When Those With Privacy Concerns Show Stronger In-Group Favoritism: Using Personal Information From In-Group and Out-Group Members to Identify Terrorist Threats

Terrorist threats and attacks provide major risks sources of public crises in the 21st century. New probabilistic computing technologies possess capability increasing success identifying terrorist solving cybersecurity encryption problems more efficiently. However, to identify threats, these would require use a large amount personal data, which cause potential concerns for privacy. We offer social-identity explanation support detection through online data. A survey study ( N = 1,204) revealed strong provided perceptions. As expected, respondents displayed in-group favoritism by strongly supporting private information from out-group members (non-U.S. citizens) than (U.S. citizens). The observed was most pronounced when had both national identity sense general privacy concern. differences were independent respondents’ political orientation age.