# Artificial Intelligence in Oncology
## 4 Ethical Aspects and Other Limitations of AI  
It is not clear whether AI fits the current ethical and legal criteria or whether AI requires the development of new criteria [77]. Artificial intelligence raises some ethical and legal concerns. Some authors draw attention to the problems that may be encountered in the implementation of ethical principles to AI. So far, unlike existing ethical and legal guidelines in the healthcare system, there are no such guidelines for AI, although the European Union has developed the _European Ethics Guidelines for Trustworthy AI_[78]. According to these Guidelines, trustworthy AI should be lawful--respecting all applicable laws and regulations; ethical--respecting ethical principles and values; and robust--both from a technical perspective, while also taking into account its social environment. In its recommendations, in particular in Policy Area 6 and Policy Area 11, UNESCO highlighted several aspects related to the use of AI, especially in the medical field such as gender bias, explainability, responsibility, accountability, health and social well-being [79]. AI systems should be based on seven pillars: (1) human agency and oversight, (2) technical robustness and safety, (3) privacy and data governance, (4) transparency, (5) diversity, non-discrimination and fairness, (6) environmental and social well-being and (7) accountability. In a systematic literature review, [PERSON] and co-authors identified five key ethical issues connected with AI in medicine: benefcience, non-maleficence, autonomy, justice and explicability [80]. The first of these principles, i.e., benefcience, addresses the problem of how AI can best use patient data, to what extent medical knowledge can be enriched by AI, how to combine the knowledge of a doctor with AI, and how to prevent bias, for example, associated with belonging to a particular minority. The second ethical issue raised by the authors is non-maleficence. What is this and how is it different from benefcience? Non-maleficence means that medical personnel should not cause or allow any harm to the patient through neglect. There are two main differences between non-maleficence and benefcience. Firstof all, non-maleficence acts as a threshold for treatment. If a treatment causes more harm than good, then it should not be considered. This is in contrast to benefence, where all valid treatment methods are considered. Second, as against benefence, where the best method of treatment is chosen in a particular situation, non-maleficence is constant in clinical practice. The next ethical problem connected with AI is autonomy. Autonomy mainly affects the problems of AI threats to medical staff such as accountability for algorithm-based decisions derived by AI, factors influencing perceptions of losing individual autonomy, and differences between AI and other technologies. The next ethical issue i.e., justice, concerns psychological support for medical practice in the case of making morally unacceptable decisions by AI, using AI to improve the patient-doctor relationship, and creating guidelines to develop AI. The last principle identified by [PERSON] et al., i.e., explicability, implies that the data obtained by AI should be presented, especially to medical staff, in an understandable way [80]. It is also important to determine which data are particularly useful for AI in communicating understandable medical decisions. The ethical aspects of AI according to [PERSON] et al. are shown in Table 1.  
Similar principles to those of [PERSON] et al. were proposed by [PERSON], who outlined four main ethical pillars for putting AI into clinical practice: medical indications (benefcience and non-maleficence), patient preferences (respect for autonomy), quality of life (benefcience, non-maleficence and respect for autonomy) and contextual features (justice and fairness) [81]. [PERSON] states that introducing ethical principles into AI practices may be connected with problems such as ethics lobbying, ethics dumping and ethics evasion [82].