Responsible innovation; responsible data. A case study in autonomous driving

Autonomous Vehicles (AVs) collect a vast amount of data during their operation (MBs/sec). What data is recorded, who has access to it, and how it is analysed and used can have major technical, ethical, social, and legal implications. By embedding Responsible Innovation (RI) methods within the AV lifecycle, negative consequences resulting from inadequate data logging can be foreseen and prevented. An RI approach demands that questions of societal benefit, anticipatory governance, and stakeholder inclusion, are placed at the forefront of research considerations. Considered as foundational principles, these concepts create a contextual mindset for research that will by definition have an RI underpinning as well as application. Such an RI mindset both inspired and governed the genesis and operation of a research project on autonomous vehicles. The impact this had on research outlines and workplans, and the challenges encountered along the way are detailed, with conclusions and recommendations for RI in practice.