AIn: Artificial Intelligence for Many

AIn — Artificial Intelligence for Many: From AI for the user to AI for society This concept paper introduces AIn (Artificial Intelligence for Many) as a framework for understanding and designing artificial intelligence systems according to their broader societal and systemic impact. While many contemporary applications of artificial intelligence focus on optimising outcomes for individual users, firms, or specific tasks, AI systems increasingly operate within complex socio-technical environments that affect communities, institutions, and planetary systems. As a result, evaluating AI solely through the lens of individual benefit is becoming insufficient. The concept of AIn proposes a shift in perspective: from AI designed primarily for individual users to AI orchestrated across systems in order to generate value for many stakeholders simultaneously. The paper introduces a canonical definition of AIn, situates the concept within the evolution of design thinking and socio-technical systems research, and proposes practical tools for applying the framework in real-world contexts. Key elements of the framework include: The AIn System Layers Model, which illustrates how AI systems interact across nested layers including users, communities, societal systems, and planetary systems. The concept of AI touchpoints, describing points within complex systems where artificial intelligence can meaningfully influence decision-making, coordination, or optimisation. A distinction between beneficial AI applications and AIn ecosystems, emphasising that AIn emerges when multiple AI capabilities are intentionally orchestrated across a broader system rather than applied in isolation. The paper also proposes AIn as a constructive alternative to narratives that frame artificial intelligence primarily in terms of technological displacement. Instead, the framework highlights the potential of AI to support collective intelligence and systemic problem-solving in areas such as healthcare, energy systems, infrastructure, and public policy. By expanding the scope of artificial intelligence from individual optimisation to system-level impact, AIn offers a conceptual foundation for designing and evaluating intelligent technologies that contribute to societal and planetary wellbeing. Tagline:AIn — Artificial Intelligence for Many. From AI for the user to AI for society.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-11
DOI
https://doi.org/10.5281/zenodo.18965006
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

AIn: Artificial Intelligence for Many

Gilson Teixeira Jr
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

AIn: Artificial Intelligence for Many

Gilson Teixeira Jr
article en

Abstract

AIn — Artificial Intelligence for Many: From AI for the user to AI for society This concept paper introduces AIn (Artificial Intelligence for Many) as a framework for understanding and designing artificial intelligence systems according to their broader societal and systemic impact. While many contemporary applications of artificial intelligence focus on optimising outcomes for individual users, firms, or specific tasks, AI systems increasingly operate within complex socio-technical environments that affect communities, institutions, and planetary systems. As a result, evaluating AI solely through the lens of individual benefit is becoming insufficient. The concept of AIn proposes a shift in perspective: from AI designed primarily for individual users to AI orchestrated across systems in order to generate value for many stakeholders simultaneously. The paper introduces a canonical definition of AIn, situates the concept within the evolution of design thinking and socio-technical systems research, and proposes practical tools for applying the framework in real-world contexts. Key elements of the framework include: The AIn System Layers Model, which illustrates how AI systems interact across nested layers including users, communities, societal systems, and planetary systems. The concept of AI touchpoints, describing points within complex systems where artificial intelligence can meaningfully influence decision-making, coordination, or optimisation. A distinction between beneficial AI applications and AIn ecosystems, emphasising that AIn emerges when multiple AI capabilities are intentionally orchestrated across a broader system rather than applied in isolation. The paper also proposes AIn as a constructive alternative to narratives that frame artificial intelligence primarily in terms of technological displacement. Instead, the framework highlights the potential of AI to support collective intelligence and systemic problem-solving in areas such as healthcare, energy systems, infrastructure, and public policy. By expanding the scope of artificial intelligence from individual optimisation to system-level impact, AIn offers a conceptual foundation for designing and evaluating intelligent technologies that contribute to societal and planetary wellbeing. Tagline:AIn — Artificial Intelligence for Many. From AI for the user to AI for society.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 30%
Ethics and Social Impacts of AI
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