A number of commentators—including HeLEX researchers—have reflected on the role of individual consent in scientific research since the GDPR. For example, it is not easy to show that individuals can withdraw their consent as easily as they provide it. The integrity of scientific findings relies upon stable, accessible data that are retained after journal publication. This would not be possible if this information was chipped away every time a participant changed their mind.
The fate of consent in research is currently unclear. Some of our colleagues have argued we should—instead—cultivate a societally accepted norm that personal information will be re-used for research, without the need for individual consent each time. But the new proposed Regulation on European data governance (Data Governance Act) or ‘DGA’ takes a slightly different approach to pooling information for research.
The DGA introduces—in Chapter IV—new provisions setting up a system of ‘data altruism.’ Individuals can donate their personal data, and organisations can donate non-personal data to not-for-profit organisations, for broadly specified purposes such as scientific research or improving public services. Data altruism organisations must be constituted for ‘objectives of general interest’ (such as research) and can be entered on a public register for transparency purposes.
Article 22 of the proposed DGA seems to envisage that individuals donating their personal data will do so on the basis of consent under the GDPR. It even suggests that the European Commission will introduce a new standard consent form; providing a new standard for acceptable consent for public interest use.
Thus it seems that a role for individual consent in scientific research should not be counted out just yet. It remains to be seen whether the proposed DGA will pass in its current form, but its progress will be monitored closely by HeLEX researchers working within EU-STANDS4PM. The role of consent under the GDPR was explored at length in the project’s ‘Legal and ethical review of in silico modelling.’