Artificial Intelligence and Sustainable Development: A Multidisciplinary Framework for Inclusive Innovation

Stuart Russell

Artificial Intelligence and Sustainable Development: A Multidisciplinary Framework for Inclusive Innovation

Author(s)	Stuart Russell
Country	United States
Abstract	Artificial intelligence (AI) is increasingly embedded in the systems through which societies diagnose problems, allocate resources, deliver public services, design products, manage infrastructure, and generate knowledge. Its relevance to sustainable development lies not only in its capacity to process complex data or automate routine decisions, but also in its influence on who is visible in data, whose needs define innovation priorities, who has access to digital capability, and who bears the costs of technological change. AI can support climate modelling, precision agriculture, early-warning systems, health services, accessible education, energy management, and public-sector planning. At the same time, poorly governed AI can intensify exclusion, reproduce discrimination, concentrate economic value, increase surveillance, and add to environmental pressures through energy, water, and material use. This paper develops a multidisciplinary framework for inclusive innovation at the intersection of AI and sustainable development. The framework connects technical performance with social justice, environmental responsibility, institutional capacity, and democratic accountability. It treats sustainable AI not as a collection of isolated applications but as a lifecycle question: a system should be assessed from problem selection and data collection through model development, procurement, deployment, monitoring, and retirement. The central argument is that an AI system can be considered developmentally valuable only when it addresses a legitimate public or community need, expands rather than narrows meaningful participation, and remains accountable for its social and ecological effects. The paper uses an explanatory and integrative review of literature on AI, the Sustainable Development Goals (SDGs), responsible innovation, algorithmic fairness, digital inequality, climate action, education, health, agriculture, and governance. It distinguishes between AI as an enabling capability and AI as a socio-technical system shaped by data, compute infrastructure, institutions, incentives, regulations, and human judgement. The analysis considers both direct benefits, such as improved forecasting or resource optimization, and indirect risks, including biased outputs, loss of agency, unequal access to infrastructure, opaque decision-making, and rebound effects that can offset efficiency gains. The paper concludes that inclusive innovation requires needs-led problem definition, participation by affected communities, accessible data and digital infrastructure, context-sensitive evaluation, human oversight, environmental proportionality, and mechanisms for redress.
Keywords	Artificial Intelligence, Sustainable Development, Inclusive Innovation, Sustainable Development Goals, Responsible AI, Digital Inclusion, AI Governance, Algorithmic Fairness, Climate Action, Public Interest Technology
Field	Computer Applications
Published In	Volume 1, Issue 1, May-June 2026
Published On	2026-06-04

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American Journal of Innovations in Multidisciplinary Research

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Scholarly International Journal

Artificial Intelligence and Sustainable Development: A Multidisciplinary Framework for Inclusive Innovation

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