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“Would You Rather Have It Be Accurate Or Diverse?” How Male Middle-School Students Make Sense Of Algorithm Bias, Golnaz Arastoopour Irgens, Jacoya Thompson
“Would You Rather Have It Be Accurate Or Diverse?” How Male Middle-School Students Make Sense Of Algorithm Bias, Golnaz Arastoopour Irgens, Jacoya Thompson
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As data-driven decisions become more ubiquitous, it will be critical for youth to understand the impacts of algorithm bias. In this study, we discuss the design of an extra-curricular data science program and examined how the participants (12 males, ages 11 - 13) made sense of algorithm bias and discrimination. We conducted a critical discourse analysis on one classroom discussion. Results suggest that participants showed initial understandings that algorithms contain biases that may perpetuate discrimination.