Irresponsible AI: big tech's influence on AI research and associated impacts
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Abstract (arXiv)
The accelerated development, deployment and adoption of artificial intelligence systems has been fuelled by the increasing presence of big tech in the AI field. This trend has been accompanied by growing ethical concerns and intensified societal and environmental impacts. This position paper argues that irresponsible AI development is strongly driven by big tech's influence and involvement in the field. First, we examine the growing and disproportionate influence of big tech in AI research and argue that its drive for scaling and general-purpose systems is fundamentally at odds with the responsible, ethical, and sustainable development of AI. Second, we review key current environmental and societal negative impacts of AI and trace their connections to big tech's influence. Third, we discuss the underlying economic forces driving big tech's actions. Finally, as a call to action, we invite AI researchers to counter big tech's influence in irresponsible AI development through strategies that build on the responsibility of implicated actors and collective action.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 29 of its 149 references that are in the map. First posted on arXiv 27 Nov 2025.
Builds on
29 of 149 references.
References · 29
- 2020Language Models are Few-Shot Learnerscited by 32,199
- 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
- 2023Segment Anythingcited by 8,158
- 2020Scaling Laws for Neural Language Modelscited by 6,411
- 2023Power Hungry Processing: Watts Driving the Cost of AI Deployment?cited by 186
- 2021The Values Encoded in Machine Learning Researchcited by 172
- 2022Compute Trends Across Three Eras of Machine Learningcited by 161
- 2020Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligencecited by 100
- 2022SELFIES and the future of molecular string representationscited by 76
- 2025All-atom Diffusion Transformers: Unified generative modelling of molecules and materialscited by 75
- 2020The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Researchcited by 67
- 2023Counting Carbon: A Survey of Factors Influencing the Emissions of Machine Learningcited by 42
17 more
- 2020The Grey Hoodie Project: Big Tobacco, Big Tech, and the threat on academic integritycited by 38
- 2024Hype, Sustainability, and the Price of the Bigger-is-Better Paradigm in AIcited by 35
- 2025Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewardscited by 34
- 2022Dislocated Accountabilities in the AI Supply Chain: Modularity and Developers' Notions of Responsibilitycited by 33
- 2023Crystal-GFN: sampling crystals with desirable properties and constraintscited by 29
- 2024SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraintscited by 26
- 2020Against Scale: Provocations and Resistances to Scale Thinkingcited by 18
- 2024A Taxonomy of Systemic Risks from General-Purpose AIcited by 12
- 2021The Privatization of AI Research(-ers): Causes and Potential Consequences -- From university-industry interaction to public research brain-drain?cited by 9
- 2024Environmental Burden of United States Data Centers in the Artificial Intelligence Eracited by 5
- 2025OBELiX: A Curated Dataset of Crystal Structures and Experimentally Measured Ionic Conductivities for Lithium Solid-State Electrolytescited by 5
- 2025Exploring the sustainable scaling of AI dilemma: A projective study of corporations' AI environmental impactscited by 3
- 2023Big Tech influence over AI research revisited: memetic analysis of attribution of ideas to affiliationcited by 2
- 2025Limits to AI Growth: The Ecological and Social Consequences of Scalingcited by 2
- 2025The Risks of Industry Influence in Tech Researchcited by 2
- 2019Evolving Academia/Industry Relations in Computing Researchcited by 1
- 2025On the (im)possibility of sustainable artificial intelligence. Why it does not make sense to move faster when heading the wrong waycited by 1
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Citing papers per year: 2026: 1.
1 paper.