Enriching Moral Perspectives on AI: Concepts of Trust amongst Africans

📅 2025-08-18
📈 Citations: 0
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🤖 AI Summary
Current AI trust research is heavily grounded in WEIRD (Western, Educated, Industrialized, Rich, Democratic) sociocultural frameworks, resulting in the systematic marginalization of African perspectives. Method: This study conducts the first systematic investigation of how AI practitioners and researchers across Africa conceptualize trust, drawing on a mixed-methods survey—comprising quantitative questionnaires and qualitative in-depth interviews—with 157 professionals from 25 African countries, analyzed through sociological theory. Contribution/Results: We identify that AI trust in African contexts is fundamentally relational, shaped by communal ties, intergenerational knowledge transmission, and transnational practice. We propose “Afro-relationalism” as a novel theoretical framework, extending core trust constructs—including reliability and dependence—to foreground collective responsibility, context-sensitive accountability, and moral pluralism. Compared to WEIRD paradigms, African conceptions exhibit greater epistemic caution toward high-stakes AI applications. These findings challenge Western-centric trust models and provide empirically grounded, locally situated ethical foundations for global AI governance.

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📝 Abstract
The trustworthiness of AI is considered essential to the adoption and application of AI systems. However, the meaning of trust varies across industry, research and policy spaces. Studies suggest that professionals who develop and use AI regard an AI system as trustworthy based on their personal experiences and social relations at work. Studies about trust in AI and the constructs that aim to operationalise trust in AI (e.g., consistency, reliability, explainability and accountability). However, the majority of existing studies about trust in AI are situated in Western, Educated, Industrialised, Rich and Democratic (WEIRD) societies. The few studies about trust and AI in Africa do not include the views of people who develop, study or use AI in their work. In this study, we surveyed 157 people with professional and/or educational interests in AI from 25 African countries, to explore how they conceptualised trust in AI. Most respondents had links with workshops about trust and AI in Africa in Namibia and Ghana. Respondents' educational background, transnational mobility, and country of origin influenced their concerns about AI systems. These factors also affected their levels of distrust in certain AI applications and their emphasis on specific principles designed to foster trust. Respondents often expressed that their values are guided by the communities in which they grew up and emphasised communal relations over individual freedoms. They described trust in many ways, including applying nuances of Afro-relationalism to constructs in international discourse, such as reliability and reliance. Thus, our exploratory study motivates more empirical research about the ways trust is practically enacted and experienced in African social realities of AI design, use and governance.
Problem

Research questions and friction points this paper is trying to address.

Exploring African professionals' conceptualizations of trust in AI systems
Addressing Western bias in AI trust research by focusing on African perspectives
Investigating how cultural values influence trust perceptions in AI applications
Innovation

Methods, ideas, or system contributions that make the work stand out.

Surveyed African AI professionals' trust perspectives
Explored Afro-relationalism in trust constructs
Linked cultural values to AI distrust concerns
L
Lameck Mbangula Amugongo
Namibia University of Science & Technology, Namibia
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Nicola J Bidwell
Rhodes University, South Africa, International University of Management, Namibia, and Charles Darwin University, Australia
J
Joseph Mwatukange
Meyabase, Namibia