Presentation
To Pay or not to Pay: Users’ Selection Decisions for Autonomous Vehicle Ridesharing
SessionPoster Session 1
DescriptionAs user data becomes an increasingly valuable cornerstone for the development of software, it comes at the price of user privacy. This exchange results in user data being susceptible to cyberattackers, placing users at risks. Recent work developed privacy rating displays to help encourage users to engage in pro-privacy behavior by illustrating the risks and benefits of a product. However, the effect of the privacy rating tool on whether users actually engage in pro-privacy behavior has not been examined. The current study conducted an online survey that presented two automated vehicles in a ridesharing selection task that differed by privacy premium (0%, 10%, 20%), privacy risk (Low vs. High, Low vs. Medium, Medium vs. High), and a default option (pro-privacy, anti-privacy). Results revealed that when the privacy risk between the two automated vehicles was substantial, users overwhelmingly selected the pro-privacy vehicle, even with increasing privacy premiums. This result suggests that displaying privacy risk information encourages pro-privacy behavior. However, our survey did not contain a control group for direct comparison. Future research is needed to investigate the extent to which pro-privacy behavior is encouraged with privacy rating tool in comparison to a control group without privacy rating tools.
Event Type
Poster
TimeTuesday, October 14th5:30pm - 6:30pm CDT
LocationRiverside East
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