Module 3 Week 1 Felipe ChungThere is a lot of ethical issues in using AI like ChatGPT in


Module 3 Week 1

Felipe Chung

There is a lot of ethical issues in using AI like ChatGPT in writing academic papers, mainly because it compromises the academic integrity standards. The use of AI in students’ work miss-presents work as one’s own, conflicting with honesty principles dictating that academic work should be a product a student’s effort and knowledge acquisition (Lund et al., 2023). This misrepresentation impacts the learning of the individual and has potential adverse effects on the reputation of an educational institution in the event that unoriginal work gets through. Academic integrity policies require students to be truthful and not cheating, but AI usage violates these rules by disguising real understanding and critical thinking behind artificial intelligence responses (Miao et al., 2023).

In addition, overdependence on AI gives rise to other related problems such as cheating within the academic arena. As noted by Carleton (2023), AI produced work may be devoid of proper references or incorrectly attribute information hence being full of intellectual dishonesty. Furthermore, the uncontrolled utilization of AI may deteriorate peer-review standards because it could produce erroneous data into academic discussions. This can potentially undermine the scholarly credibility that forms the foundation of educational and research paradigms.


Module 3 Week 1

David Tee

The use of AI programs to generate academic work poses many ethical concerns. This is mainly because of potential violations of academic integrity. When AI-generated content is submitted as the student’s own work, the student fails to meet the educational goal of learning and skill development. This also breaks the trust educators place in students and the academic system (Miao et al., 2023). There is no proper evaluation of a student’s capability if they are not producing their material.

Another concern is that AI-generated material lacks accountability. This diminishes the quality and accuracy of the work. Since AI tools are not responsible for incorrect information, there may be errors or biased information depending on the input. In addition, the authenticity of the student’s information is diluted. This can then lead to misinformation if it continues to be unchecked by the academic community (Miao et al., 2023). Academic standards should be continually upheld at every level of academia. If AI-generated material is going to be 

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