Data underpinning journal article on the effect of public perception of autonomous vehicle capability on judgment of blame and trust in road traffic accidents

The data included in this Excel spreadsheet was collected as part of the ESRC-JST funded projected entitled "Rule of Law in the Age of AI: Principles of Distributive Liability for Multi-Agent Societies" with Phil Morgan as the primary investigator. The data underpins two experiments in the published article "Public perception of autonomous vehicle capability determines judgment of blame and trust in road traffic accidents". There are two data sheets in the file corresponding to the two experiments respectively. In both sheets, each row represents a case or a participant in the experiment. Each column represents a variable - whether it was manipulated as an independent variable or measured as a dependent variable. Key dependent variables includes demographic information of the participant, their pre-trial and post-trial ratings of trust in, and likelihood of using autonomou vehicles or human drivers as a mean of transport, their judgment of trust and blame regarding each specific scenarios (there were nine in total). There were also aggregated scores of these scenario-specific ratings.