Many apps request access to users’ contacts or photos and many consumers agree to these requests. However, agreeing is ethically questionable as it also gives apps access to others’ data. People thus regularly infringe each other’s information privacy. This behavior is at odds with offline practices and still poorly understood. Introducing a novel application of the theory of neutralization, we explore how people justify the giving away of others’ data and the emerging norms surrounding this behavior. To obtain a deeper (...) understanding of the potentially ambiguous norms surrounding the behavior, we investigate how people justify, i.e., neutralize, the behavior from both offender and victim perspectives. Across four studies, offenders appear more likely to admit to moral wrongdoing than victims assume. This suggests moral disagreement between offenders and victims. The discrepancy appears to be reasonably robust across different samples, apps and whether the other is identified, but diminishes when people learn how easily others’ data could be protected. These insights offer suggestions for businesses, consumers and public policy. (shrink)

Many apps request access to users’ contacts or photos and many consumers agree to these requests. However, agreeing is ethically questionable as it also gives apps access to others’ data. People thus regularly infringe each other’s information privacy. This behavior is at odds with offline practices and still poorly understood. Introducing a novel application of the theory of neutralization, we explore how people justify the giving away of others’ data and the emerging norms surrounding this behavior. To obtain a deeper (...) understanding of the potentially ambiguous norms surrounding the behavior, we investigate how people justify, i.e., neutralize, the behavior from both offender and victim perspectives. Across four studies, offenders appear more likely to admit to moral wrongdoing than victims assume. This suggests moral disagreement between offenders and victims. The discrepancy appears to be reasonably robust across different samples, apps and whether the other is identified, but diminishes when people learn how easily others’ data could be protected. These insights offer suggestions for businesses, consumers and public policy. (shrink)