EXPRESS: Where Should Firms Implement Differential Privacy in Targeting? Implications for Profitability
研究通过大规模实地实验和模拟，发现差分隐私在目标定位决策阶段实施比在模型训练阶段实施平均利润高五倍，为企业和政策制定者平衡隐私保护与盈利提供指导。
Firms use privacy-sensitive data to make targeting decisions, which can inadvertently reveal the underlying information driving those decisions—a risk the authors term targeting privacy risk . The authors use differential privacy to quantify and control this risk. Although firms increasingly adopt differential privacy, policymakers offer limited guidance on its implementation in a targeting framework. The crucial question, therefore, becomes: where should firms implement differential privacy? The authors find that profitability critically depends on where differential privacy is implemented within a typical targeting workflow. This insight stems from two novel targeting strategies: one implements differential privacy during model training, the other at the targeting-decision stage. Using a large-scale field experiment involving 747,975 customers and extensive simulations, the authors show that both strategies remain profitable under strong privacy protection. Notably, the decision-stage strategy yields, on average, fivefold higher profits than alternative implementations. To generalize this finding, the authors derive the expected profit for a given privacy risk level and a privacy elasticity of targeting profits. Collectively, the results offer guidelines for firms and policymakers to ensure privacy protection and profitability.