Please use this identifier to cite or link to this item:
https://openlibrary-repo.ecampusontario.ca/jspui/handle/123456789/2228
Title: | Framework for Accessible and Equitable Artificial Intelligence (AI) in Education |
Authors: | Mitchell, Jess Lo, Lorna Scheuhammer, Joseph Treviranus, Jutta Spence, Rachel Spence, Rachel |
Keywords: | Artificial Intelligence Equitable Education Accessible Education |
Issue Date: | 15-Apr-2024 |
Publisher: | Inclusive Design Research Centre, OCAD University |
Series/Report no.: | https://openlibrary.ecampusontario.ca/item-details/#/d338b18a-1b8b-43d2-ad0f-83e7514a3ac6 |
Abstract: | This is a practical guide to the dizzying domain of artificial intelligence within the education ecosystem, with a particular focus on the impact on equity and accessibility. AI and accessibility are beginning to have an interesting conversation. Not unlike the conversation about AI in general, the conversation about AI and accessibility in education can be found taking a techno-solutionist or techno-tragedist perspective. As we grow wary of this false dichotomy, we move toward what is much more likely to be the case: that it will be “both/and” and “neither/nor.” AI can make things better. It can benefit us all, it can address inequities, and it can lower barriers for people with disabilities in education. It can equally be used to amplify inequities (intentional and unintended), including discrimination against people who do not fit a “norm.” AI is neither uniformly bad nor uniformly good for furthering our goals of eliminating barriers to education for people. |
URI: | https://openlibrary-repo.ecampusontario.ca/jspui/handle/123456789/2228 |
Other Identifiers: | 3e12459e-1d24-4f1b-b12a-a00cd6dfd25c |
Appears in Collections: | Ontario OER Collection |
Files in This Item:
File | Size | Format | |
---|---|---|---|
Framework-for-AI-in-Education.docx | 186.84 kB | Microsoft Word | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.