Mr Timothy Kariotis1
1Melbourne School Of Government, , Australia
When unlocked from the institutional and individual siloes within which it is held, health data has huge potential to transform public health. One way the siloes of health data are being overcome is through empowering consumers to hold and manage their own health data. Emerging health data platforms give consumers opportunities to pool their health data and other personal data and provide it to a range of interested parties. These models have also brought an increasing interest in the consent models available to individuals consumers to decide how they want their data used. However, there is an emerging issue of collective consent where communities of consumers consent or approve specific uses of data. For example, OpenHumans is an online platform where members can share their data with projects established on the platform. However, the community must first approve any projects that are added to the platform. The issue of collective consent is particularly interesting in the context of artificial intelligence and machine learning, where individual data only has an impact when pooled together. Further, the collective impact of these data uses may be based on data collected from a sub-population of that collective using individual consent. This idea of collective consent is also not new, as it has been considered in discussions on Indigenous Data Sovereignty. This presentation will compare collective consent to other models of consent in the context of health data platforms that give consumers greater control over their health data.
Bio to come.