Macau University of Science and Technology
Guidelines on Artificial Intelligence Application and Ethical Governance
(September 2024)
Guidance for Students
Incorporate generative AI tools into the curriculum:
Use of AI tools in Research:
Guidance for Staff
Academics and staff engaged in teaching
Academics and staff engaged in research
For All students (both undergraduate and postgraduate)
Important note
Please be mindful that employing AI tools such as ChatGPT, Sora or similar platforms to generate an assignment, or any portion thereof, and subsequently presenting it as your own work constitutes academic misconduct. The University, in general, embraces the usage of AI tools in teaching, learning, and research, but strictly forbids academic misconduct (the employment of unfair practices during any form of assessment). Examples of misconduct include, but are not limited to, plagiarism, self-plagiarism (submitting the same work for credit twice, either at the same institution or different institutions), collusion, falsification, cheating (including contract cheating, wherein a student commissions another individual to produce or edit his/her work), deceit, and personation (impersonating another student or allowing someone else to impersonate a student during an assessment or examination).
It is important that you are fully aware of:
▲ The limitations inherent in the AI tools you are using:
*AI tools make predictions based on patterns learned from large datasets. These datasets may contain flaws, inaccuracies, biases, and limitations. They also have limited information about the world and events beyond a certain timeline (e.g., 2021 for ChatGPT).
*AI tools function as language machines rather than comprehensive knowledge databases. Avoid relying solely on AI-generated content as a primary source; it should be used alongside other reliable sources.
*AI systems operate without a sense of morality and may generate offensive or misleading content without awareness of their implications.
▲ The factual accuracy of the content generated by AI tools:
*AI-generated text/software/code can have security vulnerabilities, bugs. It is necessary for knowledgeable human review and iterative checks.
*AI assisted tools may produce fake citations and references.
▲ The risks of infringing on intellectual property (IP) rights in AI tools:
*AI-generated software/code may utilize illegal libraries or calls, potentially infringing copyrights.
*hidden plagiarism can occur, as AI may use words and ideas from human authors without proper referencing, which qualifies as plagiarism.
*there is a risk of copyright infringement when using pictures or other copyrighted materials without obtaining consent by original producer(s).
On the other hand, AI tools can be used (whilst recognizing its pitfalls) to enhance learning and research and teaching assignments. The following are some of the numerous possibilities:
▲ Generative AI tools can assist students at various stages of the learning process by providing explanations, generating content, and facilitating knowledge transfer.
▲ By exploring and experimenting with generative AI tools, students can gain insights into how AI technologies work and how they can be applied in different contexts.
▲ Using generative AI tools, students can develop practical skills, such as natural language processing, data analysis, and problem-solving, which are increasingly in demand in the workforce.
▲ Declaration should be made on how and to what extent the outcomes of generative AI, have been used in completing class assignments and projects.
MUST adopts a stance that all members of the MUST community can benefit from a culture that promotes the effective and ethical use of AI. At the undergraduate level, a basic AI literacy is required. At the PG or research level, AI tools can be incorporated into active learning methods, hands-on activities, and real-world projects:
▲ Real-world projects provide students with opportunities to tackle authentic challenges, develop problem-solving skills, and gain practical experience.
▲ AI tools can actively facilitate the exploration of new or complex topics through interactive explanations that engage learners in the understanding process.
▲ Postgraduate students should have access to specialized training programs focused on advanced AI concepts and methodologies. AI tools, such as machine learning algorithms and data analysis software, can enhance postgraduate study by enabling advanced data processing, pattern recognition, and predictive modeling.
▲ Research opportunities, such as collaborative projects, internships, and industry partnerships, provide postgraduate students with hands-on experience and exposure to cutting-edge AI technologies.
▲ When incorporating AI tools into methodologies and data analysis techniques, it is crucial to avoid entering any personal, proprietary, or otherwise sensitive information into models or prompts
▲ Please maintain a cautious attitude towards the data analysis results generated by AI tools. When necessary, use multiple verification methods to assessment the results to ensure their accuracy.
All staff, academic and administrative, may use generative AI in their work. The University permits its staff to utilize AI tools in their professional endeavors and resultant outputs, on the condition that they refrain from asserting authorship over AI-generated work as their own original creation. AI and related digital technologies serve as exceptional tools, offering supplementary assistance in the process. In case of any inquiries, you are encouraged to seek guidance. The global community continues to explore myriad applications of emerging AI and other digital technology.
Academics and staff involved in educational instruction should engage in discussions with students to ensure their awareness of the University's policy and guidelines regarding the utilization of generative AI and other digital technologies. It is essential to communicate with clarity to students regarding the acceptable usages of AI tools within their particular academic context.
Academics and staff engaged in research should understand the capabilities and limitations of AI tools, ensure ethical use and data privacy. It is critical to maintain academic integrity by distinguishing and crediting AI-generated content; to foster collaboration, transparency, and continuous learning, staying updated on AI advancements, to fully engage in responsible AI usages and explore innovative applications for research and creative work. AI outputs in research results should be carefully evaluated, while adhering to institutional policies and contributing to innovative research.
Be aware of the reliability of ChatGPT, Sora and other generative AI Tools:
▲ Cautions are necessary for the authenticity of the output of generative AI tools, and it is deemed appropriate to check the reliability and confirm the originality of AI-assisted work.
▲ Despite new data management features, there are no guarantees of privacy or confidentiality in ChatGPT and other generative AI Tools. Treat input data as if it were public and avoid sharing personal, confidential, or copyrighted information.
Examples of "prompts," which refer to the input text provided to the AI, can be found in the key references and Appendices of this paper. The following principles and best practices on the use of AI for academic and administrative staff are suggested:
▲ AI and related digital technologies should be used responsibly and ethically.
▲ Academic staff should be provided with training on the use of AI tools to develop new courses to meet the educational challenges and adapting teaching pedagogies to meet individual student needs. Training should include seminars, practical workshops, tutorials, and online resources to support staff in integrating AI into their teaching and assessment practices.
▲ Develop training programs and resources to support administrative staff in teaching, research, and administrative roles.
▲ AI can be used for formative and summative assessment, providing personalized feedback. In the Teaching and Learning assessment, AI tools can be employed to conduct equitable evaluations considering multiple factors like classroom performance, mitigating differential student access to AI text refinement capabilities.
▲ Staffs should be aware of updated development in areas such as data management, AI tools and technologies, and online learning platforms, and updating course material related to interactive generative AI to keep the teaching current and relevant.
