Resum
The healthcare sector has been an early adopter of new technologies such as artificial intelligence, nanotechnology, or genome sequencing. They are expected to improve healthcare systems and augment practitioners’ skills. The deployment of wearable sensors and healthcare trackers are empowering individuals, making them self-aware of their wellbeing but also turning them into data donors. Personal data are essential to train machine learning models used to support healthcare professionals in decision making. However, it is extremely relevant to consider the power of the (mis-)represented population in the data analyzed. Artificial intelligent systems used in precision medicine need to be robust, not only technically but also socially by tackling gender imbalance, technology access, or other issues that may affect vulnerable groups in healthcare. This chapter offers an overview on the opportunities of digital health ecosystems while highlighting some social, ethical, and technical challenges. It also provides a review of the relation of the traditional ethical principles used in health and biomedicine and those defined for the design, deployment, and use of a trustworthy AI in Europe.
| Idioma original | Anglès |
|---|---|
| Títol de la publicació | Sex and Gender Bias in Technology and Artificial Intelligence |
| Subtítol de la publicació | Biomedicine and Healthcare Applications |
| Editor | Elsevier |
| Pàgines | 219-238 |
| Nombre de pàgines | 20 |
| ISBN (electrònic) | 9780128213926 |
| ISBN (imprès) | 9780128213933 |
| DOIs | |
| Estat de la publicació | Publicada - 1 de gen. 2022 |