
Ken Shelton: AI Bias and Discrimination
The Generative Age: AI in Education
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Navigating Bias and Discrimination in AI Models
This chapter explores the challenges of bias and discrimination in AI models, touching on the black box problem and the impact of biased data on outcomes. It stresses the importance of digital literacy in questioning AI-generated results to mitigate biases and highlights the need to receive all information, not just the best, to avoid oversimplification. The discussion also covers detecting bias in text-based AI generators, using multiple language models for vetting results, and the ethical implications of predictive AI in education.
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