Today we face a technological paradox: while most people view Artificial Intelligence (AI) with curiosity but limited technical knowledge, primarily associating it with robots, chatbots, or voice assistants, science already considers it a life-saving solution. To bridge this gap, on April 23, 2026, Villa Quartara in Genoa, Italy, hosted the conference “AI for Healthcare, Longetivity & Wellness ,” organized by  Fusion AI Labs , with the goal of bringing AI to hospitals. The discussion revealed a crucial fact: 80% of projects fail not due to technical limitations, but rather due to implementation difficulties. Between regulatory complexity and data integration, the current challenge is no longer limited to research, but focuses on daily application. Today we explore how to transform these promises into concrete healthcare solutions.

In this context of digital transformation in medicine, we interviewed one of the key figures, Professor Ricard Martínez , Chair of Privacy and  Digital Transformation at the University of Valencia. An expert at the intersection of law and clinical practice, Martínez collaborates on cutting-edge European projects such as  Cancer Image Europe  (EUCAIM), which focuses on data security and protection in the use of AI in oncology.

Q: Professor Martínez, you head a chair dedicated to privacy and digital transformation. In short, how can we ensure that our most sensitive health data remains protected and anonymized when AI systems use it?

A: “I will try to be concise, although it is a topic that tends to be lengthy due to its complexity. The protection of health data against artificial intelligence is built through a robust set of safeguards that I divide into three essential layers: the legal, the technological, and, above all, the ethical.”

In the legal field, we have moved from a general protection framework, the General Data Protection Regulation (GDPR), to a more specific one, the European Health Data Area Regulation (EHDS), which allows for transparent research, supported by the  Data Governance Act  (DGA), to promote altruistic models so that citizens voluntarily share their information for the common good.

Technologically, we apply anonymization and pseudonymization. The system uses two layers to protect patient identity. Following the ruling of the European Court of Human Rights (ECHR) in September 2025, the key criterion is the user’s technical ability to re-identify themselves; if this is not possible, the data is not considered personal. Beyond data anonymization, the infrastructure must guarantee security through strict environmental control, such as preventing third-party access to the data. In projects like  Cancer Image Europe  (EUCAIM), we use secure processing environments where data is not downloaded, guaranteeing absolute traceability and total control, and where there is no possibility of re-identification through linking or individualization.

Finally, the Declaration of Helsinki (2024), along with the European Union’s ALTAI ( Assessment List for Trustworthy Artificial Intelligence ) model, creates a robust and practical ethical framework for medical research using AI, ensuring that technological innovation in health respects human dignity, privacy, and security. We assessed 63 controls across seven domains to ensure our tools are transparent, explainable, and free from bias, already proactively complying with the standards of the new AI Act.

D: Many people fear losing control over their sensitive data. In the future European Health Data Area, will patients truly have the ability to choose whether or not to share their data for research?

R: “It’s a common misconception; we fear the state, which manages data to protect our health, more than private corporations, with whom we share sensitive information daily without questioning the risks.”

Although the European Health Data Space (EHDS) guarantees high standards of security and control (such as portability and traceability), the current  binary (all or nothing) opt-out  model  is considered a strategic risk, as it makes the system vulnerable to misinformation. The proposed solution is a  granular opt-out  that allows patients to selectively choose what data to share and with whom, thus reconciling public trust with the progress of scientific research.

D: What guarantees a citizen that decisions made with the help of artificial intelligence are ethical and free from errors?

A: “In the healthcare sector, where safety is the most valuable asset, we leave nothing to chance. Ensuring the ethics and reliability of artificial intelligence doesn’t depend on a single rule, but on a network of fundamental pillars that guarantee comprehensive protection:

A double regulatory shield. One regulation is not enough; we require that all AI used for medical purposes simultaneously comply with the  AI ​​Act  and the  Medical Device Regulation  (MDR). This redundant protection ensures both technical quality and clinical safety. Risk assessment is rigorous, we prohibit manipulative practices, and we mandate human rights impact assessments before any tool reaches the patient.

Data governance and transparency: here we apply the rigor of the GDPR to manage information, combating bias  and  ensuring  that those who deploy the technology have all the necessary technical information to use it correctly . 

Non-negotiable human oversight is the core of our system. Any automated process must be capable of being reversed or integrated under human supervision at any point in the design and implementation.

Post-market surveillance, because monitoring doesn’t end with the sale. We require manufacturers to demonstrate, through traceability and continuous auditing, that the system remains safe and effective once implemented in the real-world environment.

We implement training and clinical responsibility ( AI literacy).  Technology doesn’t decide; the professional does. We mandate training so that doctors and nurses understand the tool, reaffirming that, whatever the AI’s suggestion, legal and clinical responsibility rests exclusively with the human operator.

D: Will AI change the way we interact with our doctors? Will everything become colder, or will these technologies help us provide more humane and personalized care?

A: “The integration of AI, augmented reality (AR), and digital twins will not dehumanize medicine, but rather enable a more patient-centered practice. Today, doctors must spend only 5 or 10 minutes with their patients, which means they end up interacting more with the computer screen or paper medical records than with the patient. The goal of these technologies is to eliminate this visual barrier so that doctors can fully dedicate themselves to talking with their patients. In 10 years, the technology will act as an invisible interface: using augmented reality glasses, doctors will be able to consult biometric data and the patient’s medical history in real time, maintaining eye contact and human connection. Simultaneously, the system will process the patient’s medical history and sociogenetic context during the consultation, offering accurate diagnoses and highly effective therapeutic suggestions. Far from being a cold intrusion, this advancement seems more humane to me than what we have today.”

D: In a rapidly aging society, which puts pressure on the public health system, can better data management actually translate into cost reductions and more efficient services for the elderly population?

A: “By adopting a holistic vision that integrates clinical and social factors, we are moving from reactive to preventive medicine. Predictive tools are the catalyst, enabling early detection. For example, in  breast cancer screening  , artificial intelligence can detect abnormalities that the human eye cannot yet see, guaranteeing immediate action, greater survival rates, and savings of over €200,000 for the healthcare system. In the management of chronic patients, we can monitor parameters to prevent imbalances and hospitalizations, transforming what would be an emergency into a simple routine check-up. Our ultimate goal is ambitious. Medicine is granting us greater longevity, but often at the cost of quality of life. Thanks to data, we want to promote policies that guarantee healthy aging, where living longer means living with a low prevalence of disease and a high level of well-being.”