# AutoLike

Page: https://stenobird.com/podcast/data-skeptic/autolike
Text version: https://stenobird.com/podcast/data-skeptic/autolike.md
Podcast: [Data Skeptic](https://stenobird.com/podcast/data-skeptic)
Published: 2026-06-17T18:00:00+00:00
Episode link: https://dataskeptic.com/blog/episodes/2026/autolike
Audio file: https://pscrb.fm/rss/p/mgln.ai/e/35/traffic.libsyn.com/secure/dataskeptic/Hieu_No_Ads_V1.mp3?dest-id=201630
Processing state: not_requested
JSON: https://stenobird.com/v1/public/podcasts/data-skeptic/episodes/autolike
Duration seconds: 2118

## Resource

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.

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## Transcript

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