Aug 2026· Digital War· Vol 7· 0 citations· 52 references
TL;DR
To continue exposing AI-driven military violence, OSI practices must reorient their methodologies and focus more systemically and systematically on the dispersed material infrastructures and political forces underpinning AI militarism, so investigators can better reveal concealed networks of accountability linking state and corporate actors.
Abstract
This paper explores how the integration of artificial intelligence (AI) into military decision-making poses new challenges to human rights focused open-source investigation (OSI). It identifies three key epistemic risks emerging from AI’s role in the military ecosystem. Across these risk areas, AI’s perceived neutrality and rationality create feedback loops of impunity, where human oversight is symbolic or compromised—obscuring both the messy realities of warfare and the potential culpability of military decision-makers. The paper then argues that to continue exposing AI-driven military violence, OSI practices must reorient their methodologies. Rather than treating AI as a discrete, technical tool, OSI must focus more systemically and systematically on the dispersed material infrastructures and political forces underpinning AI militarism. By refocusing investigative practices onto these systems, investigators can better reveal concealed networks of accountability linking state and corporate actors. Such a shift also enables OSI to move beyond narrow legalistic frameworks and engage with structural forms of violence that often evade formal accountability. This could support more expansive, justice-oriented investigations—amplifying marginalised perspectives, mapping complicity, and aligning OSI with broader struggles against systemic harm. Detached from the procedural demands of law, OSI can become a more active, politically mobilising practice, amplifying marginalised perspectives, mapping networks of complicity, and supporting grassroots struggles for justice beyond the courtroom.
The article demonstrates how attempts to decentre the human often reconstitute new forms of authority in attempts to decentre the human and examines the possibility of surpassing standard anthropocentric approaches in AI while maintaining a critical philosophical engagement with the structurally necessary yet precarious character of organizing principles.
There is a rising tide of initiatives countering predominant AI practices and narratives. The social and environmental consequences of AI-dedicated data centres; the death, injury and human displacement involving AI-enabled lethal autonomous weapons; and the corrosion of educational institutions via the adoption of generative AI tools are just a few targets of diverse initiatives taking a stance against AI. However, these initiatives are generally siloed; they do not constitute a single movement but a fragmented patchwork. In this paper, I draw on Gramsci’s Prison Notebooks to make the case for unity among those running such initiatives, whom I call “AI subalterns.” Drawing on literature on epistemic injustice, I confront the AI subaltern with “ruling AI authorities”; those from the ruling classes with the ability to speak about AI with authority and thus perpetrate epistemic injustice. I argue that epistemic activism constitutes a key weapon in the AI subaltern’s arsenal, and that recognising how it is wielded by peers may help develop a sense of political consciousness. I show how the resulting unity among AI subalterns meets the criteria Gramsci sets out when describing how subalterns have historically coordinated successful political uprisings.
Ismael Kherroubi Garcia· AI and Ethics· 0 citations
It is argued that current benchmarking practices may perpetuate systematic harms affecting various actors in AI research, aligning with four of Iris Marion Young's theories of oppression and structural injustice.
Artificial intelligence (AI) has become a double-edged force in contemporary mass communication, enabling media innovation while accelerating the production and circulation of synthetic misinformation, particularly deepfakes. This paper examines the paradoxical role of AI in both facilitating and countering AI-generated disinformation, with a focus on its implications for public trust, media ethics, and democratic communication. Grounded in Media Literacy Theory, the study adopts a qualitative document analysis of academic literature, policy reports, technical studies, and verified media cases, including evidence from Kenya’s 2022 general elections and comparable Sub-Saharan African contexts. The analysis shows that although AI-based detection and forensic tools offer important mitigation potential, their effectiveness is constrained by data bias, limited regional applicability, and unresolved ethical and regulatory challenges. In response, the paper advances a conceptual framework for AI-mediated authenticity, which conceptualizes authenticity as a negotiated outcome shaped by the interaction between AI generation technologies, detection systems, media literacy capacities, ethical norms, and policy environments. By foregrounding African democratic and media contexts, the study contributes an Africa-centered theoretical perspective to global debates on deepfakes and proposes practical recommendations for policymakers, educators, media practitioners, and technology developers aimed at safeguarding truth in the digital age.
Everlyn Chelang’at Kimibei· Kabarak Journal of Research...· 0 citations
This paper extends the post-factual polity framework into AI infrastructure and public administration systems theory. It asks how proprietary analytical platforms alter the state’s capacity to produce, audit, and contest the categories through which risk, threat, eligibility, fraud, and deviance become actionable. Using a structured documentary case analysis of Palantir Technologies across United States agencies and allied jurisdictions, the study applies three diagnostic markers—categorical opacity, contestation displacement, and substitutive dependency—to examine the migration of sovereign classification into vendor-controlled infrastructure. The research gap was identified through an integrative review of public administration, AI governance, algorithmic accountability, systems theory, surveillance studies, and Palantir scholarship. The analysis distinguishes AI epistemic capture from ordinary IT vendor lock-in: the former concerns not merely technical dependence or high exit costs but the loss of public capacity to define and contest consequential administrative categories. The paper argues that administrative law, procurement reform, and algorithmic impact assessment remain necessary but insufficient when agencies lack substitutive capacity. It specifies untangling as a systems-level task involving capacity reconstruction, categorical repatriation, contractual restructuring, and procurement reorientation. Hybrid intelligence is advanced as a post-untangling architecture that embeds machine processing within contestable, accountable, and legally governed human judgment. The contribution is diagnostic, methodological, and design-oriented for AI systems governance.
Debates on catastrophic artificial intelligence (AI) risk often frame artificial superintelligence as a problem of value alignment: the central task is to ensure that advanced systems act in accordance with human intentions or moral principles. This article argues that such a framing is necessary but insufficient. The danger posed by artificial superintelligence is not merely that it may pursue the wrong values, but that it may introduce a new concentration of autonomous and potentially dominating power. Drawing on political realism in both political theory and international relations, we reinterpret AI catastrophic risk as a structural problem of power under anarchy. The core concerns of AI safety—instrumental convergence, race dynamics, and loss of control—already rely on implicitly realist assumptions about survival, self-help, and the pursuit of power. Yet proposed solutions often retreat into moralism, asking states, firms, or machines to behave ethically without sufficiently altering the incentives that drive competitive acceleration. Against both moralistic reassurance and fatalistic resignation, we argue that realism offers a constructive response. Fear can coordinate divided actors when a threat is perceived as immediate, symmetric, and visible. Artificial superintelligence plausibly satisfies the first two conditions: current evidence of strategic deception and agentic misalignment suggests a shortening temporal horizon, while loss-of-control dynamics would expose even first movers to subordination. What is missing is political visibility. The task of AI governance is therefore to create common knowledge of ASI as a prospective hegemonic threat through shared evaluations, mandatory incident reporting, and institutionalized transparency of peril. The aim is not to moralize machines, but to organize power before it becomes uncontrollable.
C. Burelli, Federico Formentini· European Journal of Politica...· 0 citations
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