Social Science Is Necessary for Operationalizing Socially Responsible Foundation Models

TL;DR

The paper tackles the problem that foundation models can entrench or reshape existing social power structures if developed and deployed without social-science insight. It proposes a sociotechnical framework that integrates social science throughout the foundation-model lifecycle, focusing on understanding power dynamics, designing interventions, and anticipating impacts. Key contributions include a principled rationale for involvement of social scientists by providers and deployers, concrete practices like bias transparency and model-cards, and actionable incentives to foster interdisciplinary collaboration. The work highlights practical significance for reducing social harms, guiding responsible deployment, and informing policy and industry incentives for sustainable, equitable AI development.

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.

Figures (1)

• Figure 1: Steps of the Foundation Model R&D pipeline. The top pipeline illustrates the stages for training a foundation model (providers), while the bottom pipeline describes the stages of deploying foundation models (deployers).