Abstract
Artificial intelligence is steadily being integrated into all areas of medicine. In
reproductive medicine, artificial intelligence methods can be utilized to improve
the selection and
prediction of sperm cells, oocytes, and embryos and to generate better predictive
models for in vitro fertilization. The use of artificial intelligence in this field
is justified by the
suffering of persons or couples who wish to have children but are unable to conceive.
However, research into the use of artificial intelligence in reproductive medicine
is still in the early
experimental stage and furthermore raises complex normative questions. There are ethical
research challenges because evidence of the efficacy of certain pertinent systems
is often lacking
and because of the increased difficulty of ensuring informed consent on the part of
the affected persons. Other ethically relevant issues include the potential risks
for offspring and the
difficulty of providing sufficient information. The opportunity to fulfill the desire
to have children affects the welfare of patients and their reproductive autonomy.
Ultimately, ensuring
more accurate predictions and allowing physicians to devote more time to their patients
will have a positive effect. Nevertheless, clinicians must be able to process patient
data
conscientiously. When using artificial intelligence, numerous actors are involved
in making the diagnosis and deciding on the appropriate therapy, raising questions
about who is ultimately
responsible when mistakes occur. Questions of fairness arise with regard to resource
allocation and cost reimbursement. Thus, before implementing artificial intelligence
in clinical
practice, it is necessary to critically examine the quantity and quality of the data
used and to address issues of transparency. In the medium and long term, it would
be necessary to
confront the undesirable impact and social dynamics that may accompany the use of
artificial intelligence in reproductive medicine.
Keywords artificial intelligence - reproductive medicine - infertility - medical ethics - research
ethics
