Authors:
Francesca Lizzi
1
;
Alessandra Retico
1
and
Maria Fantacci
2
Affiliations:
1
National Institute for Nuclear Physics, Pisa Division, Pisa, Italy
;
2
Department of Physics, University of Pisa, Pisa, Italy
Keyword(s):
Deep Learning, Ethics, Epistemology, Multi Disciplinary Science, Medical Imaging.
Abstract:
Machine and deep learning methods applied to medicine seem to be a promising way to improve the performance in solving many issues from the diagnosis of a disease to the prediction of personalized therapies by analyzing many and diverse types of data. However, developing an algorithm with the aim of applying it in clinical practice is a complex task which should take into account the context in which the software is developed and should be used. In the first report of the World Health Organization (WHO) about the ethics and governance of Artificial Intelligence (AI) for health published in 2021, it has been stated that AI may improve healthcare and medicine all over the world only if ethics and human rights are a main part of its development. Involving ethics in technology development means to take into account several issues that should be discussed also inside the scientific community: the epistemological changes, population stratification issues, the opacity of deep learning algor
ithms, data complexity and accessibility, health processes and so on. In this work, some of the mentioned issues will be discussed in order to open a discussion on whether and how it is possible to address them.
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