German AI Start-Ups and AI Ethics: Using A Social Practice Lens for Assessing and Implementing Socio-Technical Innovation

TL;DR

This paper develops a social practice-based framework to analyze how German AI start-ups understand and implement AI ethics, emphasizing cultural and historical contexts to improve socio-technical innovations for ethical AI.

Contribution

It introduces a novel practice-based approach for understanding ethical AI and provides empirical insights into how German AI start-ups operationalize ethics within their social and cultural contexts.

Findings

AI ethics are deeply rooted in specific cultural and historical practices.

Ethical AI practices can be characterized by principles, needs, narratives, materializations, and genealogies.

Understanding social practices aids in designing effective socio-technical innovations for ethical AI.

Abstract

Within the current AI ethics discourse, there is a gap in empirical research on understanding how AI practitioners understand ethics and socially organize to operationalize ethical concerns, particularly in the context of AI start-ups. This gap intensifies the risk of a disconnect between scholarly research, innovation, and application. This risk materializes acutely as mounting pressures to identify and mitigate the potential harms of AI systems have created an urgent need to assess and implement socio-technical innovation for fairness, accountability, and transparency. Building on social practice theory, we address this need via a framework that allows AI researchers, practitioners, and regulators to systematically analyze existing cultural understandings, histories, and social practices of ethical AI to define appropriate strategies for effectively implementing socio-technical innovations. Our contributions are threefold: 1) we introduce a practice-based approach for understanding ethical AI; 2) we present empirical findings from our study on the operationalization of ethics in German AI start-ups to underline that AI ethics and social practices must be understood in their specific cultural and historical contexts; and 3) based on our empirical findings, we suggest that ethical AI practices can be broken down into principles, needs, narratives, materializations, and cultural genealogies to form a useful backdrop for considering socio-technical innovations.