Thea Pitman

It is noticeable that many of the voices critiquing AI from a decolonial and/or Indigenous perspective in an Anglophone settler (post)colonial context are those of artists. At the ‘Indigenous Protocol for Artificial Intelligence’ residency organised by Jason Edward Lewis and colleagues and held in Honolulu in 2020, although the explicit focus of the workshop was not specifically on the creation of art, a significant number of the people present were artists or designers, working across various different media, including Lewis himself, alongside Kite, Skawennati (Kanien’kehá:ka [Mohawk]), Scott Benesiinaabandan (Anishinaabe), Michelle Brown (Diné [Navajo]), Angie Abdilla (Palawa) and others. This meant that their examples and debates very much reflected artists’ perspectives.

This involvement of artists in the theorisation of Indigenous AI coincides with the arguments made by some of those critiquing the representation of race in generative AI, in the art world and the field of visual culture more generally, as mentioned in Chapter 1, who also turn to racially minoritised artists to show the way forward. For example, Michele Elam, in her article, ‘Signs Taken for Wonders: AI, Art, and the Matter of Race’ (2023), argues that

Instead of asking artists to adapt to the world models and pedagogies informing technological training – which, as with any education, is not simply the neutral acquisition of skills but an inculcation to very particular ways of thinking and doing – industry might do well to adapt to the broader vernacular cultural practices and techne of marginalized Black, Latinx, and Indigenous communities. Doing so might shift conversation in the tech industry from simply mitigating harm or liability from the differentially negative impact of technologies on these communities. Rather, it would require a mindset in which they are recognized as equal partners, cultural producers of knowledge(s), as the longtime makers, not just the recipients and consumers, of technologies. (245)

She concludes, as noted previously, by flagging ‘AI artist-technologists, especially those of color’ as those best suited to ‘reimagine’ AI and its impact on society (254).

Similarly, in a report stemming from an artists’ residency hosted by the NGO Salzburg Global in 2024 and dedicated to ‘Creating Futures: Art and AI for Tomorrow’s Narratives’, the authors argue that, ‘With their ability to work critically with technology, artists play a key role in seeking out AI’s flaws, inaccuracies, and limitations, as well as questioning the applications of technology across society’, and, furthermore, that

It is vital that all artists are able to explore these [new tools] in the global arena of multiple cultures and ways of seeing the world. To achieve that, we need to increase the levels of AI literacy and engage new and experienced generations of artists, underrepresented groups and Indigenous communities, so that everyone is able to share their perspectives authentically and make their mark in AI development. (Elliott 2024)

Here, their argument in relation to ‘underrepresented groups and Indigenous communities’ is more based on inclusivity in contrast with Elam’s (2023) identification of ‘AI artist-technologists’ as actually at the forefront of creative responses to AI.

In terms of the way Indigenous artists might approach AI, these novel technologies and the possibility of generating images of anything one wants, including things that are technically not possible or at least improbable, have tended to encourage either revisionist or speculative, futurist art practices. In revisionist mode, these tools can be used to backfill the historical record where portraits of ancestors do not exist or to reverse dominant perspectives, flipping, quite literally, the perspective from which a scene is captured or widening the frame (‘inpainting’ in AI image-generation terminology) to see things that are typically not depicted. In a more speculative, futurist mode, generative AI is often used as a means of imagining, of visualising, of ‘dreaming’ Indigenous futures, as per Lewis and colleagues’ concept of ‘the future imaginary’. In a discussion of Kite’s (2021) own art practice with respect to AI tools, she emphasises the importance of dreaming in this respect, subtly placing the generative nature of AI tools at the service of dreaming:

Dreaming is difficult, complex, and generative. Dreaming values the unknowable over the knowable. Dreaming makes new knowledge. Dreaming is the act of making art. Art is the translation of dreams. Collective dreaming is the concentration of our dreams, enhancing their power. When we as a collective make something this sacred, dreaming feels like a form of resistance.

There is also discussion among Indigenous artists around the status of AI as a tool or as a non-human collaborator that should be treated as ‘kin’. While from the outside, some critics have argued that AI is just another tool for Indigenous artists and that ‘By integrating AI into Indigenous art, it can become an Indigenous practice in its own right and one that will allow us to add another chapter to the long history of Indigenous visual culture’ (Rtology 2022, ‘What is the meaning of AI indigenous art?’), others, such as Lewis and colleagues, argue that ‘our goal is that we, as a species, figure out how to treat these new non-human kin respectfully and reciprocally – and not as mere tools, or worse, slaves to their creators’ (Lewis et al. 2018, 2). Karina Kesserwan (2018) also looks to Indigenous epistemologies – where non-human entities, such as mountains and rivers, as well as animals, are accorded respect and perceived to have ‘spirit’ – to argue that AI should be understood as ‘non-human kin’ in part of an ‘extended “circle of relationships”’.¹ And in an extension of discussions on kinship, Kite and others (cf. Menezes 2025) have also explored the idea that what artists are doing is potentially creating ‘AI ancestors’ for future generations. This is perhaps an Indigenous twist on philosopher Nick Bostrom’s (2009) argument that current AI developers and users will be the ancestors of future beings that may be wholly or part AI themselves (that is, if we are not already AI simulations ourselves, as he speculates elsewhere [Bostrom 2003]), and we thus bear considerable responsibility for what we ‘future ancestors’ do now and how it will impact the way the future unfolds. The Indigenous version of this scenario is rather less alarmist because Indigenous epistemologies are more oriented towards coexistence and collaboration with non-human entities.

Nonetheless, all these approaches are united in their willingness to conceive of a fruitful engagement between Indigenous art(ists) and AI. Many other voices have raised serious concerns about the potential of generative AI ‘tools’ to exponentially increase the cultural appropriation or ‘colonisation’ of artists’ work in general (Dhar 2023) and of Indigenous art in particular (Hendrix 2023; Wilson 2024). See, for example, the NightCafe Studio website’s offer to help its users ‘Create Aboriginal-inspired art with AI. Easily generate your own Aboriginal art with our free AI image generator. No experience needed!’² Furthermore, attempts to correct Indigenous invisibilisation or misrepresentation in major commercial image-generation tools by providing more and better data (if one could ever even manage to provide enough) will, arguably, simply provide mainstream society with better ways of appropriating the cultural production of Indigenous Peoples. These are issues with which any Indigenous artistic engagement with generative AI will need to wrestle.