LASIE is a Test to Determine Whether People are "Super-Recognisers"
References: greenwichuniversity.eu.qualtrics & boingboing.net
LASIE is a test developed by Josh P. Davis, a psychology professor at the University of Greenwich. The test is designed to determine whether or not the taker is a "super-recogniser," or a person with a preternaturally strong ability to recognize and remember other people's faces.
The layout of the online LASIE test is straightforward. First, the test shows users an image of a face for between four and seven seconds. Then, that face disappears and the test brings up an array of eight different faces, one of which is the face that was on screen a moment ago. Users then have to pick out the correct face. Though it may seem easy, the test alternates between straight-on images, images of faces in profile and faces from different angles.
A score of 10 or higher means that the user may be a super-recogniser.
The layout of the online LASIE test is straightforward. First, the test shows users an image of a face for between four and seven seconds. Then, that face disappears and the test brings up an array of eight different faces, one of which is the face that was on screen a moment ago. Users then have to pick out the correct face. Though it may seem easy, the test alternates between straight-on images, images of faces in profile and faces from different angles.
A score of 10 or higher means that the user may be a super-recogniser.
Trend Themes
1. Super-recognisers - Opportunity for developing facial recognition technology that leverages the abilities of individuals with exceptional facial recognition skills.
2. Online Facial Recognition Tests - Opportunity to create more sophisticated online tests to identify individuals with super-recogniser abilities for various applications.
3. Face Recognition Training - Opportunity to develop training programs that enhance facial recognition skills for the general population.
Industry Implications
1. Technology - Disruptive innovation opportunity in developing advanced facial recognition software and applications.
2. Education - Opportunity to create training programs or courses that specifically focus on improving facial recognition abilities.
3. Security - Opportunity to enhance security systems by incorporating super-recogniser technology for better face recognition and identification.
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