Developing epistemic insights in (Gen)AI education

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For aims and values, students need to recognise that AI and science sometimes strive to produce high-quality intellectual outcomes. Also, the application of AI technologies in the field of science fosters interdisciplinary thinking. Some human qualities are involved when students apply AI to scientific knowledge, including problem-solving, creativity and co-operation, and algorithmic thinking.

‘Students should question how scientific knowledge is generated in GenAI tools … Asking these big questions can help students become aware of the strengths and limitations of GenAI tools, and develop their agency in using azerbaijan consumer email list these tools for making meaning of scientific knowledge.’

In relation to methods, the disciplines of AI and science also involve observation and classification. AI, or specifically GenAI, does not engage in empirical scientific evidence itself, but it can serve as a tool for scientists to analyse data more accurately by mathematical predictions and modelling. GenAI analyses occurrence of word patterns and generates outputs based on statistical probabilities. On the other side, scientists can use these AI tools to identify patterns of scientific data, and draw scientific conclusions. A new technique has emerged to classify phases of physical systems in order to help scientists identify novel materials.