Invitation Text

Generating AI Alternatives: Collaborating And Creating Intersections 

[Insert date, time and location]

[Insert facilitators' names]

Based on a workshop by Louise Drumm, Helen Beetham, Catherine Cronin and Rosemarie McIlwhan

Workshop overview:

It is now several years since the release into the wild of unregulated generative AI models and their chatbot front-ends. Between the hype from big tech on the one hand, and a sense of despair on the other, alternative, critical and ethical activities have begun to emerge (Bender et al., 2021; Bozkurt, A. et al., 2023; Conrad, 2023; Fischer et al., 2023; Nerantzi et al., 2023; Rahm, 2023). These new computational approaches – so far confined to the largest and most capital-intensive tech companies – can generate human-like content at an unprecedented speed and scale. As an alternative, we will produce knowledge at a human speed and scale, through creative collaborations in a range of media, including generated, ‘made’ and found contents. Our goal is not only to understand and critique computational generativity, but to reconnect with ‘generation’ as a curious, expansive and generous practice in education.

Participants will respond creatively to provocations with, against and around generative AI. Making materials will be provided in place and online, and participants will also be encouraged to find and generate their own. This will help participants to reflect collectively and respond critically to the emerging ethical, epistemological and relational challenges of generative AI. No special knowledge is required, just a willingness to collaborate, create and be curious.

Please view the Workshop Participant Guide for the workshop materials and provocations.

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Contacts:

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References:

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? . Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623. https://doi.org/10.1145/3442188.3445922

Bozkurt, A., Xiao, J., Lambert, S., Pazurek, A., Crompton, H., Koseoglu, S., Farrow, R., Bond, M., Nerantzi, C., Honeychurch, S., Bali, M., Dron, J., Mir, K., Stewart, B., Costello, E., Mason, J., Stracke, C. M., Romero-Hall, E., Koutropoulos, A., ... Jandrić, P. (2023). Speculative futures on ChatGPT and generative artificial intelligence (AI): A collective reflection from the educational landscape. Asian Journal of Distance Education, 18(1), 53-130. https://doi.org/10.5281/zenodo.7636568

Conrad, K. (2023). Sneak Preview: A Blueprint for an AI Bill Of Rights for Education. Critical AI. https://criticalai.org/2023/07/17/a-blueprint-for-an-ai-bill-of-rights-for-education-kathryn-conrad/

Fischer, I., Mirbahai, L., Buxton, D., Ako-Adounvo, M.-D., Beer, L., Bortnowschi, M., Fowler, M., Grierson, S., Griffin, L., Gupta, N., Lucas, M., Lukeš, D., Voice, M., Walker, M., Xiang, L., Xu, Y., & Yang, C. (2023). How can Artificial Intelligence (AI) be harnessed by educators to support teaching, learning and assessments? Actionable Insights. Warwick International Higher Education Academy (WIHEA) University of Warwick. https://warwick.ac.uk/fac/cross_fac/academy/activities/learningcircles/future-of-learning/ai_report_for_educators_16-7-23.pdf

Nerantzi, C., Abegglen, S., Karatsiori, M., & Martínez-Arboleda, A. (2023). 101 creative ideas to use AI in education, A crowdsourced collection. Zenodo. https://creativehecommunity.wordpress.com/2023/06/23/oa-book-101-creative-ideas-to-use-ai-in-education/

Rahm, L. (2023). Educational imaginaries of AI. In S. Lindgren (Ed.), Handbook of Critical Studies of Artificial Intelligence (pp. 289–300). Edward Elgar Publishing. https://doi.org/10.4337/9781803928562.00031