Towards a Multi-Perspective Model of Responsible Innovation Ecosystem (RIE) : Trust-Based Autonomous Vehicles (TAVs)

Interest in autonomous vehicles (AVs) has increased in recent years across sectors due to their potential for optimizing civic sector services related to urban transportation. AVs are expected to account for 66% of passenger kilometers and more than 80% of mobility market sales by 2040. Yet, public distrust in AVs remains a major obstacle to the establishment of smart cities worldwide. The core issue underlying public distrust in AVs is the gap between two processes: the embedding of social responsibility in machine learning algorithms (development of a responsible algorithm), and a nascent culture of institutional management that defines and safeguards ethical technology as a central value (responsible infrastructure). This paper proposes a multi-perspective model of responsible innovation Ecosystem, which includes a responsibility embedded algorithm and a responsible regulatory infrastructure to facilitate public trust in AV technology. Drawing on scholarship from multiple disciplines, this paper draws together expertise from technological, social, and legal fields to investigate the development of trust based AVs (TAVs). Our paper is built on interactional theories of trust and explores socio-legal and technological solutions to promote TAVs. At the infrastructural level, we will discuss how various institutions define and safeguard technological trust as a value. At the algorithmic level, we will propose the concept of a responsible algorithm that embeds legal rules and ethical concerns into AV computing.