Artificial intelligence (AI) based clinical decision support systems (CDSS) are becoming ever more widespread in healthcare and could play an important role in diagnostic and treatment processes. For this reason, AI‐based CDSS has an impact on the doctor–patient relationship, shaping their decisions with its suggestions. We may be on the verge of a paradigm shift, where the doctor–patient relationship is no longer a dual relationship, but a triad. This paper analyses the role of AI‐based CDSS for shared decision‐making to better (...) comprehend its promises and associated ethical issues. Moreover, it investigates how certain AI implementations may instead foster the inappropriate paradigm of paternalism. Understanding how AI relates to doctors and influences doctor–patient communication is essential to promote more ethical medical practice. Both doctors' and patients' autonomy need to be considered in the light of AI. (shrink)

Informed consent is at the core of the clinical relationship. With the introduction of machine learning in healthcare, the role of informed consent is challenged. This paper addresses the issue of whether patients must be informed about medical ML applications and asked for consent. It aims to expose the discrepancy between ethical and practical considerations, while arguing that this polarization is a false dichotomy: in reality, ethics is applied to specific contexts and situations. Bridging this gap and considering the whole (...) picture is essential for advancing the debate. In the light of the possible future developments of the situation and the technologies, as well as the benefits that informed consent for ML can bring to shared decision-making, the present analysis concludes that it is necessary to prepare the ground for a possible future requirement of informed consent for medical ML. (shrink)

Background While the theoretical benefits and harms of Artificial Intelligence (AI) have been widely discussed in academic literature, empirical evidence remains elusive regarding the practical ethical challenges of developing AI for healthcare. Bridging the gap between theory and practice is an essential step in understanding how to ethically align AI for healthcare. Therefore, this research examines the concerns and challenges perceived by experts in developing ethical AI that addresses the healthcare context and needs. Methods We conducted semi-structured interviews with 41 (...) AI experts and analyzed the data using reflective thematic analysis. Results We developed three themes that expressed the considerations perceived by experts as essential for ensuring AI aligns with ethical practices within healthcare. The first theme explores the ethical significance of introducing AI with a clear and purposeful objective. The second theme focuses on how experts are concerned about the tension that exists between economic incentives and the importance of prioritizing the interests of doctors and patients. The third theme illustrates the need to develop context-sensitive AI for healthcare that is informed by its underlying theoretical foundations. Conclusions The three themes collectively emphasized that beyond being innovative, AI must genuinely benefit healthcare and its stakeholders, meaning AI also aligns with intricate and context-specific healthcare practices. Our findings signal that instead of narrow product-specific AI guidance, ethical AI development may need a systemic, proactive perspective that includes the ethical considerations (objectives, actors, and context) and focuses on healthcare applications. Ethically developing AI involves a complex interplay between AI, ethics, healthcare, and multiple stakeholders. (shrink)

Healthcare cybersecurity is increasingly targeted by malicious hackers. This sector has many vulnerabilities and health data is very sensitive and valuable. Consequently, any damage caused by malicious intrusions is particularly alarming. The consequences of these attacks can be enormous and endanger patient care. Amongst the already-implemented cybersecurity measures and the ones that need to be further improved, this paper aims to demonstrate how penetration tests can greatly benefit healthcare cybersecurity. It is already proven that this approach has enforced cybersecurity in (...) other sectors. However, it is not popular in healthcare since many prejudices still surround the hacking practice and there is a lack of education on hackers’ categories and their ethics. The present analysis aims to comprehend what hacker ethics is and who ethical hackers are. Currently, hacker ethics has the status of personal ethics; however, to employ penetration testers in healthcare, it is recommended to draft an official code of ethics, comprising principles, standards, expectations, and best practices. Additionally, it is important to distinguish between malicious hackers and ethical hackers. Amongst the latter, penetration testers are only a sub-category. Acknowledging the subtle differences between ethical hackers and penetration testers allows to better understand why and how the latter can offer their services to healthcare facilities. (shrink)