Ethical artificial intelligence for teaching-learning in higher education

Airaj, Mohammed

doi:10.1007/s10639-024-12545-x

Cited by 5 publications

(3 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The responsible use of AI in higher education necessitates the establishment of ethical frameworks and the development of policies that address both the potential and the challenges posed by AI technologies. Studies by [48,55] exemplify the discourse on creating comprehensive policies that support ethical AI integration. Airaj emphasizes a humancentered AI approach that adheres to ethical guidelines, ensuring equitable access and privacy [48].…”

Section: Cluster 1: Ethical Framework and Policy Developmentmentioning

confidence: 99%

“…Studies by [48,55] exemplify the discourse on creating comprehensive policies that support ethical AI integration. Airaj emphasizes a humancentered AI approach that adheres to ethical guidelines, ensuring equitable access and privacy [48]. Similarly, Duah and McGivern highlight the need for university policies that clarify generative AI's role in academic writing, like ChatGPT, thus mitigating ethical ambiguities [55].…”

Section: Cluster 1: Ethical Framework and Policy Developmentmentioning

confidence: 99%

“…The landscape of AI in higher education is one of dynamic tension between its potential for innovation and the imperative for ethical governance. On one side, research such as that by [48] advocates for the creation of comprehensive ethical guidelines and strategic integration of AI, with studies like Mahapatra's underscoring the positive outcomes of AI when students are effectively guided [63]. Conversely, concerns about the integrity of scholarship surface in works by Kasani et al, who warn of the risks of plagiarism [59], and Khalaf, who cautions against an over-reliance on AI that may lead to academic dishonesty [60].…”

Section: Conceptualizing Ethical Ai In Academiamentioning

confidence: 99%

See 2 more Smart Citations

Generative AI, Research Ethics, and Higher Education Research: Insights from a Scientometric Analysis

Qadhi,

Alduais,

Chaaban

et al. 2024

Information

View full text Add to dashboard Cite

In the digital age, the intersection of artificial intelligence (AI) and higher education (HE) poses novel ethical considerations, necessitating a comprehensive exploration of this multifaceted relationship. This study aims to quantify and characterize the current research trends and critically assess the discourse on ethical AI applications within HE. Employing a mixed-methods design, we integrated quantitative data from the Web of Science, Scopus, and the Lens databases with qualitative insights from selected studies to perform scientometric and content analyses, yielding a nuanced landscape of AI utilization in HE. Our results identified vital research areas through citation bursts, keyword co-occurrence, and thematic clusters. We provided a conceptual model for ethical AI integration in HE, encapsulating dichotomous perspectives on AI’s role in education. Three thematic clusters were identified: ethical frameworks and policy development, academic integrity and content creation, and student interaction with AI. The study concludes that, while AI offers substantial benefits for educational advancement, it also brings challenges that necessitate vigilant governance to uphold academic integrity and ethical standards. The implications extend to policymakers, educators, and AI developers, highlighting the need for ethical guidelines, AI literacy, and human-centered AI tools.

show abstract

Section: Cluster 1: Ethical Framework and Policy Developmentmentioning

confidence: 99%