Special Session on legal and ethical aspects of AI systems in the biomedical field
IEEE CIBCB 2025 - 22th IEEE International Conference on Computational Intelligence/AI in Bioinformatics and Computational Biology

National Cheng Kung University, Tainan, Taiwan

August 20-22, 2025

CALL FOR PAPERS
Aim
In recent years, the development of AI systems aimed at supporting clinical decisions has greatly expanded, employing a wide range of techniques, such as machine learning and deep learning. AI systems are used for a variety of applications, such as diagnosis, personalized medicine, triage assessment, disease prevention and monitoring, and drug development. In some areas, such as radiology, the performance of AI systems has even surpassed that of humans.
However, the biomedical field is also a sector in which complaints, litigation, criminal charges for medical malpractice, and administrative fines are increasing worldwide, therefore special attention should be paid to legal issues that may arise from the use of AI systems. AI systems may, in fact, have a significant legal impact on multiple stakeholders: researchers, producers, health care professionals, patients, and society as a whole.
From a legal point of view, the whole AI life cycle generates the need for regulatory and ethical compliance. Because of the fact that health data, which are considered special categories of data according to art. 9 of GDPR, are involved, privacy compliance, including correct anonymization pursuant to the Working Party 29’s guidelines of 2014, is a key issue. In addition, due to the known issues regarding discrimination in health care, the ethical assessment is also extremely important.
At a global level, there is a call for the development of Trustworthy AI systems, which is particularly important in the biomedical field. As highlighted by the High-Level Expert Group on AI set up by the European Commission, “Trustworthy AI has three components, which should be met throughout the system's entire life cycle:
1. it should be lawful, complying with all applicable laws and regulations;
2. it should be ethical, ensuring adherence to ethical principles and values; and
3. it should be robust, both from a technical and social perspective, since, even with good intentions, AI systems can cause unintentional harm”.

Some scholars have even pushed the debate further, advocating for explainability and interpretability for all systems employed in the healthcare sector, thus considering black-box approaches not compliant with ethical and legal standards.

This Special Session aims at gathering scholars who are investigating new directions and ideas in the field of AI and Law & AI Ethics, in particular in the biomedical field.
Scope
This Special Session welcomes papers regarding any legal issue (including privacy) and ethical aspects of AI systems; in particular, we are interested in Automated Decision-Making systems (ADM), applied in the context of the biological or medical domain.

Examples include but are not limited to:
Explainable/Interpretable AI systems for medical decision support
Right of explanation and Trustworthy AI in the biomedical field
Biases in AI systems and debiasing techniques
Fair methods for data preprocessing
Unbiased data augmentation and privacy-preserving generative models
Anonymization and pseudonymization of biobanks
How personalized medicine through AI systems can contribute to mitigating discrimination and inequalities in healthcare
Privacy aspects of telemedicine
The use of synthetic data to protect personal data
Legal and ethical issues of data collection, data cleaning, feature/variable selection, and other phases of the development
Ethical framework for medical AI systems
Ownership of patients’ data and conditions for reuse
Legal consequences of a biased AI model
Medical device regulation and AI
AI regulation proposal and AI models in biomedical research
Legal and ethical issues concerning the use of smart robots for surgery
Civil liability derived from Automated Decision Making systems in medical practice
Legal aspects of machine learning applied to medical imaging
Legal issues of open-source AI systems
Sustainable AI & environmental issues
Critical Data Theories regarding AI in the biomedical field
AI and the European Health Data Space
Data Governance Act and Health Data Altruism for AI
Comparative perspectives on the above issues in different legal systems (papers exploring the legal system of under-represented countries are very welcome)
Important Dates
Submission deadline: 10th of March 2025
Short paper submission: 10th of June 2025
Notification of acceptance 10th of June 2025
Final paper submission: 30th of June 2025
Format
Prospective authors are invited to submit papers of no more than eight (8) pages in IEEE conference format, including results, figures, and references. Papers must be in PDF and written in English. Detailed instructions and templates for preparing your manuscripts can be found on the IEEE website. Papers will be published in the proceedings of the conference.
Submission guidelines
Special session papers should be uploaded online through the IEEE CIBCB 2025 EasyChair system. Please select the corresponding special session name (“Special Session on legal and ethical aspects of AI systems in the biomedical field”). All papers will be peer-reviewed by experts in the fields of the call and ranked based on the criteria of originality, significance, quality, and clarity, and special attention will be paid to case studies. Please note that submission implies the willingness of at least one of the authors to register and present the paper at the conference. The conference fees are listed on the conference website.
Organizers
Chiara Gallese (University of Turin, Italy)
Chiara Gallese is a Marie Sklodowska-Curie Postdoctoral Fellow a University of Turin’s Department of Law (italy); Guest researcher at the Department of Electrical Engineering at Eindhoven University of Technology (the Netherlands); Subject Expert at the School of Engineering at Carlo Cattaneo University - LIUC (Italy); and Fellow at the University of Milan’s Information Societ Law Center. Her research focuses on Data Protection, AI & Law, and AI & Ethics.

Elena Falletti (Carlo Cattaneo University LIUC, Italy)
Elena Falletti is an Associate Professor at the School of Engineering at Carlo Cattaneo University - LIUC (Italy). Her research focuses on antidiscrimination law, comparative law, and AI & privacy.

Daniele Papetti (University of Milano-Bicocca, Italy)
Daniele Papetti is an Assistant Professor at the Department of Informatics, Systems and Communications at the University of Milano-Bicocca (Italy). His research focuses on computational biomedicine, system biology, and optimization.