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Plenary talk- Smart Health and Equity: Mitigation AI biases
0
Zitationen
2
Autoren
2022
Jahr
Abstract
Artificial intelligence and machine learning are becoming more present in several sectors in society today and are expected to become more pervasive in the future. These technologies have proven to be effective in a variety of fields including healthcare; however, in addition to the fact that they can provide incorrect outcomes, which may inflict harm (e.g., incorrect diagnoses). AI displays an important shortcoming in the form of biases that have the potential to propagate or embolden currently existing biases including social biases, racial biases, gender biases and health biases.
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