Background: Artificial intelligence (AI) is considered the fourth industrial revolution that will change the evolution of humanity technically and relationally. Although the term has been around since 1956, it has only recently become apparent that AI can revolutionize technologies and has many applications in the medical field. Areas of Uncertainty: The ethical dilemmas posed by the use of AI in medicine revolve around issues related to informed consent, respect for confidentiality, protection of personal data, and last but not least the accuracy of the information it uses. Data Sources: A literature search was conducted through PubMed, MEDLINE, Plus, Scopus, and Web of Science (2015–2022) using combinations of keywords, including: AI, future in medicine, and machine learning plus ethical dilemma. Ethics and Therapeutic Advances: The ethical analysis of the issues raised by AI used in medicine must mainly address nonmaleficence and beneficence, both in correlation with patient safety risks, ability versus inability to detect correct information from inadequate or even incorrect information. The development of AI tools that can support medical practice can increase people's access to medical information, to obtain a second opinion, for example, but it is also a source of concern among health care professionals and especially bioethicists about how confidentiality is maintained and how to maintain cybersecurity. Another major risk may be related to the dehumanization of the medical act, given that, at least for now, empathy and compassion are accessible only to human beings. Conclusions: AI has not yet managed to overcome certain limits, lacking moral subjectivity, empathy, the level of critical thinking is still insufficient, but no matter who will practice preventive or curative medicine in the next period, they will not be able to ignore AI, which under human control can be an important tool in medical practice.

The main objective of this cross sectional study was to assess the psychometric properties of a new research instrument. The secondary aim was to analyze patients’ levels of dissatisfaction with the professionalism of medical staff. A social survey questionnaire was created and administered online. The instrument consisted of two scales: the 30-item patient dissatisfaction scale and the 10 items institutional scale. In this article, we assessed only the patient dissatisfaction scale. The research population includes 1838 subjects. The statistical procedures used were descriptive statistics, Pearson’s correlation, and factorial analyses with the SPSS.19 software. The internal consistency of the instrument was determined using the Cronbach’s alpha coefficient. We used a principal component analysis to investigate the factorial validity of the scale. The patients’ scale of dissatisfaction obtained an alpha Cronbach score of 0.81. Three latent factors corresponding to three dimensions of dissatisfaction emerged from the data: medical staff’s ability to communicate, medical staff’s hygiene, as well as sanitary and privacy conditions within the hospital. The first factor explained 43.47% of the variance in patient dissatisfaction, the second factor explained 10.24%, and the third factor explained 7.59%; overall, the three factors explained 61.30% of the total variance. The Romanian healthcare system has an organization and management structure which has shown few changes since the communist period. Our study indicates that although more than 25 years have passed since the political regime changed in Romania and the introduction of a different system of social care, there have been no corresponding changes in the medical staff’s mentality or in the way that patients are approached. The present assessment of patient dissatisfaction is not a strictly theoretical exercise; it also represents a valuable instrument for healthcare system management.