Gaydar

Gaydar (a portmanteau of gay and radar) is a colloquialism referring to the intuitive ability of a person to assess others' sexual orientations as homosexual, bisexual or straight.

[9] In 1987, a Journal of Homosexuality study[10] asked people to judge sexual orientation from video clips, with results concluding that it was a myth.

A 1999 study in the Journal of Personality and Social Psychology showed that people could judge sexual orientation more accurately than chance.

[24] Other studies have found that men and women with body shapes and walking styles similar to people of the opposite sex are more often perceived as gay.

Detailed acoustic analyses have highlighted a number of factors in a person's voice[32] that are used, one of which is the way that gay and straight men pronounce "s" sounds.

[35] This work points out that the scientific work reviewed above that claims to demonstrate accurate gaydar falls prey to the false positive paradox (see also the base rate fallacy), because the alleged accuracy discounts the very low base rate of LGBT people in real populations, resulting in a scenario where the "accuracy" reported above in lab studies translates to high levels of inaccuracy in the real world.

Stanford University researchers Michal Kosinski and Yilun Wang carried out a study in 2017 which claimed that a facial recognition algorithm using neural networks could identify sexual orientation in 81% of the tested cases for men and 74% with women by reviewing photos of online dating profiles.

[39][40] Kosinski voiced concern about privacy and the potential for misuse of AI, and suggested that his findings were consistent with the prenatal hormone theory of sexual orientation, which hypothesizes that levels of androgens exposure in the womb help determine whether a person is straight, bisexual or gay.