Helping Users with Information Disclosure Decisions                                       Potential for Adaptation      Ba...
Mobile apps need personal data                 Mobile applications often                 use personalization              ...
Justifying disclosure                  Privacy problems!                     Give people control                  Privacy ...
Justification typesExplain the reason why the information is requested   May prove the legitimacy of the disclosure request...
Outline (spoiler alert)Which justification works best?   Actually, “no justification” works best!Can we do better?   We can ...
Experiment             INFORMATION AND COMPUTER SCIENCES
Experiment             INFORMATION AND COMPUTER SCIENCES
Manipulations      Location, etc.    Gender, etc.  Gender, etc.               Location, etc.   Context data first   Demogra...
Manipulations5 justification types                       INFORMATION AND COMPUTER SCIENCES
Manipulations5 justification types   None                       INFORMATION AND COMPUTER SCIENCES
Manipulations5 justification types   None   Useful for you                       INFORMATION AND COMPUTER SCIENCES
Manipulations5 justification types   None   Useful for you   Number of others                       INFORMATION AND COMPUTE...
Manipulations5 justification types   None   Useful for you   Number of others   Useful for others                       INF...
Manipulations5 justification types   None   Useful for you   Number of others   Useful for others   Explanation            ...
Which one is best?Which increases disclosure the most?Which increases satisfaction the most?                              ...
Results                              Disclosure*behavior*                                              *           Demogra...
Results                                   Disclosure*behavior*                                                   *        ...
ResultsJustifications are perceived               Perceived(value(of(to be helpful          Disclosure*behavior* disclosure...
ResultsJustifications are perceived                Perceived(privacy(to be helpful          Disclosure*behavior*     threat...
ResultsJustifications are perceived                                                   Trust&in&the&&to be helpful          ...
ResultsJustifications are perceived                 Sa#sfac#on)with))to be helpful          Disclosure*behavior*   the)syst...
Problem!Justifications did not have the expected effectsPeople liked the help, but:   No increase in disclosure (bad for pe...
Idea: Adaptation           I care about           the benefits                 I do whatever                    others do  ...
Idea: Adaptation                    I am more                  hesitant about    Location, etc. demographics          Gend...
Adapt to what?Big differences in privacy behavior:      2 groups, 0-22 items and 23-31 items3 privacy groups, based on dis...
Heuristics                                                               Males with low disclosure tendency (73 participan...
Heuristics              Satisfaction              - Context first, ‘explanation’ justification              - Demographics fi...
Heuristics -- best compromise                                                          Males with low disclosure tendency ...
50%!                                                                                                                35%! D...
0,0! 50%!     66%!                    -0,5!                              64%! -0,5!                                   40%!...
0,0! 50%!                                                  -0,5!                                       -0,5!              ...
Following the heuristicsHow to discover gender? - Can just be the first item to request - Highest disclosure rate of all it...
Future workTest the heuristics in a real system   And not just an app recommenderFind the rationale behind the heuristics ...
Conclusion (you already know this)Which justification works best?   Actually, “no justification” works best!Can we do better...
Thank youbart.k@uci.edu :: www.usabart.nl :: @usabart
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Helping Users with Information Disclosure Decisions: Potential for Adaptation (IUI2013 presentation)

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Presentation at IUI2013, Santa Monica. The full paper can be found at http://bit.ly/iui2013full

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Helping Users with Information Disclosure Decisions: Potential for Adaptation (IUI2013 presentation)

  1. 1. Helping Users with Information Disclosure Decisions Potential for Adaptation Bart P. Knijnenburg Alfred KobsaDepartment of Informatics, UC Irvine Department of Informatics, UC Irvine
  2. 2. Mobile apps need personal data Mobile applications often use personalization This requires personal information - Demographical data (e.g. age, hobbies, income) - Contextual data (e.g. app usage, calendar, location) INFORMATION AND COMPUTER SCIENCES
  3. 3. Justifying disclosure Privacy problems! Give people control Privacy calculus: Tradeoff between privacy and expected benefits Benefits are hard to grasp Provide justifications INFORMATION AND COMPUTER SCIENCES
  4. 4. Justification typesExplain the reason why the information is requested May prove the legitimacy of the disclosure requestHighlight the benefits of disclosure Privacy calculus: tip the scales in favor of the benefitsAppeal to the social norm Eschew privacy calculus by conforming to the majorityPrevious work: Justifications seem to work Our goal: Find out which one works best INFORMATION AND COMPUTER SCIENCES
  5. 5. Outline (spoiler alert)Which justification works best? Actually, “no justification” works best!Can we do better? We can adapt the justification (and request order) to the user!What does that give us? A set of implementable heuristics!How can we extend these findings? Create a fully adaptive system! INFORMATION AND COMPUTER SCIENCES
  6. 6. Experiment INFORMATION AND COMPUTER SCIENCES
  7. 7. Experiment INFORMATION AND COMPUTER SCIENCES
  8. 8. Manipulations Location, etc. Gender, etc. Gender, etc. Location, etc. Context data first Demographical data first INFORMATION AND COMPUTER SCIENCES
  9. 9. Manipulations5 justification types INFORMATION AND COMPUTER SCIENCES
  10. 10. Manipulations5 justification types None INFORMATION AND COMPUTER SCIENCES
  11. 11. Manipulations5 justification types None Useful for you INFORMATION AND COMPUTER SCIENCES
  12. 12. Manipulations5 justification types None Useful for you Number of others INFORMATION AND COMPUTER SCIENCES
  13. 13. Manipulations5 justification types None Useful for you Number of others Useful for others INFORMATION AND COMPUTER SCIENCES
  14. 14. Manipulations5 justification types None Useful for you Number of others Useful for others Explanation INFORMATION AND COMPUTER SCIENCES
  15. 15. Which one is best?Which increases disclosure the most?Which increases satisfaction the most? INFORMATION AND COMPUTER SCIENCES
  16. 16. Results Disclosure*behavior* * Demographics*disclosure * *Context*disclosure* Context#first# Demographics#first# Context#first# Demograpics#first#100%# 90%# 80%# 70%# 60%# 50%# 40%# 30%# 20%# 10%# 0%# INFORMATION AND COMPUTER SCIENCES
  17. 17. Results Disclosure*behavior* * Demographics*disclosure * *Context*disclosure* Context"first" Demographics"first" Context"first" Demograpics"first"100%" 90%" 1" 80%" ***" 70%" *" **" *" 60%" *" *" 50%" 40%" 30%" 20%" 10%" 0%" none" useful"for"you" #"of"others" useful"for"others" explanaDon" INFORMATION AND COMPUTER SCIENCES
  18. 18. ResultsJustifications are perceived Perceived(value(of(to be helpful Disclosure*behavior* disclosure(help( (except “# of others”) * Demographics*disclosure * ***" *Context*disclosure* Context"first" Demographics"first" 1,00" Context"first" ***" Demograpics"first"100%" 0,75" **" 90%" 1" 80%" ***" 0,50" 70%" 0,25" *" **" *" 60%" 0,00" *" *" 50%" #0,25" 40%" 30%" #0,50" 20%" #0,75" 10%" #1,00" 0%" none" useful"for"you" #"of"others" useful"for"others" explanaDon" INFORMATION AND COMPUTER SCIENCES
  19. 19. ResultsJustifications are perceived Perceived(privacy(to be helpful Disclosure*behavior* threat( (except “# of others”) * Demographics*disclosure * *Context*disclosure* Context"first" Demographics"first" 1,00" Context"first" Demograpics"first"100%"Higher privacy threat seen 90%" 1" 0,75" *"for “useful for others” 80%" ***" 0,50" 70%" 0,25" *" **" *" 60%" 0,00" *" *" 50%" #0,25" 40%" 30%" #0,50" 20%" #0,75" 10%" #1,00" 0%" none" useful"for"you" #"of"others" useful"for"others" explanaDon" INFORMATION AND COMPUTER SCIENCES
  20. 20. ResultsJustifications are perceived Trust&in&the&&to be helpful Disclosure*behavior* company& (except “# of others”) * Demographics*disclosure * *Context*disclosure* Context"first" Demographics"first" 1,00" Context"first" Demograpics"first"100%"Higher privacy threat seen 90%" 1" 0,75"for “useful for others” 80%" ***" 0,50" 70%" 0,25" *" **" *"Lower trust in the company 60%"50%" 0,00" *" *" $0,25" 40%" (esp. “useful for others”) $0,50" 30%" 1" 20%" $0,75" **" 10%" $1,00" 0%" none" useful"for"you" #"of"others" useful"for"others" explanaDon" INFORMATION AND COMPUTER SCIENCES
  21. 21. ResultsJustifications are perceived Sa#sfac#on)with))to be helpful Disclosure*behavior* the)system) (except “# of others”) * Demographics*disclosure * *Context*disclosure* Context"first" Demographics"first" 1,00" Context"first" Demograpics"first"100%"Higher privacy threat seen 90%" 1" 0,75"for “useful for others” 80%" ***" 0,50" 70%" 0,25" *" **" *"Lower trust in the company 60%"50%" 0,00" *" *" $0,25" 40%" (esp. “useful for others”) $0,50" 30%" 1" **" **"Lower satisfaction 20%" $0,75"10%" $1,00" ***" 0%" none" useful"for"you" #"of"others" useful"for"others" explanaDon" INFORMATION AND COMPUTER SCIENCES
  22. 22. Problem!Justifications did not have the expected effectsPeople liked the help, but: No increase in disclosure (bad for personalization) No decrease in perceived threat, no increase in trust Satisfaction is lower INFORMATION AND COMPUTER SCIENCES
  23. 23. Idea: Adaptation I care about the benefits I do whatever others do INFORMATION AND COMPUTER SCIENCES
  24. 24. Idea: Adaptation I am more hesitant about Location, etc. demographics Gender, etc.Gender, etc. Location, etc. I am more hesitant about context data INFORMATION AND COMPUTER SCIENCES
  25. 25. Adapt to what?Big differences in privacy behavior: 2 groups, 0-22 items and 23-31 items3 privacy groups, based on disclosure tendency Privacy fundamentalists, pragmatists, and unconcernedGender Females have higher concerns, especially for context dataAge didn’t work Older people have higher concerns, but are also more careful INFORMATION AND COMPUTER SCIENCES
  26. 26. Heuristics Males with low disclosure tendency (73 participants)! 87%! Demograhics data! Context data! 80%! 90%! 98%! p = .057!Disclosure probability! 100%! 90%! 67%! p = .003! 67%! ■ Demographics first 80%! p = .003! ● Context first 70%! 60%! 45%! p = .079! 46%! 69%! 42%! 50%! p < .001! 35%! 40%! 53%! 57%! 48%! p < .001! 30%! 46%! p < .001! P = .002! p < .001! P = .004! 20%! p < .001! 30%! 29%! 30%! ! ! 10%! p = .055! p = .076! p = .054! 17%! 14%! 0%! no! useful! number ! useful for! expla-! no! useful! number ! useful for! expla-! justification! for you! of others! others! nation! justification! for you! of others! others! nation! Demographics disclosure Females with low disclosure tendency (88 data disclosure Context participants)! - Demographics first, - Context first, no Demograhics data! Context data!Disclosure probability! 100%! 90%! 81%! 79%! 75%! 57%! ‘explanation’ justification justification 80%! p = .027! 89%! 70%! 51%! 47%! 51%! 60%! 46%! 50%! 66%! 64%! 40%! 60%! 58%! 40%! ! p < .001! Overall disclosure: Context first, ‘useful for < .001! justification p you’ p < .001! p < .001! 48%! p = .010! p = .009! 30%! p = .005! p < .001! ! 20%! ! p < .001! ! 36%! ! 27%! 10%! 23%! 20%! 0%! 11%! no! useful! number ! useful for! expla-! no! useful! number ! useful for! expla-! INFORMATION AND COMPUTER SCIENCES justification! for you! of others! others! nation! justification! for you! of others! others! nation!
  27. 27. Heuristics Satisfaction - Context first, ‘explanation’ justification - Demographics first ‘useful for you’ justification Males with low disclosure tendency (73 participants) ■ Demographics first ● Context firstPerceived disclosure help! Perceived privacy threat! Trust in the company! Satisfaction!2,0! 1,5! p=.063 1,5! 1,0! p=.0231,5! 1,0! 1,0! 0,5!1,0! 0,5! p=.089 0,5! 0,0! p=.097 p=.052 p=.0660,5! 0,0! 0,0! -0,5! p=.045 p=0230,0! -0,5! -0,5! -1,0! p=.009 p=.008 p=.012 p=.006-0,5! =.009 -1,0! -1,0! p=.036 p=.038 -1,5!-1,0! -1,5! -1,5! -2,0! useful! usef. useful! usef. useful! usef. useful! usef. no! for # of! for expl.! no! for # of! for expl.! no! for # of! for expl.! no! for # of! for expl.! just.! you! othrs! othrs! just.! you! othrs! othrs! just.! you! othrs! othrs! just.! you! othrs! othrs! INFORMATION AND COMPUTER SCIENCES
  28. 28. Heuristics -- best compromise Males with low disclosure tendency (73 participants)! 87%! Demograhics data! Context data! 80%! 90%! 98%! p = .057!Disclosure probability! 100%! 90%! 67%! p = .003! 67%! ■ Demographics first 80%! p = .003! ● Context first 70%! 60%! 45%! p = .079! 46%! 69%! 42%! 50%! p < .001! 35%! 40%! 53%! 57%! 48%! p < .001! 30%! 46%! p < .001! P = .002! p < .001! P = .004! 20%! p < .001! 30%! 29%! 30%! ! ! 10%! p = .055! p = .076! p = .054! 17%! 14%! 0%! no! useful! number ! useful for! expla-! no! useful! number ! useful for! expla-! justification! for you! of others! others! nation! justification! for you! of others! others! nation! Males with low disclosure tendency (73 participants) Perceived disclosure help! Females with low disclosure tendency (88 participants)! Perceived privacy threat! Trust in the company! Satisfaction! 2,0! 1,5! 1,5! 1,0! Demograhics data! p=.063 Context data! p=.023Disclosure probability! 100%! 1,5! 1,0! 1,0! 0,5! 90%! 81%! 79%! 75%! 57%! p=.089 1,0! 80%! 0,5! 0,5! 0,0! p=.097 p = .027! 89%! p=.052 p=.066 0,5! 70%! 0,0! 0,0! 51%! -0,5! 51%! 60%! p=.045 46%! 47%! p=023 40%! 0,0! 50%! 66%! -0,5! 64%! -0,5! -1,0! p=.009 p=.008 p=.012 60%! 58%! 40%! ! p=.006 p < .001! p = .010! p = .009!-0,5! 30%! p = .005! p < .001! -1,0!< .001! p 48%! -1,0! -1,5! p=.036 =.009 p=.038 p < .001! ! 20%! p < .001! ! p < .001! ! 36%!-1,0! -1,5! -1,5! ! -2,0! 27%! 10%! useful! usef. useful! usef. 23%! useful! usef. 20%! useful! usef. no! for # of! for expl.! 0%! no! for # of! for expl.! no! for # of! 11%! expl.! for no! for # of! for expl.! just.! you!no! useful! othrs! othrs! just.! ! number you!useful for! othrs! othrs! expla-! just.!no! useful! you! othrs! othrs! number just.!useful for! othrs! ! you! othrs! expla-! INFORMATION AND COMPUTER SCIENCES justification! for you! of others! others! nation! justification! for you! of others! others! nation!
  29. 29. 50%! 35%! Disclosure p < .001! 57%! 40%! 53%! 48%! p < .001! 30%! 46%! p < .001! P = .002! p < .001! P = .004! 20%! p < .001! 30%! 29%! 30%! ! Heuristics ! 10%! p = .055! p = .076! p = .054! 17%! 14%! 0%! no! useful! number ! useful for! expla-! no! useful! number ! useful for! expla-! justification! for you! of others! others! nation! justification! for you! of others! others! nation! Males with low disclosure tendency (73 participants) Perceived disclosure help! Females with low disclosure tendency (88 participants)! Perceived privacy threat! Trust in the company! Satisfaction! 2,0! 1,5! Demograhics data! p=.063 1,5! 1,0! Context data! p=.023 Disclosure probability! 100%! 1,5! 1,0! 1,0! 0,5! 90%! 57%! 81%! 79%! 75%! ■ Demographics first 1,0! 80%! p = .027! 0,5! 89%! p=.089 0,5! 0,0! ● Context first p=.097 70%! p=.052 p=.066 0,5! 0,0! 0,0! 51%! -0,5! 51%! 60%! p=.045 46%! 47%! p=023 40%! 0,0! 50%! 66%! -0,5! 64%! -0,5! -1,0! p=.009 p=.008 p=.012 60%! 58%! 40%! ! p=.006 p < .001! p = .010! p = .009! -0,5! 30%! p = .005! p < .001! -1,0!< .001! p 48%! -1,0! -1,5! p=.036 =.009 p=.038 p < .001! ! 20%! p < .001! ! p < .001! ! 36%! -1,0! -1,5! -1,5! ! -2,0! 27%! 10%! useful! usef. useful! usef. 23%! useful! usef. 20%! useful! usef. 0%! for # of! for expl.! no! no! for # of! for expl.! no! for # of! for 11%! expl.! no! for # of! for expl.! just.! you!no! useful! othrs! othrs! number you!useful for! just.! ! othrs! othrs! expla-! just.!no! useful! you! othrs! othrs! number just.!useful for! othrs! ! you! othrs! expla-! justification! for you! of others! others! nation! justification! for you! of others! others! nation! Females with low disclosure tendency (88 participants) Perceived disclosure help! Perceivedwith high disclosure tendency (150 participants)! Males privacy threat! Trust in the company! Satisfaction!2,0! 1,5! Demograhics data! 1,5! 1,0! Context data! 99%! 98%! 97%! 100%! 99%! Disclosure probability!1,5! 100%! 1,0! p=.012 1,0! 0,5! 87%! 76%! 78%! ! 90%! p=.036 p = .063! p=.036 78%! 88%! p = .041!1,0! 97%! 0,5!95%! 98%! p = .055! 80%! 95%! p=.006 p = .055! 93%! 0,5! 0,0! 70%! p = .012! p = .014! p = .099! 85%!0,5! 0,0! p = .002! 0,0! 82%! 80%! -0,5! 60%! p=.026 70%! p=.061 72%!0,0! 50%! -0,5! -0,5! -1,0! p = .014! p = .004! p=.045 40%! p<.001-0,5! 30%! -1,0! -1,0! -1,5! p<.001 20%!-1,0! -1,5! -1,5! -2,0! 10%! useful! usef. useful! usef. useful! usef. useful! usef. 0%! for # of! for expl.! no! no! for # of! for expl.! no! for # of! for expl.! no! for # of! for expl.! no! othrs!useful! just.! you! othrs! number you! useful for! just.! ! othrs! othrs! expla-! no! useful! just.! you! othrs! othrs! number !just.! you!for! useful othrs! othrs! expla-! justification! for you! of others! others! nation! justification! for you! INFORMATION ANDothers! SCIENCES of others! COMPUTER nation!
  30. 30. 0,0! 50%! 66%! -0,5! 64%! -0,5! 40%! -1,0! p=.009 p=.008 p=.012 Disclosure 60%! 58%! 40%! ! p=.006 p < .001! p = .010! p = .009! -0,5! 30%! p = .005! p < .001! -1,0!< .001! p 48%! -1,0! -1,5! p=.036 =.009 p=.038 p < .001! ! 20%! p < .001! ! p < .001! ! 36%! 27%! Heuristics -1,0! -1,5! -1,5! ! -2,0! 10%! useful! usef. useful! usef. 23%! useful! usef. 20%! useful! usef. 0%! for # of! for expl.! no! no! for # of! for expl.! no! for # of! 11%! expl.! for no! for # of! for expl.! just.! you!no! useful! othrs! othrs! just.! ! number you!useful for! othrs! othrs! expla-! just.!no! useful! you! othrs! othrs! number just.!useful for! othrs! ! you! othrs! expla-! justification! for you! of others! others! nation! justification! for you! of others! others! nation! Females with low disclosure tendency (88 participants) Perceived disclosure help! Perceivedwith high disclosure tendency (150 participants)! Males privacy threat! Trust in the company! Satisfaction!2,0! 1,5! Demograhics data! 1,5! 1,0! Context data! 99%! 98%! 97%! 100%! 99%! p=.012 Disclosure probability!1,5! 100%! 1,0! ! 1,0! 78%! 0,5! 87%! 76%! 90%! p=.036 p = .063! p=.036 78%! 88%! p = .041!1,0! 97%! 0,5!95%! 98%! p = .055! 80%! 95%! p=.006 p = .055! 93%! 0,5! 0,0! 70%! p = .012! p = .014! p = .099! 85%!0,5! 0,0! p = .002! 0,0! 82%! 80%! -0,5! 60%! p=.026 70%! p=.061 72%!0,0! 50%! -0,5! -0,5! -1,0! p = .014! p = .004! p=.045 40%! p<.001-0,5! 30%! p<.001 -1,0! -1,0! -1,5! ■ Demographics first-1,0! 20%! 10%! useful! usef. -1,5! useful! usef. -1,5! useful! usef. -2,0! ● useful! first Context usef. 0%! for # of! for expl.! no! no! for # of! for expl.! no! for # of! for expl.! no! for # of! for expl.! just.! you! no! othrs!useful! othrs! number you! useful for! just.! ! othrs! othrs! expla-! no! useful! just.! you! othrs! othrs! number !just.! you!for! useful othrs! othrs! expla-! justification! for you! of others! others! nation! justification! for you! of others! others! nation! Males with high disclosure tendency (150 participants)Perceived disclosure help! Females with high disclosure tendency (178 participants)! Perceived privacy threat! Trust in the company! Satisfaction!2,0! 1,5! Demograhics data! 99%! 1,5! 95% ! 1,0! Context data! 99%! 99%! 96% ! p = .024! Disclosure probability!1,5! 100%! 1,0! 1,0! 88%! 86%! 0,5! 83%! 84%! p=.056 ! p = .049! 71% ! 90%!1,0! 80%! p=.011 95%! 0,5! 96%! 96%! 0,5! p = .003! 0,0! p=.001 p=.032 91%! p=.003 92%! p=.049 p = .069!0,5! 70%! p = .029! p = .002! p = .001! p=.039= .046! 0,0! p p=.032 0,0! -0,5! p=.047 60%! p=.061 71%! 75%! 75%! p<.001 p<.001 68%! 0,0! 50%! -0,5! p=.060 -0,5! p = .004! p = .016! 65%! -1,0! p = .018! p < .001! p = .001! 40%!-0,5! 30%! -1,0! -1,0! -1,5! 20%!-1,0! -1,5! -1,5! -2,0! 10%! useful! usef. useful! usef. useful! usef. useful! usef. 0%! for # of! for expl.! no! no! for # of! for expl.! no! for # of! for expl.! no! for # of! for expl.! no! othrs!useful! just.! you! othrs! number you! useful for! just.! ! othrs! othrs! expla-! no! useful! just.! you! othrs! othrs! number !just.! you!for! useful othrs! othrs! expla-! justification! for you! of others! others! nation! justification! for you! INFORMATION ANDothers! SCIENCES of others! COMPUTER nation!
  31. 31. 0,0! 50%! -0,5! -0,5! -1,0! p = .004! p=.045 p = .014! Disclosure 40%! p<.001-0,5! 30%! -1,0! -1,0! -1,5! p<.001 20%! Heuristics-1,0! -1,5! -1,5! -2,0! 10%! useful! usef. useful! usef. useful! usef. useful! usef. 0%! for # of! for expl.! no! no! for # of! for expl.! no! for # of! for expl.! no! for # of! for expl.! just.! you! no! othrs!useful! othrs! just.! ! number you! useful for! othrs! othrs! expla-! just.! you! othrs! othrs! no! useful! number !just.! you!for! useful othrs! expla-! othrs! justification! for you! of others! others! nation! justification! for you! of others! others! nation! Males with high disclosure tendency (150 participants)Perceived disclosure help! Females with high disclosure tendency (178 participants)! Perceived privacy threat! Trust in the company! Satisfaction!2,0! 1,5! Demograhics data! 99%! 1,5! 95% ! 1,0! Context data! 99%! 99%! 96% ! p = .024! Disclosure probability! 1,5! 100%! p=.056 1,0! ! 1,0! 88%! 86%! 0,5! 83%! 84%! p = .049! 71% ! 90%! 1,0! p=.011 0,5! p=.003 96%! 96%! 0,5! p = .003! 0,0! 80%! 95%! p=.001 p=.032 91%! 92%! p=.039= .046! p p=.049 p = .069! p=.032 0,5! 70%! p = .029! p = .002! 0,0! = .001! p 0,0! -0,5! p=.047 60%! p<.001 p=.061 71%! 75%! 75%! p<.001 p = .016! 68%! p = .018! 0,0! 50%! -0,5! p=.060 -0,5! p = .004! 65%! -1,0! p < .001! p = .001! 40%!-0,5! 30%! -1,0! -1,0! -1,5! ■ Demographics first-1,0! 20%! -1,5! -1,5! -2,0! ● Context first 10%! useful! usef. useful! usef. useful! usef. useful! usef. 0%! for # of! for expl.! no! no! for # of! for expl.! no! for # of! for expl.! no! for # of! for expl.! just.! you! no! othrs!useful! othrs! number you! useful for! just.! ! othrs! othrs! expla-! no! useful! just.! you! othrs! othrs! number !just.! you!for! useful othrs! othrs! expla-! justification! for you! of others! others! nation! justification! for you! of others! others! nation! Females with high disclosure tendency (178 participants)Figure 3: disclosure help! justification type and request order on disclosure (for each type of data, gender, and disclosure tendency) Perceived The effects of Perceived privacy threat! Trust in the company! Satisfaction!Error bars are ±1 standard error.1,5! best strategy is labeled with an arrow; strategies with a p-value perform significantly worse 2,0! The 1,5! 1,0! 1,5! 1,0! 1,0! 0,5! p=.001 1,0! p=.032 0,5! p=.002 0,5! 0,0! p=.058 p=.025 p=.074 p=.039 0,5! 0,0! 0,0! -0,5! p=.001 p=.049 p=.059 p=.003 p=.039 p=.041 0,0! -0,5! -0,5! -1,0!-0,5! -1,0! -1,0! -1,5!-1,0! -1,5! -1,5! -2,0! useful! usef. useful! usef. useful! usef. useful! usef. no! for # of! for expl.! no! for # of! for expl.! no! for # of! for expl.! no! for # of! for expl.! just.! you! othrs! othrs! just.! you! othrs! othrs! just.! you! othrs! othrs! just.! you! othrs! othrs! INFORMATION AND COMPUTER SCIENCES
  32. 32. Following the heuristicsHow to discover gender? - Can just be the first item to request - Highest disclosure rate of all items in our study (94.9%)How to discover disclosure tendency? - Make some (potentially invasive) requests (not desirable) - Ask about (or otherwise determine) stated privacy concerns, mobile Internet usage and/or tech-savvyness INFORMATION AND COMPUTER SCIENCES
  33. 33. Future workTest the heuristics in a real system And not just an app recommenderFind the rationale behind the heuristics E.g. why do males and females require different justifications?Make the system even more adaptive - Select the optimal justification for each item - Order the requests dynamically to ensure the highest possible disclosure (without reducing satisfaction) INFORMATION AND COMPUTER SCIENCES
  34. 34. Conclusion (you already know this)Which justification works best? Actually, “no justification” works best!Can we do better? We can adapt the justification (and request order) to the user!What does that give us? A set of implementable heuristics!How can we extend these findings? Create a fully adaptive system! INFORMATION AND COMPUTER SCIENCES
  35. 35. Thank youbart.k@uci.edu :: www.usabart.nl :: @usabart

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