
This exploratory research focuses on the need to equip educators with a critical understanding of ethical issues in the AI space such as algorithmic discrimination so they can anticipate and respond to issues related to the collection, processing and use of AI in the development of OER. OE advocates for reducing the barriers to access and participation, widening learning opportunities while democratising education. This involves OEP which promotes collaboration and sharing good, effective, creative and innovative practices, and the use and creation of OER, which are currently defined as “teaching and learning materials that are freely available to use, adapt, and share”. This definition does not address the possibilities of AI-enabled OER. AI services now present opportunities to create, adapt, personalise and contextualise resources in all shapes and forms. It’s even been suggested that OER could consist just of prompts - AI can generate the rest. We must considering that the risks implied in this process, due to the biases encrusted into data- and algorithm- driven systems.
open education, AI in education, Data ethics
open education, AI in education, Data ethics
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