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        The AI Matrix

        Profits, Power, Politics

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        Author(s)
        Mugge, Daniel
        Paul, Regine
        Stan, Vali
        Language
        English
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        Abstract
        Artificial intelligence (AI) is heralded as a revolutionary force in the global economy. But the transformation it brings is not simply about new technology as a driver of change. It is about who owns it, what they want to do with it, who can pay for it, and how other economic actors around the world – from legacy manufacturing firms in the Global North to farmers in the Global South – must adjust. This book explores AI systems as products of unequal and conflictual power relations. It exposes grand AI narratives as rhetorical ammunition in political fights over tech futures and socio-economic distribution. Tech giants leverage infrastructure and data to cement their global dominance. Meanwhile, geopolitical competition between China and the United States increasingly dominates the AI economy, entrenching globe-spanning dependencies. The AI Matrix is an essential guide to the real-world economic dynamics that AI unleashes.
        URI
        https://library.oapen.org/handle/20.500.12657/108963
        Keywords
        LLM; Silicon Valley; generative AI; ChatGPT; robotics; tech colonialism; data centres; open source software; cloud computing; surveillance capitalism; chatbots
        ISBN
        9781788218672, 9781788218672, 9781788218597
        Publisher
        Agenda Publishing Limited
        Publisher website
        https://www.agendapub.com/
        Publication date and place
        Newcastle upon Tyne, UK, 2026
        Classification
        Artificial intelligence
        Digital and information technologies: social and ethical aspects
        Political economy
        Pages
        160
        Public remark
        Funded by: University of Bergen
        Rights
        https://creativecommons.org/licenses/by-nc-nd/4.0/
        • Imported or submitted locally

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        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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