Statement: Artificial Intelligence offers meaningful applications for decolonial research methodologies.

How?

It is well-documented that AI can be a helpful tool in identifying biases, tone, and other patterns in writing. Beyond some of those fundamental tools, however, GenAI can meaningfully support engagement with and research governed by decolonial and other ethical future-oriented methodologies.

Researching

• Help locate and navigate databases and archives from the Global South.
• Identify what the archive omits and the voices or contributors excluded from formal records. Interrogating archival silences can surface bias and create space to critique the archive itself.
• Surface articles, commentary, community writing, and other knowledge from nontraditional contributors, including those from the Global Majority.
• Translate and produce multilingual content that cultivates a research culture of exchange and actively interrupts epistemic injustice in Eurocentric academic-speak norms and hierarchies. This may also help reduce overtly extractive methods (ex. interviewing participants using a translator, then writing up final research in a language that is foreign to those same participants). Real-time transcription can alleviate reliance on external translators and reduce meaning lost or distorted through mediation.
• Identify gaps in research.
• Explore impact and relevance of research on underserved communities.
• Produce graphs and visual content to make the data more interactive and engaging for both researcher and reader.
• Serve as a reflective ethics sounding board and partner; GenAI can be used to help researchers develop ethics plans and provide a range of potential alternative views and critiques of their ethics. All informed and benchmarked by institutional requirements, scholarship, and researchers’ positionality and methodologies.
• As a research and writing partner, AI offers a powerful reflectivity tool that can help researchers transparently engage with their ideas and their work.

Engagement and Interaction

• Develop accessible research and scholarly thinking for the masses.
• Create interactive multimedia (websites, zines, dynamic presentations, books, etc.) that is accessible and inclusive.
• Assist researchers in proactively updating research material; acting as an automated tool for systematic reviews. This helps educators and scholars think more proactively and can enrich classroom discussion.
• Build community-centered and people-focused archives that champion civic participation in research and knowledge making.
• Make research output more dynamic and tailored to specific communities and audiences.
• Email drafting and correspondence.

Accessibility

• Decolonial methodologies are concerned with dismantling Eurocentric and Western systems that actively oppress the bodies, knowledge, and voices of people traditionally excluded, including those from the Global South, disabled, and neurodivergent, and, of course, indigenous communities’ whose knowledge and approach to knowledge production has been long dismissed by the academy. With that in mind, making content that is accessible and producing accessible learning journeys and knowledge production processes is critical. In general, machine learning may aid researchers, educators, and scholars with this in mind:
  • Develop accessible content.
    • GenAI to create content that is friendly for the visually impaired, dyslexic readers, and learners who benefit from clearer and more accessible language (not simply challenging Eurocentric academic-speak, but fostering a culture of accessible and people-oriented research).
    • Examples:
      • Allow real-time definitions or summaries of sections of text
      • Including estimated reading time required.
      • Adapt web content to improve readability and interactivity, especially for readers who find dynamic and interactive content more engaging.
  • Make learning and research more fun, accessible, and inclusive.
    • Formal scholar or curious readers and researchers alike, learning should be meaningfully engaging and joyful for all. GenAI may be used to support cognitive scaffolding, aiding those with memory issues, individuals who struggle with academic-speak, aid neurodivergent scholars, and aid support reducing cognitive load.
    • Examples:
      • Assist in outline development and proofreading.
      • Support academic writing. Draft writing schedules, improve accessibility.
      • Act as a thinking partner, similarly to how a peer might edit or proofread a peer’s work.
      • Serve as a knowledge base, reminding writers of gaps in their drafts.
      • Decluttering user notes and working to identify patterns and user logic.
      • Act as a transparency tool. Demonstrate to researchers where their argument or logic is neither clear nor transparent to readers.