Deep Learning Indaba 2024 Workshop
This workshop explores the ethical, safe, and innovative application of artificial intelligence, focusing on human-centered approaches. Participants will engage in expert-led sessions, interactive discussions, and collaborative activities, addressing both established and emerging challenges within AI. Focusing on the Global South, the workshop aims to share innovative solutions, critically analyze methodologies, and foster impactful collaborations across academia and industry. Our sessions will stimulate discussions on controversial and emerging AI topics and promote new partnerships, shaping future research and practice in AI Safety.
This workshop is designed for AI researchers and enthusiasts, ML practitioners, data scientists, and legal experts engaged in or interested in AI Safety and 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.
The exact day (September 6 or 7, 2024) is TBD
This workshop is the first in the series "Centering Humans in a Safe AI Future" that covers the following topics and subtopics:
Discuss the principles and practices that ensure AI systems are designed and deployed ethically, including transparency, accountability, and the impact on societal norms. Consider weaknesses of existing Agile methodologies in respect to more accurate persona-building for new AI markets.
Explore the development and enforcement of safety protocols to prevent unintended consequences of AI technologies, focusing on physical, psychological, and data security aspects. Share best practice and methodologies used by existing regulated domains such as finance and aviation.
Examine new interfaces and interaction models between humans and AI systems that enhance usability and accessibility while fostering positive human outcomes. Real innovation comes from envisioning a different, better future for the planet where AI works for humans, not the other way around.
Address the challenges of bias in AI algorithms and data sets. Discuss methodologies for designing fairness into systems and strategies for ongoing monitoring and mitigation. Ideate on fairness measures that align with community needs and priorities.
Delve into cutting-edge research and debates within AI, including the potential for AI in decision-making processes, the future of autonomous agents, and ethical considerations of advanced AI capabilities. Weigh the costs and benefits of more work automation with the commodification of the previously personal via generative AI, including languages, images and cultures.