The dark side of artificial intelligence in higher education

References

• Abramo, G., D’Angelo, C. A., & Rosati, F. (2014). Relatives in the same university faculty: Nepotism or merit? Scientometrics, 101(1), 737–749. https://doi.org/10.1007/s11192-014-1273-z
   Web of Science ®Google Scholar
• Ahmad, N., Murugesan, S., & Kshetri, N. (2023). Generative artificial intelligence and the education sector. Computer, 56(6), 72–76. https://doi.org/10.1109/MC.2023.3263576
   Web of Science ®Google Scholar
• Alexeeva, T., Diep, Q. B., Kuznetsov, N., & Zelinka, I. (2023). Forecasting and stabilizing chaotic regimes in two macroeconomic models via artificial intelligence technologies and control methods. Chaos, Solitons & Fractals, 170, 113377. https://doi.org/10.1016/j.chaos.2023.113377
   Web of Science ®Google Scholar
• Al-haimi, B., Hujainah, F., Nasir, D., & Alhroob, E. (2021). Higher education institutions with artificial intelligence: Roles, promises, and requirements. In A. Hamdan, A. E. Hassanien, R. Khamis, B. Alareeni, A. Razzaque, & B. Awwad (Eds.), Applications of artificial intelligence in business, education and healthcare (pp. 221–238). Springer.
   Google Scholar
• Allal-Chérif, O., Aranega, A. Y., & Sánchez, R. C. (2021). Intelligent recruitment: How to identify, select, and retain talents from around the world using artificial intelligence. Technological Forecasting and Social Change, 169, 120822. https://doi.org/10.1016/j.techfore.2021.120822
   Web of Science ®Google Scholar
• Alter, A. (2017). Irresistible: The rise of addictive technology and the business of keeping us hooked. Penguin.
   Google Scholar
• Álvarez-Huerta, P., Muela, A., & Larrea, I. (2023). Disposition towards critical thinking and student engagement in higher education. Innovative Higher Education, 48(2), 239–256. https://doi.org/10.1007/s10755-022-09614-9
   Web of Science ®Google Scholar
• Amhar, A., Sabrina, R., Sulasmi, E., & Saragih, M. (2022). Student critical thinking skills and student writing ability: The role of teachers’ intellectual skills and student learning. Cypriot Journal of Educational Sciences, 17(7), 2493–2510. https://doi.org/10.18844/cjes.v17i7.7683
   Google Scholar
• Angelelli, C. V., de Campos Ribeiro, G. M., Severino, M. R., Johnstone, E., Borzenkova, G., & da Silva, D. C. O. (2023). Developing critical thinking skills through gamification. Thinking Skills and Creativity, 49, 101354. https://doi.org/10.1016/j.tsc.2023.101354
   PubMed Web of Science ®Google Scholar
• Anjum, T., Farrukh, M., Heidler, P., & Tautiva, J. A. D. (2021). Entrepreneurial intention: Creativity, entrepreneurship, and university support. Journal of Open Innovation: Technology, Market, and Complexity, 7(1), 11. https://doi.org/10.3390/joitmc7010011
   Google Scholar
• Baker-Brunnbauer, J. (2021). TAII framework for trustworthy AI systems. ROBONOMICS: The Journal of the Automated Economy, 2, 17.
   Google Scholar
• Bearman, M., Ryan, J., & Ajjawi, R. (2023). Discourses of artificial intelligence in higher education: A critical literature review. Higher Education, 86(2), 369–385. https://doi.org/10.1007/s10734-022-00937-2
   Web of Science ®Google Scholar
• Belitski, M., & Desai, S. (2016). Creativity, entrepreneurship and economic development: City-level evidence on creativity spillover of entrepreneurship. The Journal of Technology Transfer, 41(6), 1354–1376. https://doi.org/10.1007/s10961-015-9446-3
   Web of Science ®Google Scholar
• Bleher, H., & Braun, M. (2022). Diffused responsibility: Attributions of responsibility in the use of AI-driven clinical decision support systems. AI and Ethics, 2(4), 747–761. https://doi.org/10.1007/s43681-022-00135-x
   PubMedGoogle Scholar
• Cambridge Dictionary. (2023). Ethics. https://dictionary.cambridge.org/dictionary/english/ethic
   Google Scholar
• Chen, H., Geng, L., Zhao, H., Zhao, C., & Liu, A. (2022). Image recognition algorithm based on artificial intelligence. Neural Computing and Applications, 34(9), 6661–6672. https://doi.org/10.1007/s00521-021-06058-8
   Web of Science ®Google Scholar
• Chen, L., Chen, P., & Lin, Z. (2020). Artificial intelligence in education: A review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510
   Web of Science ®Google Scholar
• Chiu, T. K. F., Xia, Q., Zhou, X., Chai, C. S., & Cheng, M. (2023). Systematic literature review on opportunities, challenges, and future research recommendations of artificial intelligence in education. Computers and Education: Artificial Intelligence, 4, 100118. https://doi.org/10.1016/j.caeai.2022.100118
   Google Scholar
• Choi, E. P. H., Lee, J. J., Ho, M. H., Kwok, J. Y. Y., & Lok, K. Y. W. (2023). Chatting or cheating? The impacts of ChatGPT and other artificial intelligence language models on nurse education. Nurse Education Today, 125, 105796–105796. https://doi.org/10.1016/j.nedt.2023.105796
   PubMed Web of Science ®Google Scholar
• Clarke, R. (2010). What is Überveillance? (And what should be done about it?) IEEE Technology and Society Magazine, 29(2), 17–25. https://doi.org/10.1109/MTS.2010.937030
   Web of Science ®Google Scholar
• Columbus, L. (2023). Artificial intelligence and its impact on pricing technology. In S. M. Liozu & A. Hinterhuber (Eds.), Digital pricing strategy: Capturing value from digital innovations (pp. 251–257). Routledge.
   Google Scholar
• Corazza, G. E. (2016). Potential originality and effectiveness: The dynamic definition of creativity. Creativity Research Journal, 28(3), 258–267. https://doi.org/10.1080/10400419.2016.1195627
   Web of Science ®Google Scholar
• Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20(1), 22. https://doi.org/10.1186/s41239-023-00392-8
   Web of Science ®Google Scholar
• Crow, M. (2009). University task force deepens academic involvement in ERP system. In T. D. Kidd (Ed.) Handbook of research on technology project management, Planning, and Operations (pp. 397–405). IGI Global. https://doi.org/10.4018/978-1-60566-400-2.ch025
   Google Scholar
• Culver, K. C., Braxton, J., & Pascarella, E. (2019). Does teaching rigorously really enhance undergraduates’ intellectual development? The relationship of academic rigor with critical thinking skills and lifelong learning motivations. Higher Education, 78(4), 611–627. https://doi.org/10.1007/s10734-019-00361-z
   Web of Science ®Google Scholar
• Cumming, G. (1998). Artificial intelligence in education: An exploration. Journal of Computer Assisted Learning, 14(4), 251–259. https://doi.org/10.1046/j.1365-2729.1998.1440251.x
   Web of Science ®Google Scholar
• Davenport, T. H. (2018). The AI advantage: How to put the artificial intelligence revolution to work. The MIT Press.
   Google Scholar
• Dimitrakopoulos, G., Tsakanikas, A., & Panagiotopoulos, E. (2021). Autonomous vehicles: Technologies, regulations, and societal impacts. Elsevier.
   Google Scholar
• Dogru, T., Line, N., Mody, M., Hanks, L., Abbott, J. A., Acikgoz, F., Assaf, A., Bakir, S., Berbekova, A., Bilgihan, A., Dalton, A., Erkmen, E., Geronasso, M., Gomez, D., Graves, S., Iskender, A., Ivanov, S., Kizildag, M., Lee, M., … Zhang, T. (2023). Generative artificial intelligence in the hospitality and tourism industry: Developing a framework for future research. Journal of Hospitality & Tourism Research, 1–19. https://doi.org/10.1177/10963480231188663
   Web of Science ®Google Scholar
• Dougherty, M. V. (2020). Disguised academic plagiarism: A typology and case studies for researchers and editors. Springer Nature.
   Google Scholar
• Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., Ahuja, M., Albanna, H., Albashrawi, M. A., Al-Busaidi, A. S., Balakrishnan, J., Barlette, Y., Basu, S., Bose, I., Brooks, L., Buhalis, D., … Wright, R. (2023). Opinion paper: “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. https://doi.org/10.1016/j.ijinfomgt.2023.102642
   Web of Science ®Google Scholar
• Eisenhardt, K. M. (1989). Agency theory: An assessment and review. The Academy of Management Review, 14(1), 57–74. https://doi.org/10.2307/258191
   Web of Science ®Google Scholar
• Elrayah, M. (2021). Can business ethics-based education improve HR graduates’ employability, knowledge, skills, and competence? Journal of Education for Business, 96(8), 522–529. https://doi.org/10.1080/08832323.2021.1874255
   Web of Science ®Google Scholar
• Escotet, M. Á. (2023). The optimistic future of artificial intelligence in higher education. PROSPECTS, 1–10. https://doi.org/10.1007/s11125-023-09642-z
   Google Scholar
• Fan, X., & Li, J. (2023). Artificial intelligence-driven interactive learning methods for enhancing Art and design education in higher institutions. Applied Artificial Intelligence, 37(1), 2225907. https://doi.org/10.1080/08839514.2023.2225907
   Web of Science ®Google Scholar
• Ferrer, X., van Nuenen, T., Such, J. M., Cote, M., & Criado, N. (2021). Bias and discrimination in AI: A cross-disciplinary perspective. IEEE Technology and Society Magazine, 40(2), 72–80. https://doi.org/10.1109/MTS.2021.3056293
   Web of Science ®Google Scholar
• Fesenmaier, D. R., & Wöber, K. (2023). AI, ChatGPT and the university. Annals of Tourism Research, 101, 103578. https://doi.org/10.1016/j.annals.2023.103578
   Web of Science ®Google Scholar
• Filgueiras, F. (2023). Artificial intelligence and education governance. Education, Citizenship and Social Justice. https://doi.org/10.1177/1746197923116067
   Web of Science ®Google Scholar
• Fillis, I. A. N., & Rentschler, R. (2010). The role of creativity in entrepreneurship. Journal of Enterprising Culture, 18(1), 49–81. https://doi.org/10.1142/S0218495810000501
   Google Scholar
• Fomin, V. V. (2021). The shift from traditional computing systems to artificial intelligence and the implications for bias. In J. S. Gordon (Ed.), Smart technologies and fundamental rights (pp. 316–333). Brill. https://doi.org/10.1163/9789004437876_015
   Google Scholar
• Government of Western Australia. (n.d.). Scope of Critical and creative thinking. https://k10outline.scsa.wa.edu.au/home/teaching/general-capabilities-over/critical-and-creative-thinking/introduction/scope-of-critical-and-creative-thinking
   Google Scholar
• Güngör, H. (2020). Creating value with artificial intelligence: A multi-stakeholder perspective. Journal of Creating Value, 6(1), 72–85. https://doi.org/10.1177/2394964320921071
   Google Scholar
• Halder, S., & Saha, S. (2023). The routledge handbook of education technology (1st ed.). Routledge India. https://doi.org/10.4324/9781003293545
   Google Scholar
• Händel, M., Stephan, M., Gläser-Zikuda, M., Kopp, B., Bedenlier, S., & Ziegler, A. (2022). Digital readiness and its effects on higher education students’ socio-emotional perceptions in the context of the COVID-19 pandemic. Journal of Research on Technology in Education, 54(2), 267–280. https://doi.org/10.1080/15391523.2020.1846147
   Web of Science ®Google Scholar
• Hardwicke, T. E., Wallach, J. D., Kidwell, M. C., Bendixen, T., Crüwell, S., & Ioannidis, J. P. (2020). An empirical assessment of transparency and reproducibility-related research practices in the social sciences (2014–2017). Royal Society Open Science, 7(2), 190806. https://doi.org/10.1098/rsos.190806
   PubMed Web of Science ®Google Scholar
• Heffernan, T., & Harpur, P. (2023). Discrimination against academics and career implications of student evaluations: University policy versus legal compliance. Assessment & Evaluation in Higher Education, 1–12. https://doi.org/10.1080/02602938.2023.2225806
   Web of Science ®Google Scholar
• Hofeditz, L., Clausen, S., Rieß, A., Mirbabaie, M., & Stieglitz, S. (2022). Applying XAI to an AI-based system for candidate management to mitigate bias and discrimination in hiring. Electronic Markets, 32(4), 2207–2233. https://doi.org/10.1007/s12525-022-00600-9
   PubMed Web of Science ®Google Scholar
• Horikami, A., & Takahashi, K. (2022). The tripartite thinking model of creativity. Thinking Skills and Creativity, 44, 101026. https://doi.org/10.1016/j.tsc.2022.101026
   Web of Science ®Google Scholar
• Hunkenschroer, A. L., & Luetge, C. (2022). Ethics of AI-enabled recruiting and selection: A review and research agenda. Journal of Business Ethics, 178(4), 977–1007. https://doi.org/10.1007/s10551-022-05049-6
   Web of Science ®Google Scholar
• Ivanov, S. (2023a). Automated decision-making. Foresight, 25(1), 4–19. https://doi.org/10.1108/FS-09-2021-0183
   Web of Science ®Google Scholar
• Ivanov, S. (2023b). The economics of generative AI. In Z. Lv (Ed.), Applications of generative AI. Springer Nature. in press.
   Google Scholar
• Ivanov, S., Kuyumdzhiev, M., & Webster, C. (2020). Automation fears: Drivers and solutions. Technology in Society, 63, 101431. https://doi.org/10.1016/j.techsoc.2020.101431
   Web of Science ®Google Scholar
• Ivanov, S., & Soliman, M. (2023). Game of algorithms: ChatGPT implications for the future of tourism education and research. Journal of Tourism Futures, 9(2), 214–221. https://doi.org/10.1108/JTF-02-2023-0038
   Web of Science ®Google Scholar
• Ivanov, S., & Umbrello, S. (2021). The ethics of artificial intelligence and robotisation in tourism and hospitality – A conceptual framework and research agenda. Journal of Smart Tourism, 1(4), 9–18. https://doi.org/10.52255/smarttourism.2021.1.4.3
   Google Scholar
• Ivanov, S., & Webster, C. (2018). Adoption of robots, artificial intelligence and service automation by travel, tourism and hospitality companies – a cost-benefit analysis. In V. Marinov, M. Vodenska, M. Assenova, & E. Dogramadjieva (Eds.), Traditions and innovations in contemporary tourism (pp. 190–203). Cambridge Scholars Publishing.
   Google Scholar
• Jacobs, F. R., & Chase, R. B. (2023). Operations and supply chain management: The core (6th ed.). McGraw-Hill.
   Google Scholar
• Jain, A. (2021). SPAM filtering using artificial intelligence. In N. Bhargava, R. Bhargava, P. S. Rathore, & R. Agrawal (Eds.), Artificial intelligence and data mining approaches in security frameworks. Wiley. https://doi.org/10.1002/9781119760429.ch15
   Google Scholar
• Kaplan, A., & Haenlein, M. (2019). Siri, siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1), 15–25. https://doi.org/10.1016/j.bushor.2018.08.004
   Web of Science ®Google Scholar
• Keiper, M. C., Fried, G., Lupinek, J., & Nordstrom, H. (2023). Artificial intelligence in sport management education: Playing the AI game with ChatGPT. Journal of Hospitality, Leisure, Sport & Tourism Education, 33, 100456. https://doi.org/10.1016/j.jhlste.2023.100456
   Web of Science ®Google Scholar
• Khatun, A., George, B., & Dar, S. N. (2021). Knowledge management practices in the higher education sector with special reference to business schools. Education & Self Development, 16(2), 47–59. https://doi.org/10.26907/esd.16.2.04
   Google Scholar
• King, P. M., & Mayhew, M. J. (2002). Moral judgement development in higher education: Insights from the defining issues test. Journal of Moral Education, 31(3), 247–270. https://doi.org/10.1080/0305724022000008106
   Web of Science ®Google Scholar
• Kırbaşlar, M., & Özsoy-Güneş, Z. (2015). The effect of critical thinking disposition on entrepreneurship levels: A study on future teachers. Procedia - Social and Behavioral Sciences, 174, 199–207. https://doi.org/10.1016/j.sbspro.2015.01.647
   Google Scholar
• Laufer, M., Leiser, A., Deacon, B., Perrin de Brichambaut, P., Fecher, B., Kobsda, C., & Hesse, F. (2021). Digital higher education: A divider or bridge builder? Leadership perspectives on edtech in a COVID-19 reality. International Journal of Educational Technology in Higher Education, 18(1). https://doi.org/10.1186/s41239-021-00287-6
   PubMed Web of Science ®Google Scholar
• Leavy, A., Dick, L., Meletiou-Mavrotheris, M., Paparistodemou, E., & Stylianou, E. (2023). The prevalence and use of emerging technologies in STEAM education: A systematic review of the literature. Journal of Computer Assisted Learning, 39(4), 1061–1082. https://doi.org/10.1111/jcal.12806
   Web of Science ®Google Scholar
• Lee, M., Song, Y. H., Li, L., Lee, K. Y., & Yang, S. B. (2022). Detecting fake reviews with supervised machine learning algorithms. The Service Industries Journal, 42(13-14), 1101–1121. https://doi.org/10.1080/02642069.2022.2054996
   Web of Science ®Google Scholar
• Li, B., Chen, Y., Liu, L., & Zheng, B. (2023). Users’ intention to adopt artificial intelligence-based chatbot: A meta-analysis 智能聊天机器人的用户采纳意愿研究：一项元分析. The Service Industries Journal, 1–23. https://doi.org/10.1080/02642069.2023.2217756
   Web of Science ®Google Scholar
• Li, P. P., & Wang, B. (2023). Artificial intelligence in music education. International Journal of Human–Computer Interaction, 1–10. https://doi.org/10.1080/10447318.2023.2209984
   Web of Science ®Google Scholar
• Lin, F., Wang, R., & Feng, K. (2023). Regional favouritism in Chinese university admissions. Economics of Transition and Institutional Change. https://doi.org/10.1111/ecot.12385
   Google Scholar
• Llerena, R., Álvarez, E., Castro, J. W., Rodríguez, N., & Llerena, L. (2023). Impact of lecturer training on absenteeism and Job performance: Ecuador’s higher education institution case. In A. Mesquita, A. Abreu, J. V. Carvalho, & C. H. P. de Mello (Eds.), Perspectives and trends in education and technology: Selected papers from ICITED 2022 (pp. 333–344). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-6585-2_30
   Google Scholar
• Marcinkowski, F., Kieslich, K., Starke, C., & Lünich, M. (2020). Implications of AI (un-) fairness in higher education admissions: The effects of perceived AI (un-) fairness on exit, voice and organizational reputation. In Proceedings of the 2020 conference on fairness, accountability, and transparency, Barcelona, Spain (pp. 122–130). New York: ACM. https://doi.org/10.1145/3351095.3372867
   Google Scholar
• Masters, K. (2019). Artificial intelligence in medical education. Medical Teacher, 41(9), 976–980. https://doi.org/10.1080/0142159X.2019.1595557
   PubMed Web of Science ®Google Scholar
• Merken, S. (2023, June 26). New York lawyers sanctioned for using fake ChatGPT cases in legal brief. Reuters. https://www.reuters.com/legal/new-york-lawyers-sanctioned-using-fake-chatgpt-cases-legal-brief-2023-06-22/
   Google Scholar
• Michael, M. G., & Michael, K. (2014). Uberveillance and the social implications of microchip implants: Emerging technologies. IGI Global.
   Google Scholar
• Mikalef, P., Conboy, K., Lundström, J. E., & Popovič, A. (2022). Thinking responsibly about responsible AI and ‘the dark side’ of AI. European Journal of Information Systems, 31(3), 257–268. https://doi.org/10.1080/0960085X.2022.2026621
   Web of Science ®Google Scholar
• Mukherjee, S., Baral, M. M., Nagariya, R., Venkataiah, C., Rao, U. A., & Rao, K. S. (2023). Systematic literature review and future research directions for service robots in hospitality and tourism industries. The Service Industries Journal, 1–34. https://doi.org/10.1080/02642069.2023.2243592
   Web of Science ®Google Scholar
• Müller, V. C. (2021). Ethics of artificial intelligence and robotics. In E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy (summer 2021 edition). https://plato.stanford.edu/archives/sum2021/entries/ethics-ai/
   Google Scholar
• Murugesan, S., & Cherukuri, A. K. (2023). The rise of generative artificial intelligence and Its impact on education: The promises and perils. Computer, 56(5), 116–121. https://doi.org/10.1109/MC.2023.3253292
   Web of Science ®Google Scholar
• Nguyen, A., Ngo, H. N., Hong, Y., Dang, B., & Nguyen, B. P. T. (2023). Ethical principles for artificial intelligence in education. Education and Information Technologies, 28(4), 4221–4241. https://doi.org/10.1007/s10639-022-11316-w
   PubMed Web of Science ®Google Scholar
• Nikolic, S., Daniel, S., Haque, R., Belkina, M., Hassan, G. M., Lyden, S., Neal, P., & Sandison, C. (2023). ChatGPT versus engineering education assessment: A multidisciplinary and multi-institutional benchmarking and analysis of this generative artificial intelligence tool to investigate assessment integrity. European Journal of Engineering Education, 48(4), 559–614. https://doi.org/10.1080/03043797.2023.2213169
   Web of Science ®Google Scholar
• Ouyang, F., Jiao, P., McLaren, B. M., & Alavi, A. H. (Eds.). (2022). Artificial intelligence in STEM education: The paradigmatic shifts in research, education, and technology (1st ed.). CRC Press. https://doi.org/10.1201/9781003181187
   Google Scholar
• Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, 27(6), 7893–7925. https://doi.org/10.1007/s10639-022-10925-9
   Web of Science ®Google Scholar
• Pani, S. K., Muduli, K., Jana, S. K., Bathula, S., & Khan, G. S. (Eds.). (2023). Advancements in artificial intelligence, blockchain technology, and IoT in higher education: Mitigating the impact of COVID-19 (1st ed.). Apple Academic Press. https://doi.org/10.1201/9781003300458
   Google Scholar
• Peters, M. A., Jandrić, P., & Means, A. J. (2019). Education and technological unemployment. Springer.
   Google Scholar
• Pham, S. T., & Sampson, P. M. (2022). The development of artificial intelligence in education: A review in context. Journal of Computer Assisted Learning, 38(5), 1408–1421. https://doi.org/10.1111/jcal.12687
   Web of Science ®Google Scholar
• Popenici, S. (2022). Artificial intelligence and learning futures: Critical narratives of technology and imagination in higher education (1st ed.). Routledge. https://doi.org/10.4324/9781003266563
   Google Scholar
• Porter, M. (1985). Competitive advantage. Creating and sustaining superior performance. The Free Press. Reprinted in 1998 with a new introduction.
   Google Scholar
• Prakash, A. V., Joshi, A., Nim, S., & Das, S. (2023). Determinants and consequences of trust in AI-based customer service chatbots. The Service Industries Journal, 43(9-10), 642–675. https://doi.org/10.1080/02642069.2023.2166493
   Web of Science ®Google Scholar
• Pupovac, V., & Fanelli, D. (2015). Scientists admitting to plagiarism: A meta-analysis of surveys. Science and Engineering Ethics, 21(5), 1331–1352. https://doi.org/10.1007/s11948-014-9600-6
   PubMed Web of Science ®Google Scholar
• Puzanova, Z. V., & Larina, T. I. (2021). Influence of university education on changes in students’ value orientations. Vysshee Obrazovanie v Rossii = Higher Education in Russia, 30(4), 99–111. https://doi.org/10.31992/0869-3617-2021-30-4-99-111
   Google Scholar
• Rana, N. P., Chatterjee, S., Dwivedi, Y. K., & Akter, S. (2022). Understanding dark side of artificial intelligence (AI) integrated business analytics: Assessing firm’s operational inefficiency and competitiveness. European Journal of Information Systems, 31(3), 364–387. https://doi.org/10.1080/0960085X.2021.1955628
   Web of Science ®Google Scholar
• Robertson, M. (1976). Artificial intelligence in education. Nature, 262(5568), 435–437. https://doi.org/10.1038/262435a0
   Web of Science ®Google Scholar
• Romiszowski, A. J. (1987). Artificial intelligence and expert systems in education: Potential promise or threat to teachers? Educational Media International, 24(2), 96–104. https://doi.org/10.1080/0952398870240208
   Google Scholar
• Siegel, H. (1987). Critical thinking as an intellectual right. Analytic Teaching, 8(1), 19–24.
   Google Scholar
• Simonovic, B., Vione, K., Stupple, E., & Doherty, A. (2023). It is not what you think it is how you think: A critical thinking intervention enhances argumentation, analytic thinking and metacognitive sensitivity. Thinking Skills and Creativity, 49, 101362. https://doi.org/10.1016/j.tsc.2023.101362
   Web of Science ®Google Scholar
• Singh, S. V., & Hiran, K. K. (2022). The impact of AI on teaching and learning in higher education technology. Journal of Higher Education Theory and Practice, 22(13), 135–148. https://doi.org/10.33423/jhetp.v22i13.5514
   Google Scholar
• Sinnewe, E., Yao, D., & De Zwaan, L. (2023). Developing critical thinking: An examination of contemporary practices in accounting. Accounting & Finance, 63(1), 403–425. https://doi.org/10.1111/acfi.13054
   Web of Science ®Google Scholar
• Skrzek-Lubasińska, M., & Malik, R. (2023). Is critical thinking a future skill for business success: Science mapping and literature review. Central European Management Journal, 31(1), 48–63. https://doi.org/10.1108/CEMJ-09-2021-0110
   Google Scholar
• Slack, N., Brandon-Jones, A., & Burgess, N. (2022). Operations management (10th ed.). Pearson.
   Google Scholar
• Smith, H. J., Jaurique, A., & Ryan, D. (2016). The mistreatment of others: Discrimination can undermine university identification, student health, and engagement. Social Justice Research, 29(4), 355–374. https://doi.org/10.1007/s11211-016-0274-x
   Web of Science ®Google Scholar
• Sollosy, M., & McInerney, M. (2022). Artificial intelligence and business education: What should be taught. The International Journal of Management Education, 20(3), 100720. https://doi.org/10.1016/j.ijme.2022.100720
   Web of Science ®Google Scholar
• Sousa, M. J., de Bem Machado, A., & Aparecida Dandolini, G. (Eds.). (2023). Technologies for sustainable global higher education (1st ed.). Auerbach Publications. https://doi.org/10.1201/9781003424543
   Google Scholar
• Squires, M. E., Yu, Y., & Schnackenberg, H. L. (2020). Ethics in higher education. Nova Science Publishers.
   Google Scholar
• Statista. (2023). E-learning and digital education. https://www.statista.com/study/17598/e-learning-and-digital-education-statista-dossier/
   Google Scholar
• Stevenson, W. J. (2021). Operations management (14th ed.). McGraw-Hill.
   Google Scholar
• Stoilova, E. (2021). AI chatbots as a customer service and support tool. ROBONOMICS: The Journal of the Automated Economy, 2, 21.
   Google Scholar
• Tang, C., Mao, S., Naumann, S. E., & Xing, Z. (2022). Improving student creativity through digital technology products: A literature review. Thinking Skills and Creativity, 44, 101032. https://doi.org/10.1016/j.tsc.2022.101032
   Web of Science ®Google Scholar
• Tarbit, J., Wirtz, J., Kunz, W., & Hartley, N. (2023). Interpretation of corporate digital responsibility risks and concerns by automated service technologies: An AI Co-created article. ROBONOMICS: The Journal of the Automated Economy, 4, 52.
   Google Scholar
• Teng, Y., Zhang, J., & Sun, T. (2023). Data-driven decision-making model based on artificial intelligence in higher education system of colleges and universities. Expert Systems, 40(4), e12820. https://doi.org/10.1111/exsy.12820
   Web of Science ®Google Scholar
• Tetzlaff, L., Schmiedek, F., & Brod, G. (2021). Developing personalized education: A dynamic framework. Educational Psychology Review, 33(3), 863–882. https://doi.org/10.1007/s10648-020-09570-w
   Web of Science ®Google Scholar
• Tuomi, A., Tussyadiah, I., Ling, E. C., Miller, G., & Lee, G. (2020). X=(tourism_work) y=(sdg8) while y=true: Automate(x). Annals of Tourism Research, 84, 102978. https://doi.org/10.1016/j.annals.2020.102978
   Web of Science ®Google Scholar
• Tutuncu, L., Yucedogru, R., & Sarisoy, I. (2022). Academic favoritism at work: Insider bias in turkish national journals. Scientometrics, 127(5), 2547–2576. https://doi.org/10.1007/s11192-022-04355-0
   Web of Science ®Google Scholar
• UNESCO. (2023). Global education monitoring report, 2023: Technology in education: a tool on whose terms? https://unesdoc.unesco.org/ark:/48223/pf0000385723
   Google Scholar
• Van Slyke, C., Johnson, R. D., & Sarabadani, J. (2023). Generative artificial intelligence in information systems education: Challenges, consequences, and responses. Communications of the Association for Information Systems, 53(1), 1–21. https://doi.org/10.17705/1CAIS.05301
   Web of Science ®Google Scholar
• Wagner, D. (2021). Artificial intelligence and the dark side of management. ROBONOMICS: The Journal of the Automated Economy, 1, 10.
   Google Scholar
• Walia, C. (2019). A dynamic definition of creativity. Creativity Research Journal, 31(3), 237–247. https://doi.org/10.1080/10400419.2019.1641787
   Web of Science ®Google Scholar
• Wang, S., Sun, Z., & Chen, Y. (2023). Effects of higher education institutes’ artificial intelligence capability on students’ self-efficacy, creativity and learning performance. Education and Information Technologies, 28(5), 4919–4939. https://doi.org/10.1007/s10639-022-11338-4
   Web of Science ®Google Scholar
• Webster, C., & Ivanov, S. (2020). Robotics, artificial intelligence, and the evolving nature of work. In B. George & J. Paul (Eds.), Digital transformation in business and society theory and cases (pp. 127–143). Palgrave-MacMillan.
   Google Scholar
• Williamson, B. (2019). Policy networks, performance metrics and platform markets: Charting the expanding data infrastructure of higher education. British Journal of Educational Technology, 50(6), 2794–2809. https://doi.org/10.1111/bjet.12849
   Web of Science ®Google Scholar
• Wirtz, B. W., Weyerer, J. C., & Sturm, B. J. (2020). The dark sides of artificial intelligence: An integrated AI governance framework for public administration. International Journal of Public Administration, 43(9), 818–829. https://doi.org/10.1080/01900692.2020.1749851
   Web of Science ®Google Scholar
• Wirtz, J., Hofmeister, J., Chew, P. Y., & Ding, X. (2023). Digital service technologies, service robots, AI, and the strategic pathways to cost-effective service excellence. The Service Industries Journal, 1–24. https://doi.org/10.1080/02642069.2023.2226596
   Web of Science ®Google Scholar
• Xie, X., & Wang, T. (2023). Artificial intelligence: A help or threat to contemporary education. Should students be forced to think and do their tasks independently? Education and Information Technologies, 1–15. https://doi.org/10.1007/s10639-023-11947-7
   Web of Science ®Google Scholar
• Xing, L., Giger, M. L., & Min, J. K. (2021). Artificial intelligence in medicine: Technical basis and clinical applications. Academic Press.
   Google Scholar
• Yang, S. J., Ogata, H., Matsui, T., & Chen, N. S. (2021). Human-centered artificial intelligence in education: Seeing the invisible through the visible. Computers and Education: Artificial Intelligence, 2, 100008. https://doi.org/10.1016/j.caeai.2021.100008
   Google Scholar
• Yazdani, M., & Lawler, R. W. (1986). Artificial intelligence and education: An overview. Instructional Science, 14(3-4), 197–206. https://doi.org/10.1007/BF00051820
   Web of Science ®Google Scholar
• Zaka, B., Safran, C., & Kappe, F. (2006). A blended learning approach in the news domain. In Proceedings of the international conference on multimedia and information and communication technologies in education (pp. 1027–1031). Formatex. https://www.researchgate.net/publication/237968760_A_blended_learning_approach_in_the_news_domain
   Google Scholar
• Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0
   Web of Science ®Google Scholar
• Zhang, K., & Aslan, A. B. (2021). AI technologies for education: Recent research & future directions. Computers and Education: Artificial Intelligence, 2, 100025. https://doi.org/10.1016/j.caeai.2021.100025
   Google Scholar
• Zhou, C. (2023). Integration of modern technologies in higher education on the example of artificial intelligence use. Education and Information Technologies, 28(4), 3893–3910. https://doi.org/10.1007/s10639-022-11309-9
   Web of Science ®Google Scholar