auditing. Big Data & Society, 11(4). https://doi.org/10.1177/20539517241299732
Sharma, S., Kumawat, S., & Garg, K. (2021). Predicting student potential using machine learning techniques. In Proceedings of the International Conference on Artificial Intelligence and Smart Systems (pp. 485–495). Springer. https://doi.org/10.1007/978-981-16-2594-7_40
Spors, V., Flintham, M., Brundell, P., & Murphy, D. (2023). Care-full data, care-less systems: Making sense of self-care technologies for mental health with humanistic practitioners in the United Kingdom. Frontiers in Computer Science, 5, Article 1230284. https://doi.org/10.3389/fcomp.2023.1230284
Stoltz, K. B., Apodaca, M., & Mazahreh, L. G. (2018). Extending the narrative process: Guided imagery in career construction counseling. The Career Development Quarterly, 66(3), 259–268. https://doi.org/10.1002/cdq.12147
Velasquez, P. A. E., & Montiel, C. J. (2018). Reapproaching Rogers: A discursive examination of client-centered therapy. Person-Centered & Experiential Psychotherapies, 17(3), 253–269. https://doi.org/10.1080/14779757.2018.1527243
Viberg, O., Kizilcec, R. F., Wise, A. F., Jivet, I., & Nixon, N. (2024). Advancing equity and inclusion in educational practices with AI-powered educational decision support systems (AI-EDSS). British Journal of Educational Technology. Advance online publication. https://doi.org/10.1111/bjet.13507
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