About
The Empowering African Voices in AI: Data, Models, and Innovation workshop will take place on September 6, 2024 at the Amadou Mahtar Mbow University (UAM) in Dakar, Senegal as part of Deep Learning Indaba 2024.
The workshop is structured to explore both the human-centric and technical aspects of AI, particularly in under-resourced communities within the Global South. It will delve into critical considerations such as data generation, annotation, legal frameworks, and sharing protocols, emphasising culturally contextual datasets and the governance frameworks that support them. Furthermore, the workshop will address sharing AI models and datasets through various licensing frameworks, emphasizing ethical data collection, community engagement, and the management of AI innovations in a manner that respects local cultures and languages.
Abstract
The transformative potential of AI and ML is immense, reshaping sectors from healthcare to finance. However, the pace of AI development and its benefits are not uniformly distributed, with under-resourced communities, particularly those historically disadvantaged, experiencing a lack of access to the rewards of AI. This disparity highlights the need for responsible, ethical, and community-centric approaches to AI development that prioritize local needs, cultures, and languages. This workshop aims to address these disparities by focusing on the human aspects of AI. It seeks to move beyond the technicalities of algorithms and computation to delve into the foundational elements of AI, the data itself. Doing so emphasizes the importance of data practices that are efficient, ethical, culturally aware, and inclusive. Participants will engage in discussions and practical sessions that explore data generation, annotation, legal frameworks, and sharing protocols. Special attention will be given to creating culturally contextual datasets that reflect African communities’ linguistic and societal nuisances. The workshop will also cover critical topics such as data governance, synthetic data implications, and cross-cultural data safety challenges and opportunities. The goal is to equip researchers, ML practitioners, and policymakers with the knowledge and skills necessary to implement AI projects that are ethical, inclusive, and impactful, thereby fostering an AI ecosystem that truly benefits all, especially those in marginalized communities. Through this endeavour, the workshop will contribute to shaping a future where AI development in Africa is driven by African voices and directly addresses the continent’s unique challenges and aspirations.
Target Audience
This workshop is designed for AI researchers and enthusiasts, ML practitioners, data scientists, and legal experts engaged in or interested in responsible AI development within African contexts. It will also be valuable for stakeholders from global data training companies, open-source data benchmark consortia, and technology firms operating in Africa.
Workshop Objectives & Goals
- To equip participants with skills in efficient AI data collection and ethical data utilization.
- To discuss and provide recommendations on proprietary, open, and open-source licensing for sharing NLP datasets and AI models.
- To foster a deeper understanding of AI policy, data rights, and the ethical use of AI in Africa.
- To engage participants in creating a multilingual, augmented dataset that reflects diverse African languages and contexts.
- To facilitate discussions on building sustainable economies with data and leveraging synthetic data creation.
Detailed Full-Day Workshop Agenda
Time | Agenda | Speaker |
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08:00 AM - 08:15 AM | Opening remarks: Brief introduction, overview of the workshop's goals, and what participants can expect throughout the day | Chris Emezue |
08:15 AM - 08:50 AM | Keynote Talk from Meta | - |
08:50 AM - 10:20 AM | Discussion & Tutorial: Navigating Licensing for AI Innovation in Africa. In this session, we will explore the role of licensing in the sharing and development of AI resources across Africa. Participants will be introduced to various types of licenses for AI datasets and models, with practical guidance on how to choose the most suitable license for different projects and cultural contexts. Whether you’re developing open-source tools or proprietary models, this tutorial will equip you with the knowledge to navigate the complex landscape of AI licensing and foster innovation responsibly. |
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10:20 AM - 10:30 AM | Mental Exercise / Reflections | - |
10:30 AM - 11:00 AM | Coffee Break | - |
11:00 AM - 12:00 PM | Panel Discussion: Ethical AI - Balancing Innovation and Data Rights in Africa |
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12:00 PM - 12:30 PM | Invited Talk: Data Practices for AI Development: Building Sustainable Models | Dr. Lillian Wanzare |
12:30 PM - 2:00 PM | Lunch Break | - |
02:00 PM - 03:00 PM | Immersive Activity: Creating |
Ndapewa Onyothi (Wilhelmina) Nekoto |
03:00 PM - 03:25 PM | Invited Talk: Low Resource Language Data Challenges at Meta | Aisha Iqbal |
03:25 PM - 03:45 PM | Behind the Research: Author Insights in 5 Minutes | - |
03:45 PM - 03:40 PM | Certificate Last Check-in, Feedback, and Wrap-Up | - |
Expected Outcomes
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Enhanced Understanding of Ethical AI Practices: Participants will gain a comprehensive grasp of responsible AI practices, focusing on ethical data collection and management.
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Skills in Data Collection and Utilization: Attendees will learn and apply essential skills in data handling and ethical usage, including creating a culturally contextual, multilingual dataset.
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Legal and Licensing Framework Insights: The workshop will elucidate various licensing options for AI development, helping attendees navigate legalities and strategic considerations in the African context.
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Creation of Culturally Relevant AI Resources: Participants will contribute to developing a novel dataset, promoting inclusivity in AI technologies.
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Collaborative Network Building: The event will connect researchers, practitioners, and experts, fostering collaborations that may lead to future AI innovations.
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Comprehensive AI Lifecycle Awareness: Attendees will acquire a holistic view of the AI data lifecycle, enhancing project management and decision-making.
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Strategic Guidance for AI Projects: Invited talks and discussions will offer guidance on managing AI projects effectively within legal and ethical frameworks.
Organizing Committee
- Chris Emezue, Lanfrica Labs.
- Dr. Chijioke Okorie, Data Science Law Lab, University of Pretoria
- Dr. Sarah Luger, ML Commons and Consumer Reports
- Dr. Melissa Omino, Centre for Intellectual Property and IT Law, Strathmore University
- Jade Newton, NLP Data and Business Consultant
- Florence Ogonjo, Centre for Intellectual Property and IT Law, Strathmore University
- Catriona Anyango, Centre for Intellectual Property and IT Law, Strathmore University
Invited Speakers
- Ndapewa Onyothi Wilhelmina Nekoto, Namibia/Masakhane
- Dr. Chinasa T. Okolo, Brookings Institution
- Balkissa Ide Siddo, Meta
- Leonida Mutuku, LDRI
- Dr. Lilian Wanzare, Maseno University
- Dr. Ololade Shyllon, Meta
- Prof. Vukosi Marivate, University of Pretoria and LelapaAI