Istiqlal-e-Marifat: An Iqbalian Framework for Epistemic Justice in Artificial Intelligence

Abstract

When AI systems are trained on datasets drawn predominantly from Western, English-speaking, secular-rationalist corpora, they do not merely encode information, they absorb one civilization's answers to the most fundamental questions of moral life: what constitutes a good life, what obligations bind human beings to one another, and how human experience is narrated and valued. We argue that this process constitutes an epistemic displacement rather than a mere problem of data representation. To address this problem philosophically, we introduce “Istiqlal-e-Marifat”, sovereignty of deep knowing, as a novel philosophical concept derived from the thought of Allama Muhammad Iqbal. Using a conceptual and interpretive methodology, we reconstruct this principle from three dimensions of Iqbal's framework: the dynamism of Khudi at the civilizational level, his critique of stagnant and borrowed thought, and his affirmation of Eastern and Islamic intellectual traditions as bearers of irreducible epistemic resources. We apply this framework to three structural mechanisms of coded morality in AI, reinforcement learning from human feedback, tokenization reduction, and model collapse, showing how each enacts precisely the form of epistemic displacement Iqbal diagnosed. We find that Istiqlal-e-Marifat yields three normative implications: AI training must preserve epistemic structures rather than merely diversify data, governance must position communities as active epistemic partners rather than data sources, and evaluation must adopt moral benchmarks drawn from plural traditions rather than dominant world-models alone.