This article develops the second stage of the algorithmic colonialism framework by distinguishing data colonialism from algorithmic colonialism. Data colonialism explains the extraction of human life as data. Algorithmic colonialism explains what can happen after extraction: the conversion of data into systems of prediction, behavioural steering, social classification, epistemic filtering, dependency, and identity capture. The central argument is that the contemporary colonial frontier is not only land, labour, or raw materials, but increasingly the behavioural and identity structure of the human being. Artificial intelligence, platform infrastructures, recommendation systems, predictive analytics, biometric technologies, automated governance, and digital dependency do not merely observe society. Under conditions of unequal power, they may participate in organising attention, shaping preference, ranking visibility, directing behaviour, and mediating the conditions through which individuals and communities understand themselves. The paper builds on debates around digital colonialism, data colonialism, surveillance capitalism, the colonial matrix of AI power, Indigenous data sovereignty, linguistic marginalisation, and global AI governance. It extends these debates through the IAAP framework, Identity in the Age of Algorithmic Power, which analyses identity capture across four domains: memory, emotion, choice, and behaviour. The paper argues that decolonising AI requires more than data protection, ethical principles, or technological inclusion. It also requires protection of human agency, cultural memory, epistemic autonomy, behavioural freedom, and the capacity of societies to shape their own digital futures.
Osama S Qatrani (Sun,) studied this question.