1 / 27

Nudging People

Nudging People. Janne Lindqvist WINLAB, Dept. of ECE, Rutgers University NSF/DIMACS Workshop for Aspiring PIs in Secure and Trustworthy Cyberspace October 15, 2012. Preparing a Proposal Nugget. When evaluating NSF proposals, reviewers should consider what the proposers want to do,

yuki
Download Presentation

Nudging People

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Nudging People Janne Lindqvist WINLAB, Dept. of ECE, Rutgers University NSF/DIMACS Workshop for Aspiring PIs in Secure and Trustworthy Cyberspace October 15, 2012

  2. Preparing a Proposal Nugget • When evaluating NSF proposals, reviewers should consider what the proposers • want to do, • why they want to do it, • how they plan to do it, • how they will know if they succeed, • and what benefits would accrue if the project is successful. • http://www.nsf.gov/bfa/dias/policy/merit_review/overview.pdf

  3. Human-Centric Research Agenda My agenda: Applying soft nudges to human behavior with computer systems

  4. Research Interests • Problems that exist in the world or practical problems • (Ordinary) people - daily lives • Going beyond WEIRD (Western, Educated, Industrialized, Rich, and Democratic)

  5. Method • Spot a problem • Study behavior or attitudes • Implement a software system • Recruit people to use the system in their daily lives • See what happens

  6. Spot a Problem: Phones and Driving • 2009 mobile phones while driving cited as a factor in [US DOT HS 811 379]: • 995 deaths and 24,000 injuries in the US • During a typical daylight moment in the US in 2009, 9% of all drivers were using a hand-held or hands-free phone while driving. [US DOT HS 811 372]

  7. Nudge with the Phone

  8. Method • Spot a problem • Study behavior or attitudes • Implement a software system • Recruit people to use the system in their daily lives • See what happens

  9. Wall Street Journal Your Apps are Watching You Dec 2010

  10. Why Is This Important? • As of January 2012: • the Android Market offered 390,000 apps with more than 10 billion downloads since the Market’s launch • the Apple App Store offered more than 500,000 apps with over 18 billion downloads since its launch.

  11. What Are Your Apps Really Doing? Shares your location,gender, unique phone ID, phone# with advertisers Uploads your entire contact list to their server (including phone #s)

  12. Problem Should I install this app or not? People might ask? What do these permissions mean? Why does app need this permission? When does it usethese permissions?

  13. Method • Spot a problem • Study behavior or attitudes • Implement a software system • Recruit people to use the system in their daily lives • See what happens

  14. Expectation and Purpose: Understanding Users’ Mental Models of Mobile App Privacy through Crowdsourcing Jialiu Lin, Shahriyar Amini, Jason I. Hong, Norman Sadeh (CMU), Janne Lindqvist (Rutgers) Joy Zhang (CMU)in 14th ACM International Conference on Ubiquitous Computing (UbiComp’12)

  15. Can We Use Crowdsourcing? • Almost nobody reads privacy policies • We want to install the app • Reading policies not part of main task • Complexity of reading these policies (boring!!!!!) • Clear cost (my time) for unclear benefit • Crowdsourcing can mitigate these problems • But what to crowdsource here? • Our idea: expectations and misconceptions

  16. Privacy as Expectations • Apply this idea of mental models for privacy • Compare what people expect an app to do vs what an app actually does • Emphasize the biggest gaps, the misconceptions that most people had App Behavior (What an app actually does) User Expectation (What people think the app does)

  17. New Summaries • Simplified terms and bolded permissions • Only focused on permissions that affect privacy • Sorted by highest surprises • Added if above threshold

  18. What’s Next? • Spot a problem • Study behavior or attitudes • Implement a software system • Recruit people to use the system in their daily lives • See what happens

  19. Preparing a Proposal Nugget (Again) • When evaluating NSF proposals, reviewers should consider what the proposers • want to do, • why they want to do it, • how they plan to do it, • how they will know if they succeed, • and what benefits would accrue if the project is successful. • http://www.nsf.gov/bfa/dias/policy/merit_review/overview.pdf

  20. Summary

  21. Thank you! janne@winlab.rutgers.edu

  22. BACKUP SLIDES

  23. Changing Behavior with Computer Systems? • Understanding people • How are we nudged? • How can we be nudged? • Building systems • Engineering • Laboratory trials • Deploying systems for people to use in their daily lives • A lot of engineering

  24. Problem Focus • Should I install this app or not • This is what people are supposed to be asking, but they do not • Nudge people to ask it

  25. Ubiquity of Location-Enabled Devices [Berg Insight ‘10] 2009: 150 million GPS-equipped phones shipped 2014: 770 million GPS-equipped phones expected to ship (~5x increase!) Future: Every mobile device will be location-enabled

  26. Location-Based Services Growing

  27. Foursquare changes privacy settings as we recommended

More Related