Data Ethics Simplified
Denis emphasizes the importance of removing biased data fields such as gender and marital status from models, advocating for a focus on age and education as key predictors of income. By stripping away unnecessary variables, he highlights how ethical data practices can lead to clearer insights in explainable AI. The conversation underscores the need for fairness and transparency in algorithmic predictions.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
SDS 513: Transformers for Natural Language Processing — with Denis Rothman
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