Information security and data protection are critical considerations when using AI. Uploading students’ submissions, personal data or other confidential information to an external AI application that has not been formally approved by their University is prohibited. The information security and data protection policies of Tampere Universities must be strictly followed.
Some student submissions may be confidential under the Finnish Act on the Openness of Government Activities or the institutional data classification model. AI tools must not be used to support the assessment of such submissions.
Confidential materials, or those containing intellectual property belonging to Tampere Universities, must only be processed using formally approved AI tools (such as Microsoft Copilot). AI tools that transfer ownership of input data to the provider, or use input data to train their language models, should not be used when processing materials at Tampere Universities.
Teachers’ pedagogical responsibility for the use of AI helps to safeguard the academic integrity of learning outcomes and to uphold reliable student assessment, data protection, ethical guidelines, and the fair and non-discriminatory treatment students. Adherence to these principles ensures that AI is used responsibly and appropriately in the context of teaching. The misuse of AI constitutes academic misconduct and will be investigated in accordance with the institutional guidelines. Students must be provided with clear instructions on how to use AI to minimise any risk of misunderstanding. Examples of AI misuse include generating final outputs using AI, using AI-provided references without verifying the original sources, using AI in assignments where its use is prohibited, and failing to acknowledge the use of AI.
What are the environmental impacts of AI?
The use of AI applications consumes significantly more energy than, for example, a Google search, as these applications rely on systems that require substantial computing power. While AI can be an effective tool to support learning and teaching, its use has a considerable impact on the environment. From a carbon footprint perspective, the responsible approach is to use AI tools sparingly, especially for repetitive or routine tasks where lighter digital alternatives may be sufficient.
Electricity is required to train large language models, interact with AI tools and maintain the systems that support them. AI systems rely on data centres, which consume a considerable amount of water for cooling purposes. In addition, minerals must be mined to manufacture the hardware needed to run these centres, which causes environmental issues and may also raise ethical concerns. The proportion of global energy consumption attributed to data centres has increased, with the maintenance of AI technology accounting for a growing share. The overall impact of this increase in energy consumption also depends on the environmental impact of the energy sources used.
Overall, the use of AI and the demand for energy have grown more rapidly than improvements in energy efficiency or the increase in the use of renewable energy sources. As a result, the environmental impact of AI has not yet decreased significantly, despite increasing investments in sustainability and optimisation.