HackerTube

THE VIDEO SHELF · algorithms and truth online

There is No Algorithm for Truth - with Tom Scott

Tom Scott's Royal Institution discourse on science communication in the age of social media, how recommendation algorithms shape popularity, and why view counts can matter more than truth. It includes a segment on parasocial relationships.

Watch & explore the libraryYouTube ↗

Why HN readers recommended it

HN returns to it in discussions of algorithmic feeds, misinformation and parasocial relationships, as a clear and thoughtful talk.

This is a summary from the source dataset, not an endorsement by Hacker News or the video creator.

Video & recommendation details

Creator / channel
The Royal Institution
Topic
algorithms and truth online
Format
talk
Level
general
HN recommenders in dataset
3
HN mentions in dataset
7
Recommendation years in dataset
2019–2025

These counts and years describe the included Hacker News records; they are not YouTube views or the video’s publication date.

From the original HN conversations

Excerpts from the recorded comments. Follow each source for the full comment and surrounding discussion.

  • > Someone who can get pop-culture’s attention needs to do a fucking Ted Talk and explain why this is usually a bad idea. Tom Scott made a good attempt recently: [VIDEO]

    pdkl95 on Hacker News · 2019-11
    In Algorithms were supposed to make VA judges fairer: it's far more complicated

  • Not without a certain amount of irony, everybody's parasocial internet friend Tom Scott did a really good segment on the parasocial relationship as part of his talk to the Royal Institution: [VIDEO] I swear it's also a short video on its own somewhere, but neither …

    codefreeordie on Hacker News · 2022-05
    In Parasocial Relationships: Imaginary Friends of the Social Network Age

  • RIYL: Tom Scott's There Is No Algorithm For Truth [1] delivered to the Royal Society in October 2019. 1. [VIDEO]

    nativeit on Hacker News · 2025-03
    In Kill your Feeds – Stop letting algorithms dictate what you think

Summaries, classifications and recommendation records are from the HackerTube source dataset. Read about this library and its limitations.