Legal aspects of generative artificial intelligence and large language models in examinations and theses

被引:5
作者
Maerz, Maren [1 ]
Himmelbauer, Monika [2 ]
Boldt, Kevin [3 ]
Oksche, Alexander [4 ,5 ]
机构
[1] Charite Univ Med Berlin, AG Progress Test Med, Teaching Div, Charitepl 1, D-10117 Berlin, Germany
[2] Med Univ Vienna, Teaching Ctr, Vienna, Austria
[3] State Commissioner Data Protect & Freedom Informat, Mainz, Germany
[4] Inst Med & Pharmazeut Prufungsfragen IMPP, Mainz, Germany
[5] Justus Liebig Univ Giessen, Rudolf Buchheim Inst Pharmacol, Giessen, Germany
关键词
assessment; AI; large language models; legal framework; PERFORMANCE; CHATGPT;
D O I
10.3205/zma001702
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
The high performance of generative artificial intelligence (AI) and large language models (LLM) in examination contexts has triggered an intense debate about their applications, effects and risks. What legal aspects need to be considered when using LLM in teaching and assessment? What possibilities do language models offer? Statutes and laws are used to assess the use of LLM: - University statutes, state higher education laws, licensing regulations for doctors - Copyright Act (UrhG) - General Data Protection Regulation (DGPR) - AI Regulation (EU AI Act) LLM and AI offer opportunities but require clear university frameworks. These should define legitimate uses and areas where use is prohibited. Cheating and plagiarism violate good scientific practice and copyright laws. Cheating is difficult to detect. Plagiarism by AI is possible. Users of the products are responsible. LLM are effective tools for generating exam questions. Nevertheless, careful review is necessary as even apparently high-quality products may contain errors. However, the risk of copyright infringement with AI- generated exam questions is low, as copyright law allows up to 15% of protected works to be used for teaching and exams. The grading of exam content is subject to higher education laws and regulations and the GDPR. Exclusively computer-based assessment without human review is not permitted. For high-risk applications in education, the EU's AI Regulation will apply in the future. When dealing with LLM in assessments, evaluation criteria for existing assessments can be adapted, as can assessment programmes, e.g. to reduce the motivation to cheat. LLM can also become the subject of the examination themselves. Teachers should undergo further training in AI and consider LLM as an addition.
引用
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页数:14
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