Liberties launches project on patient data and clinical AI accountability
The project aims to strengthen oversight of health AI through research, monitoring and policy recommendations.
The civil liberties organisation Liberties has launched the AI in the Healthcare Project to examine how personal data is used in the development and deployment of clinical AI systems.
The project, developed with Liberties member and partner organisations and independent expert Júlia Keserű, aims to improve transparency, accountability, and data protection practices in healthcare AI.
According to Liberties, the first phase will gather information through literature review, stakeholder consultations, interviews, freedom of information requests, and GDPR-based data subject access requests. Requests will be submitted to government agencies, regulatory bodies, public health authorities, publicly funded hospitals, and research institutions.
A second phase, led by Liberties, will focus on capacity development for watchdog organisations and civil society groups. The organisation said the work will provide methodologies, research tools, and collaboration platforms to help groups independently monitor the development and use of health AI systems.
The final stage will develop policy recommendations at the EU and national levels to promote responsible, transparent, and accountable health data practices. The recommendations will also seek to support compliance with existing frameworks such as the AI Act and the GDPR.
Liberties said AI systems are increasingly being integrated into healthcare, relying on data from sources such as electronic health records, wearable devices, mobile health apps, genetic testing services, and data brokers. However, it warned that transparency around data sources and their integration into clinical AI systems remains limited, creating risks to privacy, human rights, security, and safe use.
Why does it matter?
The project targets one of the most sensitive areas of AI deployment: healthcare systems that rely on personal and health data. As clinical AI tools become more common, questions about data sources, consent, transparency, GDPR rights, and accountability will become central to whether patients can trust AI-supported healthcare.
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