Beyond the algorithm: Putting human conscience at the heart of healthcare AI

By Anna Gallinat in conversation with Carina Dantas, CEO of SHINE 2Europe 

If you have ever felt a quiet flicker of hesitation when asked to share your personal health details online, you are certainly not alone. The public anxiety surrounding Artificial Intelligence (AI) in healthcare is deeply felt, and for good reason. While patients and clinicians alike can see the tremendous good emerging technologies can do, a persistent, healthy scepticism remains about how our most sensitive health data is handled. 

Crucially, this mistrust is not about being “against” technology. Instead, it often comes from a very human place: a lack of clear, accessible knowledge about the broader societal impacts of these tools, and how disconnected the public can feel from the long, iterative journey of scientific research, says Carina Dantas, CEO of SHINE 2Europe.  

To move forward, we need to step away from divisive, binary debates about being pro- or anti-AI. Instead, we must roll up our sleeves and focus on the practical, human mechanics of how these systems are actually built. 

Carina Dantas and her team at SHINE 2Europe are at the forefront of this thoughtful approach. Our mission is as simple as it is vital: to ensure that technological innovation is always firmly grounded in genuine human conscience. 

Co-designing AI: Bringing ethics to life in practice 

While high-level ethical guidelines and legal frameworks are essential for setting boundaries, they can often feel a bit abstract, dry, or disconnected from the realities of daily care. To bridge this gap, SHINE uses a participatory ethics model. This means bringing patients, doctors, nurses, AI developers, policy makers and community stakeholders into the room to actively co-create technology throughout its entire development – not just at the end. 

This human-centred framework comes to life in projects such as MAYA, developing an AI-powered healthcare ecosystem built around a smart mirror interface. When the team sat down early on to listen to potential users, they discovered a wide range of personal comfort levels. Some people felt completely at ease interacting with a smart mirror in a community health centre or living lab, while others felt much more comfortable using it in the privacy of their own home, or preferred a simple smartphone app instead. 

In a shared community space, an ethical priority is making sure the mirror would not accidentally capture or store data from bystanders walking by. At home, concerns shift to protecting the privacy of visiting family and friends who have not given consent. By listening early and deeply, the team is able to design a flexible, respectful system that adapts to people’s real lives, rather than forcing everyone into a rigid, one-size-fits-all box. 

Bridging research and European policy 

Carina Dantas’s ongoing PhD research in applied AI ethics forms a strong foundation for this work. Having spent decades listening to end-users, she saw how often non-technical voices were brought into tech projects far too late. Her academic work¹ focuses on creating clear, structured pathways so that human values and user feedback are woven directly into the software code from day one. 

This balanced approach is becoming increasingly vital as Europe moves forward with the European Health Data Space (EHDS). In the rush of global competition and rapid technological change, it can be tempting to push for quick, seamless data integration. According to Carina Dantas, however, moving too fast without embedding ethical care into the infrastructure risks losing the most important element of all: public trust. 

At the same time, health technologies must actively help reduce social inequalities. Biases in AI often stem from long-standing disparities in income, geography, or digital skills. To guard against this, SHINE works closely with local municipalities and community groups, particularly those supporting rural, migrant, or digitally isolated populations, to ensure these tools are genuinely accessible, inclusive, and culturally sensitive for everyone. 

A shared path to the common good 

Finding the sweet spot between protecting our personal data and building effective AI is a delicate, ongoing balance. High-performing AI requires rich, comprehensive data, yet none of us want to share our private medical details if we worry they might be misused by insurers, employers, or opaque algorithms. Resolving this tension is not about finding a clever technical shortcut; it is about building genuine trust, so people feel empowered to make informed, confident choices. 

Ultimately, ethical AI in healthcare invites us to view sharing health data as a collective act for the common good, much like organ or blood donation. As we navigate rapid technological shifts together, creating trustworthy systems simply means taking the time to do things right. 

Ethics does not have to be an overwhelming or complicated burden. As Carina Dantas reminds us, “we need to remember the basics”. At its heart, ethics is simply the foundation of good, thoughtful practice. True ethical care isn’t a final destination we reach and check off; “it is a pathway, not a solution.” By keeping human conscience, warmth, and care at the heart of our code, healthcare AI can evolve from a subject of hesitation into a deeply trusted ally for public well-being.