Privacy Calculus
Tobias Dienlin · 2023
The privacy calculus states that before disclosing personal information online, people engage in a rudimentary tradeoff by comparing expected benefits with anticipated costs. If benefits exceed costs, people are more likely to self-disclose. In this chapter, I present the privacy calculus’ theoretical underpinnings and empirical implementations. Focusing on the privacy paradox, I discuss how the privacy calculus is challenged from other perspectives. I counter these critiques by adopting a meta-position, building on general psychological models of behavior and a philosophy of science perspective. In asking which of the two competing models (i.e., privacy calculus vs. privacy paradox) seems more likely in light of the available data, I introduce a Bayesian approach to the discussion. I also briefly discuss the privacy calculus from a political perspective: Although behavior is (at least somewhat) rational on the level of the individual level, the situation is different on the societal level. I end with a new take on the privacy calculus, namely a probabilistic privacy calculus model. I argue that it is more fruitful to pursue the perspective of the privacy calculus instead of the privacy paradox, acknowledging relevant limitations and outlining promising paths for future research.