Abundant intelligences: placing AI within Indigenous knowledge frameworks
Open accessAbstract
The current trajectory of artificial intelligence development suffers from fundamental epistemological shortcomings, resulting in the systematic operationalization of bias against non-white, non-male, and non-Western peoples. We argue that these failings are, in part, the result of certain Western rationalist epistemologies that exclude many ways of knowing about the world, and therefore they cannot provide a sufficient foundation on which to adequately, robustly, and humanely conceptualize intelligence. We present a new research agenda, Abundant Intelligences, an Indigenous-led, Indigenous-majority international, interdisciplinary research program that imagines anew how to conceptualize and design artificial intelligence (AI) based on Indigenous knowledge (IK) systems. Abundant Intelligences draws on the rich plurality of Indigenous knowledge systems, bringing together diverse sets of thought, culture, and protocol together. We show IK systems provide one way to rebuild AI’s epistemological foundations and transform these tools’ current role in reinforcing colonial practices of exclusion, extraction, manipulation, and eradication into engines of abundance that enable us to care better for ourselves, our communities, and our world. Our proposition is to fully engage with AI to explore how different conceptions of intelligence could be embodied in these technologies. In this paper, we present the tenets of the research program in detail, account for our methodological approach, describe the impact and limitations, and conclude on a discussion of the implications of the program.
AI snapshot
Written from the paper’s full text.
TL;DR
The authors argue that AI's problems are fundamentally epistemological rather than merely ethical, stemming from Western rationalist frameworks that treat intelligence as a property of isolated individuals. They propose Abundant Intelligences, an Indigenous-led, Indigenous-majority international research program that rebuilds AI's foundations on Indigenous knowledge systems organized around relationality, regeneration, generosity, and reciprocity.
Key findings
- The paper's central claim is that "the AI industry-academic complex does not have an ethics problem, it does, however, have an epistemology problem," producing systematic bias against non-white, non-male, and non-Western peoples.
- Mainstream AI definitions, exemplified by Legg and Hutter's "Intelligence measures an agent's general ability to achieve goals in a wide range of environments," are critiqued for treating intelligence as a property of a discrete, self-contained agent and ignoring the relational, cultural, and environmental conditions in which intelligence emerges. The authors trace this lineage to Linda Gottfredson's 1994 *Wall Street Journal* definition and its connections to eugenics and the Pioneer Fund.
- The program is organized around three axes — Integrations, Imaginaries, and Intelligences — and identifies five technical areas for engagement: language (NLP for low-resource Indigenous languages), storytelling, environmental stewardship, multi-agent systems, and socio-neuro AI.
- The research team comprises individuals from 16 Indigenous communities across Aotearoa New Zealand, North America, the Pacific, and Africa; the program currently has four Pods (Haudenosaunee-Niitsitapi, Ka Hawai'i Pae Aina, Aotearoa, and Wihanble S'a) and hopes to eventually have at least six.
Methods
- This is a research-agenda/programmatic paper, not an empirical study; the authors state "No data has been used in this article."
- Macro methodology: three axes — Integrations (synthesizing IK with AI research frameworks), Imaginaries (future imaginaries and speculative design workshops), and Intelligences (prototyping culturally grounded AI).
- Conduct of research: locally rooted "Pods" anchored in Indigenous-centered labs, using mixed methods (research-creation, Indigenous qualitative research, and Indigenous-led quantitative research), governed by OCAP and CARE data sovereignty principles. A six-phase micro methodology is outlined: understand, imagine, formalize, develop, implement, integrate.
Limitations
- Stated risks: integrating IK and computational practices "may turn out to be too difficult, or, worse, unsuited to transforming AI research"; epistemic gaps "might be too wide to meaningfully bridge"; initial relations across cultural, geographic, and institutional differences may be difficult to maintain; complexities of IK interacting with Western intellectual property regimes and data sovereignty; challenges integrating participants across computational sciences, natural sciences, humanities, arts, and community backgrounds; and skepticism among Indigenous communities about sharing knowledge with academia and industry.
- The paper also acknowledges that even if outcomes fall short, benefits would include relationship networks, diversification of AI research, increased numbers of trained Indigenous researchers, and experimental models for data sovereignty.
- Evident from the text: the paper reports no empirical results, prototypes, or evaluated outcomes — all impacts and outcomes are anticipated rather than demonstrated.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
5 of 25 cited sources checked · 1 supported · 0 flagged · accuracy not yet measured
- Premisecitation
The historical alliance between colonialism, capitalism, and research practices involved traditional knowledges being extracted from communities to serve Western science and commerce at the expense of those communities.
“We are mindful of the historical alliance between colonialism, capitalism, and research practices where traditional knowledges were extracted from communities to serve Western science and commerce at the expense of those communities (e.g., Abbass et al. 2022).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Abbass et al. 2022 source
Sections 2.1–2.2 describe Aboriginal languages and explain how the authors drew on Jingulu grammar for an AI-teaming language. They do not address a historical alliance between colonialism, capitalism, and research, or say that traditional knowledge was extracted for Western science and commerce at communities’ expense. Searches for those concepts and for Indigenous-knowledge appropriation found no supporting passage in our copy; page numbers were unavailable. (LLM, conf=0.73)
Experimental — accuracy not yet measured
- Interpretationcitation
There are deep-seated connections between white supremacy and the quest of artificial general intelligence (AGI).
“One thing to address here in Legg and Hutter's definition is the deep-seated connections between white supremacy and the quest of artificial general intelligence (AGI).”
Quote in the paperSubstantial claim1 of 1 sources checked- cites Andrews et al. 2024 source
The Introduction discusses the revival of physiognomic research through machine learning, and “A history of misbegotten science” links physiognomy and eugenics to racial hierarchies. Neither passage addresses the pursuit of artificial general intelligence or connects that pursuit to white supremacy. Searches for AGI, general intelligence, and Legg and Hutter found no passage making the attributed point. (LLM, conf=0.76)
Experimental — accuracy not yet measured
- Interpretationcitation
The epistemic failings are inextricably linked with the ethical failings we observe in AI today.
“As the prevalence of pseudoscientific formulations in AI is increasingly targeted by critical scholars (e.g., Andrews et al. 2024), it becomes clearer how the epistemic failings are inextricably linked with the ethical failings we observe in AI today.”
Quote in the paperNot a substantial claim1 of 1 sources checked- cites Andrews et al. 2024 source
- Interpretationcitation
If left unaddressed, these blindnesses auger a future where the integration of AI into every nook and cranny of our societies will radically entrench economic inequality.
“If left unaddressed, these blindnesses auger a future where the integration of AI into every nook and cranny of our societies will radically entrench economic inequality (Clark and Gevorkyan 2020;Goyal and Aneja 2020;Kim 2022)”
Quote in the paperNot a substantial claim0 of 3 sources checked - Interpretationreasoning
AI systems incorporate deep structural blindnesses and biases that render them incompetent, even dangerous, when confronted with the complexity and variety of human social systems.
“Namely, these systems incorporate deep structural blindnesses and biases that render them incompetent, even dangerous, when confronted with the complexity and variety of human social systems.”
Quote in the paperNot a substantial claim
- Interpretationreasoning
The epistemologies with which computational systems are designed and deployed embed the assumption that the only useful knowledge is that produced through rational instrumentality.
“These include the user is an individual; the individual prioritizes her personal well-being; culture is an epiphenomenon rather than the phenomenon; text and context can be separated; and that the only useful knowledge is that produced through rational instrumentality.”
Quote in the paperSubstantial claim - Interpretationreasoning
Legg and Hutter's view does not consider the social, cultural, political, and material environment to be as significant to intelligence as the agent itself.
“In short, this view does not consider the social, cultural, political, and material environment to be as significant to intelligence as the agent itself.”
Quote in the paperSubstantial claim - Interpretationreasoning
Legg and Hutter's conception relies heavily on a framework built on the idea of hierarchy between races and the measurability of that hierarchy via intelligence tests.
“Legg and Hutter's only disclaimer about this is to say that they do not completely agree with Gottfredson's definition (Legg and Hutter 2007, p. 12); however, their conception relies heavily on this framework that is built on the idea of hierarchy between races and the measurability of that hierarchy via intelligence tests.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Legg and Hutter 2007 source
- Interpretationreasoning
What an Indigenous person considers worth knowing about a domain may be significantly different from and more multidimensional than what a normative AI scientist considers necessary.
“The result is that what an Indigenous person considers worth knowing about a domain may be significantly different from and more multidimensional than what a normative AI scientist considers necessary.”
Quote in the paperNot a substantial claim - Interpretationreasoning
The epistemologies with which computational systems are designed and deployed embed the assumption that culture is an epiphenomenon rather than the phenomenon.
“These include the user is an individual; the individual prioritizes her personal well-being; culture is an epiphenomenon rather than the phenomenon; text and context can be separated; and that the only useful knowledge is that produced through rational instrumentality.”
Quote in the paperSubstantial claim - Interpretationreasoning
The intertwinement of the notion of intelligence and white nationalism is not an accident.
“The intertwinement of the notion of intelligence and white nationalism is not an accident.”
Quote in the paperSubstantial claim - Interpretationnone given
The epistemologies with which computational systems are designed and deployed embed the assumption that the individual prioritizes her personal well-being.
“These include the user is an individual; the individual prioritizes her personal well-being; culture is an epiphenomenon rather than the phenomenon; text and context can be separated; and that the only useful knowledge is that produced through rational instrumentality.”
Quote in the paperSubstantial claim - Interpretationcitation
If left unaddressed, these blindnesses auger a future where the integration of AI into every nook and cranny of our societies will systemize racial injustice.
“systemize racial injustice (Benjamin 2019;Noble 2018)”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Benjamin 2019
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Noble 2018
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationreasoning
Engineering practices favor those ways of thinking (e.g., binary; goal oriented) that are easily amenable to computational implementation, rather than most appropriate to specific contexts.
“Engineering practices favor those ways of thinking (e.g., binary; goal oriented) that are easily amenable to computational implementation, rather than most appropriate to specific contexts.”
Quote in the paperNot a substantial claim - Interpretationcitation
Expanding and diversifying the knowledge systems that AI researchers seek to simulate will enable the development of more effective and socially relevant computing systems.
“Expanding and diversifying the knowledge systems that AI researchers seek to simulate will enable the development of more effective and socially relevant computing systems.”
Quote in the paperNot a substantial claim - Interpretationreasoning
The epistemologies with which computational systems are designed and deployed embed the assumption that the user is an individual.
“These include the user is an individual; the individual prioritizes her personal well-being; culture is an epiphenomenon rather than the phenomenon; text and context can be separated; and that the only useful knowledge is that produced through rational instrumentality.”
Quote in the paperSubstantial claim - Premisecitation
Indigenous people have been adapting their knowledge systems to new scientific and technological advances for millennia.
“Indigenous people have been adapting their knowledge systems to new scientific and technological advances for millenia.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Whaanga and Mato 2020 source
- Interpretationcitation
If left unaddressed, these blindnesses auger a future where the integration of AI into every nook and cranny of our societies will make it impossible to escape state control and surveillance capitalism.
“make it impossible to escape state control and surveillance capitalism (Yeung 2018;Zuboff 2020)”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Yeung 2018 source
- cites Zuboff 2020
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Premisecitation
Computer science approaches such questions from relatively narrow foundations.
“Computer science approaches such questions from relatively narrow foundations.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Ackerman 2000 source
- Interpretationcitation
Gottfredson's 'scientific' definition conceals a racist, eugenicist, and white nationalist impetus in the intelligence research community.
“This 'scientific' definition, 5 however, conceals a racist, eugenicist, and white nationalist impetus in the intelligence research community.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Tucker 2002
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Interpretationreasoning
The epistemologies with which computational systems are designed and deployed embed the assumption that text and context can be separated.
“These include the user is an individual; the individual prioritizes her personal well-being; culture is an epiphenomenon rather than the phenomenon; text and context can be separated; and that the only useful knowledge is that produced through rational instrumentality.”
Quote in the paperSubstantial claim
- Classified as probably not a substantial claim. 32
- May combine two claims. 12
Probably not a substantial claim: may not pass S2 (checkable).
InterpretationcitationIf left unaddressed, these blindnesses auger a future where the integration of AI into every nook and cranny of our societies will cement white supremacy into the core operating system(s) of the world.
“cement white supremacy into the core operating system(s) of the world (Cave and Dihal 2020;Katz 2020;Phan 2019).”
Quote in the paperNot a substantial claim2 of 3 sources checked- cites Cave and Dihal 2020 source
The Conclusion and Implications (section 4; page not provided) says White portrayals of AI can sustain racial prejudice and contribute to products that benefit one group while disadvantaging others. It also warns that racialised AI could exacerbate injustice in automated decisions. These conditional, specific harms support the concern, but not the stronger prediction that AI's integration throughout society will cement white supremacy into the world's core operating systems. (LLM, conf=0.84)
Experimental — accuracy not yet measured - cites Katz 2020 source
- cites Phan 2019 source
In “Race, Voice, and Figurative Narratives” (page unavailable), Phan argues that Alexa’s white-speaking persona erases histories of racialized exploitation and that such figurations can shape attitudes to power. The Conclusion (page unavailable) also describes how Alexa obscures exploited, predominantly racialized labor. The paper does not establish the broader prediction that AI throughout society will cement white supremacy into the world’s core systems. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.
InterpretationreasoningThese failings are, in part, the result of certain Western rationalist epistemologies that exclude many ways of knowing about the world, and therefore they cannot provide a sufficient foundation on which to adequately, robustly, and humanely conceptualize intelligence.
“We argue that these failings are, in part, the result of certain Western rationalist epistemologies that exclude many ways of knowing about the world, and therefore they cannot provide a sufficient foundation on which to adequately, robustly, and humanely conceptualize intelligence.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe current trajectory of AI development suffers from fundamental epistemological shortcomings, resulting in the systematic operationalization of bias against non-white, non-male, and non-Western peoples.
“The current trajectory of artificial intelligence development suffers from fundamental epistemological shortcomings, resulting in the systematic operationalization of bias against non-white, non-male, and non-Western peoples.”
- Also stated in: § 1 Introduction · plain
“The current trajectory of AI development suffers from fundamental epistemological shortcomings, resulting in the systematic operationalization of bias against non-white, non-male, and non-Western peoples.”
Quote in the paperNot a substantial claim- Also stated in: § 1 Introduction · plain
Probably not a substantial claim: may not pass S4 (based). May combine two claims.
Interpretationnone givenThe Abundant Intelligences project enables cultural-technical collaborations between Indigenous communities, brings together scientific practice with cultural concerns, and creates a test bed for technologies imagined in the communities and prototyped with AI expertise.
“The project enables cultural-technical collaborations between Indigenous communities, brings together scientific practice with cultural concerns, and creates a test bed for various technologies imagined in the communities and prototyped in collaboration with world-class AI expertise.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenThe notion of intelligence is increasingly impoverished under the banner of AI.
“From our perspective, it is clear that the notion of intelligence is increasingly impoverished under the banner of AI, and bringing in the notion of abundance is a direct response to this.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
InterpretationreasoningThis blindness stems from an intellectual lineage heavily infected with Cartesian duality, monotheistic eschatology, and computational reductionism.
“This blindness stems from an intellectual lineage heavily infected with Cartesian duality, monotheistic eschatology, and computational reductionism.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningWhen one treats intelligence as a property of an individual that can be analytically abstracted and not a collectively established relationality, the wider matrix in which our attributions of intelligence to certain activities or proclivities become obscured.
“When one treats intelligence as a property of an individual that can be analytically abstracted and not a collectively established relationality, the wider matrix in which our attributions of intelligence to certain activities or proclivities become obscured.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenThe summer intensives and Pod workshops enable Indigenous groups to be more actively involved with the creation and deployment of AI systems.
“The summer intensives and Pod workshops enable Indigenous groups to be more actively involved with the creation and deployment of AI systems.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
InterpretationcitationIntegrating AI into Indigenous knowledge practices will be the latest example of this ongoing innovation.
“Integrating AI into their knowledge practices will be but the latest example of this ongoing innovation (Whaanga and Mato 2020).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Whaanga and Mato 2020 source
Classified as probably not a substantial claim.
InterpretationreasoningLegg and Hutter's definition falls short because it takes intelligence to be a property of a singular and individual entity.
“However, Legg and Hutter's definition falls short in our consideration as it takes intelligence to be a property of a singular and individual entity.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningWhat is missing from most operationalized definitions of intelligence, including Legg and Hutters', is the very cultural context in which all such intelligent operations take place.
“What is missing from most operationalized definitions of intelligence, including Legg and Hutters', is the very cultural context in which all such intelligent operations take place.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenWestern scientific framework prioritizes climbing a ladder of abstraction to reach simple universal principles that can be applied across all individuals, communities, and territories.
“This can make it seem unruly when viewed from within a Western scientific framework, which prioritizes climbing a ladder of abstraction to reach simple universal principles that can be applied across all individuals, communities, and territories.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
InterpretationreasoningIK systems provide one way to rebuild AI's epistemological foundations and transform these tools' current role in reinforcing colonial practices of exclusion, extraction, manipulation, and eradication into engines of abundance that enable us to care better for ourselves, our communities, and our world.
“We show IK systems provide one way to rebuild AI's epistemological foundations and transform these tools' current role in reinforcing colonial practices of exclusion, extraction, manipulation, and eradication into engines of abundance that enable us to care better for ourselves, our communities, and our world.”
- Also stated in: § Abstract · plain
“IK systems provide one way to rebuild AI's epistemological foundations and transform these tools' current role in reinforcing colonial practices of exclusion, extraction, manipulation, and eradication into engines of abundance that enable us to care better for ourselves, our communities, and our world.”
Quote in the paperNot a substantial claim- Also stated in: § Abstract · plain
May combine two claims.
PremisecitationIK systems are a class of epistemologies reflecting a different understanding of intelligence, offering alternative methods for considering how knowledge is generated, validated, and propagated.
“IK systems are a class of epistemologies reflecting a different understanding of intelligence, offering alternative methods for considering how knowledge is generated, validated, and propagated (Cajete 2000;Descola 2013;Hester & Cheney 2001;Little Bear & Heavy Head 2004;Meyer 2003;Posthumus 2018;Smith 2016;Turner 2006;Waters 2004).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Cajete 2000
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Descola 2013
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites Hester & Cheney 2001 source
Probably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningThis makes AI system engineers blind to vital aspects of human existence-such as trust, care, and community-that are fundamental to how intelligence actually operates.
“This makes AI system engineers blind to vital aspects of human existence-such as trust, care, and community-that are fundamental to how intelligence actually operates.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable). May combine two claims.
InterpretationreasoningThe hegemonic weight of the ideology of intelligence is imbued to a large degree by the AI enterprise, propagating the assumption that intelligence is an abstractable property that is self-contained and self-evident, all the while erasing different notions of intelligence from consideration.
“The hegemonic weight of the ideology of intelligence is indeed imbued to a large degree by the AI enterprise, propagating the assumption that intelligence is an abstractable property that is self-contained and self-evident, all the while erasing different notions of intelligence from consideration.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenThe Abundant Intelligences project serves as a model for other projects seeking to tackle similar issues through locally rooted research and creation Pods exploring fundamental questions pertaining to AI with a participatory and inclusive approach.
“Furthermore, it serves as a model for other projects seeking to tackle similar issues through locally rooted research and creation Pods exploring fundamental questions pertaining to AI with a participatory and inclusive approach.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenThe research team is composed of individuals from 16 Indigenous communities from across Aotearoa New Zealand, North America, the Pacific, and Africa.
“The research team itself is composed of individuals from 16 Indigenous communities from across Aotearoa New Zealand, North America, the Pacific, and Africa.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningIK systems have considerable potential, as much of them rest on a relational approach.
“IK systems have considerable potential, as much of them rest on a relational approach.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningA big portion of the intelligence question lies in the normative conditions that valorize and provide meaning as well as power to certain actions over others.
“A big portion of the intelligence question lies in the normative conditions that valorize and provide meaning as well as power to certain actions over others.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
InterpretationreasoningSuch environments are defined, in no small part, by the cultural structure of specific human communities and their relations to the natural world.
“Such environments are defined, in no small part, by the cultural structure of specific human communities and their relations to the natural world.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Premisenone givenIK insists on retaining the complexity of lived experience.
“Furthermore, IK insists on retaining the complexity of lived experience.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe environmental cost of AI systems has been a significant point of contention, especially generative AI technologies, but also others, because of their resource-intensiveness.
“For example, the environmental cost of AI systems has been a significant point of contention, especially generative AI technologies, but also others, because of their resource-intensiveness (Bender et al. 2021;Strubell et al. 2019).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Bender et al. 2021 source
- cites Strubell et al. 2019
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
PremisecitationIK systems describe a multidimensional world that is in a flux, and seek out embodiments that can take shape in this constant becoming.
“They describe a multidimensional world that is in a flux, and seek out embodiments that can take shape in this constant becoming (Little Bear and Heavy Head 2004).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Little Bear and Heavy Head 2004
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe Legg and Hutter definition draws from a 'mainstream scientific definition of intelligence' developed by Linda Gottfredson.
“The Legg and Hutter definition is a good example here: they draw from a 'mainstream scientific definition of intelligence', a public statement published in the Wall Street Journal in 1994, as developed by Linda Gottrfredson.”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Legg and Hutter 2007 source
Probably not a substantial claim: may not pass S4 (based). May combine two claims.
Premisenone givenStories, songs, dance, and lore all embed knowledge about the world and facilitate its rigorous transmission from one generation to the next.
“Stories, songs, dance, and lore all embed knowledge about the world and facilitate its rigorous transmission from one generation to the next.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
InterpretationreasoningThe need to redefine or expand the scope of what intelligent action means emerges from the narrow definitions of intelligence that underlie the AI systems and research.
“This need emerges from the narrow definitions of intelligence that underlie the AI systems and research.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenAbundant Intelligences establishes a platform for bringing together expertise from a multitude of disciplines, localities, and cultures.
“Abundant Intelligences establishes a platform for bringing together expertise from a multitude of disciplines, localities, and cultures”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningSeparating mind from the body, elevating after-life over present-life, and violently forcing all experience into binary terms to make it (appear to be) computable produces impoverished notions of what constitutes human intelligence.
“Separating mind from the body, elevating after-life over present-life, and violently forcing all experience into binary terms to make it (appear to be) computable produces impoverished notions of what constitutes human intelligence.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThis form of scientific racism still reverberates today, and definitions developed under such paradigms seem to be unproblematically employed by AGI researchers.
“This form of scientific racism still reverberates today, 6 and definitions developed under such paradigms seem to be unproblematically employed by AGI researchers.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningDefining 'appropriate' function and useful 'foresight' requires a deep understanding of the different environments in which intelligent machines might operate.
“We argue that defining 'appropriate' function and useful 'foresight' requires a deep understanding of the different environments in which intelligent machines might operate.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningThese systems do not occur in a vacuum; they are always already entangled with the (cultural, social, political, physical, economic) world around them.
“Yet, these systems do not occur in a vacuum; they are always already entangled with the (cultural, social, political, physical, economic) world around them.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningThis difference in approaches provides a generative ground for considering alternative approaches to creating AI.
“This difference in approaches provide a generative ground for considering alternative approaches to creating AI.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
InterpretationreasoningLegg and Hutter's view does not consider the relational structures that precede the actor, the web of relations into which the agent always-already arrives.
“This view does not consider the relational structures that precede the actor, the web of relations into which the agent always-already arrives.”
Quote in the paperSubstantial claimMay combine two claims.
PremisereasoningIndigenous epistemologies include observe-hypothesize-test iterations of the Western scientific method, but also practices excluded by it.
“Indigenous epistemologies include observe-hypothesize-test iterations of the Western scientific method, but also practices excluded by it.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
Interpretationnone givenThe project's online presence ensures a robust utilization of digital dissemination opportunities, contributing to debates on ethical AI design and emerging scholarship on the social and cultural aspects of AI.
“The project's online presence (e.g., through our website) ensures a robust utilization of digital dissemination opportunities, thus contributing to debates on ethical AI design and emerging scholarship on the social and cultural aspects of AI.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.
Interpretationnone givenThese systems are being increasingly tasked with interactions that have deep social, political, and legal consequences, yet the field seems to continue to fetishize rational goal seeking as the definition of intelligence.
“These systems are being increasingly tasked with interactions that have deep social, political, and legal consequences, yet the field seems to continue to fetishize rational goal seeking as the definition of intelligence.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningMainstream definitions in AI treat intelligence as something that pertains to an individual, and disregard the cultural, social, and environmental conditions in which an intelligence emerges.
“Mainstream definitions in AI treat intelligence as something that pertains to an individual, and disregard the cultural, social, and environmental conditions in which an intelligence emerges.”
Quote in the paperSubstantial claim
The paper relies on this without support.
AI is still in early developmental stages.
“We argue that interdisciplinary research and research-creation reimagining the AI project is required now, while AI is still in early developmental stages, and urgently before deeply problematic assumptions about how people behave and interact with each other and their environment is encoded into the foundations of our sociotechnical systems.”
The paper relies on this without support.
Deeply problematic assumptions about how people behave and interact with each other and their environment are being encoded into the foundations of our sociotechnical systems.
“We argue that interdisciplinary research and research-creation reimagining the AI project is required now, while AI is still in early developmental stages, and urgently before deeply problematic assumptions about how people behave and interact with each other and their environment is encoded into the foundations of our sociotechnical systems.”
The paper relies on this without support.
Many Indigenous communities are skeptical about sharing their knowledge with academia and industry.
“complicated further by the fact that many Indigenous communities are skeptical about sharing their knowledge with academia and industry.”
The paper relies on this without support.
Being Indigenous does not correlate to a monolithic landscape of values.
“We recognize that being Indigenous does not correlate to a monolithic landscape of values; indeed the project supports the diversity of Indigenous thought and practice as a benefit to knowledge creation.”
The paper relies on this without support.
Scientists and Indigenous peoples have had their encounters marked by colonial violence and power asymmetries.
“Scientists and Indigenous peoples have had their encounters marked by colonial violence and power asymmetries.”
The paper relies on this without support.
The way in which the relationship between colonizing forces and Indigenous people worked before was with a top-down organization where colonizing forces took decisions for the Indigenous people and imposed the results onto the communities.
“The way in which that relationship worked before was with a top-down organization where colonizing forces took decisions for the Indigenous people and imposed the results onto the communities.”
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Second research axis has two names
MinorThe overview names the second axis "Imaginations," but the following description and dedicated paragraph call it "Imaginaries."
“To accomplish this, we organized the work along three axes: Integrations, Imaginations, and Intelligences.”
“The Imaginaries Axis develops future imaginaries and speculative designs of Indigenous AI to guide the conceptualization of novel AI systems better suited to Indigenous flourishing.”
Cites
On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021) · Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3442188.3445922 · Cited by 6,988 · cited 1× · see citing works
“For example, the environmental cost of AI systems has been a significant point of contention, especially generative AI technologies, but also others, because of their resource-intensiveness (Bender et al. 2021; Strubell et al. 2019).”
Intelligence without representation
Brooks, R. A. (1991) · Artificial Intelligence · doi:10.1016/0004-3702(91)90053-m · Cited by 4,853 · see citing works
Energy and Policy Considerations for Deep Learning in NLP
Strubell, E., Ganesh, A., & McCallum, A. (2019) · arXiv · doi:10.48550/arxiv.1906.02243 · Cited by 3,735
Energy and Policy Considerations for Deep Learning in NLP
Strubell, E., Ganesh, A., & McCallum, A. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/p19-1355 · Cited by 3,684 · see citing works
Semantics derived automatically from language corpora contain human-like biases
Caliskan, A., Bryson, J. J., & Narayanan, A. (2017) · Science · doi:10.1126/science.aal4230 · Cited by 2,887 · see citing works
Algorithms of Oppression: How Search Engines Reinforce Racism
Noble, S. U. (2020) · doi:10.2307/j.ctt1pwt9w5 · Cited by 2,709 · see citing works
Descola, P., Lloyd, J., & Sahlins, M. (2007) · British Academy eBooks · doi:10.5871/bacad/9780197263945.003.0006 · Cited by 2,465 · see citing works
Speculative Everything: Design, Fiction, and Social Dreaming
(2014) · Choice Reviews Online · doi:10.5860/choice.51-5390 · Cited by 1,952 · see citing works
Descola, P., Lloyd, J., & Sahlins, M. (2013) · doi:10.7208/chicago/9780226145006.001.0001 · Cited by 1,539
Review of “Race After Technology: Abolitionist Tools for the New Jim Code”
Jipguep-Akhtar, M. C. (2019) · Social Forces · doi:10.1093/sf/soz162 · Cited by 1,482 · see citing works
Multi-Agent Reinforcement Learning: A Selective Overview of Theories and Algorithms
Zhang, K., Yang, Z., & Başar, T. (2021) · Studies in systems, decision and control · doi:10.1007/978-3-030-60990-0_12 · Cited by 1,403 · see citing works
Mainstream science on intelligence: An editorial with 52 signatories, history, and bibliography
Gottfredson, L. S. (1997) · Intelligence · doi:10.1016/s0160-2896(97)90011-8 · Cited by 1,137 · see citing works
Being Indigenous: Resurgences against Contemporary Colonialism
Alfred, T., & Corntassel, J. G. (2005) · Government and Opposition · doi:10.1111/j.1477-7053.2005.00166.x · Cited by 1,067 · see citing works
The Intellectual Challenge of CSCW: The Gap Between Social Requirements and Technical Feasibility
Ackerman, M. S. (2000) · Human–Computer Interaction · doi:10.1207/s15327051hci1523_5 · Cited by 892 · see citing works
Algorithmic regulation: A critical interrogation
Yeung, K. (2018) · Regulation & Governance · doi:10.1111/rego.12158 · Cited by 842 · see citing works
Universal intelligence: a definition of machine intelligence
Legg, S., & Hutter, M. (2007) · Minds and Machines · doi:10.1007/s11023-007-9079-x · Cited by 803 · see citing works
Curriculum, Replacement, and Settler Futurity
Tuck, E., & Gaztambide‐Fernández, R. (2013) · Journal of Curriculum Theorizing · doi:10.63997/jct.v29i1.411 · Cited by 526 · see citing works
Cohen, J. E. (2019) · doi:10.1093/oso/9780190246693.001.0001 · Cited by 445 · see citing works
Viewpoint: Human-in-the-loop Artificial Intelligence
Zanzotto, F. M. (2019) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1.11345 · Cited by 380 · see citing works
Thinking through other minds: A variational approach to cognition and culture
Veissière, S. P. L., Constant, A., Ramstead, M. J. D., Friston, K. J., & Kirmayer, L. J. (2020) · Behavioral and Brain Sciences · doi:10.1017/s0140525x19001213 · Cited by 348 · see citing works
Cave, S., & Dihal, K. (2020) · Philosophy & Technology · doi:10.1007/s13347-020-00415-6 · Cited by 279 · see citing works
Routledge Handbook of Critical Indigenous Studies
Hokowhitu, B., Moreton‐Robinson, A., Smith, L. T., Andersen, C., & Larkin, S. (2020) · Routledge eBooks · doi:10.4324/9780429440229 · Cited by 262 · see citing works
Oswald, M., Grace, J., Urwin, S., & Barnes, G. C. (2018) · Information & Communications Technology Law · doi:10.1080/13600834.2018.1458455 · Cited by 248 · see citing works
Research-Creation: Intervention, Analysis and “Family Resemblances”
Chapman, O. (2012) · Canadian Journal of Communication · doi:10.22230/cjc.2012v37n1a2489 · Cited by 237 · see citing works
Lewis, J. E., Arista, N., Pechawis, A., & Kite, S. (2018) · Journal of design and science · doi:10.21428/bfafd97b · Cited by 217 · see citing works
Self-citationPascua, P., McMillen, H. L., Ticktin, T., Vaughan, M. B., & Winter, K. B. (2017) · Ecosystem Services · doi:10.1016/j.ecoser.2017.03.012 · Cited by 197 · see citing works
Can artificial intelligence be decolonized?
Adams, R. (2021) · Interdisciplinary Science Reviews · doi:10.1080/03080188.2020.1840225 · Cited by 194 · see citing works
The TESCREAL bundle: Eugenics and the promise of utopia through artificial general intelligence
Gebru, T., & Torres, É. P. (2024) · First Monday · doi:10.5210/fm.v29i4.13636 · Cited by 181 · see citing works
Indigenous Protocol and Artificial Intelligence Position Paper
Abdilla, A., Arista, N., Baker, K., Benesiinaabandan, S., Brown, M., Cheung, M., Coleman, M., Cordes, A., Davison, J., Duncan, K., et al. (2020) · Concordia University Library · doi:10.11573/spectrum.library.concordia.ca.00986506 · Cited by 127 · see citing works
Self-citationDourish, P., Finlay, J., Sengers, P., & Wright, P. (2004) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/985921.986203 · Cited by 116 · see citing works
Amazon Echo and the Aesthetics of Whiteness
(2019) · Catalyst Feminism Theory Technoscience · doi:10.28968/cftt.v5i1.29586 · Cited by 111 · see citing works
The Participatory Condition in the Digital Age
Galati, G. (2017) · Leonardo · doi:10.1162/leon_r_01509 · Cited by 100 · see citing works
Special Issue “On Defining Artificial Intelligence”—Commentaries and Author’s Response
Monett, D., Lewis, C. W. P., Þórisson, K. R., Bach, J., Baldassarre, G., Granato, G., Berkeley, I. S. N., Chollet, F., Crosby, M., Shevlin, H., et al. (2020) · Journal of Artificial General Intelligence · doi:10.2478/jagi-2020-0003 · Cited by 98 · see citing works
Solving the Narrative Paradox in VEs – Lessons from RPGs
Louchart, S., & Aylett, R. S. (2003) · Lecture notes in computer science · doi:10.1007/978-3-540-39396-2_41 · Cited by 92 · see citing works
The Naturalized Female Intellect
Daston, L. (1992) · Science in Context · doi:10.1017/s0269889700001162 · Cited by 90 · see citing works
McQuillan, D. (2022) · Policy Press eBooks · doi:10.1332/policypress/9781529213492.001.0001 · Cited by 85 · see citing works
Artificial Whiteness: Politics and Ideology in Artificial Intelligence
Katz, Y. (2020) · doi:10.7312/katz19490 · Cited by 83 · see citing works
Hart, V., Whatman, S. L., McLaughlin, J., & Sharma‐Brymer, V. (2012) · Compare A Journal of Comparative and International Education · doi:10.1080/03057925.2012.706480 · Cited by 74 · see citing works
Harrell, D. F. (2013) · The MIT Press eBooks · doi:10.7551/mitpress/8834.001.0001 · Cited by 70 · see citing works
Cave, S. (2020) · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · doi:10.1145/3375627.3375813 · Cited by 59 · see citing works
Rescuing All Our Futures: The Future of Futures Studies
McMichael, P., & Sardar, Z. (2000) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2654968 · Cited by 58 · see citing works
Truth and Native American epistemology
Hester, L., & Cheney, J. (2001) · Social Epistemology · doi:10.1080/02691720110093333 · Cited by 53 · see citing works
The History and Practice of AI in the Environmental Sciences
Haupt, S. E., Gagne, D. J., Hsieh, W. W., Krasnopolsky, V. M., McGovern, A., Marzban, C., Moninger, W. R., Lakshmanan, V., Tissot, P. E., & Williams, J. K. Y. (2021) · Bulletin of the American Meteorological Society · doi:10.1175/bams-d-20-0234.1 · Cited by 51 · see citing works
Thought Space Wānanga—A Kaupapa Māori Decolonizing Approach to Research Translation
Smith, L. T., Pīhama, L., Cameron, N., Mataki, T., Morgan, H., & Nana, R. T. (2019) · Genealogy · doi:10.3390/genealogy3040074 · Cited by 47 · see citing works
Socio-Technical Futures Shaping the Present
(2019) · Technikzukünfte, Wissenschaft und Gesellschaft · doi:10.1007/978-3-658-27155-8 · Cited by 45 · see citing works
Constructing Recidivism Risk for Sentencing
Eaglin, J. (2016) · SSRN Electronic Journal · doi:10.2139/ssrn.2821136 · Cited by 45 · see citing works
Goyal, A., & Aneja, R. (2020) · Journal of Public Affairs · doi:10.1002/pa.2326 · Cited by 43 · see citing works
Mapping Abundance for a Planetary Future
Fujikane, C. (2021) · Duke University Press eBooks · doi:10.1215/9781478021247 · Cited by 40 · see citing works
Improving Multimodal Interactive Agents with Reinforcement Learning from Human FeedbackPreprint
Abramson, J., Ahuja, A., Carnevale, F., et al. (2022) · arXiv.org · doi:10.48550/arxiv.2211.11602 · Cited by 40 · see citing works
Race, Gender and IQ: the social consequence of a pseudo‐scientific discourse
Mirza, H. S. (1998) · Race Ethnicity and Education · doi:10.1080/1361332980010108 · Cited by 38 · see citing works
Indigenous stewardship through novel approaches to collaborative management in Hawaiʻi
Winter, K. B., Vaughan, M. B., Kurashima, N., Wann, L., Cadiz, E., Kawelo, A. H., Cypher, M., Kaluhiwa, L., & Springer, H. K. (2023) · Ecology and Society · doi:10.5751/es-13662-280126 · Cited by 38 · see citing works
Hawaiian Hermeneutics and the Triangulation of Meaning: Gross, Subtle, Causal
Meyer, M. A. (2021) · Open Collections · doi:10.14288/cjne.v27i2.196348 · Cited by 33 · see citing works
Social Neuro AI: Social Interaction as the “Dark Matter” of AI
Bolotta, S., & Dumas, G. (2022) · Frontiers in Computer Science · doi:10.3389/fcomp.2022.846440 · Cited by 31 · see citing works
Posthumus, D. C. (2018) · UNP - Nebraska eBooks · doi:10.2307/j.ctvvndzk · Cited by 31 · see citing works
Artificial Intelligence and Human Flourishing
Clark, C. M. A., & Gevorkyan, A. V. (2020) · The American Journal of Economics and Sociology · doi:10.1111/ajes.12356 · Cited by 22 · see citing works
The Mythical Taboo on Race and Intelligence
Jackson, J. P., & Winston, A. S. (2020) · Review of General Psychology · doi:10.1177/1089268020953622 · Cited by 21 · see citing works
The reanimation of pseudoscience in machine learning and its ethical repercussions
Andrews, M., Smart, A., & Birhane, A. (2024) · Patterns · doi:10.1016/j.patter.2024.101027 · Cited by 18 · see citing works
Vizenor, G. R. (2009) · Brill | Schöningh eBooks · doi:10.30965/9783657768639_018 · Cited by 17 · see citing works
Carbon Emissions in the Tailpipe of Generative AI
Kneese, T., & Young, M. (2024) · Harvard Data Science Review · doi:10.1162/99608f92.fbdf6128 · Cited by 14 · see citing works
Algorithmic Silence: A Call to Decomputerize
Penn, J. (2021) · Journal of Social Computing · doi:10.23919/jsc.2021.0023 · Cited by 9 · see citing works
JSwarm: A Jingulu-Inspired Human-AI-Teaming Language for Context-Aware Swarm Guidance
Abbass, H. A., Petraki, E., & Hunjet, R. (2022) · Frontiers in Physics · doi:10.3389/fphy.2022.944064 · Cited by 6 · see citing works
The Indigenous digital footprint
Whaanga, H., & Mato, P. (2020) · Routledge Handbook of Critical Indigenous Studies · doi:10.4324/9780429440229-38 · Cited by 6 · see citing works
Self-citationDoes "The Bell Curve" Ring True? A Closer Look at a Grim Portrait of American Society
Dickens, W. T., Kane, T. J., & Schultze, C. L. (1995) · The Brookings Review · doi:10.2307/20080575 · Cited by 5 · see citing works
Waiwai (Abundance) and Indigenous Futures
Baker, M. T. (2018) · Routledge eBooks · doi:10.4324/9781315671192-3 · Cited by 4 · see citing works
FCJ-205 Life and Labour of Rovers on Mars: Toward Post-Terrestrial Futures of Creative Robotics
Damjanov, K. (2016) · UWA Profiles and Research Repository (UWA) · doi:10.15307/fcj.28.205.2017 · Cited by 2 · see citing works
Recovering Missing Characters in Old Hawaiian Writing
Shillingford, B., & Jones, Ō. P. (2018) · Conference on Empirical Methods in Natural Language Processing (EMNLP) · doi:10.18653/v1/d18-1533 · Cited by 2 · see citing works
(2004) · University of Calgary Press eBooks · doi:10.1515/9781552383773-005 · Cited by 1 · see citing works
Utopic Rage: Transforming the Future Through Narratives of Black Feminine Monstrosity and Rage
Scherr, C. (2023) · Fisher Digital Publications (St. John Fisher College) · doi:10.4324/9780429317828/routledge-handbook-cofuturisms-grace-dillon-isiah-lavender-iii-taryne-jade-taylor-bodhisattva-chattopadhyay
Flagged first, then by citations
Research works printed but not linked: 19
- Adams R (2025) The new empire of AI: the future of global inequality. Polity Press. https://www.indigo.ca/en-ca/the-new-empire-of-ai-the-future-of-global-inequality/9781509553099.html
- Aylett R (2000) Emergent narrative, social immersion and “storification.” In: Proceedings of the 1st International Workshop on Narrative and Interactive Learning Environments, pp 35–44
- Brown AM (2017) Emergent strategy: shaping change, changing worlds. AK Press, California
- Daston L (2018) Calculation and the Division of Labor, 1750–1950. Bull Ger Hist Inst 62(Spring):9–30
- Eaglin JM (2017) Constructing recidivism risk. Emory Law J 67(1):59–122
- Eubanks V (2018) Automating inequality: how high-tech tools profile, police, and punish the poor (1st edition). St. Martin’s Press, New York
- Kim P (2022) AI and inequality. In: Johnson K, Reyes C (eds), Forthcoming in the Cambridge handbook on artificial intelligence & the law. https://ssrn.com/abstract=3938578
- Kovach M (2021) Indigenous methodologies: characteristics, conversations, and contexts. University of Toronto Press, Toronto
- Maracle L (2017) Ravensong—A novel (2nd edition). Women’s Press, London
- Simpson LB (2014) Land as pedagogy: Nishnaabeg intelligence and rebellioustransformation. Decolon Indigeneity, Educ Soc 3(3):1–25
- Smith LT (2016) Indigenous knowledge, methodology and mayhem: What is the role of methodology in producing indigenous insights? A discussion from Mātauranga Māori. Knowl Cult 4(3):131–156
- Smith LT (2012) Decolonizing methodologies: research and indigenous peoples (2nd edition). Zed Books
- Stone P, Brooks R, Brynjolfsson E, Calo R, Etzioni O, Hager G, Hirschberg J, Kalyanakrishnan S, Kamar E, Kraus S, Leyton-Brown K, Parkes D, Press W, Saxenian A, Shah J, Tambe M, Teller A (2016) Artificial Intelligence and Life in 2030 (Report of the 2015 Study Panel. Stanford University, One Hundred Year Study on Artificial Intelligence)
- Toupin S (2024) Feminist artificial intelligence: a new era. Politics and rights review. https://politicsrights.com/feminist-artificial-intelligence-a-new-era/. Accessed 15 May 2024
- Tucker WH (2002) The funding of scientific racism: Wickliffe Draper and the Pioneer Fund (pp x, 286). University of Illinois Press, Champaign
- Turner DA (2006) This is not a peace pipe: towards a critical indigenous philosophy. University of Toronto Press, Toronto
- Walter M, Andersen C (2013) Indigenous statistics: a quantitative research methodology. Left Coast Press, Walnut Creek, CA
- Witehira JGP (2013) Tārai Kōrero Toi: articulating a Māori design language, Doctoral Dissertation, Massey University. http://hdl.handle.net/10179/5213
- Zuboff S (2020) The age of surveillance capitalism: the fight for a human future at the new frontier of power (First Trade Paperback Edition). PublicAffairs
Cited by
Sorted by citations
Jose, B., Cleetus, A., Joseph, B., Joseph, L., Jose, B., & John, A. K. (2025) · Frontiers in Education · doi:10.3389/feduc.2025.1647687 · Cited by 63 · see citing works
Transforming mental health research and care through artificial intelligence
Opel, N., & Breakspear, M. J. (2026) · Science · doi:10.1126/science.adz9193 · Cited by 25 · see citing works
Rethinking urban AI: a critical posthumanist perspective on intelligence, autonomy, and agency
Iapaolo, F., & Lynch, C. R. (2025) · Urban Geography · doi:10.1080/02723638.2025.2510812 · Cited by 15 · see citing works
The Leadership Tree Model: A Global and AI‐Enhanced Framework for Leadership Development
Yang, Y., & Jimenez‐Luque, A. (2025) · New Directions for Student Leadership · doi:10.1002/yd.20674 · Cited by 11 · see citing works
Indigenous AI Futures: Uncle Chatty Gee, Aunty Lexi, and Algorithmic Settler Colonialism
Worrell, T., & Carlson, B. L. (2025) · Somatechnics · doi:10.3366/soma.2025.0468 · Cited by 8 · see citing works
Olaniyan, Y. D., Martins, M. O., & Al Maqrashi, R. H. (2026) · Frontiers in Human Dynamics · doi:10.3389/fhumd.2026.1790324 · Cited by 8 · see citing works
Towards a decolonial AI sovereignty model for indigenous educational settings
Mbah, M. F., & Jarvis, L. (2026) · Cogent Education · doi:10.1080/2331186x.2026.2626631 · Cited by 7 · see citing works
Yaroglu, A. C. (2024) · Kybernetes · doi:10.1108/k-09-2024-2379 · Cited by 7 · see citing works
Mhasakar, M., Baker-Ramos, R., Carter, B., Helekahi-Kaiwi, E.-B., & Hester, J. (2025) · Proceedings of the Extended Abstracts of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706599.3720282 · Cited by 6 · see citing works
Sovereignty in the digital age Indigenous perspectives on health data and emerging technologies
Hurst, S., Dhein, K., Yracheta, J., & Mackey, T. K. (2026) · SSM - Qualitative Research in Health · doi:10.1016/j.ssmqr.2025.100698 · Cited by 7 · see citing works
Mzimela, J. H., & Moyo, I. (2026) · Discover Education · doi:10.1007/s44217-026-01259-6 · Cited by 5 · see citing works
Echoes of power: investigating geopolitical bias in US and China large language models
Pacheco, A. G. C., Cavalini, A., & Comarela, G. (2026) · Humanities and Social Sciences Communications · doi:10.1057/s41599-026-06577-6 · Cited by 5 · see citing works
Handling the hype: Demystifying artificial intelligence for memory studies
Merrill, S., Makhortykh, M., Mandolessi, S., Walden, V. G., Smit, R., & Wang, Q. (2025) · Memory Mind & Media · doi:10.1017/mem.2025.10018 · Cited by 7 · see citing works
Caughman, L., Lauer, C., & Carradini, S. (2026) · Information Design Journal · doi:10.1075/idj.25022.cau · Cited by 4 · see citing works
Jamaluddin, A. B., Pratiwi, A. C., & Bahri, A. (2026) · Journal of Applied Research in Higher Education · doi:10.1108/jarhe-10-2025-0868 · Cited by 3 · see citing works
Entrepreneurship 5.0: Synchronizing Technology and Human Factor
Rajagopal, N. A. (2026) · Palgrave studies of entrepreneurship and social challenges in developing economies · doi:10.1007/978-3-031-98513-3_20 · Cited by 2 · see citing works
Bittner, D., Smith, J. U., Leontidis, G., Campbell, G. A., Biegel, J., Smith, P., Kuhnert, M., Skalský, R., Giuliani, L. M., Salik, A. W., et al. (2026) · Environmental Research Letters · doi:10.1088/1748-9326/ae3975 · Cited by 3 · see citing works
Multimodal RAG for cultural heritage: a technical exploration based on Jino traditional knowledge
Zhou, X., & Lin, J. (2026) · Digital Scholarship in the Humanities · doi:10.1093/llc/fqag042 · Cited by 2 · see citing works
Co-Designing Islamic AI Ethics: Insights from the UK Muslim Community
Campbell-Esen, R., Mahoney, J., & Talhouk, R. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790413 · Cited by 2 · see citing works
Stevens, N., & Gieseking, J. J. (2026) · Transactions of the Institute of British Geographers · doi:10.1111/tran.70046 · Cited by 2 · see citing works
Cultural Intelligence in AI Ethics: A Systematic Framework for Implementation Across Global Contexts
Kumar, D., Kumar, K., Choudhary, R. K., & Singh, V. (2025) · International Conference on Intelligent Systems, Advanced Computing and Communication (ISACC) · doi:10.1109/isacc65211.2025.10969295 · Cited by 1 · see citing works
Alterator, S., Maddox, A., Southerton, C., & Schutt, S. (2025) · British Journal of Sociology of Education · doi:10.1080/01425692.2025.2586732 · Cited by 1 · see citing works
Indongo, N. N., Kays, R., Daniel, V. S., Kaulinge, J. H., Guiob-Badmos, C., Soabes, M. L. G., Beukes, F., Smith, R. C., & Winschiers‐Theophilus, H. (2025) · International Conference on Emerging Trends in Networks and Computer Communications (ETNCC) · doi:10.1109/etncc66224.2025.11299788 · Cited by 1 · see citing works
Jogalekar, J., & Lenka, R. M. (2025) · International Journal of Information Technology · doi:10.1007/s41870-025-02936-9 · Cited by 1 · see citing works
Chen, J. (2026) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-06473-5 · Cited by 1 · see citing works
An Exploratory Study of AI in Culturally Sensitive Design in Context of Indian Crafts
Vats, A., & Bhattacharjee, A. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2633209 · Cited by 1 · see citing works
Kavanagh, E. (2026) · AI & Society · doi:10.1007/s00146-026-02938-6 · Cited by 1 · see citing works
Artificial intelligence, climate resilience, and indigenous knowledge in environmental governance
González, J. L. G. (2026) · AI & Society · doi:10.1007/s00146-026-02982-2 · Cited by 1 · see citing works
AI and Education for Planetary Flourishing: Towards Earth-Alignment
Stein, S. (2026) · Postdigital Science and Education · doi:10.1007/s42438-026-00643-7 · Cited by 2 · see citing works
Kavanagh, E. (2026) · Journal of Decision System · doi:10.1080/12460125.2026.2662348 · Cited by 1 · see citing works
A Guide to Constructing Indigenous Statistical Spaces for Prevention Science Research
de la Sierra, V. Q. (2026) · Prevention Science · doi:10.1007/s11121-026-01911-5 · Cited by 1 · see citing works
The microfoundations of human-AI knowledge co-creation – an emergent knowledge perspective
Shet, S. V., Coutinho, A., Panda, S., & Panchal, D. B. (2026) · Journal of Knowledge Management · doi:10.1108/jkm-08-2025-1212 · Cited by 2 · see citing works
Indongo, N. N., Smith, R. C., Winschiers-Theophilus, H., Kandjengo, S., & Mbinge, U. (2026) · Proceedings of the 19th Participatory Design Conference 2026, Vol. 1: Full Papers · doi:10.1145/3796624.3796667
Medina, N. C., Mendoza, C. P., & Albornoz, G. P. (2024) · Journal Boliviano de Ciencias · doi:10.52428/20758944.v20i56.1209
Reparative research for the climate and nature emergency
Stein, S. E., & Bowness, E. (2025) · Climate and Development · doi:10.1080/17565529.2025.2574075
Becker, K., Vögele, N., Surmann, H., Lubos, D., Rogowski, T., Yildiz, M. U., Abdelazim, A., Koruhama, A. K., & Winschiers‐Theophilus, H. (2025) · African Human Computer Interaction Conference (AfriCHI) · doi:10.1145/3757232.3757266
Bennett, R., Liddelow‐Hunt, S., Hastie, B., & Readman, E. (2025) · Somatechnics · doi:10.3366/soma.2025.0469
Enabling Diversity and Gender Equity in Human-Centered AI
Anderson, T. D., & Marshall, R. (2026) · Springer eBooks · doi:10.1007/978-981-97-8440-0_104-1
Exploring GenAI’s Potential Contributions as a Partner in SoTL Research: The Practice Model
Miller-Young, J. E., Hays, L., & McCollum, B. M. (2026) · Teaching & Learning Inquiry The ISSOTL Journal · doi:10.20343/teachlearninqu.14.7
Koenig, P. D., & Rone, J. (2026) · Information Communication & Society · doi:10.1080/1369118x.2026.2645876
CRIXP: Cultural Knowledge Representation for Inherent eXPlainability
Sharma, A., & Jain, S. (2026) · IEEE Transactions on Computational Social Systems · doi:10.1109/tcss.2026.3674361
Whose Knowledge Counts? Co-Designing Community-Centered AI Auditing Tools with Educators in Hawai'i
Zhao, D., Cha, H., Ryan, M. J., Wang, A., Baker-Ramos, R., Helekahi-Kaiwi, E.-B., Diego, R., Hester, J. D., & Yang, D. (2026) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3790958 · Cited by 1 · see citing works
AI for climate: from technological solutions to relational accountability
Stein, S. (2026) · npj Climate Action · doi:10.1038/s44168-026-00376-0
Potential futures for the IPCC’s approach to artificial intelligence
Buck, H. J., Khourdajie, A. A., Asayama, S., & Geden, O. (2026) · Communications Earth & Environment · doi:10.1038/s43247-026-03514-y
The Hard Political Problem: Artificial intelligence as a subject of governancePreprint
Hand, M. C. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6668598
Asɛmpayɛtsia: An Afrocentric Framework for Computational Creativity in Sound and Image
Dawson, N. A. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-24350-8_4
Do AIs dream of electric trees? Traditional knowledge and AI in environmental issues
Ojeda-Zavala, N. (2026) · Ai & Society · doi:10.1007/s00146-026-03011-y
Image of the Human Being: Intercultural Communication
Schellhammer, B. A. (2026) · Springer eBooks · doi:10.1007/978-3-031-51703-7_252-1
Enabling Diversity and Gender Equity in Human-Centered AI
Anderson, T. D., & Marshall, R. (2026) · Springer eBooks · doi:10.1007/978-981-95-3658-0_104
The Weird Turn: Spillovers of Weird Fiction into Ecology and Economy
Boletsi, M., & Soudias, D. (2025) · Parallax · doi:10.1080/13534645.2025.2638866
Kanungo, S. S., Samarpita, S., & Biswal, R. (2026) · ShodhKosh Journal of Visual and Performing Arts · doi:10.29121/shodhkosh.v7.i14s.2026.8563
Reimagining Heritage through AI and Co-Creation: A Systematic Literature Review
Almadhoob, H., & Khalfan, M. (2025) · International Conference on Sustaining Heritage (ICSH) · doi:10.1109/icsh68040.2025.11547934
Yang, Y., Huang, J., & An, R. (2026) · Springer eBooks · doi:10.1007/978-3-032-18443-6_21
Baker-Ramos, R., Mhasakar, M., Raja, V. K. B., Helekahi-Kaiwi, E.-B., Gelder, W., Carter, B., Diego, R., Cabral, A., & Hester, J. D. (2026) · ACM International Conference on Interaction Design and Children (IDC) · doi:10.1145/3773077.3806104
Sankaran, S. (2026) · AI & Society · doi:10.1007/s00146-026-03183-7
Saikia, D., Basumatary, P., & Saikia, A. (2026) · AI & Society · doi:10.1007/s00146-026-03181-9
Emerging Media Arts and Environmental Futures
Galafassi, D., & Moore, M. (2026) · World Futures Review · doi:10.1177/19467567261461912
Waiwiri, R., Cataldi, T., Whaanga, K., Fortin, J., Witehira, J. G. P., & Lewis, J. E. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-29900-0_22
Self-citationMarinov, R., Castaño-Suárez, O. M., Yolgörmez, C., Lewis, J. E., & Diamond, S. L. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-30552-7_9
Self-citationArtificial intelligence as a pedagogical companion for STEM research learning in higher education
Valentine Joseph Owan, P. D. (2026) · Discover Education · doi:10.1007/s44217-026-01906-y · Cited by 1 · see citing works
Future Imaginaries of Indigenous AI
Yolgörmez, C., Kite, S., Brown, M. L., & Lewis, J. E. (2026) · Imaginations Journal of Cross-Cultural Image Studies · doi:10.17742/image29762
Self-citationMore-than-Human Education Governance: An Introduction
Landri, P., & Peruzzo, F. (2026) · Educational governance research · doi:10.1007/978-3-032-29276-6_1
Revitalizing India's Intangible Cultural Heritage Through Indigenous Knowledge Systems
Chaturvedi, P., & Ranjan, A. (2026) · IGI Global eBooks · doi:10.4018/979-8-2600-2890-2.ch001
Nally, D. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-36775-5.00026-6
Ethical and inclusive challenges of integrating AI and indigenous knowledge systems
Tampubolon, M. (2026) · AI & Society · doi:10.1007/s00146-026-03185-5
Ali, J. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-7837-4.ch001
Reimagining Leadership in the Age of AI: Questioning Authority, Agency, and Pedagogy
Jimenez‐Luque, A., & Yang, Y. (2026) · New Directions for Student Leadership · doi:10.1002/yd.70064
Indigenous Knowledge Systems and AI
Gupta, D., Gayratovich, E. N., Akishova, S., Rasulova, I., Sottarov, A., & Nazirjon, R. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-7837-4.ch008
Introduction: Rethinking data colonialism: Local negotiations with data, postcoloniality, and power
Dutta, S., Mazumdar, S., & McInerney, K. (2026) · Big Data & Society · doi:10.1177/20539517261455429
AI Within the Dialectic of Ethics and Equity
Bonab, A. B., & Rudko, I. (2026) · Philosophy & Technology · doi:10.1007/s13347-026-01179-1
Prince, L., McIntosh, J., Maniapoto, T., Noe, K., Loban, R., Hester, J. D., & Barcham, M. (2026) · Nordic Conference on Human-Computer Interaction · doi:10.1145/3821402.3830123
Advancing Cyclone Resilience Through Community-Centered and Glocally-Informed AI Systems
Chakravarty, P., Gattupalli, S., Chakravarty, U., Chand, G., & Atandi, B. B. (2026) · Springer eBooks · doi:10.1007/978-3-032-28745-8_11
AI is locking out Indigenous voices: Toward more equitable futures
Cachipuendo-Contero, I. J., & Yeager, J. (2026) · Big Data & Society · doi:10.1177/20539517261498673
Wang, G., Bennamoun, H., Kwok, W. H., Raza, R., Sohel, F. A., Kelly, B., Ratajczak, T., Reid, C. L., Marriott, R., Walker, R., et al. (2026) · PLOS Digital Health · doi:10.1371/journal.pdig.0001709
Shah, S. S. (2026) · World Development Perspectives · doi:10.1016/j.wdp.2026.100841
Managing product availability using AI-enabled blockchain technology
Sheikh, A. A., Hassan, N. M., Zafar, H., Yu, Z., & Khan, S. A. R. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-30094-3.00001-1
Seleke, B. (2026) · New Zealand Journal of Educational Studies · doi:10.1007/s40841-026-00495-6
Decolonizing LLMs for Indigenous languages: a functional or critical interculturality perspective?
Hernández, J. L. V., & Valdivia, A. (2026) · Tapuya Latin American Science Technology and Society · doi:10.1080/25729861.2026.2728456
- Authors
- Lewis, J. E., Whaanga, H., & Yolgörmez, C.
- Affiliations
- Concordia University (CA)
- Massey University (NZ)
- Corresponding author
- Yolgörmez, Ceyda
- Venue
- AI & SOCIETY
- Published
- 2024-10-19
- Volume
- 40
- Issue
- 4
- Pages
- 2141-2157
- ISSN
- 0951-5666 (ISSN-L)
- 1435-5655
- OpenAlex
- W4403567707
- Semantic Scholar
- 027b6b788b2881c350dbe6b7d6e8b7328d1b09be
- Cited by
- 80
- References
- 60
- Citations by year
- 2026: 62 · 2025: 16 · 2024: 2
- FWCI
- 33.25
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- AI & Society (publishedVersion, cc-by-nc-nd)
- Funders
- Social Sciences and Humanities Research Council (895-2023-1022)
- Canada Research Coordinating Committee (NFRFT-2022-00241)
- Topics
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Health › Indigenous Health, Education, and Rights
- Social Sciences › Sociology and Political Science › Feminist Epistemology and Gender Studies
- Keywords
- artificial intelligence, indigenous knowledge, epistemology of AI, concept of intelligence, colonialism, Western rationalism, algorithmic bias, Indigenous-led research, embodied knowledge
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-30.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-30.
Cited sources are checked by gpt-6-sol.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review