Whose Evidence Counts? AI, Trust, and Equitable Evaluation in the Global South

Webinar | Online

About the Event

As artificial intelligence (AI) increasingly shapes monitoring and evaluation systems, it is transforming how evidence is generated, interpreted, and used. While AI offers opportunities for efficiency and real-time insights, it also raises critical concerns around bias, exclusion, and trust, particularly in Global South contexts where data systems remain uneven and historically shaped by external paradigms.
This session brings together contributors to the books ‘Equitable Evaluation: Voices from the Global South; and ‘Evaluation as a Mechanism to Foster an Equitable Society in the Global South’, alongside practitioners and emerging evaluators, to examine how evaluation can remain equitable and trustworthy in the age of AI. Drawing on practical experiences from South Africa, Tanzania, and Uganda, the discussion will explore how potential misalignments between policy, data systems, and lived realities can undermine trust in evidence, and how these risks may be further amplified by AI-enabled approaches.
Grounded in Made in Africa Evaluation (MAE), the session will interrogate whose knowledge is prioritised in AI-driven evaluation systems and advance practical recommendations for integrating AI in ways that are ethical, inclusive, and context-responsive.
By bridging Global South scholarship with practitioner experience and emerging evaluator perspectives, the session contributes to global dialogue on building evaluation systems that are both technologically robust and socially just.
Objectives:
-Examine and discuss how AI is reshaping evidence generation and use in evaluation
-Interrogate risks of bias, exclusion, and trust deficits in AI-driven systems
-Explore Made in Africa Evaluation as a framework for ethical and context-responsive AI integration
-Identify practical strategies for building trustworthy and equitable evaluation systems

Speakers

名称 标题 Biography
Dr Zacharia Grand M&E specialist Dr. Zacharia Sosten Grand, PhD. an Emerging Evaluators (EE) Programme mentor and experienced Monitoring & Evaluation and Governance Specialist with over 18 years of experience across Africa. He is currently a Postdoctoral Researcher at the University of Johannesburg, with expertise spanning public health, climate change, gender analysis, and policy research. His work is grounded in strengthening evaluation systems and advancing evidence-based decision-making. As a mentor to Desne Corneluis (FirstRand Foundation), Dr. Grand is committed to guiding and supporting the next generation of evaluators. We are proud to have him as part of our mentorship community.
Dr Nozipho Ngwabi Senior Project Manager: Research and Evaluation Dr Nozipho Ngwabi is a Senior Research Manager at the Bertha Centre, University of Cape Town, with over a decade of experience as a researcher, academic, and Monitoring and Evaluation (M&E) practitioner. She holds an MA and MPhil (cum laude) and is completing her PhD in Evaluation Studies. Nozipho has developed M&E curricula, supervised postgraduate research, and conducted evaluations globally across sectors, including social development, health, education, and financial development.
Jason Bygate Development and Innovation Specialist Jason Bygate is a seasoned consultant specialising in the development sector and public service arena. He has secured and managed large contract delivery across a variety of sectors including healthcare, social development, youth services, social enterprise, ICT for development, entrepreneurship and logistics. These project implementations have included deployments in multiple countries: South Africa, China, Zambia, Zimbabwe, Rwanda, Tanzania, Ghana, Namibia and Guatemala. As a dynamic self-starter with over 20 years' experience, Jason has come to understand the importance of data-led decision making, value-driven relationships and an agile approach to business.

Topics and Themes

Evaluators Evaluation users Decision makers VOPEs / Evaluation networks Yearly Theme: Evaluation, Evidence and Trust in the Age of AI

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