Empowered Data Societies: A Human-Centric Approach to Data Relationships

The report argues for a shift from organization-centric to human-centric data governance to bridge the 'trust gap' in data ecosystems. It introduces methodologies for mapping data journeys to identify 'tussle points'—areas of tension between stakeholders—where policy interventions can empower individuals. The document specifically examines 'proactive services' (push-model delivery) and details a blueprint developed in Helsinki, including a hybrid cloud architecture for GDPR-compliant anonymization and a 'service staircase' for data utilization levels.

• Trust in data relationships is determined by the expectations data subjects and collectors have of one another and whether those expectations are respected, which directly impacts the amount of data available for innovation.
• A human-centric approach to data governance is based on five key elements: treating the human as the logical point of integration, shifting from data protection to data empowerment, adopting an ecosystems approach for interoperability, ensuring pluralism for global applicability, and maintaining proportionality and equity.
• Trust can be reinforced through 'judicious data minimization,' which involves treating identifiable, sensitive data as a 'highly toxic asset' and avoiding the default of 'data entitlement.'
• In developing countries and emerging economies, digital divides lead to digital exclusion for vulnerable groups who do not generate a sufficient data footprint, risking further marginalization as public policy increasingly relies on AI and automated tools.
• The report introduces 'tussle points'—intersections of front-stage user experiences, backstage data flows, and legal/policy overlays—as critical junctures where targeted policy interventions can empower users.
• Proactive services shift government delivery from a 'pull' model (citizen-initiated) to a 'push' model (government-initiated), using predictive models, automatic delivery, and context awareness to meet citizen needs.
• The Helsinki experiment produced a 'Personal Data Hybrid Cloud Architecture' that ensures GDPR compliance by separating the storage, anonymization, and processing of data, using temporary servers for anonymization before pushing data to the cloud.
• Helsinki developed a 'data-based service staircase' that categorizes data utilization into five levels: (1) human operator, (2) local restricted automation, (3) federated learning, (4) centralized modelling, and (5) research and development/scientific use.

APA

World Economic Forum (2021). Empowered Data Societies: A Human-Centric Approach to Data Relationships. http://www3.weforum.org/docs/WEF_Empowered_Data_Societies_2021.pdf

Chicago

World Economic Forum. Empowered Data Societies: A Human-Centric Approach to Data Relationships. 2021. http://www3.weforum.org/docs/WEF_Empowered_Data_Societies_2021.pdf.

Wikipedia

{{cite report |author=World Economic Forum |title=Empowered Data Societies: A Human-Centric Approach to Data Relationships |date=September 2021 |url=http://www3.weforum.org/docs/WEF_Empowered_Data_Societies_2021.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{worldeconomicforum2021empowered, author = {{World Economic Forum}}, title = {{Empowered Data Societies: A Human-Centric Approach to Data Relationships}}, institution = {World Economic Forum}, year = {2021}, month = sep, url = {http://www3.weforum.org/docs/WEF_Empowered_Data_Societies_2021.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }