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EPISODE · Jun 17, 2026 · 35 MIN

AutoLike

from Data Skeptic

How can researchers audit recommendation systems when the algorithms are hidden from view? Hieu Le joins Kyle Polich to discuss Auto-Like, a reinforcement learning framework that systematically explores how platforms like TikTok personalize content feeds. The conversation covers recommendation transparency, black-box auditing, and the future of platform accountability.

Episode metadata supplied by the publisher feed · Published Jun 17, 2026

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How long is this episode of Data Skeptic?

This episode is 35 minutes long.

When was this Data Skeptic episode published?

This episode was published on June 17, 2026.

What is this episode about?

How can researchers audit recommendation systems when the algorithms are hidden from view? Hieu Le joins Kyle Polich to discuss Auto-Like, a reinforcement learning framework that systematically explores how platforms like TikTok personalize content...

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