Empowering Older Adults With Their Information Privacy Management

Literature depicts a deficit-based narrative around older adults and their technology use, suggesting that older adults are not able to keep up with their younger counterparts in adopting new technologies. In this dissertation, I argue that this view is not necessarily accurate or productive. Instead, I argue that the deficit is in the technology design, which is not inclusive and often caters to the needs of younger adults. I study older and younger adults\u27 privacy decision-making as a showcase. To study the privacy decision-making process with more granularity, I used a dual-route approach (decision heuristics and privacy calculus) to disentangle different aspects of the decision. This helps identify older and younger adults\u27 differences better. My results rebut the deficit-based narrative and show that older adults are motivated and able to manage their privacy. However, they have a different decision-making mechanism compared to younger adults. For example, older adults are more likely to make a rational decision by considering a more thorough risk/benefit trade-off than younger adults. I furthermore show that age (i.e., being older or younger adult) is only a proxy for other parameters; the different decision-making mechanisms can be justified by parameters that vary across age groups (e.g., levels of privacy literacy and privacy self-efficacy). My work introduces a new perspective in technology design and has practical implications for designing for the elderly, a population with different wants and needs

Exacerbating Mindless Compliance: The Danger of Justifications during Privacy Decision Making in the Context of Facebook Applications

Online companies exploit mindless compliance during users’ privacy decision making to avoid liability while not impairing users’ willingness to use their services. These manipulations can play against users since they subversively influence their decisions by nudging them to mindlessly comply with disclosure requests rather than enabling them to make deliberate choices. In this paper, we demonstrate the compliance-inducing effects of defaults and framing in the context of a Facebook application that nudges people to be automatically publicly tagged in their friends’ photos and/or to tag their friends in their own photos. By studying these effects in a Facebook application, we overcome a common criticism of privacy research, which often relies on hypothetical scenarios. Our results concur with previous findings on framing and default effects. Specifically, we found a reduction in privacy-preserving behaviors (i.e., a higher tagging rate in our case) in positively framed and accept-by-default decision scenarios. Moreover, we tested the effect that two types of justifications—information that implies what other people do (normative) or what the user ought to do (rationale based)— have on framing- and default-induced compliance. Existing work suggests that justifications may increase compliance in a positive (agree-by-) default scenario even when the justification does not relate to the decision. In this study, we expand this finding and show that even a justification that is opposite to the default action (e.g., a justification suggesting that one should not use the application) can increase mindless compliance with the default. Thus, when companies abide by policy makers’ requirements to obtain informed user consent through explaining the privacy settings, they will paradoxically induce mindless compliance and further threaten user privacy

Reducing Default and Framing Effects in Privacy Decision-Making

Framing and default effects have been studied for more than a decade in different disciplines. A common criticism of these studies is that they use hypothetical scenarios. In this study, we developed a real decision environment: a Facebook application in which users had to decide whether or not they wanted to be automatically publicly tagged in their friends’ pictures and/or tag their friends in their own pictures. To ensure ecological validity, participants had to log in to their Facebook account. Our results confirmed previous studies indicating a higher tagging rate in positively framed and accept-by-default conditions. Furthermore, we introduced a manipulation that we assumed would overshadow and thereby reduce the effects of default and framing: a justification highlighting a positive or negative descriptive social norm or giving a rationale for or against tagging. We found that such justifications may at times increase tagging rates

Older and younger adults are influenced differently by dark pattern designs

Considering that prior research has found older users undergo a different privacy decision-making process compared to younger adults, more research is needed to inform the behavioral privacy disclosure effects of these strategies for different age groups. To address this gap, we used an existing dataset of an experiment with a photo-tagging Facebook application. This experiment had a 2x2x5 between-subjects design where the manipulations were common dark pattern design strategies: framing (positive vs. negative), privacy defaults (opt-in vs. opt-out), and justification messages (positive normative, negative normative, positive rationale, negative rationale, none). We compared older (above 65 years old, N=44) and young adults (18 to 25 years old, N=162) privacy concerns and disclosure behaviors (i.e., accepting or refusing automated photo tagging) in the scope of dark pattern design. Overall, we find support for the effectiveness of dark pattern designs in the sense that positive framing and opt-out privacy defaults significantly increased disclosure behavior, while negative justification messages significantly decreased privacy concerns. Regarding older adults, our results show that certain dark patterns do lead to more disclosure than for younger adults, but also to increased privacy concerns for older adults than for younger

Risk-Taking Unmasked: Using Risky Choice and Temporal Discounting to Explain COVID-19 Preventative Behaviors

To reduce the spread of COVID-19 transmission, government agencies in the United States (US) have recommended COVID prevention guidelines, including wearing masks and social distancing. However, compliance with these guidelines have been inconsistent. This study examined whether individual differences in decision-making and motivational propensities predicted compliance with COVID-19 preventative behaviors in a representative sample of US adults (N=225). Participants completed an online study in September 2020 that included a risky choice decision-making task, temporal discounting task, and measures of appropriate mask wearing, social distancing, and perceived risk of engaging in public activities. Linear regression results indicated that greater risky decision-making behavior and temporal discounting were associated with less appropriate mask-wearing behavior and social distancing. Additionally, demographic factors, including political affiliation and income level, were also associated with differences in COVID-19 preventative behaviors. Path analysis results showed that risky decision-making behavior, temporal discounting, and risk perception collectively predicted 61% of the variance in appropriate mask-wearing behavior. Individual differences in general decision-making patterns are therefore highly predictive of who complies with COVID-19 prevention guidelines

Risk-taking unmasked: Using risky choice and temporal discounting to explain COVID-19 preventative behaviors.

To reduce the spread of COVID-19 transmission, government agencies in the United States (US) recommended precautionary guidelines, including wearing masks and social distancing to encourage the prevention of the disease. However, compliance with these guidelines has been inconsistent. This correlational study examined whether individual differences in risky decision-making and motivational propensities predicted compliance with COVID-19 preventative behaviors in a sample of US adults (N = 404). Participants completed an online study from September through December 2020 that included a risky choice decision-making task, temporal discounting task, and measures of appropriate mask-wearing, social distancing, and perceived risk of engaging in public activities. Linear regression results indicated that greater temporal discounting and risky decision-making were associated with less appropriate mask-wearing behavior and social distancing. Additionally, demographic factors, including personal experience with COVID-19 and financial difficulties due to COVID-19, were also associated with differences in COVID-19 preventative behaviors. Path analysis results showed that risky decision-making behavior, temporal discounting, and risk perception collectively predicted 55% of the variance in appropriate mask-wearing behavior. Individual differences in general decision-making patterns are therefore highly predictive of who complies with COVID-19 prevention guidelines