Panellists' Insights Into AI-Guardrails: a Proposed AI-Guardrail Framework for Upholding Academic Integrity

Introduction: Scholarly works framed AI guardrails as the ethical, technical, and pedagogical constraints and governance mechanisms embedded in or surrounding AI and machine learning systems to prevent harm, ensure responsible use, and align AI outputs and practices with institutional values, academic integrity, and societal norms. This study aims to explore panellists' insights into AI guardrails that provide ethical, technical, and procedural safeguards for upholding academic integrity at a higher education institution. Material and Methods: This exploratory qualitative study invited lecturers to participate in a panel for a critical conversation about their insights into AI guardrails that provide ethical, technical, and procedural safeguards for upholding academic integrity. An open-ended critical panel discussion was promoted to share views on the status of AI safety measures in their respective modules. A single case study was selected, and five panellists (PM۱ to PM۵) from higher education institutions participated in this critical conversation panel discussion session. After the session, the recorded version of the Microsoft Teams video and transcripts were downloaded and uploaded into NVivo, an AI-computerised qualitative software, to generate themes and subthemes. Results: Findings revealed that AI guardrails are widely perceived as essential safety mechanisms for protecting qualifications, data, and ethical standards. Furthermore, AI-detection tools, such as proctoring software and plagiarism checkers, are viewed as necessary deterrents, but persistent concerns exist about their accuracy, bias, transparency, and potential for false positives. Conclusion: Ultimately, an AI Guardrail Framework (AIGF) is proposed that underscores the need to move beyond purely ethical, procedural and technical solutions toward a more holistic, educationally grounded strategy to uphold academic integrity.

کلیدواژه ها:

AI-Guardrail Framework ، Guardrails ، Ethics ، Technology ، Qualitative Approach ، Panel Discussion ، NVivo