Sharing Data for Social Good: From Uninformed Consent to Misinformed Dissent

When deciding to disclose data for personal benefits, consumers are fast to underestimate privacy-related costs and hence, freely share their personal data (uninformed consent). The present research shows that this cost-benefit analysis shifts in the context of sharing data for social good. When people decide to share data with a service that serves a social good (e.g., to contain the spread of the coronavirus or fight climate change), they tend to overestimate the privacy-related costs (cost illusion). In consequence, people fail to share data for social good (misinformed dissent). To reduce this cost illusion and foster sharing data for social good, we tested two communication strategies for privacy-related information. We find that not single, but comparative information is effective in reducing the cost illusion. Thus, privacy related information of services using data should be displayed in a comparative manner. Our results provide important theoretical insights and managerial implications for the privacy calculus in the highly relevant context of sharing data for social good.