When Machine Learning technologies are used in contexts that affect citizens, companies as
well as researchers need to be confident that there will not be any unexpected social …

Background: Privacy has always been a concern, especially in the health domain. The
proliferation of mobile health (mHealth) apps has led to a large amount of sensitive data …

Sustainable development is critical to ensure the future of humanity. Therefore, the
assessment and governance of sustainability becomes a central challenge our society is …

Over the decades, Artificial Intelligence (AI) and machine learning has become a
transformative solution in many sectors, services, and technology platforms in a wide range …

Companies and organizations involved in software development are stimulated and often
obliged to consider procedures and technical solutions to guarantee data privacy and …

A transformed health ecosystem is a multi-stakeholder coalition that collects, stores, and
shares personal health information (PHI) for different purposes, such as for personalized …

Privacy has emerged as a key concern for business and social computing as security
breaches have compromised personal data for millions. Despite this, much of existing work …

Data sharing in the European Union (EU) has gained new momentum, among others for
machine learning (ML) and artificial intelligence (AI) training purposes. By enabling models' …

Data privacy is a topic of interest for researchers, data collection managers, and data system
specialists. In an attempt to assuage growing concerns regarding the collection and use of …

The research and industrial environments are struggling to identify practical approaches to
highlight the (new) duties of controllers of personal data and foster the transition of IT-based …