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This libguide is unfinished, is is being updated.
When speaking about AI, people usually refer to generative AI that are based on large language models (Large Language Model – a deep learning, generative language model based on data gained from massive datasets). In generative AI applications (for instance ChatGPT, Dall-E, Midjourney) prompts are used to create text, pictures, videos, sound or code.
Machine learning is an area of artificial intelligence that has its roots in statistics. Machine learning methods learn on the basis of the given data without separate rule programming. They improve their performance in a given task as more experience or data accumulates.
The Large Language Model (LLM) is a model based on the probabilities of the occurrence of words and word strings. Language models predict the continuation of the given text input or produce text as requested.
Generative AI combines the power of machine learning, deep learning and AI. It is able to create original content, such as text, videos, audio, code or images, in response to a request made to it. The generative AI model is trained through data and feedback and based on this it is able to create ever new innovative outputs.
In KAMK's guidelines, artificial intelligence refers to AI-based services, not the use of AI features integrated with other software.
Artificial intelligence is a tool that everyone needs in today's and tomorrow's studies and working life. Therefore, KAMK encourages the use of artificial intelligence, taking into account the restrictions set out in the guidelines and based on legislation and different contractual obligations. Students are guided to the use of artificial intelligence correctly from the beginning of their studies.
1) Artificial intelligence is a good support intelligence. In principle, it can be used to help with teaching and to support writing. The use of AI applications in study attainments may be prohibited if there is a risk that the use of applications would hinder the fullfillment of the learning objectives.
2) The use of artificial intelligence must be mentioned in the tasks. The student must indicate in writing which application has been used and in which way. AI is not a source, so it must not be named as the author and source of the text in the list of sources, unless it is allowed in the assignment.
AI is not always right and cannot take ethical perspectives into account. Utilizing it requires the student's ability to think critically and the skill to learn to evaluate and use sources appropriately. Students are always responsible for the contents of their own study assignments and the materials used in it.
3) AI applications must not be fed with confidential information, such as interview transcripts, learning assignments and essays. When processing personal data, the AI application must comply with the requirements set out in the EU General Data Protection Regulation and the data protection act.
4) If a student uses an AI application during a course or exam where the use of AI is prohibited, the student's actions are considered fraudulent. This also applies to situations where a student has reported using artificial intelligence. Plagiarism situations are handled in accordance with KAMK processes.
The ethics of the use of artificial intelligence can be derived from good general scientific practices at universities of applied sciences:
1) The authors are responsible for the accuracy, correctness, integrity and originality of their works, including the use of artificial intelligence.
2) AI does not fulfil the author’s requirements, taking into account accountability.
3) Scientific writing practices must be followed in the use of artificial intelligence. The works must be the author’s own, and they must not present the ideas, information, words or other material of others without sufficient reference. Artificial intelligence is not a source of scientific text. The author must ensure that the citations are correct.
4) The content produced by AI can be biased and damaging or strengthen existing harmful stereotypes. The author must always take ethical perspectives into account.
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