After more than a year of setting up and organising, the Grain network is set to be officially launched. The launch took place on Monday 20 November 2023, during a webinar held on the Zoom platform. The event was attended by all members of the consortium responsible for coordinating the network (IPAR, CSEA and Sunbird AI). Also taking part in the meeting were the beneficiaries of the call for proposals on the theme «Enhancing inclusion and gender equality through artificial intelligence in sub-Saharan Africa» as well as experts on gender equality and the AI ecosystem in Africa, notably the AI4D network, to explore the network’s origins and consider avenues for sustainable collaboration.
The opening of the meeting featured, amongst other things, a presentation of the GRAIN project, in particular its research objectives and prospects for sustainability. There was also a presentation of the member institutions of the consortium behind the GRAIN project, followed by a presentation of the network AI4D, the project’s initiator.
Beyond the official launch of the network, the aim of this meeting was to create a platform for dialogue amongst stakeholders to foster a better understanding of gender equality in AI. Introducing GRAIN, Dr Laure Tall of IPAR called on members to «make the network sustainable and capable of harnessing knowledge to promote learning and innovation».
With a view to broadening its social base, the GRAIN network launched in October 2022, a call for proposals inviting AI stakeholders to submit projects addressing the use of AI to tackle issues relating to gender inclusion and equity in sub-Saharan Africa. The launch of the network also provided an opportunity for the nine beneficiaries from universities and research institutions across Africa to present their projects. In their various speeches, the team leaders highlighted the many challenges Africa faces in terms of gender balance and AI, and proposed research topics.
There are numerous obstacles, including a lack of gender-disaggregated data, limited skills and low participation in the AI economy, a lack of quantitative and qualitative research, barriers to digital gender equality, the inclusion of women, women’s limited access to technology, language issues, the influence of social structures on women’s career paths in the fields of innovation and STEM, etc.
Dr Olayinka Jelili Yusuf from KWASU University, based in Kwara State, Nigeria, team leader of the «AI for Women in Agriculture’ project e – AI4WIA » During his presentation, he pointed out that their project addresses the challenges posed by climate change, which is leading to a decline in and instability of agricultural yields, particularly for women farmers. He also highlighted the socio-cultural constraints regarding resource ownership and the lack of predictive meteorological data needed to make informed decisions on the optimal cropping calendar. The study therefore aims to propose an AI-based solution to tackle this dual threat – the worsening effects of climate change and reliance on rain-fed agriculture.
Another study entitled «AI for Women in Aquaculture», led by Mutiat Mohammed Summit University, based in Offa, Kwara State, Nigeria, targets women in the aquaculture sector who have limited access to training, tools and markets. The study highlights a lack of a platform for coordinating efforts and disseminating information, as well as the limited adoption of artificial intelligence and Industry 4.0 technology, amongst other issues. The research will therefore adopt artificial intelligence techniques in aquaculture and ensure equity, diversity and gender inclusion, whilst minimising unintentional bias and providing numerous opportunities for women.
As for the study entitled «Digitalisation for Mama Mboga: Women’s Engagement and Inclusion in Agri-tech AI», led by Angella Ndaka, It targets women farmers and stakeholders in the agribusiness value chain. It is being carried out primarily in the Kiambu agricultural zone in Kenya, an area with high agricultural potential, and seeks to analyse the barriers to women’s digital inclusion, examine ways of incorporating women’s perspectives into the development and application of agricultural AI systems, and into the associated policy processes.
The circular economy presents a major challenge in Africa, which is why , Shamira AHMED, ‘’Data Economy Policy Hub’ has published a study on ’Responsible AI for Gender Equality in Africa’s Circular Economy«, which aims to explore the use of AI to reduce food waste at various stages of South Africa’s food supply chains.
In line with this approach, and more broadly speaking, Rebecca Ryakitimbo A researcher at @Core23lab in the Democratic Republic of the Congo and her team members are proposing a research project entitled «Integrating the gender dimension into AI: A Perspective from Francophone and Anglophone East Africa», which addresses the issue of gender inclusion in AI across the countries identified within the Anglophone (Tanzania, Kenya and Uganda) and Francophone East Africa (Rwanda, Burundi and the DRC). More specifically, the research will examine the barriers to the creation and use of sex-disaggregated data for AI, as well as gender gaps and biases in AI.
Walelign Tewabe Sewunetie, a professor at Debre Markos University (DMU), presented a project entitled «Natural Language Processing (NLP), Big Data Analytics, Human Data Mining», which aims to address the challenges posed by the language barrier between different local communities, as well as the issue of gender bias in machine translation datasets. The academic and his team propose to develop a machine translation prototype capable of detecting and mitigating gender bias in Ethiopia, particularly in sub-Saharan Africa.
In much the same vein, another study presented by Dr Joyce Nakatumba-Nabende from the Artificial Intelligence Laboratory at Makerere University in Uganda, entitled «Understanding gender bias in the development of artificial intelligence models in the African context», also tackles gender bias and the inclusivity of artificial intelligence tools on the African continent. The findings will be used to develop a framework and guidelines for mitigating gender bias in ASR systems through equity in data collection and model development.
This work is expected to lead to the development of a model governance framework to address the ethical and gender-related issues surrounding the data and algorithms on which ASR systems are based.
The diversity of African languages presents a range of challenges in Africa, which is why Natnael Tilahun, A computer scientist at AASTU University in Ethiopia also presented his study on «Diversity and gender equality in the AI ecosystem: An SLR of African Languages», which addresses the lack of resources for local African languages and proposes to examine the current state of representation of local African languages within the global AI ecosystem, particularly the underunder-representation of women and minorities in the AI ecosystem in Africa, which leads to a lack of diversity and inclusion.
In Kenya, for example, gender education and other initiatives aimed at ensuring gender equity, equality and inclusion remain a major challenge; that is why, Juliet Chebet Moso A lecturer at Dedan Kimathi University of Technology in Kenya presents a paper entitled «An artificial intelligence-based model for analysing gender inequality in STEM programmes and career prospects in Kenya». “The study specifically examines female students’ participation in STEM courses by investigating how gender inequality affects students’ placement and their perceptions of AI in STEM programmes and their potential career paths.”
It should be noted that all these teams selected as part of the call for proposals automatically become part of the GRAIN network.
It should be noted that the GRAIN network aims to function as a “space for collaboration”, bringing together local stakeholders with the necessary expertise – including for-profit organisations, universities, governments and research bodies – to foster self-sufficiency by building on existing capacities. Within this framework, the beneficiaries and members of the GRAIN consortium continued their work online on Tuesday 21 November to create a platform for exchange aimed at fostering a better understanding of gender equality in AI.
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