Hi, I’m Sophie. Today, my co-authors Julia, Miranda, and I
will be presenting our paper. “Taking Data out of Context to Hyper-personalize Ads: Crowdworkers’
Privacy Perceptions And Decisions To Disclose Private Information.”
In the old days, advertisements were marketed to broad, heterogeneous audiences. For example,
a billboard showing an ad about vacations to Hawaii would be seen by everyone passing
by. The rise of web tracking, email tracking, and data marketplaces has enabled far greater
personalization. Advertisers infer users interests and demographics to create increasingly targeted
and personalized ads. A logical next step would be hyper-personalized ads, like, "Sophie,
plant enthusiasts like you love Hawai'i. Book your flight from Chicago today! Prior work
has shown that some people can find personalized ads creepy. Personalization involves data
collected in one context being reused in another, which is a potential misuse of data. This
raises two questions. How would you respond to seeing your data re-contextualized in a
hyper-targeted ad? how could you prevent unwanted reuse of your data in the future? Well, of
course, one strategy for preventing unwanted re-use is to limit information disclosure
by being more hesitant about giving information out in the first place.
More specifically, our main research questions were:
Would seeing a creepy, hyper-personalized ad cause feelings of privacy invasion that
would alter information disclosure behavior? To explore these questions, we designed an
experiment, We used the Prolific crowdsourcing platform to recruit participants. We showed
them either a generic or hyper-personalized ad, then asked a series of invasive questions,
with the option not to answer. We hypothesized that, as a way to protect privacy, those who
saw the hyper-personalized ad would answer fewer invasive questions, compared to those
who saw the generic ad. Now we'll detail our methods. For validity, participants couldn't
know the ad was from us, so we designed a deception protocol. The protocol had two parts.
[*] In Part 1, we collected the information needed to personalize the ad. Then, we waited
over a week so participants would forget what information we collected, and In Part 2, we
showed the ad and asked the invasive questions. We compensated $1 for Part 1, which took 5
minutes, and $4 for Part 2, which took 30 minutes. As part of our deception, we initially
gave a generic study title, The Demographics, interests, and experiences of Americans.
And instead of using our university affiliation, we posed as the fictional "Institute for Interests
and Demographics Research” or IIDR. The goal of Part 1 was to obtain consent and gather
the information needed for the ad without arousing suspicion. To do this, we elicited
information about our participants amidst distractor questions. We asked for participants
name, phone number, preferred cuisine, relationship status, and partner's name. We also used IP
geolocation to estimate their town-level location. Having gotten information for hyper-personalizing
an ad, we waited a week so participants would have time to forget about the information
they gave. We were then ready to show the participants the ad in Part 2.
When participants began Part 2, our software automatically triggered either the display
of a banner ad on the first page of the survey, or the delivery of a robotext to the participant’s
cell phone. Robotexts are increasingly being used for
personalized ads. Furthermore, as they would likely be received on a different device than
the survey, participants would be less likely to associate the ad with our survey.
So with the information collected from Part1, we were able to create personalized ads, like
this banner ad: "Taylor, treat Ryan to a date night this week in Memphis. We know you love
Thai restaurants. Use SUPEReats.co to reserve a table at one of the 7 near you for a deal!
So on the left is the personalized ad you just saw, and as a control, we created parallel
generic ads with no personalization, that read, "Treat yourself this week, use SUPEReats.co
to reserve a restaurant near you". Robotext ads were also personalized or generic, with
similar text to the banner ads. they were sent from a short code, commonly used for
commercial purposes. So to recap our study conditions, participants
received either a banner ad or a robotext ad. The ad was either personalized or generic.
Next, we asked a series of invasive questions. We created questions taking inspiration from
sources like the American Housing Survey, US Census, and Pew Research. We also gathered
more sensitive questions from Facebook and Cosmo magazine quizzes.
From these, we selected 43 invasive questions reflecting a range of sensitivity. Earlier
questions were low invasiveness, like how many years of experience do you have with
using the Internet? The questions escalated to include things like, For what reason did
you last cry? What is the first and last name of your best friend? What is your home address?
Crucially, each question had a conspicuous “prefer not to say” option.
We called attention to this option at the start of the section and explicitly told participants
they would not be penalized for selecting it.
We hypothesized participants would select "prefer not to say" to protect their privacy
and limit information disclosure. Afterwards, we debriefed participants about
the study’s true nature. We revealed that we were not the fake IIDR, but the University
of Chicago, and that we had sent the ad. Following the debrief, we also asked participants
about their reactions and recollections of the ad: Do you remember seeing the ad?, Did
you suspect it was study related at any point? And what factors did you consider when answering
the invasive questions? Because participants could have protected
their privacy by answering questions inaccurately, we showed them a list of their answers and
asked them to select any inaccurate ones. We emphasized they would not be penalized
for having given inaccurate responses. We took great care to protect participant
privacy and follow ethical best practices. We used Prolific’s deception filter to only
recruit participants who had already consented to participate in deception studies.
Prolific approved our study design for collecting Personal Identifying Information.
We made sure we debriefed participants who dropped out of the study early.
And finally, we deleted participant PII and immediately overwrote their answers to the
invasive questions, retaining only whether they had answered each and done so accurately.
We recruited 280 participants from Prolific to participate in our study.
We wanted to verify that participants did not associate the ad with the study contents.
Following the debrief, participants self-reported whether they saw the ad and suspected it was
study related. 92 participants, or 65%, were sent the robotext
ad, saw it, and did not think it was study-related. 85 participants, or 62%, were shown the banner
ad, saw it, and were similarly not suspicious. The remainder of the results report only on
these participants. We were interested in whether participants
would be creeped out or otherwise react negatively to hyper-personalization.
Participants frequently reported feeling scared, surprised, or having other strong negative
feelings. 53% of participants who saw a personalized banner ad reported such feelings, as did 44%
of those who saw a personalized robotext ad. In contrast, 0% of participants who saw a
generic ad reported similar negative feelings. Participants perceived our ads as creepy.
For example, participant 211 wrote, “I was quite alarmed by the ad, wondering how it
knew my spouse’s name and location. I was disturbed and put off by it.” Another participant,
who had received a robotext, responded to our text message directly saying they would
“blast us on Twitter” for sending such creepy ads. Participants’ reactions often
tried to make sense of where the information came from. Some participants wrote about Google
or Facebook, two highly visible data collectors. Participant 123 thought more specifically,
and wrote, “I had a noticeable reaction of both worry and disgust, and then I realized
I had been visiting a lot of restaurant websites recently.”
For each invasive question, we measured whether participants answered it (instead of selecting
Prefer Not to Say), shown in the gray circle, and whether participants reported answering
it accurately, shown in the white circle. All participants answered less sensitive questions,
like around Internet usage. Many fewer participants answered the more sensitive questions. While
86% answered, “For what reason did you last cry?, less than half answered “What is the
first and last name of your closest friend?” and only 15% answered “What is your home
address?” The average participant, though, answered 86% of all questions, which was much
higher than we expected. We were most interested in whether information
disclosure would differ by condition. These boxplots will show the total questions answered
and total questions answered accurately for participants in each condition: Participants
who received either generic or personalized robotext ads, or
generic or personalized banner ads. Despite participants’ negative reactions to personalize
ads, Mann-Whitney U tests revealed no significant differences in the number of questions answered
by participants based on whether they saw a personalized or generic ad.
We asked participants how they chose between disclosing information or selecting "prefer
not to say". 42% of participants chose not to disclose information perceived to be personal
or embarrassing, such as when it crossed the line into their privacy. Other participants
did not disclose information that was personally-identifying or important for security. For example, “questions
that felt like phishing (mom’s maiden name) were a no-go. I cared less about it being
invasive and more about it being bad security.” In contrast, why did participants decide to
disclose information? First, it was influenced by time pressures, “To be honest, You’re
bombarded with information all the time and for the most part it’s too much effort to
try and keep up with everything.” They also desired the study compensation. “I think
there is a lot of risk, and if I wasn’t flat broke I wouldn’t be doing this,”
which highlights a known labor pressure on crowdworkers. A final consideration was weighing
the cost and benefits of disclosure, also known as privacy calculus. “It’s impossible
to really know where the data goes after you leave it. This is VERY unrestricted territory
but the fact I get compensated? Makes me feel justified in taking any risks.” This participant
acknowledged the costs of not knowing where the data would go, but reasoned that because
they get compensated, it would be worth it. Prior work has shown crowdworkers’ trust
in a requester and their reputation impacts whether they disclose information. To investigate
whether this influenced our participants, we asked them how trustworthy they perceived
our fake organization, IIDR, to be. Participants reported very mixed trust, like "they're okay,
don't know a lot about them." But we found that participants had a lot of trust in Prolific.
83% mentioned trusting the study because it was on Prolific. Many described assumptions
that Prolific vets its studies. “I feel like Prolific weeds out all the bad studies
so I had faith that Prolific would keep me safe”. Prolific does not actually proactively
screen studies on its platform. I’d like to conclude with some thoughts
for discussion. The results of our study are interesting to
consider in light of the contextual integrity theory of privacy.
Contextual integrity posits that privacy comes from appropriate flows of information, and
privacy harms arise when information is unexpectedly used or reused. Our findings seem to support
this theory, as participants had strong negative reactions to their information being repurposed
for commercial ads. However, contrary to our hypothesis, we did not observe participants
change their information disclosure behavior as a result of a potential privacy harm.
Perhaps participants compartmentalized the effects of various flows of information. That
is, they still decided to disclose sensitive information when they didn’t know from whom
to protect their information. This poses an issue. Who uses online data,
and how, is not very transparent. Our study also has implications for crowdwork.
Our crowdworkers placed a lot of trust in Prolific to help them manage privacy risks.
But, crowdworking platforms largely assume that the workers themselves will decide what
they’re willing to disclose. The burden should not be placed on crowdworkers.
Instead, we need privacy by design. Crowdworking platforms could introduce verification systems
for requester identities, they could collaborate with IRBs to ensure requesters are behaving
as they should. Further, crowdworking platforms could require
requesters to disclose the purpose of data collection to give workers more transparency
into how their data will be used. What directions are there for future work?
First, future work could investigate what it takes to creep people out enough that they
change their behavior. A single ad wasn’t enough in our study, but multiple over a longer
period of time might be. Or maybe no amount of creepiness is enough to cause behavior
change, which raises interesting questions for assumptions of user self-regulation.
Future work could also investigate competing effects in information disclosure. Some participants
could’ve taken a cautionary lesson from our study and decided not to share information
again. Others could’ve been demoralized, had their privacy hopelessness confirmed,
and decided there’s no benefit in trying to protect their privacy online at all.
Finally, future work could investigate non-crowdworking contexts to understand how others perceive
risks to disclosing information online. Thank you so much for listening to our talk.