
Live from TWIMLcon! Operationalizing Responsible AI - #310
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
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Balancing Ethics and Complexity in AI
This chapter examines the conflict between principled ethical frameworks and empirical methods in AI, focusing on the complexities of deep learning and its implications for fairness. Speakers discuss the need for greater transparency in algorithmic decision-making and the challenges of ensuring fairness in applications like machine translation.
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