# Large Language Models in Computer Science Classrooms: Ethical Challenges and Strategic Solutions
## 3 LLMs for Computer Science Studies: Advantages and Challenges
### Ethical Challenges in Using LLMs in Computer Science Studies
#### 3.3.4 Privacy and Copyrights  
LLMs often use user prompts as additional training data, which can potentially lead to privacy violations when sensitive or private information is included. [PERSON] et al. [28] have highlighted significant privacy risks associated with OpenAI's use of personal data in AI training. This issue became particularly prominent in Italy, where regulators banned ChatGPT for breaching GDPR regulations due to the unauthorized use of personal information. OpenAI's reliance on \"legitimate interests\" as justification for this practice raises complex ethical and legal challenges concerning the handling of personal data, whether public or private. To prevent privacy breaches, students and staff using LLMs must exercise caution.  
[PERSON] et al. [79] have explored the ethical challenges that LLMs introduce in computer science education, including issues of academic integrity, potential biases, hallucinations, and inaccuracies, as well as privacy concerns. Based on interviews with educators, students, and AI professionals, they highlighted the need for updated curricula and governance strategies to address these risks while promoting the responsible use of LLMs. This recommendation aligns with the emphasis placed by [PERSON] et al. on human oversight, as both studies advocate for educational practices that balance AI utilization with ethical responsibility.  
In addition, relying on ChatGPT can lead to instances of copyright violations. For example, [PERSON] (2018) reported a case where code generated by ChatGPT to solve the 8 Queens problem in the Prolog language closely resembled previously published code, without proper attribution to the original creator. This underscores the risk of copyright infringement when students use ChatGPT-generated outputs.  
In an engaging dialogue about plagiarism conducted by Prof. [PERSON] with ChatGPT-3 during its early release [PERSON] (2018), the chatbot itself outlined the drawbacks of plagiarism. It noted that students risk significant consequences if caught, including harm to their academic careers and future opportunities. Such practices also violate the ethical standards of academic writing and infringe on the copyrights of original authors or sources. Furthermore, educational institutions risk damage to their credibility and reputation if students use AI text generators for academic writing. ChatGPT concluded that relying on AI text generators for academic purposes constitutes a form of academic dishonesty.  
To address the ethical issues arising from LLM use, educators should be cognizant of these risks and establish clear guidelines for students on how to mitigate them and use LLM tools responsibly. Many academic institutions have incorporated discussions of privacy, copyright, and fairness into the formal guidelines they provide to students regarding the use of LLM tools.  
For example, the University of Pretoria's staff guide [PERSON] (2018) offers practical advice to prevent privacy breaches when interacting with LLMs. Their recommendations include excluding personal or confidential data from prompts, using anonymized and non-identifiable data, understanding data privacy regulations, and disabling the learning capabilities of AI systems during sensitive interactions. By adhering to such guidelines, educators and students can reduce the risk of sensitive information being reproduced or disclosed by LLMs.  
Building on this foundation, it becomes imperative to establish a comprehensive framework that promotes ethical AI use while supporting the development of critical skills in computer science education.