mlsanityData to 7 Oct 2026

Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence

arXiv 2007.04068 ↗First posted 8 Jul 2020cs.CY cs.AI cs.LGcited by 100

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Abstract (arXiv)

This paper explores the important role of critical science, and in particular of post-colonial and decolonial theories, in understanding and shaping the ongoing advances in artificial intelligence. Artificial Intelligence (AI) is viewed as amongst the technological advances that will reshape modern societies and their relations. Whilst the design and deployment of systems that continually adapt holds the promise of far-reaching positive change, they simultaneously pose significant risks, especially to already vulnerable peoples. Values and power are central to this discussion. Decolonial theories use historical hindsight to explain patterns of power that shape our intellectual, political, economic, and social world. By embedding a decolonial critical approach within its technical practice, AI communities can develop foresight and tactics that can better align research and technology development with established ethical principles, centring vulnerable peoples who continue to bear the brunt of negative impacts of innovation and scientific progress. We highlight problematic applications that are instances of coloniality, and using a decolonial lens, submit three tactics that can form a decolonial field of artificial intelligence: creating a critical technical practice of AI, seeking reverse tutelage and reverse pedagogies, and the renewal of affective and political communities. The years ahead will usher in a wave of new scientific breakthroughs and technologies driven by AI research, making it incumbent upon AI communities to strengthen the social contract through ethical foresight and the multiplicity of intellectual perspectives available to us; ultimately supporting future technologies that enable greater well-being, with the goal of beneficence and justice for all.

Key facts. Cited by 100 papers in the map (data through 7 Oct 2026). First posted on arXiv 8 Jul 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 17; 2022: 13; 2023: 23; 2024: 13; 2025: 18; 2026: 16.

100 papers.

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  1. 2021Scaling Language Models: Methods, Analysis & Insights from Training Gophercited by 1,199
  2. 2021Ethical and social risks of harm from Language Modelscited by 957
  3. 2022Challenges and Strategies in Cross-Cultural NLPcited by 216
  4. 2021Process for Adapting Language Models to Society (PALMS) with Values-Targeted Datasetscited by 179
  5. 2021The Values Encoded in Machine Learning Researchcited by 172
  6. 2021Expanding Explainability: Towards Social Transparency in AI systemscited by 124
  7. 2021Re-imagining Algorithmic Fairness in India and Beyondcited by 102
  8. 2023Evaluating the Social Impact of Generative AI Systems in Systems and Societycited by 91
  9. 2021Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needscited by 64
  10. 2023The Gradient of Generative AI Release: Methods and Considerationscited by 63
  11. 2021Assessing the Fairness of AI Systems: AI Practitioners' Processes, Challenges, and Needs for Supportcited by 61
  12. 2024AI Suggestions Homogenize Writing Toward Western Styles and Diminish Cultural Nuancescited by 59
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  1. 2023AI's Regimes of Representation: A Community-centered Study of Text-to-Image Models in South Asiacited by 54
  2. 2022Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Modelscited by 49
  3. 2023Charting the Sociotechnical Gap in Explainable AI: A Framework to Address the Gap in XAIcited by 33
  4. 2022Data Governance in the Age of Large-Scale Data-Driven Language Technologycited by 32
  5. 2021Envisioning Communities: A Participatory Approach Towards AI for Social Goodcited by 29
  6. 2024A Robot Walks into a Bar: Can Language Models Serve as Creativity Support Tools for Comedy? An Evaluation of LLMs' Humour Alignment with Comedianscited by 29
  7. 2022From plane crashes to algorithmic harm: applicability of safety engineering frameworks for responsible MLcited by 26
  8. 2023Factoring the Matrix of Domination: A Critical Review and Reimagination of Intersectionality in AI Fairnesscited by 26
  9. 2021Reliability Testing for Natural Language Processing Systemscited by 25
  10. 2024Do Generative AI Models Output Harm while Representing Non-Western Cultures: Evidence from A Community-Centered Approachcited by 25
  11. 2021A Sociotechnical View of Algorithmic Fairnesscited by 24
  12. 2022Rethinking Fairness: An Interdisciplinary Survey of Critiques of Hegemonic ML Fairness Approachescited by 23
  13. 2022Listening to Affected Communities to Define Extreme Speech: Dataset and Experimentscited by 21
  14. 2021Problematic Machine Behavior: A Systematic Literature Review of Algorithm Auditscited by 20
  15. 2023A Material Lens on Coloniality in NLPcited by 19
  16. 2023`It is currently hodgepodge'': Examining AI/ML Practitioners' Challenges during Co-production of Responsible AI Valuescited by 18
  17. 2024Holistic Safety and Responsibility Evaluations of Advanced AI Modelscited by 18
  18. 2024The 2024 Foundation Model Transparency Indexcited by 18
  19. 2023Explainability in AI Policies: A Critical Review of Communications, Reports, Regulations, and Standards in the EU, US, and UKcited by 13
  20. 2021Beyond "Fairness:" Structural (In)justice Lenses on AI for Educationcited by 12
  21. 2021Black Feminist Musings on Algorithmic Oppressioncited by 11
  22. 2022Metaethical Perspectives on 'Benchmarking' AI Ethicscited by 11
  23. 2023Going public: the role of public participation approaches in commercial AI labscited by 11
  24. 2022Subverting machines, fluctuating identities: Re-learning human categorizationcited by 10
  25. 2022Experimental Standards for Deep Learning in Natural Language Processing Researchcited by 9
  26. 2025LIVS: A Pluralistic Alignment Dataset for Inclusive Public Spacescited by 8
  27. 2023The Empty Signifier Problem: Towards Clearer Paradigms for Operationalising "Alignment" in Large Language Modelscited by 7
  28. 2021Generative Art Using Neural Visual Grammars and Dual Encoderscited by 6
  29. 2023Fairness and Sequential Decision Making: Limits, Lessons, and Opportunitiescited by 5
  30. 2023Towards Reliable Assessments of Demographic Disparities in Multi-Label Image Classifierscited by 5
  31. 2023Minimum Levels of Interpretability for Artificial Moral Agentscited by 5
  32. 2024The Case for Globalizing Fairness: A Mixed Methods Study on Colonialism, AI, and Health in Africacited by 5
  33. 2024Standard Language Ideology in AI-Generated Languagecited by 5
  34. 2025A taxonomy of epistemic injustice in the context of AI and the case for generative hermeneutical erasurecited by 5
  35. 2025Decentralising LLM Alignment: A Case for Context, Pluralism, and Participationcited by 5
  36. 2021Dutch Comfort: The limits of AI governance through municipal registerscited by 4
  37. 2022Global Performance Disparities Between English-Language Accents in Automatic Speech Recognitioncited by 4
  38. 2025Invisible Languages of the LLM Universecited by 4

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