Solidarity-Driven AI Governance: A Framework for Social Justice and Sustainable Technological Futures | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Solidarity-Driven AI Governance: A Framework for Social Justice and Sustainable Technological Futures Behailu Getachew Wolde, Mehamed Ahmed Abdurahman This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8587315/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Artificial Intelligence (AI) presents unprecedented opportunities for societal transformation, yet its current deployment often exacerbates existing inequalities. This work introduces the Solidarity-Driven Ethical AI Framework (SDEAF), a novel governance model that embeds principles of social justice, collective responsibility, and ecological sustainability into AI systems. Our framework uniquely integrates distributive justice mechanisms in bias mitigation, participatory transparency protocols, and solidarity-based impact assessments. Through case studies in Global South contexts, we demonstrate how SDEAF enables: 1) Equitable resource allocation through bias-aware agricultural AI, 2) Community-led transparency in public service algorithms, and 3) Sustainable AI deployment monitoring using decentralized IoT networks. The framework’s effectiveness is validated through longitudinal studies showing 40% improvement in algorithmic fairness metrics while maintaining 92% operational efficiency across diverse socioeconomic contexts. Ecological Modeling Agroecology Solidarity-Driven AI Distributive Justice Participatory Governance Sustainable Technology Decentralized Accountability Global South Perspectives Full Text Additional Declarations The authors declare no competing interests. Supplementary Files DatasetcodeRef.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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