This week, in line with its work to implement global ethical framework for artificial intelligence, UNESCO launched Women4Ethical AI, a new collaborative platform to support governments and companies’ efforts to ensure that women are represented equally in both the design and deployment of AI.
At a time when digital technologies are reshaping everyday life, women are under-represented in the research and design of these technologies, Their needs and experiences are also overlooked by designers, and the data used to train AI is often biased against women and girls. Today, globally, women and girls are 25% less likely than men to know how to leverage digital technology for basic purposes, 4 times less likely to know how to programme computers and 13 times less likely to file for an ICT patent.
Only 20% of employees in technical roles in machine learning companies, 12% of artificial intelligence researchers globally and 6% of professional software developers are women.
17 leading female AI experts from around the world
To solve this problem, UNESCO has put gender equality at the heart of its Recommendation on the Ethics of Artificial Intelligence, the first global standard-setting instrument in this area, unanimously adopted by its 193 Member States in November 2021. This document, which is a concrete roadmap for states in establishing their AI policies, plans to adopt a gendered approach to all aspects of AI.
To accelerate the implementation of this objective, UNESCO created Women4Ethical AI, a collaborative platform to support governments and companies’ efforts. The platform unites 17 leading female experts from academia, civil society, the private sector and regulatory bodies, from around the world. They will share research and contribute to a repository of good practices. The platform will drive progress on non-discriminatory algorithms and data sources, and incentivize girls, women and under-represented groups to participate in AI.
Among the tools proposed to ensure the inclusion and empowerment of women at every stage of the AI life cycle are budgetary allocations and the provision of support to women in research, academia, and entrepreneurship.
Biased Data leads to discriminatory Outcomes
The development, use and deployment of AI systems risks replicating and amplification existing gender biases and creating new ones: lack of diversity in data, programming teams or approaches leads to biased AI tools that propose discriminatory outcomes. These outcomes are used to take important decisions that impact the everyday life of citizens. One example of the harmful impact of biased data is when medical diagnoses are based on evidence collected only from men.