TY - GEN
T1 - Taking Data out of Context to Hyper-Personalize Ads
T2 - 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI 2020
AU - Hanson, Julia
AU - Wei, Miranda
AU - Veys, Sophie
AU - Kugler, Matthew
AU - Strahilevitz, Lior
AU - Ur, Blase
N1 - Funding Information:
We thank Juliette Hainline, Emmi Russo, Chris Eidsmoe, Soy-oung Eom, Wendy Li, Alex Mueller, Elizabeth Woolridge Grant, Maitreyi Nabar, and Michael Vetter. This material is based upon work supported by the National Science Foundation in collaboration with Amazon under Grant No. 1939728.
Publisher Copyright:
© 2020 Owner/Author.
PY - 2020/4/21
Y1 - 2020/4/21
N2 - Data brokers and advertisers increasingly collect data in one context and use it in another. When users encounter a misuse of their data, do they subsequently disclose less information? We report on human-subjects experiments with 25 in-person and 280 online participants. First, participants provided personal information amidst distractor questions. A week later, while participants completed another survey, they received either a robotext or online banner ad seemingly unrelated to the study. Half of the participants received an ad containing their name, partner's name, preferred cuisine, and location; others received a generic ad. We measured how many of 43 potentially invasive questions participants subsequently chose to answer. Participants reacted negatively to the personalized ad, yet answered nearly all invasive questions accurately. We unpack our results relative to the privacy paradox, contextual integrity, and power dynamics in crowdworker platforms.
AB - Data brokers and advertisers increasingly collect data in one context and use it in another. When users encounter a misuse of their data, do they subsequently disclose less information? We report on human-subjects experiments with 25 in-person and 280 online participants. First, participants provided personal information amidst distractor questions. A week later, while participants completed another survey, they received either a robotext or online banner ad seemingly unrelated to the study. Half of the participants received an ad containing their name, partner's name, preferred cuisine, and location; others received a generic ad. We measured how many of 43 potentially invasive questions participants subsequently chose to answer. Participants reacted negatively to the personalized ad, yet answered nearly all invasive questions accurately. We unpack our results relative to the privacy paradox, contextual integrity, and power dynamics in crowdworker platforms.
KW - creepy
KW - hyper-personalization
KW - targeted advertising
KW - user study
UR - http://www.scopus.com/inward/record.url?scp=85091296787&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85091296787&partnerID=8YFLogxK
U2 - 10.1145/3313831.3376415
DO - 10.1145/3313831.3376415
M3 - Conference contribution
AN - SCOPUS:85091296787
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2020 - Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 25 April 2020 through 30 April 2020
ER -