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Generative AI in higher education and beyond

Author

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  • Hashmi, Nada
  • Bal, Anjali S.

Abstract

Generative artificial intelligence (GenAI) is a method of machine learning that uses algorithms to create new content such as images, text, and video. In the last year, the popularity of GenAI has exploded. Websites like ChatGPT and DALL-E have become ubiquitous in everything from logo and NFT creation to social media content and artistic verse construction. While the popularity of GenAI is undeniable, the adoption of these technological tools has been splintered in higher education. This conceptual study examines the relationship between transparency and responsibility in the usage of GenAI. We go further, examining the relationship between training and application of skills within higher education. Finally, we propose a framework for how higher education can engage with GenAI to better prepare students to use it outside of school.

Suggested Citation

  • Hashmi, Nada & Bal, Anjali S., 2024. "Generative AI in higher education and beyond," Business Horizons, Elsevier, vol. 67(5), pages 607-614.
  • Handle: RePEc:eee:bushor:v:67:y:2024:i:5:p:607-614
    DOI: 10.1016/j.bushor.2024.05.005
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    References listed on IDEAS

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    1. Melanie Arntz & Terry Gregory & Ulrich Zierahn, 2016. "The Risk of Automation for Jobs in OECD Countries: A Comparative Analysis," OECD Social, Employment and Migration Working Papers 189, OECD Publishing.
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    4. Hannigan, Timothy R. & McCarthy, Ian P. & Spicer, André, 2024. "Beware of botshit: How to manage the epistemic risks of generative chatbots," Business Horizons, Elsevier, vol. 67(5), pages 471-486.
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    Citations

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    Cited by:

    1. Muhammad Farrukh Shahzad & Shuo Xu & Xin An & Muhammad Asif, 2025. "Are Generative AI Technologies Transforming Education for the 21st Century? Research Trends, Challenges, and Benefits," SAGE Open, , vol. 15(3), pages 21582440251, September.
    2. Retkowsky, Jana & Hafermalz, Ella & Huysman, Marleen, 2024. "Managing a ChatGPT-empowered workforce: Understanding its affordances and side effects," Business Horizons, Elsevier, vol. 67(5), pages 511-523.
    3. Berthon, Pierre & Yalcin, Taylan & Pehlivan, Ekin & Rabinovich, Tamara, 2024. "Trajectories of AI technologies: Insights for managers," Business Horizons, Elsevier, vol. 67(5), pages 461-470.
    4. Hannigan, Timothy R. & McCarthy, Ian P. & Spicer, André, 2024. "Beware of botshit: How to manage the epistemic risks of generative chatbots," Business Horizons, Elsevier, vol. 67(5), pages 471-486.
    5. Ramaul, Laavanya & Ritala, Paavo & Ruokonen, Mika, 2024. "Creational and conversational AI affordances: How the new breed of chatbots is revolutionizing knowledge industries," Business Horizons, Elsevier, vol. 67(5), pages 615-627.
    6. repec:bcp:journl:v:9:y:2025:i:10:p:1763-1775 is not listed on IDEAS
    7. Lee, Seul Chan & Baby, Tiju & Vongvit, Rattawut & Lee, Jieun & Kim, Young Woo & Cha, Min Chul & Yoon, Sol Hee, 2026. "Development and validation of Generative AI Competence Scale (GenAIComp) among university students," Technology in Society, Elsevier, vol. 84(C).
    8. Cui, Yuanyuan (Gina) & van Esch, Patrick & Phelan, Steven, 2024. "How to build a competitive advantage for your brand using generative AI," Business Horizons, Elsevier, vol. 67(5), pages 583-594.
    9. Brewer, Jordan & Patel, Dhru & Kim, Dennie & Murray, Alex, 2024. "Navigating the challenges of generative technologies: Proposing the integration of artificial intelligence and blockchain," Business Horizons, Elsevier, vol. 67(5), pages 525-535.
    10. Elena DINU, 2024. "Exploring the impact of the AI classroom on students’ analytical and creative skills," Smart Cities International Conference (SCIC) Proceedings, Smart-EDU Hub, Faculty of Public Administration, National University of Political Studies & Public Administration, vol. 12, pages 615-622, september.
    11. Abdelhalim, Esraa & Anazodo, Kemi Salawu & Gali, Nazha & Robson, Karen, 2024. "A framework of diversity, equity, and inclusion safeguards for chatbots," Business Horizons, Elsevier, vol. 67(5), pages 487-498.

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