This conceptual review argues that the GenAI paradox of opportunity and danger is rooted in the current dominant, vertically organised technological bloc of Platform Capitalism 2.0.
The article proposes the architecture of an alternative technological bloc - a horizontally organised, multi-level socialised GenAI ecosystem mediated by progressive technological organic intellectuals and a technological general intellect.
The article addresses the GenAI architectural dimension within the context of Platform Capitalism 2.0, identifying a fundamental contradiction: a 'data grab' driven by the needs of powerful Large Language Models (LLMs) is creating a new 'data scarcity' of high-quality, clean information.
To counter this, a 'socialised GenAI ecosystem' would propose new models for shared, ethically sourced, high-quality, and community-contributed datasets comprising 'data commons' - publicly accessible repositories of data, underpinned by technologies like federated learning, privacy-preserving AI techniques, and open data initiatives to ensure transparent use and collective ownership.
The article employs Celia Lury's concept of 'problem spaces' and 'recomposed research problems' to explore pathways for transitioning to this new system, based on:
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building multiple mediating layers of ethical purpose
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mediating roles of progressive technological organic intellectuals
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democratic governance
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educative infrastructures between new technologies and their users
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replacement of 'compressed technological time with 'ecosystemic transitioning time'.
The paper also highlights the growing geopolitical competition in GenAI development, notably the rivalry between the US and China, noting China's strategic commitment to LLM development and its fracturing effect on the global Platform Capitalism 2.0 formation through a diffusion of lean and open-weight large language models.
The article constitutes an initial contribution to understanding how GenAI can be transitioned from a tool of capitalist hegemony to a socialised system aligned with democratic and progressive principles.
