A design perspective on how to tackle gender biases when developing AI-driven systems

Author:

González Ana SantanaORCID,Rampino LuciaORCID

Abstract

AbstractA growing awareness of bias in artificial intelligence (AI) systems has recently emerged, leading to an increased number of publications discussing ethics in AI. Nevertheless, the specific issue of gender bias remains under-discussed. How can design contribute to preventing the emergence of gender bias in AI-driven systems? To answer this question, we investigated the current state of AI ethical guidelines within the European Union. The results revealed that most guidelines do not acknowledge gender bias but address discrimination. This raised our concerns, as addressing multiple biases simultaneously might not effectively mitigate any of them due to their often-unconscious nature. Furthermore, our results revealed a lack of quantitative evidence supporting the effectiveness of bias prevention implementation methods and solutions. In conclusion, based on our analysis, we propose four recommendations for designing effective guidelines to tackle gender biases in AI. Moreover, we stress the central role of diversity in embedding the gender perspective from the beginning in any design activity.

Funder

Politecnico di Milano

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences

Reference77 articles.

1. Dove, G., Halskov, K., Forlizzi, J., Zimmerman, J.: UX Design Innovation. In: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, pp. 278–288. ACM, New York, NY, USA (2017)

2. Yang, Q.: Machine learning as a UX design material: how can we imagine beyond automation, recommenders, and reminders?. In AAAI Spring Symposia, Vol. 1, No. 2.1, pp. 2–6 (2018)

3. Figoli, F.A., Mattioli, F., Rampino, L.: Artificial Intelligence in the design process: the impact on creativity and team collaboration. FrancoAngeli, Milano, Italy (2022)

4. Antonelli, P.: AI Is Design’s Latest Material. In: Google Design Library. AI Is Design’s Latest Material (2018). Accessed 9 May 2023

5. Ropohl, G.: Philosophy of socio-technical systems. Soc. Philos. Technol. Quarter. Electron. J. 4, 186–194 (1999). https://doi.org/10.5840/techne19994311

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3