Case Study: A Human Pre-Natal Experiment in 1944—“Do No Harm”

Iris du Pré, a professional pianist, wanted a second child, did not conceive quickly and was injected in 1944 by a doctor in Oxford with pregnant mare serum gonadotropin (PMSG). The doctor joked “This child will be a racehorse winner!” In January 1945, Jacqueline du Pré, the remarkable, world-famous cellist was born. In the 1920's and 1930's, animal experimentation and clinical studies had shown that pituitary glycoproteins stimulated the ovary (follicle-stimulating hormone, FSH) and the corpus luteum (luteal-stimulating hormone, LH) which prepared the human womb for embedding a fertilized ovum and that pregnant mare’s blood and urine contained the glycoprotein, PMSG whose origin was placental cells, but surprisingly in humans had the actions of both FSH and LH. However, the PMSG serum alone did not bring about pregnancy. The doctor did not know that without subsequent injection of another factor in correct sequence and timing, PMSG was pointless. In 1947, a placental glycoprotein, found in the 1920's in urine of pregnant women (human chorionic gonadotropin, hCG), when injected in mice subsequent to PMSG, achieved ovulation but not pregnancy. Human application of those findings was extremely risky due to impurities (up to 95%). The Federal Drug Administration (FDA), established in 1938, requested easily bye-passed marketing safety. Companies offered material “sufficiently” purified;professional bodies negated clinical use, tempting to a few. Evidence also suggests that, to sustain pregnancy the doctor also prescribed the new “eostrogen”, diethyl stilbestrol (DES) of negative fame. In 1947, the Nuremberg Code of ethics demanded human experiments by qualified personnel and trials preceded by adequate animal studies. It is not the case here. From five, du Pré had a most exceptional musical memory, almost obsessive musicality and a very difficult school-time socially. Later history: adult masculine build, awkward gait, tendency to recurrent depressions from mid-adolescence, unbalanced thyroidal metabolism, symptoms of numbness in late teens, long breaks for rest from age 25, MS diagnosis at 28 when unable to play, death aged 42. Yet at sixteen and after, she astounded all with technique, passion and unique musical interpretation. Her husband, an outstanding musician: “She had a capacity to imagine sound such as I never met in any other musician”. A close musician colleague: “... it was done before she was born”;perhaps much closer to the truth than realization, for her history it may suggest a fetal neurodevelopment abused in the womb.

Medical artificial intelligence and the black box problem:a view based on the ethical principle of“do no harm”

One concern about the application of medical artificial intelligence(AI)regards the“black box”feature which can only be viewed in terms of itsinputs and outputs,with no way to understand the AI’s algorithm.Thisis problematic because patients,physicians,and even designers,do not understand why or how a treatment recommendation is produced by AI technologies.One view claims that the worry about black-box medicine is unreasonable because AI systems outperform human doctors in identifying the disease.Furthermore,under the medical AI-physicianpatient model,the physician can undertake the responsibility of interpreting the medical AI’s diagnosis.In this study,we focus on the potential harm caused by the unexplainability feature of medical AI and try to show that such possible harm is underestimated.We will seek to contribute to the literature from three aspects.First,we appealed to a thought experiment to show that although the medical AI systems perform better on accuracy,the harm caused by medical AI’s misdiagnoses may be more serious than that caused by human doctors’misdiagnoses in some cases.Second,in patient-centered medicine,physicians were obligated to provide adequate information to their patients in medical decision-making.However,the unexplainability feature of medical AI systems would limit the patient’s autonomy.Last,we tried to illustrate the psychological and financial burdens that may be caused by the unexplainablity feature of medical AI systems,which seems to be ignored by the previous ethical discussions.