Gender and ethnicity bias in generative artificial intelligence text-to-image depiction of pharmacists.

Journal: The International journal of pharmacy practice
PMID: 39228085

Abstract

INTRODUCTION: In Australia, 64% of pharmacists are women but continue to be under-represented. Generative artificial intelligence (AI) is potentially transformative but also has the potential for errors, misrepresentations, and bias. Generative AI text-to-image production using DALL-E 3 (OpenAI) is readily accessible and user-friendly but may reinforce gender and ethnicity biases.

Authors

  • Geoffrey Currie
    School of Dentistry & Health Sciences, Charles Sturt University, Wagga Wagga, Australia. Electronic address: gcurrie@csu.edu.au.
  • George John
    School of Dentistry and Medical Sciences, Charles Sturt University, Wagga Wagga, Australia.
  • Johnathan Hewis
    School of Dentistry & Medical Sciences, Charles Sturt University, Port Macquarie, Australia.

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