HackerTube.dev

Mike Mullane - Normalisation of deviance - IAFF - Part 1

Stuart Walker · 179.6K views · 2015-08-01 · 16:36

Open on YouTube ↗

If playback is restricted in your region, try opening the original video. Use Mark watched to add it to your marked videos.

Overview

Astronaut Mike Mullane explains normalisation of deviance, where teams gradually come to accept violations of their own safety standards. He uses the Challenger shuttle disaster as the main case, drawing on NASA's ignored warnings before the launch. It is the first part of a talk given to a fire-fighters' association.

On Hacker News

HN commenters cite it whenever a thread involves ignored warnings, shortcuts or routine risk, as the clearest introduction to the concept.

Recommended by 4 HN people across 4 months · HN mentions 2018–2022

Topics

Space exploration & spaceflightManagement, leadership & organizationsPsychology & human behavior
Search by tags
challenger disastersafety culturerisknasaorganizational failure

What people said

christophilus · 2019-02 · Strong recommendation

Here is an excellent talk on this subject[0]. It's one of the few presentations I like to watch every once in a while. [0] [VIDEO]

Read the original HN comment ↗
slackerlol · 2022-07 · Recommendation

The “preventable mistakes” point reminds me of this great video about “normalization of deviance” [from routine/checklists] [VIDEO]

Read the original HN comment ↗
y04nn · 2021-07 · Recommendation

I like the term "normalization of deviance" and would recommand the Mike Mullane's talk on the Challenger disaster [1]. [1]: [VIDEO]

Read the original HN comment ↗

Sources

Video by Stuart Walker, played through YouTube.

Data and selection notes

HN summaries and labels may contain AI errors. HN dates refer to discussions, not video publication.

HN Library: HackerTube export (2026-10-31) and open-index/hacker-news. Upstream summaries and classifications may contain AI errors.

Views, duration and playback status refresh separately from the published catalog. When an update fails, existing data remains visible.

Selection checks
  • SaaS & AI candidates: Topic keywords do not match
  • Editor-approved picks: Editorial review is required

Rule matches identify candidates. They do not guarantee video quality or financial results.

About the library and its sources