Gender stereotypes in AI-generated images
DOI:
https://doi.org/10.3145/epi.2023.sep.05Keywords:
Artificial intelligence, AI, OpenAI, DALL-E, Synthetic images, AI-generated images, Imaging, Gender stereotypes, Sex biases, Gender biases, Gender differences, Professions, Workers, Ethics, Discrimination, Inequalities, Fairness, EquityAbstract
This study explores workplace gender bias in images generated by DALL-E 2, an application for synthesising images based on artificial intelligence (AI). To do this, we used a stratified probability sampling method, dividing the sample into segments on the basis of 37 different professions or prompts, replicating the study by Farago, Eggum-Wilkens and Zhang (2020) on gender stereotypes in the workplace. The study involves two coders who manually input different professions into the image generator. DALL-E 2 generated 9 images for each query, and a sample of 666 images was collected, with a confidence level of 99% and a margin of error of 5%. Each image was subsequently evaluated using a 3-point Likert scale: 1, not stereotypical; 2, moderately stereotypical; and 3, strongly stereotypical. Our study found that the images generated replicate gender stereotypes in the workplace. The findings presented indicate that 21.6% of AI-generated images depicting professionals exhibit full stereotypes of women, while 37.8% depict full stereotypes of men. While previous studies conducted with humans found that gender stereotypes in the workplace exist, our research shows that AI not only replicates this stereotyping, but reinforces and increases it. Consequently, while human research on gender bias indicates strong stereotyping in 35% of instances, AI exhibits strong stereotyping in 59.4% of cases. The results of this study emphasise the need for a diverse and inclusive AI development community to serve as the basis for a fairer and less biased AI.
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References
Agudo, Ujué; Liberal, Karlos G. (2020). "El automágico traje del emperador". Medium.com, 9 septiembre. https://medium.com/bikolabs/el-automagico-traje-del-emperador-c2a0bbf6187b
Archer, Cynthia J. (1984). "Children´s attitudes toward sex-role division in adult occupational roles". Sex roles, v. 10. https://doi.org/10.1007/BF00287742
Belhadi, Amine; Kamble, Sachin; Fosso-Wamba, Samuel; Queiroz, Maciel M. (2022). "Building supply-chain resilience: an artificial intelligence-based technique and decision-making framework". International journal of production research, v. 60, n. 14, pp. 4487-4507. https://doi.org/10.1080/00207543.2021.1950935
Bolukbasi, Tolga; Chang, Kai-Wie; Zou, James; Saligrama, Venkatesh; Kalai, Adam (2016). "Man is to computer programmer as woman is to homemaker? Debiasing word embeddings". In: NIPS´16: Proceedings of the 30th international conference on neural information processing systems, pp. 4356-4364. https://doi.org/10.48550/arXiv.1607.06520
Borji, Ali (2022). Generated faces in the wild: quantitative comparison of stable diffusion, midjourney and DALL-E 2. Quintic AI, San Francisco, CA. https://arxiv.org/pdf/2210.00586.pdf
Brown, Tom B.; Mann, Benjamin; Ryder, Nick; Subbiah, Melanie; Kaplan, Jared; Dhariwal, Prafulla; Neelakantan, Arvind; Shyam, Pranav; Sastry, Girish; Askell, Amanda; Agarwal, Sandhini; Herbert-Voss, Ariel; Krueger, Gretchen; Henighan, Tom; Child, Rewon; Ramesh, Aditya; Ziegler, Daniel M.; Wu, Jeffrey; Winter, Clemens; Hesse, Christopher; Chen, Mark; Sigler, Eric; Litwin, Mateusz; Gray, Scott; Chess, Benjamin; Clark, Jack; Berner, Christopher; McCandlish, Sam; Radford, Alec; Sutskever, Ilya; Amodei, Dario (2020). "Language models are few-shot learners". Advances in neural information processing systems, v. 33, pp. 1877-1901. https://doi.org/10.48550/arXiv.2005.14165
Buolamwini, Joy; Gebru, Timnit (2018). "Gender shades: intersectional accuracy disparities in commercial gender classification". Proceedings of machine learning research, v. 81. https://proceedings.mlr.press/v81/buolamwini18a/buolamwini18a.pdf
Caliskan, Aylin; Bryson, Joanna J.; Narayanan, Arvind (2017). "Semantics derived automatically from language corpora contain human-like biases". Science, v. 356, n. 6334, pp.183-186. https://doi.org/10.1126/science.aal4230
Cortina-Orts, Adela (2019). "í‰tica de la inteligencia artificial". Anales de la Real Academia de Ciencias Morales y Políticas, pp. 379-394. Ministerio de Justicia. https://www.boe.es/biblioteca_juridica/anuarios_derecho/articulo.php?id=ANU-M-2019-10037900394
Crawford, Kate (2021). The atlas of AI: power, politics, and the planetary costs of artificial intelligence. Yale University Press. ISBN: 978 0 300252392 https://doi.org/10.2307/j.ctv1ghv45t
Criado-Pérez, Caroline (2020). La mujer invisible. Descubre cómo los datos configuran un mundo hecho por y para los hombres. Barcelona: Seix Barral. ISBN: 978 84 32236136
DALL-E 2 (2021). OpenAI. https://openai.com/dall-e-2
De-Carvalho, André-Carlos-Ponce-de-Leon-Ferreira (2021). Inteligíªncia artificial: riscos, benefícios e uso responsável. Estudos avaní§ados, v. 35, 101. https://doi.org/10.1590/s0103-4014.2021.35101.003
D´Ignazio, Catherine; Klein, Lauren F. (2020). Data feminism. Cambridge: MIT Press. ISBN: 978 0 262547185
Eichenberger, Livia (2022). "DALL-E 2: Why discrimination in AI development cannot be ignored". Statworx blog post, 28 June. https://www.statworx.com/en/content-hub/blog/dalle-2-open-ai
Estupiñán-Ricardo, Jesús; Leyva-Vázquez, Maikel-Yelandi; Peñafiel-Palacios, Álex-Javier; El-Asaffiri-Ojeda, Yusef (2021). "Inteligencia artificial y propiedad intelectual". Universidad y sociedad, v. 13, n. S3, pp. 362-368. https://rus.ucf.edu.cu/index.php/rus/article/view/2490
Eubanks, Virginia (2018). Automating inequality: how high-tech tools profile, police, and punish the poor. New York: St. Martin´s Press. ISBN: 978 1 250074317
Farago, Flora; Eggum-Wilkens, Natalie D.; Zhang, Linlin (2021). "Ugandan adolescents´ gender stereotype knowledge about jobs". Youth & society, v. 53, n. 5, pp. 723-744. https://doi.org/10.1177/0044118X19887075
Francescutti, Pablo (2018). La visibilidad de las científicas españolas. Fundación Dr. Antoni Esteve, Grupo de estudios avanzados de comunicación, Barcelona. https://www.raco.cat/index.php/QuadernsFDAE/issue/download/30066/439
Franganillo, Jorge (2022). "Contenido generado por inteligencia artificial: oportunidades y amenazas". Anuario ThinkEPI, v. 16, e16a24. https://doi.org/10.3145/thinkepi.2022.e16a24
Gamir-Ríos, José; Tarullo, Raquel (2022). "Predominio de las cheapfakes en redes sociales. Complejidad técnica y funciones textuales de la desinformación desmentida en Argentina durante 2020". adComunica, v. 23, pp. 97-118. https://doi.org/10.6035/adcomunica.6299
García-Ull, Francisco-José (2021). "Deepfakes: el próximo reto en la detección de noticias falsas". Anàlisi, n. 64, pp. 103-120. https://doi.org/10.5565/rev/analisi.3378
Goodfellow, Ian J.; Pouget-Abadie, Jean; Mirza, Mehdi; Xu, Bing; Warde-Farley, David; Ozair, Sherjil; Courville, Aaron; Bengio, Yoshua (2014). "Generative adversarial networks. Advances in neural information processing systems". Communications of the ACM. v. 63, pp. 139-164. https://doi.org/10.48550/arXiv.1406.2661
Gottfredson, Linda S. (1981). "Circumscription and compromise: A developmental theory of occupational aspirations". Journal of counseling psychology, v. 28, n. 6, pp. 545-579. https://doi.org/10.1037/0022-0167.28.6.545
Laino, María-Elena; Cancian, Pierandrea; Salvatore-Politi, Letterio; Della-Porta, Matteo-Giovanni; Saba, Luca; Savevski, Victor (2022). "Generative adversarial networks in brain imaging: A narrative review". Journal of imaging, v. 8, n. 4, 83. https://doi.org/10.3390/jimaging8040083
Leavy, Susan (2018). "Gender bias in artificial intelligence: the need for diversity and gender theory in machine learning". In: Proceedings of the 1st international workshop on gender equality in software engineering, pp. 14-16. https://doi.org/10.1145/3195570.3195580
Leavy, Susan; Meaney, Gerardine; Wade, Karen; Greene, Derek (2020). "Mitigating gender bias in machine learning data sets". In: Bias2020 workshop: Bias and social aspects in search and recommendation. https://doi.org/10.1007/978-3-030-52485-2_2
Liben, Lynn S.; Bigler, Rebecca S.; Krogh, Holleen R. (2001). "Pink and blue collar jobs: children´s judgments of job status and job aspirations in relation to sex of worker". Journal of experimental child psychology, v. 79, n. 4, pp. 346-363. https://doi.org/10.1006/jecp.2000.2611
Loftus, Tyler J.; Tighe, Patrick J.; Filiberto, Amanda C.; Efron, Philip A.; Brakenridge, Scott C.; Mohr, Alicia M.; Rashidi, Parisa; Upchurch, Gilbert R.; Bihorac, Azra (2020). "Artificial intelligence and surgical decision-making". JAMA surgery, v. 155, n. 2, pp. 148-158. https://doi.org/10.1001/jamasurg.2019.4917
Manassero, Antonia; Vázquez, Ángel (2003). "Las mujeres científicas: un grupo invisible en los libros de texto". Revista investigación en la escuela, v. 50, pp. 31-45. https://revistascientificas.us.es/index.php/IE/article/view/7582
Millán, Víctor (2022). "DALL-E 2: ¿cómo funciona y qué supone? La IA que crea imágenes de la nada y es, simplemente, perfecta y aterradora". Hipertextual, 29 mayo. https://hipertextual.com/2022/05/dall-e-2
Nica, Elvira; Sabie, Oana-Matilda; Mascu, Simona; Luţan-Petre, Anca-Georgeta (2022). "Artificial intelligence decision-making in shopping patterns: consumer values, cognition, and attitudes". Economics, management and financial markets, v. 17, n. 1, pp. 31-43. https://doi.org/10.22381/emfm17120222
O´Neil, Cathy (2018). Armas de destrucción matemática: cómo el big data aumenta la desigualdad y amenaza la democracia. Capitán Swing Libros. ISBN: 978 84 947408 4 8
OpenAI (2022a). "DALL-E now available without waitlist". Openai, September 28. https://openai.com/blog/dall-e-now-available-without-waitlist
OpenAI (2022b). "Reducing bias and improving safety in DALL-E 2". OpenAI, July 18. https://openai.com/blog/reducing-bias-and-improving-safety-in-dall-e-2
Ortiz-de-Zárate-Alcarazo, Lucía (2023). "Sesgos de género en la inteligencia artificial". Revista de occidente, v. 1, n. 502. https://dialnet.unirioja.es/servlet/articulo?codigo=8853265
Pérez-Gómez, Miguel-Ángel; Echazarreta-Soler, Carmen; Audebert-Sánchez, Meritxell; Sánchez-Miret, Cristina (2020). "El ciberacoso como elemento articulador de las nuevas violencias digitales: métodos y contextos". Communication papers. Media literacy and gender studies, v. 9, n. 18. https://doi.org/10.33115/udg_bib/cp.v9i18.22470
Porayska-Pomsta, Kaska; Rajendran, Gnanathusharan (2019). "Accountability in human and artificial intelligence decision-making as the basis for diversity and educational inclusion". In: Knox, Jeremy; Wang, Yuchen; Gallagher, Michael. Artificial intelligence and inclusive education: speculative futures and emerging practices. Springer, pp. 39-59. https://doi.org/10.1007/978-981-13-8161-4_3
Postman, Neil (1991). Divertirse hasta morir, el discurso público en la era del show business. Barcelona: Ediciones la Tempestad. ISBN: 978 84 79480462
Quirós-Fons, Antonio; García-Ull, Francisco-José (2022). La inteligencia artificial como herramienta de la desinformación: deepfakes y regulación europea. Los derechos humanos en la inteligencia artificial: su integración en los ODS de la Agenda 2030. Thomson Reuters Aranzadi, pp. 537-556. ISBN: 978 84 1124 557 9
Rassin, Royi; Ravfogel, Shauli; Goldberg, Yoav (2022). "DALL-E 2 is seeing double: flaws in word-to-concept mapping in text2image models". https://doi.org/10.48550/arXiv.2210.10606
Sainz, Milagros; Arroyo, Lidia; Castaño, Cecilia (2020). Mujeres y digitalización: de las brechas a los algoritmos. Instituto de la Mujer y para la Igualdad de Oportunidades. https://www.inmujeres.gob.es/diseno/novedades/M_MUJERES_Y_DIGITALIZACION_DE_LAS_BRECHAS_A_LOS_ALGORITMOS_04.pdf
Sourdin, Tania (2018). "Judge v Robot? Artificial intelligence and judicial decision-making". UNSW law journal, v. 41, n. 4, pp. 1114-1133. https://www.unswlawjournal.unsw.edu.au/wp-content/uploads/2018/12/Sourdin.pdf
Teig, Stacey; Susskind, Joshua E. (2008). "Truck driver or nurse? The impact of gender roles and occupational status on children´s occupational preferences". Sex roles, v. 58, pp. 848-863. https://doi.org/10.1007/s11199-008-9410-x
Traylor, Jake (2022). "No quick fix: how OpenAI´s DALL-E 2 illustrated the challenges of bias in AI". NBC news, July 27. https://www.nbcnews.com/tech/tech-news/no-quick-fix-openais-dalle-2-illustrated-challenges-bias-ai-rcna39918
Véliz, Carissa (2021). Privacidad es poder: datos, vigilancia y libertad en la era digital. Debate. ISBN: 978 84 18056680
Vincent, James (2020). "OpenAI´s latest breakthrough is astonishingly powerful, but still fighting its flaws". The verge tech, July 30. https://www.theverge.com/21346343/gpt-3-explainer-openai-examples-errors-agi-potential
Wang, Tianlu; Zhao, Jieyu; Yatskar, Mark; Chang, Kai-Wei; Ordóñez, Vicente (2019). "Balanced datasets are not enough: estimating and mitigating gender bias in deep image representations". In: International conference on computer vision, ICCV 2019. https://doi.org/10.48550/arXiv.1811.08489
Zhou, Yufan; Zhang, Ruiyi; Chen, Changyou; Li, Chunyuan; Tensmeyer, Chris; Yu, Tong; Gu, Jiuxiang; Xu, Jinhui; Sun, Tong (2021). "Towards language-free training for text-to-image generation". https://arxiv.org/pdf/2111.13792v3.pdf
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