Health Citizens – European Research Center

Tag: Data Privacy

  • Inteligência Artificial no setor da saúde: desafios jurídicos e regulação

    Inteligência Artificial no setor da saúde: desafios jurídicos e regulação

    Artificial Intelligence in the health sector: legal challenges and regulation

    AI can significantly improve the quality of health services, but its use also raises well-founded concerns. This paper, published by the Office for Strategy and Studies (GEE) of the Portuguese Ministry of Economy, analyses the current landscape of AI in the Portuguese health sector and proposes public policy solutions for Portugal.

    The author focuses on three main challenges: the opacity of AI systems, which can undermine patients’ informed consent; bias and discrimination; and the protection of health data and privacy. On bias, she explains that it comes mostly from the data used to train AI, which can reflect existing social prejudices and be skewed by factors such as age, sex, race and socioeconomic background. The paper also analyses how these systems fit within the EU AI Act, with particular attention to the obligation of human oversight.

    To reduce these risks, the author proposes measures such as ethical requirements in the development and choice of AI systems, impact assessments and independent data audits before approval, periodic evaluation with a mechanism for reporting failures, and training for health professionals so that they can understand AI and recognise its errors.

    Learn more about this paper here: https://EconPapers.repec.org/RePEc:mde:wpaper:187

    Reference:

    Paixão Cansado, M. (2024). Inteligência Artificial no setor da saúde: desafios jurídicos e regulação (GEE Paper No. 187). Gabinete de Estratégia e Estudos, Ministério da Economia.

  • Exploring Gender Bias in AI for Personalized Medicine: Focus Group Study With Trans Community Members

    Exploring Gender Bias in AI for Personalized Medicine: Focus Group Study With Trans Community Members

    Precision medicine aims to tailor healthcare to each person, but trans people are often left out of this research. Little is known about how AI tools in healthcare could be adapted to their specific health needs. This study explored the challenges, obstacles and possible solutions for using AI in personalised medicine for trans people.

    The researchers worked together with trans community representatives to co-design the study and its data collection tools, and held three focus groups with 16 trans adults. Participants raised concerns about data privacy, algorithmic bias and the lack of health data that reflects trans experiences. They also worried that AI built on data models that assume everyone is cisgender could lead to misdiagnosis or inappropriate treatment.

    At the same time, participants saw opportunities for AI to improve health outcomes. They proposed community-led data collection, more transparent algorithms, including trans-specific health markers in datasets, involving community members in AI development, and ethical frameworks that respect gender diversity. The authors conclude that precision medicine needs a trans-inclusive approach, with AI designed around the health needs and lived realities of trans people.

    Learn more about this study here: https://doi.org/10.2196/72325

    Reference:

    Buslón, N., Cirillo, D., Rios, O., & Perera del Rosario, S. (2025). Exploring gender bias in AI for personalized medicine: Focus group study with trans community members. Journal of Medical Internet Research, 27, e72325.