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Decoloniality impact assessment for AI.

Damian Eke1, Ricardo Chavarriaga2, Bernd Stahl1

  • 1School of Computer Science, University of Nottingham, Nottingham, UK.

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|April 27, 2026
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Summary
This summary is machine-generated.

Current AI impact assessments (IAs) fail to address the "coloniality problem." We propose Decoloniality Impact Assessment (DIA) to ensure AI innovation is just, equitable, and respects diverse knowledge systems.

Keywords:
AIColonialityDecolonialityEthicsGlobal SouthImpact assessmentResponsibility

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Area of Science:

  • Artificial Intelligence Ethics
  • Sociotechnical Systems Analysis
  • Global Development Studies

Background:

  • Numerous AI impact assessments (IAs) have been developed by global organizations to ensure responsible AI.
  • Existing IAs, primarily from Global North frameworks, neglect Global South perspectives and perpetuate inequalities.
  • A critical review reveals these IAs fail to address fundamental issues of power, knowledge valuation, and benefit distribution in AI innovation.

Purpose of the Study:

  • To critically review existing AI impact assessments and identify their limitations regarding coloniality.
  • To propose a novel approach, Decoloniality Impact Assessment (DIA), to address the "coloniality problem" in AI.
  • To advocate for integrating DIA into the AI innovation lifecycle to promote justice and sovereignty.

Main Methods:

  • Critical review of current AI impact assessment frameworks and literature.
  • Analysis of AI innovation lifecycle stages to identify manifestations of coloniality.
  • Conceptual development of Decoloniality Impact Assessment (DIA) as a critical evaluative approach.

Main Results:

  • Current AI IAs are insufficient as they overlook the "coloniality problem" rooted in Global North frameworks.
  • AI development practices risk perpetuating inequalities by neglecting Global South perspectives and extractive data logic.
  • DIA offers a context-sensitive approach to assess AI's colonial legacies and power asymmetries.

Conclusions:

  • Decoloniality Impact Assessment (DIA) is essential for addressing structural inequalities and epistemic injustices in AI.
  • DIA must be integrated throughout the AI innovation lifecycle, from ideation to deployment.
  • Reframing AI innovation through DIA promotes technological futures centered on justice, pluriversality, and sovereignty.