Challenges in Supporting End-User Privacy and Security Management with Social Navigation

1. Challenges in Supporting End-User Privacy and Security Management with Social Navigation Jeremy Goecks, W. Keith Edwards, and Elizabeth D. Mynatt

2. Decision Making in End-User Privacy and Security Management • Privacy and security management often about boundary management (Palen and Dourish, 2003; Dourish et al. 200?) • make decisions about what to allow across boundary • “hard on the outside, soft on the inside” • often cannot automate privacy and security management (Edwards et al., 2007) • Users must make decisions, but: • minimal knowledge • low motivation • prefer to delegate (Dourish et al. 200?) 2

3. Social Navigation • Collects, aggregates, and displays community data • Many kinds of community data • actions, choices • tags • free text • Supports socially-aided choices and decision making 3

4. Matching Social Nav to Decision- Making Problems also (Herzog & Shahmehri, 2007 ) also (DiGioia & Dourish, 2005 ) 4

5. Outline • Introduction • Acumen and Bonfire • Challenges • Summary 5

6. Acumen 6

7. Mavens (experts) data shown inside of community data promote good herding Automatic cookie management via rules balance automation with control make clear whether cookies blocked manually or via rule Acumen 7

8. Reflections on Acumen • Approach • support for “in the moment” decision making for privacy management with social navigation • promote good herding, mitigate bad herding • Preliminary deployment: 9 people, 6 weeks, ~2650 websites • Observations • difficult to evaluate decisions • multiple information sources • herding behavior observed; difficult to manage • experts not trusted, so not possible to promote “good” herding 8

9. Bonfire 9

10. Bonfire • Approach • mitigate herding by answering “what” and “why” • complementary sources of social navigation data • Lessons Learned • providing “what” and “why” makes it easier to use community data • cost of wrong answers is high, so preventing wrong answers is critical 10

11. Outline • Introduction • Acumen and Bonfire • Challenges • Summary 11

12. Challenges Raised by Acumen & Bonfire • Supporting use of multiple information sources for decision making • information that individual already has • community data • Managing herding • general lack of knowledge & ranges of expertise • desire to delegate • undesirable feedback loop that can lead to false majority 12

13. Traditional & Non-Traditional, Incomplete Information • Social navigation traditionally applied to decisions for books, movies, music • information is relatively complete • clear grasp of personal preferences • Privacy and many security decisions often different • use of incomplete and potentially inaccurate information • potentially unclear grasp of personal preferences 13

14. Model for Decision Making with Social Navigation Preferences, Incentives, Biases My Choice! • go with observations, knowledge, or facts • go with community consensus My Choice! Observations, knowledge, facts Community data 14

15. Lack of Info or Uncertainty Follow Majority Misrepresentation of Info “False” Majority Informational Cascades • Informational cascades - herding that arises when people ignoring their own information and go with the community(Banerjee 1992; Bikhchandani, Hirshleifer et al. 1992) • Real-world examples: financial markets(Devenow and Welch 1996; Walden and Browne 2002), movies & fads(Walden and Browne 2002), IT adoption(Bikhchandani, S., D. Hirshleifer, et al. 1998), politics(Bartels 1988), medicine(Robin 1984, Taubes 2007) 15

16. Informational Cascades in Social Navigation Systems • Social nav systems meet cascades criteria • sequential decision making • can see what others have done • discrete set of choices • Cascade behavior has been shown to occur in social nav systems (Goecks 2009) • Cascades occur regardless of system functionality • CF vs. simple aggregation • activity data collection vs. ratings 16

17. Info Cascades + Social Nav + Privacy and Security Management • Cascades are especially likely in social nav systems for privacy and security management • Because • general lack of expertise & knowledge • limited interest in providing additional data • desire to delegate 17

18. Mitigation via Algorithms • Methods for • limiting malicious ratings in a social nav system (Resnick and Sami, 2007) • starting cascades (Domingos & Richardson, 2001) • identifying cascades (Leskovec et al., 2007) • Challenges • unclear how to mitigate cascades • cascades often started by accident, different people • substantial data required for modeling • early adopters hurt • users must maintain stable identities 18

19. Mitigation via UI Techniques • Balance competing goals • use of community data • capture user knowledge and expertise 19

20. Future Work • Quantifying cascades impact • how often do cascades occur? • what is the cost of a “bad” decision? of many “bad” decisions? • true, false positives / true, false negatives • Bridging social navigation research with crowd wisdom research • when is a choice considered “correct”? • when can a choice be automatically acted on? 20

21. Summary • Acumen and Bonfire demonstrate how simple social navigation systems can be applied to privacy and security management activities • Info cascades can be quite problematic for social nav systems applied to privacy and security management • much use of incomplete, inaccurate information • much potential herding • Going forward • mitigating cascades via algorithms & user interaction • understanding the prevalence and cost of cascades • when to automatically act on community data 21

22. Contact Information http://www.cc.gatech.edu/~jeremyjeremy@cc.gatech.edu Jeremy GoecksEveryday Computing Lab & GVU CenterSchool of Interactive Computing, College of ComputingGeorgia Institute of Technology Thanks! 22

23. Social Influence Individual Normative Influence Informational Influence Herding Group Irrational Herding Informational Cascades Understanding Individual & Group Behavior in Social Nav Systems 23