Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
STEM professionals and teacher perception in images created with ChatGPT and DALL-E
0
Zitationen
1
Autoren
2026
Jahr
Abstract
This research was conducted to examine artificial intelligence’s perceptions of STEM professionals and STEM teachers. The research employed a document analysis review method. Images created by ChatGPT’s DALL-E integration were used for the study. The images generated in response to prompts such as “draw a scientist” written to ChatGPT were evaluated and interpreted. Separate visuals were obtained for each STEM profession. The scientist was portrayed as a person working in a laboratory, the technologist as a person working on artificial intelligence in virtual reality style, the engineer as a person designing with technical equipment, and the mathematician as a person dealing with writing formulas. When asked to draw a STEM professional, it revealed a perception that emphasized the field of science in a technological laboratory. The most striking finding is that while it drew all STEM professionals in male gender, it drew the STEM teacher in female gender. Comparisons were made with the results of studies in which people’s perceptions of STEM professionals were determined through drawings. ChatGPT has been found to be within the stereotypical images and gender biases seen in people regarding STEM professions. This research includes assessments and recommendations on stereotypical biases regarding artificial intelligence and how these biases can be reduced.
Ähnliche Arbeiten
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
2019 · 8.402 Zit.
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
2019 · 8.270 Zit.
High-performance medicine: the convergence of human and artificial intelligence
2018 · 7.702 Zit.
Proceedings of the 19th International Joint Conference on Artificial Intelligence
2005 · 5.781 Zit.
Peeking Inside the Black-Box: A Survey on Explainable Artificial Intelligence (XAI)
2018 · 5.507 Zit.