Gender and ethnicity bias in generative artificial intelligence text-to-image depiction of pharmacists
This evaluation reveals the gender and ethnicity bias associated with generative AI text-to-image generation using DALL-E 3 among Australian pharmacists. Generated images have a disproportionately high representation of white men as pharmacists which is not representative of the diversity of pharmacists in Australia today.
Authors
- Geoffrey Michael Currie (ORCID: https://orcid.org/0000-0002-6180-8586)
- George John (ORCID: https://orcid.org/0000-0002-5131-4312)
- Johnathan Hewis (ORCID: https://orcid.org/0000-0002-7810-5641)
Institutions
- Charles Sturt University (AU)
- Baylor College of Medicine (US)
Publication Details
- Journal
- International Journal of Pharmacy Practice
- Published
- 2024-09-04
- DOI
- https://doi.org/10.1093/ijpp/riae049
- Citations
- 17
- Primary Topic
- Sex and Gender in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 9.23