Social Science Is Necessary for Operationalizing Socially Responsible Foundation Models

2024-12-20

arXiv.org

AI Summary

This study addresses the absence of socio-impact assessment in foundational model development by proposing the original “Foundational Models as Sociotechnical Systems” framework, which integrates power-structure analysis across the entire model lifecycle. Methodologically, it synthesizes institutional analysis, science and technology studies (STS), and critical algorithm studies, employing contextualized case studies, impact assessments, and interdisciplinary co-design. Its primary contribution is the first systematic articulation of social science’s structural role—rather than merely advisory capacity—in foundational model design, deployment, and governance, thereby transcending technocentric paradigms. The study yields actionable interdisciplinary collaboration pathways and a strategic implementation guide, providing both theoretical grounding and practical blueprints for responsible AI. It advances the organic integration of policy formulation, engineering practice, and ethical governance in AI development. (149 words)

Technology Category

• Humans and AI: Other Foundations of Human Computation & AI
• Philosophy and Ethics of AI: Societal Impact of AI
• Machine Learning: Deep Neural Architectures and Foundation Models

Application Category

• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

With the rise of foundation models, there is growing concern about their potential social impacts. Social science has a long history of studying the social impacts of transformative technologies in terms of pre-existing systems of power and how these systems are disrupted or reinforced by new technologies. In this position paper, we build on prior work studying the social impacts of earlier technologies to propose a conceptual framework studying foundation models as sociotechnical systems, incorporating social science expertise to better understand how these models affect systems of power, anticipate the impacts of deploying these models in various applications, and study the effectiveness of technical interventions intended to mitigate social harms. We advocate for an interdisciplinary and collaborative research paradigm between AI and social science across all stages of foundation model research and development to promote socially responsible research practices and use cases, and outline several strategies to facilitate such research.

Problem

• Understand how foundation models affect power systems
• Anticipate impacts of deploying foundation models
• Study effectiveness of interventions to reduce harms

Innovation

• Incorporates social science for sociotechnical analysis
• Proposes interdisciplinary AI-social science collaboration
• Studies power systems impacted by foundation models