With an academic background that bridges health law, privacy law and bioethics, Shabani has spent more than fifteen years researching the responsible use of health data. This interdisciplinary perspective has made her particularly attentive to the societal risks of data-driven innovation in healthcare: “AI is already here. The question is not whether we use it, but how we use it in the best interests of patients.”

Her central concern is that artificial intelligence may unintentionally reinforce existing inequalities in healthcare rather than reduce them.“Data-driven technologies do not benefit all communities equally. In fact, they can exacerbate existing health inequities.”

A five-year research project on fairness in data-driven health technologies

With the support of a Vidi grant of approximately €850,000, Shabani is launching a five-year research project that places fairness in data-driven healthcare technologies at its core. The project focuses in particular on artificial intelligence and its growing role in medical practice.

At the heart of the research lies a fundamental question: what does fairness actually mean in the context of AI in healthcare? Shabani observes that the answer varies widely depending on disciplinary background: “Computer scientists, lawyers, philosophers and ethicists all talk about fairness, but they often mean very different things.”

By linking fairness explicitly to health equity, the project examines how AI systems may fail to serve certain populations adequately. These include people from different ethnic backgrounds, older adults with lower digital literacy, linguistic and cultural minorities, and individuals whose mental health or socio-economic circumstances are insufficiently reflected in existing data. “If health data is not representative, the resulting algorithms will not work equally well for everyone.”

Combining theory, empirical research and regulation

The project is designed as an interdisciplinary and iterative process that moves continuously between conceptual work and real-world input. It begins with theoretical analysis, drawing on legal, ethical and philosophical perspectives to clarify what fairness should entail in healthcare AI.

This theoretical work is then complemented by empirical research. Shabani will organise focus groups with a wide range of stakeholders, including healthcare professionals, policymakers, AI developers, patients and members of the general public. Particular attention will be paid to including voices that are often underrepresented, both within the Netherlands and internationally, using online tools to broaden participation. “I want to hear from those who are often overlooked and understand what they expect from a fair AI system.”

Ensuring accessibility is a key challenge in this phase. Participants must receive enough information to engage meaningfully with the topic, while avoiding undue influence on their views. “People need to understand the basics, but we also want to capture their genuine perceptions.”

The insights gathered from theory and practice will ultimately be translated into concrete guidelines and frameworks. These are intended to support regulators, oversight bodies and policymakers who are responsible for evaluating and approving new AI-based medical technologies. “The goal is to help decision-makers recognise fairness-related risks when assessing new tools.”

Future perspective: Towards more equitable healthcare innovation

While academic publications are an important outcome of the project, Shabani emphasises its broader societal ambitions. She hopes the research will raise awareness among policymakers, healthcare professionals and the general public about the fairness challenges associated with AI in healthcare. “Creating societal awareness is just as important as influencing regulation.”

Although the guidelines are primarily developed for the European regulatory context, they align with frameworks such as the AI Act, the Medical Device Regulation and the GDPR. As a result, their relevance may extend far beyond Europe. “European regulation often shapes global standards, which means this work can have international impact.”

The project also closely aligns with Shabani’s involvement in the ELSA Lab AI for Health Equity, which focuses on the ethical, legal and social aspects of AI in healthcare. Together, these initiatives create synergy in both content and timing. Ultimately, Shabani’s ambition is clear: to contribute to a healthcare system that embraces technological innovation while remaining fundamentally equitable.“Innovation should never come at the expense of fairness. The interests of patients must always come first.”