The DOI matches its Crossref record; 71 of the 74 references it cites were found in a registry or an index; none of the 64 sources its claims cite is checked for support yet.
Algorithmic injustice: a relational ethics approach
Open accessAbstract
It has become trivial to point out that algorithmic systems increasingly pervade the social sphere. Improved efficiency-the hallmark of these systems-drives their mass integration into day-to-day life. However, as a robust body of research in the area of algorithmic injustice shows, algorithmic systems, especially when used to sort and predict social outcomes, are not only inadequate but also perpetuate harm. In particular, a persistent and recurrent trend within the literature indicates that society's most vulnerable are disproportionally impacted. When algorithmic injustice and harm are brought to the fore, most of the solutions on offer (1) revolve around technical solutions and (2) do not center disproportionally impacted communities. This paper proposes a fundamental shift-from rational to relational-in thinking about personhood, data, justice, and everything in between, and places ethics as something that goes above and beyond technical solutions. Outlining the idea of ethics built on the foundations of relationality, this paper calls for a rethinking of justice and ethics as a set of broad, contingent, and fluid concepts and down-to-earth practices that are best viewed as a habit and not a mere methodology for data science. As such, this paper mainly offers critical examinations and reflection and not "solutions."
Overview
AI snapshot
Written from the paper’s full text.
TL;DR
Birhane argues that algorithmic injustice is perpetuated by technical fixes that fail to center disproportionately impacted communities, and proposes a shift from rational to relational ethics. Relational ethics grounds justice and ethics in context, history, lived experience, and power asymmetries rather than technical solutions.
Key findings
- The paper contends that dominant responses to algorithmic harm—such as debiasing datasets and fairness metrics—are inadequate because they treat bias as a static deviation from a “correct” description and obscure structural, historical, and power asymmetries.
- It proposes four tenets of relational ethics: knowing that centers human relations and the disproportionately impacted; bias is not a deviation from the “correct” description; prioritizing understanding over prediction; and treating data science as a practice that alters the social fabric.
- It claims marginalized groups are disproportionately harmed by algorithmic systems and hold epistemic privilege to recognize harm, citing examples including object detection, recidivism, gender recognition/classification, and medicine.
- It calls for ethics as a down-to-earth habit and practice, not a mere methodology or tool, and states that this work is never done.
Methods
- Design: critical, conceptual, and reflective essay; no empirical study, dataset, or sample is used.
- Main analysis: comparative and philosophical argument drawing on Afro-feminist epistemology, enactive cognitive science, ubuntu, Bakhtinian dialogism, and complexity science to contrast rationality and relationality.
- No quantitative analysis or original numerical results are reported.
Limitations
- The paper states it mainly offers critical examinations and reflection and not “solutions”; it is not a set of general guidelines, principles, or out-of-the-box tools.
- The paper states relational ethics is not a rationally constructed abstract “theory of ethics” and does not provide implementable remedies.
- Evident from the text: no empirical validation, case study, or measurement is provided; the framework is conceptual and programmatic.
Model-written summary. Check it against the paper before relying on it.
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Claims the paper makes
60 Not checked yet · 23 No basis given · 17 Own interpretation
In the paper
“Pushing back against the dominant Western orthodoxy, Afro-feminist epistemology grounds knowing in an active and engaged practice.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [31] Collins, 2002
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In the paper
“Mhlambi11 has further argued that the AI industry, grounded in rationality, reproduces harmful and discriminatory outcomes.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
What the sources say
- Not checked yetcites [11] Mhlambi, 2020, From rationality to relationality: ubuntu as an ethical and human rights framework for artificial intelligence governance
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In the paper
“The reality of the Western straight white male then masquerades as the invisible background that is taken as the “normal,” “standard,” or “universal” position.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
What the sources say
- Not checked yetcites [17] Ahmed, 2007, A phenomenology of whiteness, Femin. Theor. source
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In the paper
“a persistent and recurrent trend within the literature indicates that society's most vulnerable are disproportionally impacted.”
§ Algorithmic injustice: a relational ethics approach > Abstract
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In the paper
“In contrast, for Afro-feminist thought, the researcher is an important participant in the knowledge production process.33”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [33] Nnaemeka, 2004, Nego-feminism: theorizing, practicing, and pruning Africa’s way, Signs source
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In the paper
“Unjust and harmful outcomes, as a result, are treated as side effects that can be treated with technical solutions such as “debiasing” datasets8 rather than problems that have deep roots in the mathematization of ambiguous and contingent issues, historical inequalities, and asymmetrical power hierarchies or unexamined problematic assumptions that infiltrate data practices.”
§ Algorithmic injustice: a relational ethics approach > Introduction
What the sources say
- Not checked yetcites [8] Gonen, 2019, Lipstick on a pig: debiasing methods cover up systematic gender biases in word embeddings but do not remove them, arXiv
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In the paper
“The intrinsically political tasks of categorizing and predicting things such as “acceptable” behavior, “ill” health, and “normal” body type then pass as apolitical technical sorting and categorizing tasks.7”
§ Algorithmic injustice: a relational ethics approach > Introduction
What the sources say
- Not checked yetcites [7] Bowker, 2000
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In the paper
“Data science, and the wider discipline of computer science, have implicitly or explicitly inherited this worldview.11”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
What the sources say
- Not checked yetcites [11] Mhlambi, 2020, From rationality to relationality: ubuntu as an ethical and human rights framework for artificial intelligence governance
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In the paper
“according to the sub-Saharan tradition of ubuntu as encapsulated by Mbiti's28 phrase “I am because we are, and since we are, therefore I am,” a person comes into being through the web of relations.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [28] Mbiti, 1969
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In the paper
“socially and politically contested matters that were traditionally debated in the open are now reduced to mathematical problems with a technical solution.6”
§ Algorithmic injustice: a relational ethics approach > Introduction
What the sources say
- Not checked yetcites [6] McQuillan, 2020, Non-fascist AI
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“In the process of data collection, for example, the data scientist decides what is worth measuring (making some things visible and others invisible by default) and how.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
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In the paper
“Wisdom, and not “book learning,” enables one to resist oppression.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [31] Collins, 2002
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The rational worldview that aspires to an “objective” knowledge from a “God's eye view” has resulted in the treatment of the researcher as invisible, and their interests, motivations, and background as inconsequential.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
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In the paper
“In the desire to establish timeless and absolute knowledge, abstract and contextless reasoning is prioritized over concrete lived experience submersed in co-relations, interdependence, fluidity, and connectedness.16”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
What the sources say
- Not checked yetcites [16] Merleau-Ponty, 1968
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In the paper
“Knowledge claims are not worked out in isolation from others but are developed in dialog with the community.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [31] Collins, 2002
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Relational frameworks emphasize the primacy of relations and dependencies.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
plain- Asserted: passes — The authors put it forward as true.
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In the paper
“Knowledge, according to this worldview, is rooted in the ideal rational, static, self-contained, and self-sufficient subject that contemplates the external world from afar in a “purely cognitive” manner as a disembodied and disinterested observer.15”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
What the sources say
- Not checked yetcites [15] Gardiner, 1998, The incomparable monster of solipsism: Bakhtin and Merleau-Ponty
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In the paper
“Knowing and being are active processes that are necessarily political and ethical.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [31] Collins, 2002
plaincorrelational- Asserted: passes — The authors put it forward as true.
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None of the sources cited for this claim have been checked yet.
In the paper
“algorithmic systems, especially when used to sort and predict social outcomes, are not only inadequate but also perpetuate harm.”
§ Algorithmic injustice: a relational ethics approach > Abstract
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“However, despite the association of Bayes with rational predictions, Bayesian models are prone to spurious relationship and amplification of socially held stereotypes.24”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
What the sources say
- Not checked yetcites [24] Pager, 2009, Bayesian bigot? Statistical discrimination, stereotypes, and employer decision making, Ann. Am. Acad. Polit. Soc. Sci. source
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Subsequently, discussions and understanding of concepts such as knowledge and ethics tend to be abstract, genderless, contextless, and raceless.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
plain- Asserted: passes — The authors put it forward as true.
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“can be exemplified by the deep contention that reason and logical coherence are superior for knowledge production (in understanding the world) above and beyond relational and embodied becoming.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Since the rational worldview has come to be seen as the standard, anything outside of this is viewed as an outlier.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“A proponent of this position, Hanne De Jaegher,35 contends that our most sophisticated human knowing lies in how we engage with each other.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [35] De Jaegher, 2019, Loving and knowing: reflections for an engaged epistemology, Phenomenol. Cogn. Sci.
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In the paper
“The privileging of reason as the ultimate criterion makes knowing a distant act.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
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In the paper
“Far from a distant and “objective” discretizing logic, knowing is an activity that happens in the relationship between the knower and the known.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [35] De Jaegher, 2019, Loving and knowing: reflections for an engaged epistemology, Phenomenol. Cogn. Sci.
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In the paper
“Kyselo,27 for example, contends that the self is social through and through—it is co-generated in interactions and relations with others.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [27] Kyselo, 2014, The body social: an enactive approach to the self, Front. Psychol. source
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In the paper
“Current data practices, for the most part, follow the rational model of thinking where data are assumed to represent the world out there in a “neutral” way.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
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In the paper
“In the process of data cleaning, rich information that provides context about which data are collected and how datasets are structured is stripped away.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
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In the paper
“Ahmed17 contends that all bodies inherit history and the inheritance of Cartesianism is grounded in a white straight ontology.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
What the sources say
- Not checked yetcites [17] Ahmed, 2007, A phenomenology of whiteness, Femin. Theor. source
plaindirect- Asserted: passes — The authors put it forward as true.
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In the paper
“Any data scientist working to automate issues of a social nature, in effect, is engaged in making moral and ethical decisions”
§ Algorithmic injustice: a relational ethics approach > Introduction
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In the paper
“The rational view serves as the backbone for much of Western science and philosophy, permeating most fields of enquiry”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
What the sources say
- Not checked yetcites [11] Mhlambi, 2020, From rationality to relationality: ubuntu as an ethical and human rights framework for artificial intelligence governance
- Not checked yetcites [12] Terry, 1986
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In the paper
“Bakhtin29 emphasized that nothing is simply itself outside the matrix of relations in which it exists.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [29] Bakhtin, 1984
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In the paper
“The most reliable form of knowledge, especially concerning social and historical injustice, is grounded in lived experience.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [31] Collins, 2002
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In the paper
“At the heart of it, the Afro-feminist approach to knowing contends that concrete experiences are primary and abstract reasoning secondary.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [31] Collins, 2002
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In the paper
“The mathematization and formalization of social issues brings with it a veneer of objectivity and positions its operations as value-free, neutral, and amoral.”
§ Algorithmic injustice: a relational ethics approach > Introduction
What the sources say
- Not checked yetcites [7] Bowker, 2000
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In the paper
“Data science and data practices reincarnate rationalism in many forms, including in the manner in which messiness, ambiguity, and uncertainty are not tolerated”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
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In the paper
“Distant statistics or theoretical accuracies do not take precedence over the actual experience of a person.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [31] Collins, 2002
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In the paper
“The deep quest for the rational worldview is certainty, stability, and order, and thus isolation, separation, and clear binaries form the foundations in place of connectedness, interdependence, and dynamic relation.13”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
What the sources say
- Not checked yetcites [13] Prigogine, 1984
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In the paper
“Selfhood and knowledge are evolving and dynamic; the self is never finished—it is an open book.30”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [30] Birhane, 2017, Descartes was wrong:‘a person is a person through other persons’, Aeon
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Not only does the inheritance of rationality to data sciences and computation make these fields inadequate to deal with complex and inherently indeterminable phenomena”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Rationality: the dominant orthodoxy
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The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Contrary to the rationalist and individualist worldview, relational perspectives view existence as fundamentally co-existent in a web of relations.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“Any generalization or theory constructed in the absence of deep understanding, not grounded in the concrete and particular, is vacuous.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Prioritizing of understanding over prediction
What the sources say
- Not checked yetcites [58] Geertz, 1973
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. It may be too vague to check against evidence.
In the paper
“machine learning presents an extreme case of a very human predicament, which is that the only way we can generalize is on the basis of past experience.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Prioritizing of understanding over prediction
What the sources say
- Not checked yetcites [61] Gross
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In a supposedly objective worldview, bias, injustice, and discrimination are (mis)conceived as being able to be permanently corrected.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Bias is not a deviation from the “correct” description
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
None of the sources cited for this claim have been checked yet.
In the paper
“Furthermore, gender classification systems often operate under essentialist assumptions and operationalize gender in a trans-exclusive way, resulting in disproportionate harm to trans people.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Knowing that centers human relations
What the sources say
- Not checked yetcites [48] Hamidi, 2018, Gender recognition or gender reductionism? The social implications of embedded gender recognition systems
- Not checked yetcites [50] Keyes, 2018, The misgendering machines: trans/HCI implications of automatic gender recognition, Proc. ACM Hum.-Comput. Interact.
plaindirect- Asserted: passes — The authors put it forward as true.
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- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Eventness is always particular, and never exhaustively describable in terms of rules.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Prioritizing of understanding over prediction
What the sources say
- Not checked yetcites [59] Morson, 1989
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
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- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
In the paper
“The machine-detected patterns often provide “answers” to fuzzy, contingent, and open-ended questions. These “answers” neither reveal any causal relations nor provide explanation on why or how.65”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Data science as a practice that alters the social fabric
What the sources say
- Not checked yetcites [65] Pasquale, 2015
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
In the paper
“our deepest intuitions about all sorts of things, and in particular justice and injustice, can change dramatically.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Prioritizing of understanding over prediction
What the sources say
- Not checked yetcites [61] Gross
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“For any individual person, community, or situation, algorithmic classifications and predictions give either an advantage or they hinder.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Data science as a practice that alters the social fabric
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
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- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Humans are inherently historical, social, cultural, gendered, politicized, and contextualized organisms.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
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Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
In the paper
“Proposing an understanding of human knowing in analogy with loving, De Jaegher argues that in knowing, like loving, what happens is not neutral, general, or universal.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [35] De Jaegher, 2019, Loving and knowing: reflections for an engaged epistemology, Phenomenol. Cogn. Sci.
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“neither people nor the environment and context in which they are embedded are static.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Bias is not a deviation from the “correct” description
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
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Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The rationalist tradition's tendency toward timeless and generalizable knowledge aspires to establish timeless laws and generalizable theories.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Prioritizing of understanding over prediction
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“Not only do machine-learning systems detect patterns and cluster similarities, they also make predictions based on the observed patterns.62”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Prioritizing of understanding over prediction
What the sources say
- Not checked yetcites [62] O’Neil, 2013
plain- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Nonetheless, the relational versus rational divide is not something that can be clearly demarcated, but overlaps with fuzzy boundaries.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
In the paper
“Likewise, the historian of science Lorraine Daston contends that the endeavor for a universal law is a predicament that does not stand against unanticipated particulars, since no universal ever fits the particulars.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Prioritizing of understanding over prediction
What the sources say
- Not checked yetcites [60] Daston, 2018, Calculation and the division of labor, 1750-1950, Bull. German Hist. Inst.
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Since knowing is a relational affair, it matters who enters into the knower-known relations.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Knowing that centers human relations
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
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Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Machine-learning systems “work” by identifying patterns in vast amounts of data.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Prioritizing of understanding over prediction
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. The paper may give no reason why it holds.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“What society deems fair and ethical changes over time and with context and culture.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Bias is not a deviation from the “correct” description
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
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- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
In the paper
“To understand people, we must take into account “unrepeatable contextual meaning.””
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Prioritizing of understanding over prediction
What the sources say
- Not checked yetcites [59] Morson, 1989
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
In the paper
“Living bodies, according to Di Paolo et al.,37 are processes, practices, and networks of relations which have “more in common with hurricanes than with statues.””
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [37] Di Paolo, 2018
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Machine learning, at its core, is a tool that predicts. It reveals statistical correlations with no understanding of causal mechanisms.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Prioritizing of understanding over prediction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may state two separate claims as one.
In the paper
“While the latter approaches often neglect those at the margins53 and shy away from power asymmetries and structural inequalities that permeate the social world”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Knowing that centers human relations
What the sources say
- Not checked yetcites [53] Harrington, 2020, The forgotten margins: what is community-based participatory health design telling us?, Interactions source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“The findings of Wilson et.al.,44 for instance, demonstrate that object detection systems designed to predict pedestrians display higher error rates identifying dark-skinned pedestrians while light-skinned pedestrians are identified with higher precision.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Knowing that centers human relations
What the sources say
- Not checked yetcites [44] Wilson, 2019, Predictive inequity in object detection, arXiv
boostedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Accordingly, their knowing and understanding of the world around them necessarily takes place through their respective lenses.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although datasets are often part of the problem, this commonly held belief relegates deeply rooted societal and historical injustices, nuanced power asymmetries, and structural inequalities to mere datasets.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Bias is not a deviation from the “correct” description
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Concepts such as bias, fairness, and justice, however, are moving targets.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Bias is not a deviation from the “correct” description
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Furthermore, underlying the idea of “fixing” bias is the assumption that there exists a single correct description of reality where a deviation from it has resulted in bias.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Bias is not a deviation from the “correct” description
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
In the paper
““Our most sophisticated knowing,” according to De Jaegher, “is full of uncertainty, inconsistencies, and ambiguities.””
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
What the sources say
- Not checked yetcites [35] De Jaegher, 2019, Loving and knowing: reflections for an engaged epistemology, Phenomenol. Cogn. Sci.
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Before we delve into that, it is worth reemphasizing that while the rational worldview tends to see knowledge, people, and reality in general as stable, for relational perspectives, we are fluid, active, and continually becoming.”
§ Algorithmic injustice: a relational ethics approach > Relational ethics: the roots > Relationality
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The harm, bias, and injustice that emerge from algorithmic systems varies and is dependent on the training and validation data used, the underlying design assumptions, and the specific context in which the system is deployed, among other factors.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Knowing that centers human relations
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. The paper may give no reason why it holds.
In the paper
“Bakhtin argues that such attempts to abstract general rules from particulars “loses the most essential thing about human activity, the very thing in which the soul of morality is to be found,” which Bakhtin calls the “eventness” of the event.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Prioritizing of understanding over prediction
What the sources say
- Not checked yetcites [59] Morson, 1989
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“These systems process people's behaviors, actions, and the social world at large.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Data science as a practice that alters the social fabric
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The core of what machine-learning systems do can be exemplified as clustering similarities and differences, abstracting commonalities, and detecting patterns.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Prioritizing of understanding over prediction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“the most marginalized hold the epistemic privilege to recognize harm and injustice”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Knowing that centers human relations
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds.
None of the sources cited for this claim have been checked yet.
In the paper
“Some identities (and not others) are recognized as a pedestrian,44 or fit for an STEM career,69 or in need of medical care.1 Some are ignored and made invisible altogether.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Data science as a practice that alters the social fabric
What the sources say
- Not checked yetcites [44] Wilson, 2019, Predictive inequity in object detection, arXiv
- Not checked yetcites [69] Lambrecht, 2019, Algorithmic bias? An empirical study of apparent gender-based discrimination in the display of STEM career ads, Manag. Sci. source
- Not checked yetcites [1] Obermeyer, 2019, Dissecting racial bias in an algorithm used to manage the health of populations, Science source
plaincorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Seemingly banal tasks such as identifying and predicting “employable” or “criminal” characteristics carry grave consequences for those that do not conform to the status quo.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Data science as a practice that alters the social fabric
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The process of categorizing, sorting, and generalizing, therefore, is far from a mere technical task.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Data science as a practice that alters the social fabric
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Algorithmic systems never emerge in a social, historical, and political vacuum, and to divorce them from the contingent background in which they are embedded is erroneous.”
§ Algorithmic injustice: a relational ethics approach > Closing remarks
plain- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
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- Based: fails — The paper may give no reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. The paper may give no reason why it holds. It may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Certain patterns are made visible and types of being objectified while other types are erased.”
§ Algorithmic injustice: a relational ethics approach > Ethics built on the foundations of relationality > Data science as a practice that alters the social fabric
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: fails — It may be too vague to check against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. It may be too vague to check against evidence. It may state two separate claims as one.
The paper relies on this without support.
Most solutions on offer for algorithmic injustice revolve around technical solutions.
“most of the solutions on offer (1) revolve around technical solutions”
The paper relies on this without support.
Most solutions on offer for algorithmic injustice do not center disproportionally impacted communities.
“and (2) do not center disproportionally impacted communities.”
The paper relies on this without support.
Automated and standardized solutions to complex social issues often contribute more harm than good.
“automated and standardized solutions to complex and contingent social issues often contribute more harm than good”
The paper relies on this without support.
Algorithmic systems increasingly pervade the social sphere.
“algorithmic systems increasingly pervade the social sphere.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“concerns over GenAI's sustainability also intersect with social justice issues, as communities that already suffer environmental disadvantages stand to be disproportionately harmed [16]”
From Understanding the Practices, Perceptions, and (Dis)Trust of Generative AI among Instructors: A Mixed-methods Study in the U.S. Higher Education (2025) · cites this paper as [16]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Nevertheless, Birhane (2021) argues that Western AI often imposes rigid, decontextualized systems that clash with the communal and contextual ways knowledge is held in Indigenous cultures.”
From Data colonialism and indigenous languages in AI: a critical review of existing initiatives and their struggles with data sovereignty (2026) · cites this paper as Birhane 2021
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“This concentration of agenda-setting power and dominance of a small set of corporate actors risks narrowing the imaginaries of AI futures, privileging commercial interests over broader social concerns [6, 8, 21].”
From Reimagining Open Source and Openness in AI: Co-Creating Responsible Technological Futures (2026) · cites this paper as [8]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The current AI field is shaped by rapid cycles of innovation and hype, with dominant generative AI narratives and agendas largely led by a narrow set of powerful actors (particularly large technology firms, but also influential standards bodies and platform owners) who exercise disproportionate influence in how openness is defined, operationalized, and legitimized.”
From Reimagining Open Source and Openness in AI: Co-Creating Responsible Technological Futures (2026) · cites this paper as [8]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“AI fairness scholarship has already underscored the need to examine power distribution and structures of exclusion inhabited by AI technologies [15, 93].”
From AI and Non-Western Art Worlds: Reimagining Critical AI Futures through Artistic Inquiry and Situated Dialogue (2025) · cites this paper as [15]
In the citing paper
“These systems have been shown to reinforce social and historical human prejudices and people who are traditionally marginalized in our society are disproportional negatively impacted [8].”
From Current Challenges and Future Opportunities for XAI in Machine Learning-Based Clinical Decision Support Systems: A Systematic Review (2021) · cites this paper as [8]
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Five views on the foundations of data science
Kristal, B. S., McCradden, M. D., Thiyagalingam, J., Zhang, Z., & Goble, C. (2026) · Patterns · doi:10.1016/j.patter.2026.101566
“Abeba Birhane 9 offers a justice-based framing of how statistical biases reflect real systematic patterns of differential treatment and problematizes how data science encourages ‘‘solution-ism’’ under the backdrop of deeply complex social conditions.”
InfluentialPublic say versus public sway: ‘Lived experience literacy’ in the pursuit of participatory AI
Annand, P., Garasto, S., & Groves, L. (2026) · Big Data & Society · doi:10.1177/20539517261447845
“It is not simply procedural but epistemic, requiring a process of unlearning embedded hierarchies that have historically devalued experiential and community-based knowledge in favour of rationalist, ‘ scien-ti fi c ’ or technical expertise (Birhane, 2021; Díaz and Smith, 2024).”
Lived, affective, and cultural dimensions of ethical AI: beyond procedural AI ethics
Tettegah, S. Y. (2026) · AI & Society · doi:10.1007/s00146-026-03165-9
“Fifth, the global deployment of AI systems demands that ethical frameworks attend to the cultural conditions through which affect acquires meaning and resist the reproduction of epistemic hierarchies in the name of universalism (Birhane 2021; Mesquita 2022).”
InfluentialMolin, L. D. (2026) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3805689.3806520
“Here, critical scholarship suggests that the mere mirroring of social reality is not value-neutral, but rather saturated with the perpetuation of hegemonic power [9] [10] [11].”
Mehdiyeva, J. (2026) · Development in Practice · doi:10.1080/09614524.2026.2689992
Hlaimi, S., & Maloney, J. (2026) · Citizenship Social and Economics Education · doi:10.1177/14788047261461204
Lancaster, E. A., & Marasinghe, V. (2026) · IGI Global eBooks · doi:10.4018/979-8-3373-6630-2.ch010
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Bailey, P. (2026) · IGI Global eBooks · doi:10.4018/979-8-3373-8192-3.ch010
MISHRA, A. R. (2026) · IGI Global eBooks · doi:10.4018/979-8-3373-8424-5.ch012
The case for humanities-based studies of AI production and effects
Asscher, O. (2026) · AI & Society · doi:10.1007/s00146-026-03170-y
“All the more so, some claim, when these involve unjust data training processes, environmental cost, low diversity, and potential ethical harm (Birhane, 2021), Birhane, 2024).”
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Rocha, E. S. S., Andrade, D. R. D. S., & dos Santos, J. C. F. (2026) · Revista Ibero-Americana de Ciência da Informação · doi:10.26512/rici.v19.n1.2026.57464
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Karumbaiah, S., Ganesh, A., & Maravi, A. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-29794-5_20
3. An Introduction to the Philosophy of Artificial Intelligence
Torbjørnsen, R. R., & Kyselo, M. (2026) · Universitetsforlaget eBooks · doi:10.18261/9788294167234-26-03
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Torbjørnsen, R. R., & Kyselo, M. (2026) · Universitetsforlaget eBooks · doi:10.18261/9788294167234-26-04
Ghebreab, S., & Dignum, V. (2026) · AI & Society · doi:10.1007/s00146-026-03166-8
“While there are increasing calls—particularly from the Global South—to engage with frameworks such as Ubuntu or Indigenous knowledge systems (Birhane 2021; Dignum 2022), these efforts remain limited and do not signal a structural paradigm shift.”
Reimagining sovereignty in the Global South: digital dependency, AI and cybersecurity
Egbobamwonyi-Bedaux, J. U. (2026) · Third World Quarterly · doi:10.1080/01436597.2026.2690081
de Boer, B., Puzio, A., Bergen, J. P., & Nagenborg, M. (2026) · Foundations of Science · doi:10.1007/s10699-026-10040-9
Saikia, D., Basumatary, P., & Saikia, A. (2026) · AI & Society · doi:10.1007/s00146-026-03181-9
“The process of classification and institutionalization often reshape Indigenous knowledge by decontextualizing it from its context of origin, thereby reinforcing existing power hierarchies and allowing greater control by the dominant institutions (Agrawal 2002; Birhane 2021).”
Socio-Ecological Responsibility in the Triple Planetary Crisis
Sanders, K., & Washington, J. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-2691-5.ch003
Fang, S., & Chen, S. (2026) · AI and Ethics · doi:10.1007/s43681-026-01244-7
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Sedano, J. J. F., Valadez, M. E., & Castillo, A. I. D. (2026) · IGI Global eBooks · doi:10.4018/979-8-3373-8592-1.ch005
Abdulmajid, M., Alali, N., & Alsharrah, A. (2026) · Digital Education Review · doi:10.1344/der.2026.49.114-132
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Lu, W., & Sun, S. (2026) · Synthese · doi:10.1007/s11229-026-05713-8
“Formosa characterizes autonomy as “substantive control over life” ( 2021 , p. 610), arguing that an agent’s degree of autonomy is contingent upon the extent of control they exercise over the critical aspects of life—greater control implies enhanced autonomy.”
Hedayati, M. (2026) · Creativity and Cognition · doi:10.1145/3803784.3809259
Dialogical Participation for Social Change: A Story of Street Art, Conflict and Activism
Murray, M., Scriven, R., O'Keefe, H., Coughlan, C., & Sterling, M. (2026) · Creativity and Cognition · doi:10.1145/3803784.3809285
Andalibi, N., & Haimson, O. L. (2026) · ACM Journal on Responsible Computing · doi:10.1145/3831367
“In sum, self-reports enabled by our scale offer a useful, complementary lens by centering these lived and interpretive dimensions [9] of harm quantitatively.”
InfluentialNegi, B., Shukla, S., Gupta, D., Tuli, M., & Chaudhary, N. (2026) · Integrative Psychological and Behavioral Science · doi:10.1007/s12124-026-10017-0
“Where interactions are shaped by trust, disclosure, and cultural nuance, ethical responsibility requires ongoing negotiation that centres participants’ agency and control over representation (Birhane, 2021).”
AI Research and Disabled, Neurodivergent, Deaf Researchers and Other Professionals
Hersh, M. A., Ali, N., & Ayoub, M. (2026) · Lecture notes in computer science · doi:10.1007/978-3-032-31308-9_41
Balakrishnan, P. (2026) · Educational governance research · doi:10.1007/978-3-032-29276-6_2
Imagination Will Not Be Automized: On AI Image Generators and Epistemic Oppression
Abel, S. (2026) · Constellations · doi:10.1111/1467-8675.70065
Epistemic Delegation and Africa’s Future in the Age of AI
Negedu, I. A., Mamah, J. C., & Akpan, T. M. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2706239
Bilici, M. V. (2026) · İstanbul Üniversitesi Sosyoloji Dergisi / İstanbul University Journal of Sociology · doi:10.26650/sj.2025.46.1.1172
Cultural and ethical dimensions of anthropomorphizing technology in Africa
Akerele, T. S., Folorunso, S. O., & Àìná, A. À. (2026) · Digital Scholarship in the Humanities · doi:10.1093/llc/fqag105
Attia, B. M. (2026) · Journal of Ethnic and Cultural Studies · doi:10.66815/ejecs/2640
“In addition to statistical bias, scholars also conceptualize algorithmic injustice as relational harm embedded within power structures and data infrastructures (Birhane, 2021; Işıklı & Fazlıoğlu, 2026).”
Seeing against the machine: reframing generative AI error as pedagogical insight in art education
Abdulmajid, M. (2026) · Journal of Visual Literacy · doi:10.1080/1051144x.2026.2710031
The perks and perils of artificial intelligence on the digital divide
Alane, N. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-36775-5.00010-2
Queniahan, M., Taiuru, K., Mehdipour, F., Mahanti, A., Ebrahimi, N., & Aharari, A. (2026) · Advances in sustainability science and technology · doi:10.1007/978-3-032-25267-8_1
Eickers, G., Pismenny, A., & PRINZ, J. J. (2026) · Inquiry · doi:10.1080/0020174x.2026.2712986
Egara, O. W., Oviemuno, B., & ELIJAH, C. (2026) · Mathematics and Computer Science · doi:10.11648/j.mcs.20261103.12
Musole, E. (2026) · Research Square · doi:10.21203/rs.3.rs-10332787/v1
Riding the Fire Horse: culture change and Philippine readiness in the Intelligence Age
Taduran, R. J. O. (2026) · AI & Society · doi:10.1007/s00146-026-03315-z
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Ducasse, A. M., & Caño, E. (2026) · Business and Professional Communication Quarterly · doi:10.1177/23294906261467895 · Cited by 1
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Akay, S. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-3373-7837-4.ch004
Brooke, S., & Pandiani, D. S. M. (2026) · Oxford University Press eBooks · doi:10.1093/9780198960256.003.0045
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Gupta, H., Roy, R., & Narbariya, S. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-44247-6.00008-7
Planting Ethics: The SEED Framework for Responsible AI in Agricultural Systems
Noll, S. E., Conklin, S. L., & LaRosa, E. (2026) · Journal of Agricultural and Environmental Ethics · doi:10.1007/s10806-026-09991-7
“Second, it assesses the promises and risks of AI-assisted pollination, showing why technological substitution results in ecological oversimplification that poses significant ethical concerns (Birhane, 2021; Rotz et al., 2019).”
Gupta, S., Gupta, S., Nyamasvisva, T. E., Srivastava, A. P., Tiwari, K., & Sharma, R. (2026) · International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI (ICSCAI) · doi:10.1109/icscai68849.2026.11648599
Gupta, S., Gupta, S., Nyamasvisva, T. E., Srivastava, A. P., Sharma, A., & Tiwari, K. (2026) · International Conference on Sustainable Computing and Integrated Communication in Changing Landscape of AI (ICSCAI) · doi:10.1109/icscai68849.2026.11648628
Diogo, J. E., & Andrade, C. S. (2026) · AI & Society · doi:10.1007/s00146-026-03332-y
Bai, Q., Zhan, Y., Song, Y., & Yu, T. (2026) · International Conference on Computer Science and Technologies in Education (CSTE) · doi:10.1109/cste69562.2026.11649634
“…education specifically, tensions persist between low-threshold creative outputs encouraged by generative systems and the structured progression emphasized in curricula, which rely on theoretical knowledge, harmony, and sustained skill development such as ear training and instrumental practice [6].”
A Decolonial Reading of Vulnerability in AI Legal Language
Aimen, T. (2026) · Springer eBooks · doi:10.1007/978-3-031-87993-7_192-1
ChatGPT as journalistic gatekeeper: GenAI news summaries, sourcing practices, and geographic bias
Hossain, M. S., & Ekdale, B. (2026) · Online Media and Global Communication · doi:10.1515/omgc-2026-0009
“Not only do technological biases raise ethical concerns for journalists (Culver and Min-ocher 2021; Thomson et al. 2025; Usher 2026), they can produce negative outcomes for marginalized groups (Birhane 2021; Gebru 2020).”
Gamage, D., Nanayakkara, I., & Sasahara, K. (2026) · Computers in Human Behavior Reports · doi:10.2139/ssrn.7360004
Epistemic Trust and Ethical Governance in AI-Driven Adaptive Learning
Said, N. A. (2026) · Advances in computational intelligence and robotics book series · doi:10.4018/979-8-2600-1232-1.ch003
Algorithmic Thermostat: LLMs Standardize Political Expression Without Shaping Semantic StancesPreprint
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Designing Epistemic Friction: Architecture and Protocols for Trickster AI in Leadership Education
Ofosu-Asare, Y., & Nally, R. A. (2026) · New Directions for Student Leadership · doi:10.1002/yd.70072
“It draws on relational accounts of personhood and AI ethics (Birhane 2021 ; Mhlambi and Tiribelli 2023 ), Ubuntu-informed accounts of responsibility and community (Obasa 2024 ), and decolonial critiques of epistemic dominance (Santos 2014 ; Mignolo 2009 ).”
Zhou, C.-H. (2026) · International Journal of Heritage Studies · doi:10.1080/13527258.2026.2723869
Silva, A., & Lino, M. (2026) · Nursing Inquiry · doi:10.1111/nin.70162
“At the same time, multiple AI systems developed by different organizations now coexist, each trained on distinct data-sets, optimized through different alignment processes, and operating under different technical constraints and governance environments (Birhane 2021; Bommasani et al. 2023).”
Babamahmoodi, A. (2026) · Research Square · doi:10.21203/rs.3.rs-10864198/v1
Mathuloe, T. J., Byrne, J. R., & Bresnihan, N. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7396760
Purboadji, A. (2026) · Cogent Arts and Humanities · doi:10.1080/23311983.2026.2724163
The Trickster Turn: Decolonial Epistemology for AI in Leadership Education
Ofosu-Asare, Y., & Nally, R. A. (2026) · New Directions for Student Leadership · doi:10.1002/yd.70071
“Birhane ( 2021 ) argued for relational ethics in response to algorithmic injustice, cautioning against abstract moralism that ignores context.”
Pugliese, R. (2026) · AI and Ethics · doi:10.1007/s43681-026-01367-x
Bennett, S., Hernández, A. D., & Wahome, M. N. (2026) · De Gruyter eBooks · doi:10.1515/9783111373096-033
Ouko, K. O., Yugi, C. L., & Ogola, R. J. O. (2026) · Food and Energy Security · doi:10.1002/fes3.70317
Joshua, O. (2026) · Social Science and Humanities Journal · doi:10.18535/sshj.v10i08.2452
Creely, E., & Mehta, R. (2026) · Linguistics and Education · doi:10.1016/j.linged.2026.101585 · Cited by 1
Mnguni, L. E., Nuangchalerm, P., Sari, I. J., Ramulumo, M., Camara, J. S., Biên, N. V., & Islami, R. A. Z. E. (2026) · Discover Education · doi:10.1007/s44217-026-02140-2
“Birhane [28] similarly develops a relational ethics of algorithmic injustice, foregrounding the situated, embodied, and relational realities of those most affected by automated systems.”
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Soomro, R. B. K., Bhayo, N. H., & Soomro, A. B. (2026) · Research Square · doi:10.21203/rs.3.rs-10493256/v1
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Mhlanga, D., & Dzingirai, M. (2026) · CABI eBooks · doi:10.1079/9781836994930.0011
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Mushi, R. T. (2026) · The International Information & Library Review · doi:10.1080/10572317.2026.2735044
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The circular economy, explained by AI
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Torres-Toukoumidis, Á., León-Alberca, T., & Lituma, J. P. C. (2026) · Current Psychology · doi:10.1007/s12144-026-10121-9
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InfluentialHashiguti, S. T., Ferreira, S. R., Maia, H. D. A., Benedito, M. E. D. A., Nardo, J. D. S., Fagundes, I. Z. Z., Amado, G. E., Brito, C. C. D. P., Ângelo, R. D. C., Silva, S. T. D. A. E., et al. (2026) · Trabalhos em Linguística Aplicada · doi:10.1590/01031813v65020268684688
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“…the African philosophy that human beings are essentially relational and that flourish - ing is realized in and through community, “I am because we are,” challenges individualist assumptions pervading Western AI ethics, emphasizing collective benefit and restorative responses to harm [6, 32].”
Wiles, F. (2026) · International Journal of Qualitative Methods · doi:10.1177/16094069261496017
Futures of Work in Civic and Public Interest Technology
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Ndayipfukamiye, T., Ding, J., Sentamba, E., BUKURU, D., & Ning, H. (2026) · Philosophies · doi:10.3390/philosophies11050189
Alhasnawi, S., Selvi, B., Radif, M., & Orak, S. D. (2026) · SAGE Open · doi:10.1177/21582440261491814
Aryee, J. N. A., Davies, P., Torsah, G. A., Apaw, M. M., Mwando, S. M., Kwisanga, C., Boateng, C. D., Jobunga, E. O., Mutale, D., & Amekudzi, L. K. (2026) · Frontiers in Education · doi:10.3389/feduc.2026.1968304
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Incze, A., & Treuer, T. (2026) · Frontiers in Psychology · doi:10.3389/fpsyg.2026.1917397
“Relational approaches to algorithmic injustice emphasize that harm emerges within networks of power and social dependence rather than from isolated technical errors alone (Birhane, 2021).”
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Yapay Zekânın Yabancı Dil Öğretimi Süreçlerine Katılmasına Yönelik Eğilimler: Bir Alanyazın Taraması
POLAT, Y., & İzgü, D. (2026) · Dil Eğitimi ve Araştırmaları Dergisi · doi:10.31464/jlere.1943625
Metadata
- Authors
- Birhane, A.
- Affiliations
- University College Dublin (IE)
- Corresponding author
- Birhane, Abeba
- ORCID
- Birhane, Abeba
- Venue
- Patterns
- Publisher
- Elsevier BV
- Published
- 2021-02
- Volume
- 2
- Issue
- 2
- Pages
- 100205
- ISSN
- 2666-3899 (ISSN-L)
- PMC
- PMC7892355
- OpenAlex
- W3132771424
- Semantic Scholar
- a6de042d8a2baeeeb3d7e37e03c66c1fe07e7b36
- Cited by
- 707
- References
- 74
- Citations by year
- 2026: 251 · 2025: 177 · 2024: 85 · 2023: 94 · 2022: 73 · 2021: 25
- FWCI
- 12.97
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Patterns (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Science Foundation Ireland (13/RC/2094_P2)
- European Regional Development Fund
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
- Social Sciences › Sociology and Political Science › Feminist Epistemology and Gender Studies
- Social Sciences › Law › Artificial Intelligence in Law
- Keywords
- algorithmic injustice, relational ethics, relationality, algorithmic harms, personhood, data ethics, justice
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.
A language model drew the claims from the paper on 2026-10-09, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-09 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
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 ›
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