"AI is deeply intertwined with social systems, organizations, institutions, and culture. Sociotechnical approaches to AI system development and deployment are important to contend with the socially-embedded nature of AI to ensure that these systems are safe and effective and that their risks have been appropriately managed. People with expertise in sociology, anthropology, political science, law, economics, and psychology already exist in a wide range of technical and non-technical roles in AI companies but tend to be underused in AI system development efforts. Instead, they are often relegated to siloed roles in AI ethics or governance, compliance, or pre-deployment user interface testing where they have limited input to early design and prototyping, with limited authority to substantively modify product roadmaps."