Social Psychology - Stereotypes and Bias

The study involves 27 photos of aliens with varying attributes (e.g., blue square, green circle).
Participants (six in a chain) are shown 13 of the 27 aliens.
Researchers assign six out of 48 traits (e.g., lazy) to each alien.
Participants try to guess the traits of seen and unseen aliens.
Traits initially assigned to aliens are replaced by the traits participants assign.
Accuracy in identifying traits of both seen and unseen aliens improves down the chain.
Jessica, the last person, accurately remembers traits of aliens she hasn't seen, suggesting a form of ESP.
The variety of words used to describe the aliens decreases with each participant.
Chris uses 36 of 48 traits, Annalise uses 30, and Jessica uses only 21.
The attributes of individuals are simplified as information is passed along.
Personalities become coarser and less fine-grained.

Structure is a statistic measuring the extent to which the same traits are applied to aliens with shared attributes, resembling a similarity score.
Aliens can share zero traits, leading to no similarity in assigned personality traits.
Sharing one or two features in common increases the structure score, indicating similar descriptors are applied.
The study demonstrates that we simplify words used to describe personality and retain only a small amount of variability.
This simplification models the birth of stereotypes, where appearance influences perceived traits.
False memories of unseen alien traits are created based on the rule that similar-looking aliens share traits.
Stereotypes can be inaccurate because they're based on limited information.
High-quality information combined with stereotypes can lead to consensual stereotype accuracy.
Stereotypes are applied in social group interactions, influencing our perceptions.

Two key dimensions for stereotyping: competence and warmth.
Competence indicates ability to harm or help.
Warmth indicates someone is good-natured.
Stereotype Content Model: social groups are rated/arrayed on competence vs. warmth (Susan Fiske).
Examples of groups rated high in warmth and competence: nurses, teachers, doctors, child care workers, farmers, professors.
Groups and characteristics are placed on a Cartesian plane.
Examples of people rated high in competence and warmth: Public servants, firemen, soldiers, air hostesses, professors, psychotherapists, yoga instructors.
Examples of groups rated low in competence and warmth: drug addicts, sex workers, criminals, beggars, unemployed people, urban management officers.
We want to be around competent and warm people, because these dimensions have social desirability.
Good/Bad linking with social groups.

Closely associated ideas tend to come to mind together (e.g., doctors and nurses).
IAT measures reaction times to associate faces (e.g., black vs. white) with good or bad words.
It looks for facilitation: speeding up recognition of faces after priming with good or bad words.
D score measures the extent to which bad words are associated with an outgroup and good words with a comparison group.
$D = (ReactionTime<em>{black/bad} - ReactionTime</em>{black/good}) - (ReactionTime<em>{white/bad} - ReactionTime</em>{white/good})$
IAT can be used for various social groups (sexuality, race, skin tone, body weight, age).
Average D score in online tests was 0.35, but in 2021 was 0.1.

Prejudice is declining.
Skin tone bias: declining slowly.
Explicit bias has disappeared among test takers.
Age bias: persistent negative associations with older people.
Disability bias: persistent negative associations.
Body weight bias: persistent negative associations.
Explicit bias against these groups is declining, but implicit bias will take longer to disappear.
White subjects associate white people with positive traits, but this isn't the case for black subjects.

The U.S. has some of the lowest implicit race attitudes compared to other countries.