Charles University (“CU”) supports the use of tools and education in the field of generative artificial intelligence (“AI”) by students, academics and other CU employees.
However, this use must comply with legislative standards, the law of the Czech Republic, general ethical principles and principles of academic integrity, as well as the internal regulations of Charles University and its units.
This document provides a general framework and rules for working with generative artificial intelligence in final thesis “thesis”. However, it is only a recommendation; individual faculties may determine for themselves the extent to which they will allow the use of generative AI and in which areas of thesis writing or set additional rules and restrictions of their own.
We therefore recommend that you follow the regulations concerning generative AI at individual faculties (e.g., dean's announcements, dean's orders, faculty management statements) and, in case of doubt, consult the use of generative AI with your thesis supervisor.
Students always bear full responsibility for every thesis submitted, even in cases where they use generative AI in its preparation. Students are, at all times, obliged to carefully check all outputs involving generative AI, verify their correctness and incorporate generative AI into the thesis in a way that complies with the rules of academic ethics and the assignment of the thesis.
The author of the final thesis is, in all cases, the student, who is also responsible for the factual accuracy of all content and for the quality of the text. If errors caused by generative AI are present in the thesis, they cannot be invoked retrospectively; the student bears sole responsibility for the removal of such errors and for the final form of the submitted thesis.
In accordance with the Statement by Charles University, the use of generative AI tools in particular must be transparent.
This means that students should attach a brief statement at the beginning of their thesis in which they describe truthfully and in detail how, to what extent and for what purpose they used which generative AI tools during preparation of their thesis. (If necessary, a detailed version of this statement may be attached as a separate annex.)
This statement forms an important basis for assessing the originality of the thesis. Students can utilise the prepared template Declaration on the Use of AI in the Final Thesis, which helps them summarise all relevant information in a clear, structured manner.
How to write the Declaration on the Use of Generative Artificial Intelligence ?
Users must comply with the security rules when using generative AI tools. Some generative AI models are trained on the data that users enter into them, or their providers use the data entered by the user to “improve services”. They are not designed to ensure confidentiality or protect personal data; any information placed in a generative AI environment can be used to further train the model or can become public.
It is therefore prohibited to input any personal, sensitive or protected data into windely available generative AI tools, in particular information that is marked as protected in the Categorization of data table. Tools that are approved at the University, (e.g. MS Copilot when logging in with a university account - ukčo@cuni.cz) or locally operated generative AI models (provided that they are assessed as safe by CU) are exempt from this rule.
The student also undertakes not to use generative AI tools that have been evaluated by the Czech National Cyber and Information Security Agency (NÚKIB) and CU as potentially dangerous.
Caution and the responsible handling of data are basic prerequisites when working with generative AI tools on campus.
More abour data protection here.
If a student uses generative AI in the preparation of their thesis – for example, to generate images, diagrams or passages of text – they should give a proper description of such use of generative AI.
In such a case, generative AI should be cited as a tool in the Declaration on the Use of Generative AI.
In special cases when generative AI is used as a data source – for example, when researching the statistical properties of the generated text, the tool should be cited according to the citation standard chosen for the work (for example, according to APA, ČSN ISO 690 or other).
It is important to see generative AI primarily as a tool that modifies or generates content based on instructions and data that have been fed into it, and not as a reliable source of information. Only primary and secondary literature functions in this way.
Therefore, as when using any other digital or computational tool, students are also responsible for the resulting output. The output of generative AI represents the result of interaction between the author and the tool, and not a professionally verified or independent source of information.
It is important to verify whether the citation standard used contains specific recommendations for citing generative AI. Some standards describe this citation in detail, and others do not.
Further information about declaring AI tools here
Students are entirely within their rights to reject the use of generative AI in the preparation of their thesis without giving a reason. Some students always prefer their own independent work in all cases and may be concerned that the use of generative AI would negatively affect the development of their skills and critical thinking. Others may have reservations for moral, environmental or other reasons. All students are free to decide whether and to what extent to involve generative AI in the process of writing their final thesis, and this stance must be respected.
The areas of application for generative artificial intelligence in final theses are highly diverse, from linguistic editing of the text to data processing, through the summarisation of literature to assistance in formulating the structure or providing feedback on the text.
Considering this diversity, it is not possible to clearly and universally determine what is and what is not permissible in all fields and types of work.
It is therefore important that the student consults their supervisor about their specific intentions for using AI. Open communication with the thesis supervisor helps to avoid ambiguities or misunderstandings in the assessment and at the same time leads the students to responsible and thoughtful use of generative AI in an academic context.
Generative AI models are trained, among other things, on the data fed into them by their users. Therefore, they are not usually designed to ensure the confidentiality of these data or protect information that is shared with chatbots and other tools.
For this reason, when interacting with generative AI tools learners should always eval-uate the data they are entering and the tools they are entering them into. In doing so, they shall be liable for any breaches of data protection.
From the point of view of legal and ethical responsibility, it must be borne in mind that some data are subject to special protection; according to legislation (e.g. GDPR), some personal and sensitive data in particular should not be entered into generative AI tools (with the exception of some so-called local models).
Internal university data or non-public study materials can only be shared in generative AI tools that Charles University has explicitly recommended as secure (e.g. tools with a clearly defined licence or a contractual agreement not to train data), or within verified local solutions.
The most secure and most responsible way to do this is to always use tools that have been approved and are administered by the University – currently Microsoft Copilot for education (after logging in to the University account UKČO@cuni.cz).
In all cases, we recommend that you approach generative AI with caution and sensitivi-ty, while considering the nature of the data being shared.
More about data protection here.
There is currently no technically reliable means of confidently detecting the use of generative AI. Although various “AI detectors” are available, they have so far been shown to be essentially unreliable and error-prone. However, there are indicators in-dicating the degree and manner of use of generative AI in the writing of a final thesis.
If undeclared use of generative AI or its use to an unauthorized extent is discovered, this may lead to a negative evaluation of the thesis defense or the initiation of disciplinary proceedings, or the initiation of proceedings to declare the state examination or part thereof invalid if the misconduct is discovered after the state final examination has been taken or after graduation.
Therefore, we recommend using generative AI tools in a way that is ethical and trans-parent. Students should attach a Declaration on the Use of Artificial Intelligence to their thesis and consult their supervisor about their use of generative AI.
Writing a final thesis is not only a study obligation, but also an opportunity to learn something or practice skills acquired during one’s previous studies: to immerse one-self in the study of a specific topic, organise one’s thoughts, understand the thinking of other authors and, on this basis, build a work of greater scope than what students worked on in previous studies.
If some or even all of these steps are taken by AI, the learner will not develop any of these skills, or only to a lesser extent. This should also be considered when students – ideally together with their supervisor – are deciding which AI tools they will use in the creation of their thesis, and for what purpose.
The various ways in which artificial intelligence can be involved in the process of pro-cessing a final thesis are described below. Individual activities are divided into three levels depending on how fundamentally they affect the resulting thesis – from the least fundamental first stage to the critical third stage.
Individual levels are colour-coded to match the recommendations of the Working Group on Generative AI at Charles University. This group recommends allowing free use of the first level of AI (here, it is sufficient to complete the Declaration of Use of Artificial Intelligence), always consulting your supervisor on the second level, and completely prohibit the third level.
However, this list is only advisory; individual faculties can determine for themselves the extent to which AI is to be used in what area of the final thesis, or set other rules and restrictions. The purpose is to provide guidance and inspiration. Adaptation to specific fields of study is then left to the discretion of the faculties.
Therefore, we recommend monitoring the regulations regarding AI at individual facul-ties (e.g. dean's announcement, dean's directives, statements of the faculty manage-ment) and, in case of doubt, consult their supervisor about the use of generative AI.
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Creation and composition of text |
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Level 1 |
Consultation on the basic idea of the text, discussion of the main theses of the text, generation of the draft outline of the text, obtaining feedback on ideas or one's own parts of the text during the creation of the text or after its completion. The generated text is not directly inserted into the body of the thesis. |
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Level 2 |
Generating text from text, audio or other notes, rewording of one's own text, comprehensive use of tools such as Microsoft Copilot 365 in Microsoft tools (Excel, Word, etc.) |
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Level 3 |
Creation of an entire thesis using prompts, where the learner acts only as an editor, generating entire sections of text without final supervision |
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Linguistic and stylistic editing of the thesis |
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Level 1 |
Grammatical correction of individual words or sections, correction of syntax |
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Level 2 |
Stylistic proofreading of sections of the thesis |
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Level 3 |
Uploading of large sections of text or the entire thesis and their stylistic rewriting using AI tools
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Translations
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Level 1 |
Consulting generative AI tools about one's own translation |
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Level 2 |
Correction of one's own translation using generative AI tools, translation of certain parts of the thesis using generative AI tools |
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Level 3 |
Uploading the whole text or its essential sections and their complete translation |
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Research, reading and interpretation of sources |
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Level 1 |
Performing a basic search of available resources, consultation on strategies for research, consultation of search queries, consultation to aid understanding |
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Level 2 |
Analysis of literature – prioritisation, generation of search queries, preparation of research using tools such as Consensus, Perplexity, Elicit |
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Level 3 |
Generation of literature review |
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Creating auxiliary content |
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Level 1 |
Consultation on the form of original auxiliary content (abstract, bibliography, index), generation of media content such as accompanying images, graphs and sketches. |
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Level 2 |
Generation of auxiliary content (abstract, bibliography, index) |
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Level 3 |
Generation of the introduction and conclusion of the thesis |
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Analysis and interpretation of data |
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Level 1 |
Consultation on strategies and specific methods for data analysis and interpretation
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Level 2 |
Generation of specific analytical procedures (e.g. syntax for statistical software, analytical codes) Generation of methods of interpretation of analysis results |
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Level 3 |
Generation of critical sections or the entire analysis and/or interpretation of data. |
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