Programme Session Details 2024

Generative AI for playful learning – skillshare of ethical uses

Corresponding Author: Daisy Abbott

All authors:

Length: 30 minutes
Location: Terrace Room


Warning: this abstract contains Opinions! There are several reasons NOT to use generative AI. You may believe that it’s unethical at its very core, has unreasonable energy requirements (de Vries, 2023) or is just too biased (Zembylas, 2023). However, there are lots of ways that you can engage with GAI to brainstorm ideas, or to improve either the efficiency or rigour of your work. If you *do* choose to use GAI in any context then come to this workshop and share your Opinions!

To start us off:
– Opinion 1: The cat is out of the bag. Like it or not, people will use GAI.
– Opinion 2: Therefore, you have an ethical duty to make sure you educate yourself. This is not only to make sure you are using it “right” and it does not waste time, produce inadequate or problematic results, and waste energy, but also so that you can gain a nuanced understanding of when it can be useful vs when using it is problematic.
– Opinion 3: Ethical AI use is a core skill that our students want to learn – we need to learn it first to support them to use it well and reduce its potential harm.

Please bring with you:
1. Your smartphone.
2. Opinions about generative AI
3. (Optional): Examples or suggestions for ethical GAI use in playful learning. You will be asked to share these verbally (maximum 3 minutes please!) and I will add them to our Augmented Reality skillshare poster.

This workshop will begin with a very brief introduction to three playful uses of generative AI (10-15 minutes):
1. ChatGPT as a low-effort games master for exploring “difficult” issues through roleplaying
(drawing on Saito, 2023)
2. Automatic production of “choose your own adventure” or escape room code using ChatGPT and Inform7 (drawing on Fernandez-Vara, 2024)
3. Exploring AI bias with a simple “guess the prompt” game (adapting Hosseini, 2023) The second half (15-20 minutes) will be a collaborative skillshare where participants offer their own suggestions/demos for playful uses, and share or challenge opinions. Please focus on *our* use not student use.

Please take away with you:
1. (New?) opinions
2. A link to the Augmented Reality poster/Thinglink for consulting later, and sharing with and
between the rest of the delegates and wider PL community.

References, web links and other resources:

de Vries, A., 2023. The growing energy footprint of artificial intelligence. Joule, 7(10), pp.2191-2194. Zembylas, M. (2023). A decolonial approach to AI in higher education teaching and learning: strategies for undoing the ethics of digital neocolonialism. Learning, Media and Technology, 48(1), 25-37. Saito, K. et al.
(2023). Double Impact: Children’s Serious RPG Generation/Play with a Large Language Model of Their Deeper Engagement in Social Issues. Lecture Notes in Computer Science, vol 14309. Springer, Cham. Fern√°ndez-Vara, C. (2024) Generating Parser-based Games to Teach Narrative Design. in Learning To Teach Creative Technologies with Generative AI – online webinar Jan 2024 Dustin Hosseini (2023) “Generative AI: a problematic illustration of the intersections of racialized gender, race, ethnicity” intersections-of-racialized-gender-race-ethnicity

In addition to the references above, here are some more related readings: Mohamed, S., Png, M.-T., & Isaac, W. (2020). Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence.
Philosophy & Technology, 33(4), 659-684. Noble, S. U. (2018). Algorithms of Oppression: How Search Engines Reinforce Racism. New York University Press.
danah boyd & Kate Crawford (2012) CRITICAL QUESTIONS FOR BIG DATA, Information, Communication & Society, 15:5, 662-679, DOI: 10.1080/1369118X.2012.678878Links to an external site.