HackerTube

selective attention test

Daniel Simons3 HN recommenders · recommended in 3 months, 2011–2025
YouTube
demo · general · evergreen · 2011–2025 on HN

The original invisible gorilla awareness test by Daniel Simons and Christopher Chabris, in which viewers count basketball passes and often miss a gorilla crossing the scene. It demonstrates inattentional blindness.

HN uses it constantly as the classic demonstration that attention is selective, in threads on driving, motorcycles, AI and perception.

12 comments from Hacker News

@chrisweekly2019-10 · in “Lethal memory fail: Why drivers see, and then forget motorcyclists”

As a motorcyclist -- and lifelong learner w/ a degree in cognitive psychology -- I really appreciate demonstrations like this one^1 from Daniel Simons. It's a short video (< 90s), but for many first-time viewers, it's an eye-opening experience. ^1. ▶ this video Edit: just saw @elosarv's link to a longer but more relevant "motorcycle invisibility training" video ( link

Strongly recommends View on HN
@meowster2024-08 · in “Massachusetts 'Reviewing' Kei Car Ban After Uproar over Canceled Registrations”

It's called Selective Attention which explained in another comment: > Notably, people tend to see what they expect to see. > When they are looking for cars, they tend not to see motorcycles, even when they are in plain view. Watch/take this Selective Attention test (1 min 22 sec): ▶ this video

Recommends View on HN
@crispyambulance2018-09 · in “A Fighter Pilot’s Guide to Surviving on the Roads”

This is sound advice. The only time I've made contact with a moving car as a cyclist was when I was going past an off-ramp. The weird thing was that I thought the driver "saw me". It was late morning, no problem with visibility. From my POV, she was looking right at me. In fact, she was looking "through" me. She simply was expecting other cars and a person on a bike was not what she was looking for. Human attention is very much selective. Check out this shocking video: ▶ this video After that, I ride with a bright flashing headlight at all times, even daylight. It gives some measure of protection, I think.

Recommends View on HN
@Joel_Mckay2025-07 · in “How Tesla is proving doubters right on why its robotaxi service cannot scale”

It is true most humans can not track more than 5 objects concurrently. However, lidar data sets tend to produce sparse unambiguous point cloud data that is a lot more feasible to process. For example, a picture/reflection of a road on a bus is not a viable option with 3D data. Cheers =3 ▶ this video

@rsanek2025-02 · in “Are LLMs able to notice the “gorilla in the data”?”

Humans seem to me to be just as likely to make these kinds of errors in the general case. See the classic ▶ this video , which has an interesting parallel with this paper.