Videos
Playlist
-
Training Workshop on AI and Gender – video
See more... -
A gender-sensitive approach to research into the development and deployment of responsible AI in Africa
See more...Moderated by Ernest Mwebaze, Executive Director of Sunbird AI, Uganda, the panel featured the following speakers: Nokuthula Olorunju, lawyer and researcher at Research ICT Africa, South Africa; Dr Adekemi Omutubora, Senior Lecturer at the University of Lagos, Nigeria; Adedeji Adeniran, Director of Research at CSEA Nigeria; Caitlin Kraft-Bruchmann – CEO and Founder of Women at the Table.
-
NOlayinka Yusuf: AI for women in agriculture – AI4WIAew video
See more...Against the backdrop of worsening climate change, which leaves African farmers vulnerable to the adverse effects of erratic weather due to their heavy reliance on rain-fed agriculture, this study aims to propose an artificial intelligence-based solution to address this threat, particularly as it affects women farmers, who play a pivotal role in production and reproduction within rural households in sub-Saharan Africa. More specifically, the study seeks to adapt existing AI-based solutions to address climate-related issues, particularly the erratic weather conditions faced by women farmers, and to formulate data-driven policy recommendations on how women farmers can be empowered to make the best use of appropriate and responsible AI-based solutions. The project will be extremely useful in building the capacity of women farmers as recognised drivers of the socio-economic status of rural households and will contribute to the achievement of the Sustainable Development Goals aimed at promoting gender equality, the eradication of poverty and the eradication of hunger (Sustainable Development Goals 5, 1 and 2 respectively).
-
New vDr Moso: An AI-based model for analysing gender inequality in STEM programmes and career projections
See more...In this fascinating interview, Juliet Chebet Moso, a senior lecturer at Dedan Kimathi University of Technology, takes us on a journey into the world of science, technology, engineering and mathematics in Kenya. She sheds light on the challenges women face in these fields and the innovative solutions she is proposing through the use of artificial intelligence.
-
Understanding gender biases in the development of automatic speech recognition models in the African context
See more...Machine learning technologies such as automatic speech recognition systems, language models and machine translation systems are developed to operate in environments where gender and other forms of bias and discrimination are present.
These biases are present in the datasets used to train the models and in the choices made regarding machine learning models. The machine learning models that are developed ultimately reinforce the biases embedded in the training data.
This research will focus on a data-driven approach to conduct a scoping study aimed at gaining a deeper understanding of 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 fairness in data collection and model development.
Finally, this work will develop a model governance framework to address ethical and gender issues relating to the data and algorithms on which ASR systems are based.
-
Angella Ndaka: Digitalisation for Mama Mboga in Kenya – New video
See more...Angella Ndaka: Digitalisation for Mama Mboga: Are women’s engagement and inclusion in agri-tech AI important? The experiences of women in Kenya’s informal agricultural sector
Project objective: The project will identify and highlight the barriers to women’s digital inclusion and examine ways of incorporating women’s perspectives into the development and implementation of agricultural AI systems, as well as into the associated policy processes.
-
New video: Rebecca Ryakitimbo: Gendering AI: A perspective from Francophone and Anglophone East Africa
See more...The project aims to examine the integration of a gender perspective into AI in the countries identified within the East African Community, namely English-speaking East Africa (Tanzania, Kenya and Uganda) and French-speaking East Africa (Rwanda, Burundi and the DRC).
-
NewBeakal Gizachew: Diversity and Gender Equity in the AI Ecosystem: A Systematic Literature Review of African Languages (video)
See more...This project aims to examine the current state of representation of local African languages within the global AI ecosystem, to identify the challenges and to explore potential opportunities for AI in Africa.
Artificial intelligence has radically transformed the way businesses operate across all sectors, and natural language processing plays a crucial role in representing identity, observations and ideas, from high-level theories to the day-to-day functions of machines. Many digital organisations have successfully collected data in written, spoken and visual forms. However, most local African languages lack sufficient resources, preventing Africans from capitalising on the opportunities offered by AI. For Africa to participate in and benefit from the global AI ecosystem, policy-makers must take decisive action in the areas of human resource development, private sector engagement and the promotion of innovation. This study aims to examine the current state of representation of African local languages within the global AI ecosystem, to identify the challenges and to explore potential opportunities for AI in Africa.
-
NeShamira Ahmed: Responsible AI for Gender Equality in Africa’s Circular Economy – a video
See more...The project aims to investigate the use of artificial intelligence to reduce food waste at various stages of the food supply chain in South Africa.
Project summary
Food waste is a systemic problem that occurs at every stage of the food supply chain, from the farm and the field to the plate. Not only does it contribute to food insecurity, poverty and inequality in South Africa, but it also exacerbates climate change, pollution and biodiversity loss. There are proposals suggesting that the deployment of data-driven systems, such as artificial intelligence (AI), can boost resource efficiency (RE) and support the transition to systems that minimise food waste at various points in the food supply chain. However, most of these proposals are merely socio-technical imaginaries from the Global North and do not shed light on the risks and harms associated with the deployment of data-driven technologies in the Global South and/or within existing inequitable ecosystems that discriminate against women. By actively incorporating an intersectional gender perspective, this case study will explore the use of AI to reduce food waste at various points along food supply chains in South Africa.
-
NeWalelign Tewabe: Multilingual neural machine translation for low-resource languages with gender … (with video)
See more...Walelign Tewabe: Neural machine translation for low-resource languages with detection and mitigation of gender bias: English–Amharic–Tigrinya–Ouomigna
The overall aim of the project is to develop a prototype multilingual machine translation system capable of detecting and mitigating gender bias in low-resource languages.
Project summary: Artificial intelligence systems replicate and reinforce existing social biases, a problem that is now widely recognised and studied. However, current research into gender bias in natural language processing (NLP) suggests a solution.
Gender bias in AI applications such as machine translation (MT) is common and must be carefully taken into account when developing these applications.
In this project, we propose to develop a machine translation prototype capable of detecting and mitigating gender bias. As the target languages – Amharic, Ge’ez and Awign – fall into the category of languages with limited resources, we will use transfer learning to draw on languages with abundant resources, such as English.
The project is relevant and timely in addressing the challenges posed by language barriers between different local communities, as well as the issue of gender bias in machine translation datasets.
Successful implementation of the project could help to address these challenges both within and outside Ethiopia, particularly in sub-Saharan Africa.
-
Dr Taliha Folorunso: Artificial intelligence for women in aquaculture 'AI4WA'
See more...Aquaculture plays an indispensable role in the livelihoods of the entire global population, from its various levels of production to its significant contributions to the economy. However, the aquaculture value chain is characterised by significant gender disparities, with women being primarily involved in post-harvest activities, which are generally less profitable. Men, on the other hand, tend to dominate fishing activities, which are generally more lucrative. The adoption of artificial intelligence techniques in aquaculture will ensure equity, diversity and gender inclusion whilst minimising unintentional bias and providing numerous opportunities for women. The project will therefore focus on evaluating and analysing the applications of artificial intelligence techniques in aquaculture systems, and on a critical gender analysis of the use of artificial intelligence in aquaculture systems, through extensive data collection, field studies, a gap analysis and engagement with stakeholders and policy-makers in order to develop innovative recommendations.
-
Launch of the GRAIN network video
See more...Following more than a year of preparation and organisation, the Grain network has been officially launched. The launch took place on Monday 20 November 2023, during a webinar held on the Zoom platform.
-
New viGRAIN WORKSHOP KAMAPLA, UGANDAdeo
See more...Highlights from the GRAIN Members’ Workshop, held from 16 to 18 April 2024 in Kampala, Uganda.
-
Virtual debate on 'How can we get more women involved in STEM?'
See more...The virtual meeting will provide an opportunity to exchange views with network members and other stakeholders in STEM (Science, Technology, Engineering and Mathematics) on strategies and opportunities to promote women’s involvement in STEM, and to discuss ways to strengthen their inclusion and active participation.
Specifically, it will assess the educational and career opportunities in STEM fields for women in Africa; identify successful initiatives and programmes that have attracted women to STEM and understand the key factors behind their success; explore the specific barriers and challenges that women face in their educational and career pathways within STEM; and formulate strategic recommendations for policymakers, the business sector and civil society to support and encourage women to pursue careers in STEM.
FR 
EN 
