Special Issue: Why Ethically Reflect on Empirical Studies in Empirical Ethics? Case Studies and Commentaries

Artificial Intelligence in Reproductive Medicine - An Ethical Perspective

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.

Acceptable objectives of empirical research in bioethics: a qualitative exploration of researchers' views

BACKGROUND

This is the first qualitative study to investigate how researchers, who do empirical work in bioethics, relate to objectives of empirical research in bioethics (ERiB). We explore reasons that make some objectives more acceptable, while others are deemed less acceptable.

METHODS

Using qualitative exploratory study design, we interviewed bioethics researchers, who were selected to represent different types of scholars working in the field. The interview data of 25 participants were analyzed in this paper using thematic analysis.

RESULTS

From the eight objectives presented to the study participants, understanding the context of a bioethical issue and identifying ethical issues in practice received unanimous agreement. Participants also supported other objectives of ERiB but with varying degrees of agreement. The most contested objectives were striving to draw normative recommendations and developing and justifying moral principles. The is-ought gap was not considered an obstacle to ERiB, but rather a warning sign to critically reflect on the normative implications of empirical results.

CONCLUSIONS

Our results show that the most contested objectives are also the more ambitious ones, whereas the least contested ones focus on producing empirical results. The potential of empirical research to be useful for bioethics was mostly based on the reasoning pattern that empirical data can provide a testing ground for elements of normative theory. Even though empirical research can inform many parts of bioethical inquiry, normative expertise is recommended to guide ERiB. The acceptability of ambitious objectives for ERiB boils down to finding firm ground for the integration of empirical facts in normative inquiry.