Fairness in Algorithms
The discussion highlights the critical need to integrate fairness concerns into model development and organizational practices. While some improvements have been made in algorithmic performance, particularly in facial recognition software, a comprehensive approach that addresses both the models and the bureaucratic structures is essential for achieving true fairness and justice. Examples, such as those from Allegheny County, illustrate the ongoing challenges and the necessity for systemic reform.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Legal and Policy Implications of Model Interpretability with Solon Barocas - TWiML Talk #219
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