This blog post has kindly been provided by co-authors Meera Darji (meera.darji@bcu.ac.uk) and Annette Naudin (annette.naudin@bcu.ac.uk), Birmingham City University.
There is no doubt that artificial intelligence has grown incredibly fast in the past year. It seems obvious that AI isn’t going anywhere. Generative AI (GenAI) is evolving in industry, in technology and in education and as educators we need to react and respond quickly. We have begun to use new GenAI digital tools in higher education teaching for idea development, research and better-quality outputs whilst also drawing attention to critical debates. The examples we share here are from a BA Media Production course, but they are relevant for different creative and arts-based disciplines and courses.
The language we use around GenAI in the classroom is crucial. As well as informing students to not rely on AI and pre-empting misuse, we believe it is important to not instil fear in students. We want to divert this discourse to focus on how GenAI can be an innovative teaching tool but also a safe space for experimentation and discussions about ethical uses of new technologies, for example teaching students about the copyright and copyleft movement.
In our curriculum, GenAI was introduced early in the teaching of a module. With the platform PromeAI, the students experimented with mixed media making using a tool called ‘Creative Fusion’ which created a new piece of art combined with generative artificial intelligence. Another application students used was Storyboarder.AI, a tool to help create professional storyboards to aid project pre-production. Students also engaged in the ‘Generative Fill’ tool in Photoshop to create an infinite zoom camera effect for their music video.
What was the outcome? The range of exercises using GenAI tools were successful in creating a sense of curiosity and excitement for staff and students. Allowing students to explore the possibilities of GenAI, has not only contributed to idea generation, an issue we see a lot amongst our students, but also bridged the gap between idea development to the execution of final projects. A confidence booster. The result is that we’ve seen better quality portfolios with evidence of: innovation, collaboration, research and technical skills. Many AI tools require prompts and students are undoubtedly forced to think about, for example, mise-en-scene and to improve their descriptive writing. In other words: if they don’t add detail, GenAI won’t give the results. On the whole, students are not shying away. They are encouraged to reflect on their uses of co-creating with AI in their essays and critically reflect on the processes they use.
Critical debates point to the challenges of over relying on AI tools. There are issues of representation such as the under-representation of marginalized identities (Luccioni et al, 2023) and well documented gender biased discrimination in new technologies (Kurta and Pernice, 2024). In addition, concerns about accuracy and integrity of information generated by Gen AI (Sharples, 2023), has informed our educational practice. For many creative subjects there are issues of affordability with GenAI tools which are not necessarily free, and we are mindful of that when integrating different platforms and tools into the curriculum. We also draw attention to environmental issues such as the energy demands from AI datacentres (Harvey, 2025).
There is a general lack of AI literacy in the curriculum, amongst staff and students. In our work, we are aiming to align our assessment and pedagogy with industry trends and educational developments. It’s not easy work and we are learning alongside our students, exploring technology in creative ways.
References
Creamer, E. (2025). Collective licence to ensure UK authors get paid for works used to train AI. The Guardian. [online] Available from < https://www.theguardian.com/books/2025/apr/23/collective-licence-to-ensure-uk-authors-get-paid-for-works-used-to-train-ai>
Harvey, F., (2025) Energy demands from AI datacentres to quadruple by 2030, says report. The Guardian [online] Available from <https://www.theguardian.com/technology/2025/apr/10/energy-demands-from-ai-datacentres-to-quadruple-by-2030-says-report>
Kurta, L., and Pernice, G., (2024), A Silenced Sector: Equality, Diversity and Inclusion Challenges in the Immersive & Virtual Production Industries. Ida XR Studio, King’s College London.
Luccioni, A. Moorosi, N., and Sefala, R., (2023) AI for Whom? Shedding Critical Light on AI for Social Good, Computational Sustainability Workshop at NeurIPS 2023.
Sharples, M. (2023) Towards social generative AI for education: theory, practices and ethics, Learning: Research and Practice, 9:2, 159-167.
GenAI Tools
Prome AI https://www.promeai.pro/creative-fusion-generation
Storyboarder AI https://storyboarder.ai/ Adobe Photoshop Generative Fill https://helpx.adobe.com/uk/photoshop/using/generative-fill.html