The Economic Consequences of Digital Dark Patterns

RESEARCH QUESTION 

The research objective is to measure the economic impacts of dark patterns in the context of consumer data sharing in the US. Companies often design digital interfaces that manipulate or coerce users into actions they may not take otherwise. These designs are called “dark patterns” when they create consumer harm. The “economic impact” means the losses in money, time, or data that consumers incur due to dark patterns. 

The research asks the following questions: (1) How effective are companies’ user interface designs in manipulating consumers’ data-sharing decisions? (2) How do dark patterns change the economic outcomes that consumers face via changing their data-sharing decisions? In particular, how do changes in data sharing affect the ads that consumers see, the types of websites they browse, and their consumption patterns? (3) Does the removal of dark patterns affect different companies differently? If so, what can be said about the indirect effects of dark patterns on consumers via changes in market functioning? 

WHY IS THIS RESEARCH IMPORTANT? 

The findings of this research can provide insights readily applicable to policy discussions, such as regulation of data sharing and dark patterns. Dark patterns erode the trust of consumers and can impede the efficient functioning of the digital marketplace; as a result, they have received increasing regulatory attention. Nevertheless, efforts to regulate dark patterns face ambiguities, given the lack of quantitative evidence. By studying the effects of design patterns across consumers and companies, this research examines when and for whom dark patterns have the most detrimental effects. The findings help policymakers understand where to target their regulatory efforts and how to design regulatory interventions. 

METHODOLOGY  

The research uses a large-scale field experiment with a recruited panel. Internet users are randomized into a control group (one-third of users) and a treatment group (two-thirds of users). Users in the control group download an extension, which passively tracks their browsing behaviours, ad exposures, and purchases. Users in the treatment group download a customized extension (that removes the dark pattern and modifies the consent banner) and are also tracked in terms of browsing behaviours, ad exposures, and purchases. 

Then, data shared, site visits, time spent, and financial expenses are compared between groups. Correlating the design patterns with changes in outcomes across treatment groups allows the understanding of the relative effectiveness of specific design elements.  

Baseline and end-line surveys to collect additional outcomes are also used. In the baseline survey, users are asked about their beliefs about the role of cookies. In the end-line survey, users are asked about their experience when browsing websites and about the relevance of ads they see. 

The comparison result allows the measurement of the degree to which dark patterns harm consumers. 

MEDIA AND PUBLICATIONS 

See below for research publications and other articles related to the research. 

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