Autonomous Vehicles, Artificial Intelligence, Risk and Colliding Narratives

Autonomous vehicles (AVs) are often claimed to offer many societal benefits. Perhaps, the most important is the potential to save countless lives through anticipated improvements in safety by replacing human drivers with AI drivers. AVs will also dramatically change the nature of transportation because AI drivers will not get tired and can work without the risk of fatigue or the need for rest. Hence, the economic and societal impacts are enormous on productivity, supply chains and access to goods. Furthermore, the algorithmic efficiencies of AVs could have significant environmental benefits through transportation optimisation and fuel management. The benefits combine to frame a utopian socio-economic vision of an AV future. While the vision communicates an AV and AI utopia, the AV vision does not communicate other important components such as the financial costs of such a radical change in transportation, who will pay for required changes in infrastructure, what are the risks of the change, and who is responsible and accountable if significant failures or problems occur with AI. Furthermore, it remians unclear who passengers are trusting with their safety and lives by using AVs. The move to AVs changes how people typically understand safety and trust. Passengers of AVs will face complex decisons built on trust. Passengers will certainly need to trust the AI driver, the corporation behind the AI operating system, state regulators overseeing and governing the production and use of AVs as well as a potential new service industry required to test and calibrate the sensors, and algorithms that the AI driving intelligence is based on. In light of the promise of an AV utopia and the many related questions, the research contrasts the AV narrative of utopian futures with the sobering reality that any AV future will be built on lucrative innovative AV business models. Hence, the analysis reframes the narrative as a construct best described as a business tool to leverage support from a broad spectrum of social stakeholders. The chapter unpacks several thematic points to understand better how the commercial use of AV narratives offers many benefits for AV commercialisation but also presents complex risks for societies. A part of the analysis focuses on elucidating the complex relationality of AV innovation to assess ethical-risk relations regarding how commercial actors influence the meaning of AVs for commercial gain. The AV narrative points to a tendency to promote optimistic visions of uncertain futures that promote trust in AI and AVs while obfuscating risks by creating complex knowledge and information asymmetries.