Irresponsible AI: big tech's influence on AI research and associated impacts

2025-11-27

AI Summary

This paper critically examines the ethical malpractice, social inequity, and environmental costs arising from large technology firms’ dominance in AI research, arguing that their commercial logic—centered on scaling and generalization—is distorting responsible AI development. Employing an integrated methodology comprising systematic literature review, policy analysis, and critical socio-technical systems inquiry, the study identifies structural tensions among AI ethics governance, sustainability practices, and capital-driven innovation imperatives. Its primary contribution is a novel collective action paradigm that transcends narrow technical governance and regulatory approaches; it advocates multi-stakeholder co-responsibility, decentralized governance architectures, and responsibility-oriented institutional design to reconfigure the AI development ecosystem. The findings provide both theoretical grounding and actionable pathways for advancing equitable, sustainable, and democratically governed AI.

Technology Category

• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Machine Learning: Ethics, Bias, and Fairness
• Humans and AI: Other Foundations of Human Computation & AI

Application Category

• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Responsible Web: Technology governance, policy, and regulations
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

Abstract

The accelerated development, deployment and adoption of artificial intelligence systems has been fuelled by the increasing involvement of big tech. This has been accompanied by increasing ethical concerns and intensified societal and environmental impacts. In this article, we review and discuss how these phenomena are deeply entangled. 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 and its underlying economic incentives. Finally, we argue that while it is important to develop technical and regulatory approaches to these challenges, these alone are insufficient to counter the distortion introduced by big tech's influence. We thus review and propose alternative strategies that build on the responsibility of implicated actors and collective action.

Problem

• Examines big tech's disproportionate influence on AI research and its conflict with responsible development.
• Reviews negative environmental and societal impacts of AI linked to big tech's economic incentives.
• Argues technical and regulatory solutions alone are insufficient, proposing alternative collective action strategies.

Innovation

• Critique big tech's scaling and general-purpose AI systems
• Link AI's negative impacts to economic incentives of big tech
• Propose collective action and actor responsibility over technical fixes