Strategies to Counter Artificial Intelligence in Law Enforcement: Cross-Country Comparison of Citizens in Greece, Italy and Spain
Petra Saskia Bayerl, Babak Akhgar, Ernesto La Mattina, Barbara Pirillo, Ioana Cotoi, Davide Ariu, Matteo Mauri, Jorge Garcia, Dimitris Kavallieros, Antonia Kardara, Konstantina Karagiorgou
TL;DR
The paper addresses how citizens respond to AI-enabled law enforcement across Greece, Italy, and Spain by conducting an online cross-country survey and validating a 10-item counter-strategy scale. It finds a moderate overall propensity to adopt counter-strategies, with Greece showing higher likelihood, and identifies attitudes toward LEA AI, perceived AI bias vulnerability, and fear of crime as significant predictors (AI knowledge is not). The regression explains $R^2$ = 0.27, underscoring meaningful variance explained by psychological and perceptual factors. The work highlights societal side-effects of security-focused AI and offers insights for designing and communicating AI deployments to maintain public acceptance and long-term viability.
Abstract
This paper investigates citizens' counter-strategies to the use of Artificial Intelligence (AI) by law enforcement agencies (LEAs). Based on information from three countries (Greece, Italy and Spain) we demonstrate disparities in the likelihood of ten specific counter-strategies. We further identified factors that increase the propensity for counter-strategies. Our study provides an important new perspective to societal impacts of security-focused AI applications by illustrating the conscious, strategic choices by citizens when confronted with AI capabilities for LEAs.