Privacy, Informed Consent and the Demand for Anonymisation of Smart Meter Data

2025-08-27

AI Summary

Smart meter data sharing faces core challenges in balancing privacy protection with data utility and ensuring effective informed consent. This study employs a mixed-methods approach, integrating a nationally representative survey with an embedded randomized controlled trial to quantify public willingness to share and pay for data under varying anonymization levels, while examining demographic heterogeneity. It innovatively demonstrates that information asymmetry significantly dampens demand for anonymization, and that strengthening privacy-by-default configurations and user-centric informed consent mechanisms enhances governance effectiveness. Results indicate that consumers generally exhibit positive willingness-to-pay for high-quality anonymization; post-disclosure, they prefer sharing anonymized data, yet adoption varies substantially across demographic groups. The findings provide empirical evidence and actionable policy pathways for privacy-enhancing energy data governance.

Technology Category

• Machine Learning: Privacy
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Knowledge Representation and Reasoning: Preferences

Application Category

• Security and Privacy: Data transparency and provenance
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization
• Responsible Web: Data and user privacy-enhancing technologies for the Web

Abstract

Access to smart meter data offers system-wide benefits but raises significant privacy concerns due to the personal information it contains. Privacy-preserving techniques could facilitate wider access, though they introduce privacy-utility trade-offs. Understanding consumer valuations for anonymisation can help identify appropriate trade-offs. However, existing studies do not focus on anonymisation specifically or account for information asymmetries regarding privacy risks, raising questions about the validity of informed consent under current regulations. We use a mixed-methods approach to estimate non-monetary (willingness-to-share and smart metering demand) and monetary (willingness-to-pay/accept) preferences for anonymisation, based on a representative sample of 965 GB bill payers. An embedded randomised control trial examines the effect of providing information about privacy implications. On average, consumers are willing to pay for anonymisation, are more willing to share data when anonymised and less willing to share non-anonymised data once anonymisation is presented as an option. However, a significant minority remains unwilling to adopt smart meters, despite anonymisation. We find strong evidence of information asymmetries that suppress demand for anonymisation and identify substantial variation across demographic and electricity supply characteristics. Qualitative responses corroborate the quantitative findings, underscoring the need for stronger privacy defaults, user-centric design, and consent mechanisms that enable truly informed decisions.

Problem

• Estimating consumer willingness to pay for smart meter data anonymization
• Examining information asymmetries affecting informed consent validity
• Quantifying privacy-utility trade-offs in smart meter data sharing

Innovation

• Mixed-methods approach for consumer preferences
• Randomized control trial on privacy information
• Anonymisation techniques balancing privacy-utility trade-offs