Hand labeling data and information bias: Jon Krohn speaks with Watchful CEO Shayan Mohanty about the pitfalls of data analysis when bias comes into the equation (spoiler alert: it always does), the importance of the Chomsky hierarchy in data management, and the importance of simulation engines for returning real-time results to users.

This episode is brought to you by Iterative (iterative.ai), your mission control center for machine learning. Interested in sponsoring a SuperDataScience Podcast episode? Visit JonKrohn.com/podcast for sponsorship information.

In this episode you will learn:
• Why bias in general is good [04:06]
• The arguments against hand labeling [09:47]
• How Shayan solves the problem of labeling at his company [24:26]
• Misconceptions concerning hand-labeled data [43:25]
• What the Chomsky hierarchy is [52:38]
• Watchful’s high-performance simulation engine [1:04:51]
• What Shayan looks for in his new hires [1:08:15]

Additional materials: www.superdatascience.com/635

635: The Perils of Manually Labeling Data for Machine Learning Models 01:18:31 Share

Super Data Science: ML & AI Podcast with Jon Krohn

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635: The Perils of Manually Labeling Data for Machine Learning Models