The role of AI, technology and education in gender equality

For two weeks in March, I had the pleasure of being chosen from over 3,000 applicants as a UN Women UK Official Delegate for the 67th Meeting of The UN Commission for the Status of Women (CSW67). This amazing global meeting of independent advocates, representatives of government and groups was focused on the primary theme of ‘Innovation and technological change, and education in the digital age for achieving gender equality and the empowerment of all women and girls.’

UN Women UK is the United Kingdom’s national committee of UN Women, a subset of the United Nations group dedicated to gender equality and women’s empowerment. UN Women UK works towards promoting gender equality and women’s rights in the UK and globally through various initiatives, campaigns and partnerships, advocating for policy change, raising awareness of gender-based discrimination and violence and promoting women’s economic empowerment.

A small but mighty charity, they work towards achieving gender equality in all spheres of life including leadership, education, health and political participation. Additionally, UN Women UK work to engage men as allies in empowering women through initiatives such as #heforshe.

Throughout the two weeks, we were treated to a range of events covering different talking points in technology, including AI and data. The core theme emphasised the need for innovation and education in areas such as data literacy to be leveraged to promote gender equality, empower women and girls, and address gender-based violence.

The intersection of tech, gender and equality

The intersections of technology, gender and equality can be complex, especially in relation to AI. A core theme of CSW67 was the lack of diversity in teams developing AI systems; one of the main challenges for the technology is its potential to perpetuate existing biases and inequalities. There is a growing concern that AI systems have been proven to be biased against women, minorities, and other marginalised groups.

For example, image generators or large language models (LLM) are trained on datasets filled with these biases. When algorithms are taught on data sets that contain biases, they are likely to reproduce them in their output. This is why it is essential to ensure that the data models draw from is representative of a wider subset of society to avoid amplifying existing problems.

Examples were given in online talks by groups such as Feminist Task Force. The group’s speakers particularly highlighted the issues faced by asylum seekers trying to access the US government migration app, ‘CBP One’, particularly in Haiti and at the US-Mexico border. One of the top issues faced by families and individuals using the app is errors in recognising faces with darker skin tones. Repetitive failure to accept entries and identify users has caused major delays in registering and processing applications, with calls now being made by legal and advocacy groups for investigations into failures.

Speaking at “A Gender Equal World with Technologies, Digitalisation and AI”, Vera Jourová of the European Commission focused on gender stereotypes, AI algorithms and the tremendous potential that technology and digitalisation has for our lives. She discussed the importance of preventing new technology from perpetuating gender stereotypes and bias, emphasising that work in this area should not undermine gender equality or the democratic model.

The European Commission want the roadmap for a global digital compact to be gender transformative, and Jourová mentioned that the EU promotes a human-centred approach to the digital transition. There are at least two proposals, according to Jourová, which are being suggested to address the gender digital divide by EU co-legislators. One of these, The Artificial Intelligence Act, covers reinforcement of biases and how they may be counteracted.

A digital education action plan, which focuses on the digital readiness of education and training systems and encourages girls to be educated in STEM, is also currently in progress and running up to 2027. The strategy includes targets to address the digital divide, including aiming for 80% of the EU population to have basic digital skills by 2030, with 20 million becoming ICT specialists — and this number should be gender balanced.

Fighting bias in AI

To address this subject and other technology-related concerns around gender equality, UN Women UK organised a special in-person event at The Roundhouse in London, attended by a select group of 250 participants chosen from the nearly 3,000 UK delegates who took part this year. The event facilitated in-depth discussions on leveraging technology to promote gender equality without perpetuating existing biases.


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