What risks, barriers and biases must system education leaders mitigate?
What are the ethical considerations related to AI in teaching and learning?
March 20, 2024 (02:11 pm)
grace.maclellan says:
Some key considerations that system education leaders have to mitigate to ensure equitable and effective implementation of AI in teaching and learning are: the actual programmed data (data bias) and data input (discrimination or how it is input), data privacy and security concerns, accessibility, inclusivity, and finally the need for robust teacher training and ongoing support. We also need to deal with the existing system data that is housed in a million different locations so that we can move forward meaningfully in taking steps to actually address these risks, barriers and biases.
