Decoding Reasonableness: Descriptive, Personal or Social Norms?
In many legal systems, contract law employs broad standards—such as “reasonable,” “good faith,” “conscionable,” and “fair”—that have long been subjects of debate among courts and legal commentators. In particular, the concept of “reasonable” behavior remains ambiguous, with its precise meaning contested in both legal practice and academic discourse. A deeper understanding of lay interpretations of “reasonable” is crucial: it not only helps clarify its conceptual scope but also aids in predicting legal outcomes where a determination of reasonableness is left to the jury. Prior vignette-based studies suggest that lay understandings of reasonableness are hybrid in nature, situated between average and ideal behavior, and influenced by observations of common behavior rather than cost-benefit considerations. In contrast, recent semantic research indicates that laypeople use the term “reasonable” as a fundamentally evaluative and normative concept. This study investigates whether lay interpretations of reasonableness are indeed rooted in descriptive norms about common behavior or rather in injunctive norms about what behavior is appropriate—and further, whether such injunctive norms stem from personal convictions or perceived societal expectations.
Using twenty-five transactional scenarios in which contractual outcomes hinge on a reasonableness standard, participants rated each behavior on four dimensions: (1) frequency (descriptive norm); (2) personal approval (personal injunctive norm); (3) perceived societal approval (social injunctive norm); and (4) reasonableness. I found that “reasonable” judgments diverge sharply from descriptive norms—common behavior is not necessarily deemed reasonable, and vice versa. Although reasonableness ratings also differ somewhat from both personal and social injunctive norms, those differences are far smaller. Crucially, in every scenario participants are much more likely to deviate from descriptive norms than from either injunctive norm when assessing reasonableness, with personal injunctive norms being least likely to diverge from reasonableness assessments.
These findings suggest that when evaluating contractual behavior, laypeople’s assessments of reasonableness are driven primarily by personal normative convictions rather than by observations of common behavior or societal consensus. This distinction has important implications for legal practice, indicating that judicial interpretations of the “reasonableness” standard might benefit from considering the normative dimensions underlying lay assessments.
Unfairness in the Eyes of the Public
Suppose a taxi-hailing app keeps prompting for location access—visibly emphasizing “Always allow” while muting “Only while using the app.” Does that nudge cross the line into an “unfair” practice? Federal and state consumer protection laws prohibit unfair conduct, yet courts and scholars continue to debate the scope of this prohibition in the context of privacy-invasive dark patterns. The now-canonical three-part test—requiring substantial injury, lack of countervailing benefits, and reasonable avoidability—was designed to replace vague moral judgments. Yet it struggles to capture manipulative tactics that cause no immediate financial harm but steadily erode user autonomy or inflict other non-monetary injuries.
This Article supplies both empirical evidence and doctrinal refinement. Drawing on a nationally representative survey of 1,191 U.S. adults, it identifies how ordinary consumers judge the acceptability of various design practices. Two key findings emerge. First, privacy-related manipulations are consistently viewed as less acceptable than otherwise benign design choices. Second, tactics that materially impair users’ ability to make free decisions draw public disapproval even in the absence of further harm.
Building on these insights, the Article proposes a Public Values Test to modernize the unfairness standard while remaining grounded in existing law. Under this framework, a practice is presumptively unfair if (1) it causes or is likely to cause substantial injury—including not only monetary harms but also a material autonomy loss and privacy intrusions, (2) the firm cannot show that its benefits outweigh these full costs, and (3) the injury cannot be reasonably avoided by consumers. Whether a manipulation materially distorts autonomy can be assessed empirically. This use of public perception as an evidentiary guide guards against regulatory overreach and anchors enforcement in shared social norms.
The payoff is twofold. First, the framework supports recent FTC and state enforcement actions that treat privacy-invasive design as unfair. Second, it maps a principled path forward: condemning autonomy-eroding practices even in the absence of downstream injury. In a data-driven marketplace, unfairness doctrine must not only prevent economic loss but also protect privacy and the freedom of consumer choice itself.
The Unintended Consequences of Labeling Complimentary Offers as Free
under review at the Journal of Consumer Psychology
with Caroline Goukens and Vicki G. Morwitz
Prior literature has traditionally emphasized the attractiveness of zero-price offers. This research, however, demonstrates that explicitly labeling complimentary offers as “free” can increase their likelihood of being rejected. Across a series of incentivized online panel experiments involving 3,960 participants, we observed that individuals are more inclined to reject beneficial offers when described as “free” compared to when their complimentary nature is not highlighted—even when accepting them would result in financial gains.
This negative impact of the word “free” may have particularly undesirable implications for public and private initiatives—e.g., free health screening, apps, or legal advice—where organizations may want to highlight the no-cost aspect. We therefore tested a series of interventions that could reduce the negative impact of the word “free.” Our findings show that adding a trust signal, like using a logo from a trustworthy institution (e.g., a university), effectively conveyed the offer’s reliability and non-profit intent, mitigating the adverse effect. Conversely, strategies such as fostering familiarity with participants through repeated interactions, assuring them that the offer comes with “no strings attached,” or encouraging careful consideration of the offer did not alleviate the negative effect.
Our findings emphasize the complexity of consumer perceptions. Companies and policy makers should be mindful of consumers’ tendency to reject offers labeled as “free” when designing promotions, public initiatives, or any programs where participation does not require any payments.
Non-monetary costs of free and paid digital products. An empirical analysis.
In this project, I compare free and paid digital goods and services to find out whether they differ with respect to potential non-monetary and deferred costs imposed on the users. Specifically, I investigate samples of digital goods and services in three categories — online news services, and navigation and personal finance mobile applications. For each product or service in the sample I collect, code and analyze the following information: (1) types of personal data gathered, (2) privacy-relevant permissions requested, (3) presence of ads and newsletters, (4) presence and type of a license to user-generated content, (5) the content of provisions on data protection and sharing, (6) the content of warranty and liability disclaimers, (7) the content of provisions on modification of terms and services, dispute resolution and termination.
Judges and machines: how do ‘predictive justice’ tools affect judicial decision-making?
with Matthias van der Haegen
In this project, we study the influence of predictive justice on judicial decision-making in a highly realistic experimental setting. Predictive justice has risen to prominence over the past years, as the legal industry discovers the potential of machine learning within the legal domain. Predictive justice holds many advantages: it may increase efficiency, accuracy and consistency of judicial decisions. In order to make sure that these advantages are indeed achieved an no negative side effects occur that would compromise the requirements of a fair trial, we need to ascertain how these tools affect judges’ decision making.
In the experiment, judges will decide upon a fictitious landlord-tenant dispute under the assumption they are judges in a fictitious country. Relevant material such as legal provisions, precedents and doctrine will be provided, but some participants will also find an A.I-generated prediction on the probability of a landlord being liable in a given case. In our experiment, we will measure the influence of this prediction on the final decision and the decision-making process. We are currently piloting our experimental design with law students. As the next step, we plan to run the study with judges of one of the Dutch District Courts.
The impact of preferential selection on group decision-making
with Angela Dorrough, Andreas Gloeckner, and Madeline Heilman
In addition to securing gender equality, legislators claim that preferential selection will also have positive effects on corporate performance by, for example, increasing the quality of group decision-making. Previous research on preferential selection has primarily focused on individual task performance whereas the evidence on the effects on group behaviors is scarce. We plan to investigate whether preferential selection of women has an effect on the quality of group decision-making in male-dominated domains and shed light on the underlying mechanisms. Specifically, we will focus on the evaluation of men’s and women’s performance in a group task and the group members’ willingness to interact with each other after the introduction of preferential treatment.
Monika Leszczyńska 