CFP: AI & IKS Workshop

1st Call for papers – Topical Collection in the journal AI & Society

We invite papers for the Topical Collection on Indigenous Knowledge Systems and AI in AI & Society

Synopsis:

In the context of Indigenous knowledge systems and artificial intelligence (AI), AI has the ability to reshape how we understand and engage with knowledge across different domains. As a knowledge-making technology, AI must expand the boundaries of knowledge to include and respect Indigenous knowledge systems if it is to develop into a fair and equitable knowledge-making technology and field of research. Ignoring rich and diverse knowledge traditions not only hinders the decolonisation of AI but, moreover, without integrating Indigenous ways of knowing, the epistemological frameworks that guide AI development will remain incomplete and inadequate to address the complex ethical, social, and cultural dimensions that these technologies increasingly impact.

The aim of this topical collection is to interrogate the possibilities and limitations of the intersection of these two fields. AI technology can negatively impact Indigenous knowledge systems by leading to the erosion of cultural knowledge, especially when Indigenous information is digitised and disseminated without proper context or consent, risking misappropriation by non-Indigenous groups. It can also result in Indigenous persons’ loss of ownership and control of their own knowledge systems, as AI systems developed by institutions in the Global North may commodify Indigenous knowledge without proper collaboration. Data extraction is another concern, where AI’s reliance on large datasets, including Indigenous knowledge, can reinforce colonial patterns of extraction and exploitation. Additionally, AI systems trained on biased data can perpetuate harmful stereotypes about Indigenous peoples. However, Indigenous knowledge systems can significantly enhance AI development by bringing ethical and contextual sensitivity rooted in holistic worldviews. Their local and contextual expertise can contribute to solving real-world problems, such as environmental and resource management (as exemplified by recent work done by the Social Sciences and Humanities Research Council). Furthermore, incorporating Indigenous knowledge can lead to more inclusive AI systems that respect diverse worldviews, thus helping to train systems that could lead to more inclusive as opposed to biased outputs.

Topical Collection Themes:

Questions of interest include (but are not limited to):

·      How can Indigenous knowledge contribute to AI governance?

·      What are the current risks that AI, digital and emerging technologies pose to Indigenous knowledge?

·      What are the implications for Indigenous knowledge systems if Global North values and methodologies are prioritised in the construction of AI, digital and emerging technologies?

·      How can we implement strategies to preserve or encourage the use of Indigenous Knowledge Systems on digital platforms?

·      What kinds of social, epistemic, and political injustices are caused by the marginalisation of Indigenous Knowledge Systems in Technological Spaces? Do new issues surrounding questions of authorship in the arts arise in AI-mediated contexts? How might this affect Indigenous and Traditional Knowledge or artists?

·      Does the use of AI technology influence how a global audience views what art, knowledge or heritage is valuable to preserve?

·      How does algorithmic bias impact the curation, preservation, and archiving of Indigenous Knowledge?

·      How can AI technology and digital platforms impact authenticity and authorship issues in preserving art, heritage or the knowledge systems of Indigenous persons?

·      Why might the current epistemological framework(s) of AI remain incomplete or inadequate without integrating Indigenous ways of knowing?

·      How can Indigenous research methodologies be relevant to designing new or critiquing current AI and digital technologies?

·      How might industry leaders and academics in the field of AI expand the boundaries of digital knowledge to include and respect Indigenous Knowledge Systems?

·      What political, epistemic, social, psychological or artistic issues arise when prioritising Indigenous persons, knowledge, heritage or art to help foster the creation of fair and equitable knowledge-making technology?

·      How can the project of decolonisation of AI be strengthened or undermined by the inclusion or exclusion of Indigenous knowledge traditions?

We invite submissions that explore these research questions through various theoretical perspectives, such as critical data studies, digital humanities, archival studies, and cultural heritage studies. We welcome the use of diverse research methodologies, both qualitative and quantitative, including approaches from data and computer science. Contributions from government professionals and those in the Libraries, Archives, and Museums sectors are encouraged. Submissions from early-career academics and practitioners are also highly valued.

Important Dates:

Manuscript submission:                                                           1 June 2025

Review and editorial window:                                                  June 2025 – September 2025

Revised paper due:                                                                   1 October 2025

Publication date:                                                                      February 2026

Submission Formatting:

Authors must submit via the “Submit your manuscript” button on the journal webpage (https://link.springer.com/journal/146).

Authors can indicate during submission that their paper is intended for this Topical Collection.

The submission site will be open as of 1st April

Submissions will close automatically on the deadline (1st June 2025).

For inquiries, please contact [email protected].

Review

All papers will undergo the usual AI & Society double blind review.

Guest Editors:

Veli Mitova, Paige Benton and Dimpho Moletsane