Privacy and Algorithmic Fairness
MP4 | Video: AVC 1920x1080 | Audio: AAC 48KHz 2ch | Duration: 29M | 1.41 GB
Genre: eLearning | Language: English
Understanding how algorithms can reinforce societal biases has become an important topic in data science. Recent work for auditing models for fairness often requires access to potentially sensitive demographic information, placing algorithmic fairness in conflict with individual privacy.
For example, gender recognition technology struggles to recognize the gender of transgender individuals. To develop more accurate models, we require information that could "out" these individuals, putting their social, psychological, and physical safety at risk.
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