Masculine Defaults in Academic Science, Technology, Engineering, and Mathematics (STEM) Fields

Garr-Schultz, Alexandra; Muragishi, Gregg A.; Mortejo, Therese Anne; Cheryan, Sapna

doi:10.1177/15291006231170829

Cited by 2 publications

(2 citation statements)

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“…Although we focused on portrayals of people in STEM, this phenomenon is likely not content-specific. A lack of representation of certain demographic groups or stereotypical representations could have numerous negative downstream effects on their interests, educational ambitions and performance (Garr-Schultz et al, 2023;Schmader, 2023).…”

Section: Discussionmentioning

confidence: 99%

“…Several lines of theory and research point out that the underrepresentation and stereotypic representation of women and POC influence interests, educational goals, and the performance of these groups (Garr-Schultz et al, 2023;Schmader, 2023). In STEM, cultural gender stereotypes play a key role for explaining the relatively low interest of women in some parts of this field (Starr, 2018).…”

Section: Perceptionsmentioning

confidence: 99%

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Algorithmic Bias in Image-Generating Artificial Intelligence: Prevalence and User Perceptions

Messingschlager,

Appel

2024

Preprint

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Image-generating AI is among the most popular generative AI applications, likely changing the visual mediated environments humans are exposed to on a mass scale. Prior work found that AI can be biased against women and minorities (algorithmic bias), whereas humans attribute rather high objectivity to AI. We focused on image-generating AI, analyzing the extent of algorithmic bias in AI-generated pictures, as well as human responses to bias in image-generating AI. Study 1 showed that AI-generated portraits of people in STEM professions were almost exclusively depicting male, white (and older) individuals. Study 2 (experimental, N = 495) showed that the responses to AI-generated pictures vary, depending on the portrayed group. Participants perceived pictures to be less biased if they were introduced as AI-generated, but only if pictures showed college students (vs. older people). If images showed older people, participants reported higher moral outrage if pictures were supposedly generated by AI (vs. human creators).

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Section: Discussionmentioning

confidence: 99%