Notice anything unusual about this lung scan? Harvard researchers Trafton Drew and Jeremy Wolfe found that 83 percent of radiologists didn't notice the gorilla in the top right portion of this image. Can you spot the gorilla?
The striking fact is that even professional people can miss novel information because of their attention bias. They can be blind to the obvious but also blind to their blindness (D. Kahnemann, "Thinking, Fast and Slow").
If you never heard about the "invisible gorilla" experiment, here is a summary. When testing for for inattentional blindness, researchers ask participants to complete a primary task while an unexpected stimulus is presented. Afterwards, researchers ask participants if they seen anything unusual during the primary task.
In the Invisible gorilla test, conducted by Daniel Simons and Christopher Chabris, they asked subjects to watch a short video of two groups of people pass a basketball around. The subjects are told to count the number of passes made by one of the teams. A gorilla walks through the scene. After watching the video the subjects are asked if they saw anything out of the ordinary take place. In most groups, 50% of the subjects did not report seeing the gorilla. The failure to perceive the gorilla is attributed to the failure to attend to it while engaged in the difficult task of counting the number of passes of the ball.
These results indicate that the relationship between what is in one's visual field and perception is based much more on attention than was previously thought. These findings are of interest for psychology and also cast an alarming shadow when critical decisions depend on spotting novel and unexpected patterns, like in some medical diagnosis tasks.
In the cited radiology experiment, the gorilla was not detected because the radiologists were looking for cancer nodules, not gorillas, so "they look right at it, but because they're not looking for a gorilla, they don't see that it's a gorilla."
In other words, what we're thinking about — what we're focused on — filters the world around us so aggressively that it literally shapes what we see. We need to think carefully about the instructions we give to professional searchers like radiologists, because what we tell them to look for will in part determine what they see and don't see.
Proper classifiers trained by machine learning do not suffer from inattentional blindness, and they can learn from millions of cases, for sure many more than a single expert can see in his entire professional life. Appropriate "novelty detector" filters can in fact spot "gorillas" even if no gorilla has been encountered before during training. Expect more automated classifiers helping doctors in the near future.
Additional info: wikipedia