Attitudes toward vehicle-based sensing and recording

Vehicles increasingly include features that rely on hi-tech sensors and recording; however, little is known of public attitudes toward such recording. We use two studies, an online survey (n=349) and an interview-based study (n=15), to examine perceptions of vehicle-based sensing and recording. We focus on: 1) how vehicle-based recording and sensing may differ from perceptions of current recording; 2) factors that impact comfort with vehicle-based recording for hypothetical drivers versus bystanders; and 3) perceptions of potential privacy-preserving techniques. We find that vehicle-based recording challenges current mental models of recording awareness. Comfort tends to depend on perceived benefits, which can vary by stakeholder type. Perceived privacy in spaces near cars can also impact comfort and reflect mental models of private spaces as well as the range of potentially sensitive activities people perform in and near cars. Privacy-preserving techniques may increase perceived comfort but may require addressing trust and usability issues.

[1]  Gregory D. Abowd,et al.  Technological approaches for addressing privacy concerns when recognizing eating behaviors with wearable cameras , 2013, UbiComp.

[2]  Elaine M. Huang,et al.  Hacking the Natural Habitat: An In-the-Wild Study of Smart Homes, Their Development, and the People Who Live in Them , 2012, Pervasive.

[3]  Sunny Consolvo,et al.  Using the Experience Sampling Method to Evaluate Ubicomp Applications , 2003, IEEE Pervasive Comput..

[4]  Marc Langheinrich,et al.  Encountering SenseCam: personal recording technologies in everyday life , 2009, UbiComp.

[5]  Gregory D. Abowd,et al.  Prototypes and paratypes: designing mobile and ubiquitous computing applications , 2005, IEEE Pervasive Computing.

[6]  Shwetak N. Patel,et al.  Investigating receptiveness to sensing and inference in the home using sensor proxies , 2012, UbiComp.

[7]  Gregory D. Abowd,et al.  Prototyping and sampling experience to evaluate ubiquitous computing privacy in the real world , 2006, CHI.

[8]  Tadayoshi Kohno,et al.  In situ with bystanders of augmented reality glasses: perspectives on recording and privacy-mediating technologies , 2014, CHI.

[9]  Srdjan Capkun,et al.  Home is safer than the cloud!: privacy concerns for consumer cloud storage , 2011, SOUPS.

[10]  Daniel R. Horne,et al.  The Privacy Paradox: Personal Information Disclosure Intentions versus Behaviors , 2007 .

[11]  Martin Ortlieb,et al.  A Comparison of Six Sample Providers Regarding Online Privacy Benchmarks , 2014 .

[12]  Fahim Kawsar,et al.  Exploring the design space for geo-fenced connected devices and services at home , 2014, UbiComp Adjunct.

[13]  Faisal Z. Qureshi,et al.  Negotiating Privacy Preferences in Video Surveillance Systems , 2011, IEA/AIE.

[14]  Batya Friedman,et al.  The Watcher and the Watched: Social Judgments About Privacy in a Public Place , 2006, Media Space 20+ Years of Mediated Life.

[15]  Khai N. Truong,et al.  Understanding Recording Technologies in Everyday Life , 2010, IEEE Pervasive Computing.

[16]  Gillian R. Hayes,et al.  Situating the concern for information privacy through an empirical study of responses to video recording , 2011, CHI.

[17]  Antti Oulasvirta,et al.  Long-term effects of ubiquitous surveillance in the home , 2012, UbiComp.

[18]  Carman Neustaedter,et al.  Exploring video streaming in public settings: shared geocaching over distance using mobile video chat , 2014, CHI.

[19]  Adam J. Berinsky,et al.  Evaluating Online Labor Markets for Experimental Research: Amazon.com's Mechanical Turk , 2012, Political Analysis.

[20]  Sunny Consolvo,et al.  Living in a glass house: a survey of private moments in the home , 2011, UbiComp '11.

[21]  Michael D. Buhrmester,et al.  Amazon's Mechanical Turk , 2011, Perspectives on psychological science : a journal of the Association for Psychological Science.