Towards Ethical and Responsible AI Perspectives from Postcolonial Contexts

This thesis critically explores the ethical challenges and opportunities that arise from artificial intelligence (AI) development in postcolonial contexts, explicitly focusing on West Africa. Although the global conversation surrounding AI ethics has expanded significantly, the development of AI continues to be shaped mainly by Euro-American perspectives. These perspectives frequently neglect the intricate historical, structural, and epistemic factors that influence the adoption and integration of technology within postcolonial contexts. This oversight raises important questions about the inclusivity and comprehensiveness of ethical considerations in AI development and deployment, especially in regions where colonial legacies continue to influence technological frameworks and societal structures. Through a thesis-by-publication model, this research advances a decolonial understanding of AI ethics by combining a systematic literature review, an empirical investigation, and the development of a normative conceptual framework. The first paper presents a systematic review of 50 peer-reviewed studies on ethical AI in postcolonial contexts. Employing postcolonial theory, it identifies three interrelated dynamics: structural dependency, algorithmic colonialism, and epistemic erasure. It shows how global AI ethics frameworks marginalise local knowledge while reinforcing infrastructural and political-economic asymmetries. This review underscores the urgent need for contextually responsive and pluriversal approaches to AI governance, which can better address AI development's unique challenges and opportunities in postcolonial contexts. The second paper draws on 45 semi-structured interviews and one focus group with AI developers in Nigeria and Ghana to examine how ethical challenges are experienced in practice. The findings reveal patterns of structural domination, digital and data colonisation, technological mimicry, and limited representation. These dynamics highlight how AI development reproduces historical forms of dependency, labour exploitation, and epistemic marginalisation, while also surfacing forms of resistance and aspirations for decolonial alternatives. The third paper introduces the EquiAI Framework, a decolonial and contextually responsive model for ethical AI development. Being grounded in postcolonial and decolonial theory, and informed by empirical insights, the framework advances four core constructs: coloniality of power and knowledge, algorithmic colonialism, epistemic disobedience, and relational ethics. It articulates the principles of inclusivity, intersectionality, and epistemic justice, supported by structural pillars such as participatory governance, data sovereignty, and adaptive implementation. The EquiAI Framework offers theoretical and practical guidance for equitable AI development in postcolonial societies. These three studies contribute substantially to information systems scholarship by reframing AI ethics beyond universalist paradigms and centring the political economy, lived realities, and epistemic diversity of postcolonial contexts. The thesis contends that developing equitable AI is not merely an objective but a moral obligation. It calls for dismantling structural dependencies, a resistance to algorithmic colonialism, and the adoption of decolonial, participatory, and contextually relevant governance models that resonate with the values and knowledge of local communities.