Anto Čartolovni1, Ana Tomičić2, Elvira Lazić Mosler3. 1. Digital Healthcare Ethics Laboratory (Digit-HeaL), Catholic University of Croatia, Ilica 242, 10 000 Zagreb, Croatia; School of Medicine, Catholic University of Croatia, Ilica 242, 10 000 Zagreb, Croatia. Electronic address: anto.cartolovni@unicath.hr. 2. Digital Healthcare Ethics Laboratory (Digit-HeaL), Catholic University of Croatia, Ilica 242, 10 000 Zagreb, Croatia. Electronic address: ana.tomicic@unicath.hr. 3. School of Medicine, Catholic University of Croatia, Ilica 242, 10 000 Zagreb, Croatia; General Hospital Dr. Ivo Pedišić, Sisak, Croatia. Electronic address: elvira.lazic@unicath.hr.
Abstract
INTRODUCTION: Recent developments in the field of Artificial Intelligence (AI) applied to healthcare promise to solve many of the existing global issues in advancing human health and managing global health challenges. This comprehensive review aims not only to surface the underlying ethical and legal but also social implications (ELSI) that have been overlooked in recent reviews while deserving equal attention in the development stage, and certainly ahead of implementation in healthcare. It is intended to guide various stakeholders (eg. designers, engineers, clinicians) in addressing the ELSI of AI at the design stage using the Ethics by Design (EbD) approach. METHODS: The authors followed a systematised scoping methodology and searched the following databases: Pubmed, Web of science, Ovid, Scopus, IEEE Xplore, EBSCO Search (Academic Search Premier, CINAHL, PSYCINFO, APA PsycArticles, ERIC) for the ELSI of AI in healthcare through January 2021. Data were charted and synthesised, and the authors conducted a descriptive and thematic analysis of the collected data. RESULTS: After reviewing 1108 papers, 94 were included in the final analysis. Our results show a growing interest in the academic community for ELSI in the field of AI. The main issues of concern identified in our analysis fall into four main clusters of impact: AI algorithms, physicians, patients, and healthcare in general. The most prevalent issues are patient safety, algorithmic transparency, lack of proper regulation, liability & accountability, impact on patient-physician relationship and governance of AI empowered healthcare. CONCLUSIONS: The results of our review confirm the potential of AI to significantly improve patient care, but the drawbacks to its implementation relate to complex ELSI that have yet to be addressed. Most ELSI refer to the impact on and extension of the reciprocal and fiduciary patient-physician relationship. With the integration of AIbased decision making tools, a bilateral patient-physician relationship may shift into a trilateral one.
INTRODUCTION: Recent developments in the field of Artificial Intelligence (AI) applied to healthcare promise to solve many of the existing global issues in advancing human health and managing global health challenges. This comprehensive review aims not only to surface the underlying ethical and legal but also social implications (ELSI) that have been overlooked in recent reviews while deserving equal attention in the development stage, and certainly ahead of implementation in healthcare. It is intended to guide various stakeholders (eg. designers, engineers, clinicians) in addressing the ELSI of AI at the design stage using the Ethics by Design (EbD) approach. METHODS: The authors followed a systematised scoping methodology and searched the following databases: Pubmed, Web of science, Ovid, Scopus, IEEE Xplore, EBSCO Search (Academic Search Premier, CINAHL, PSYCINFO, APA PsycArticles, ERIC) for the ELSI of AI in healthcare through January 2021. Data were charted and synthesised, and the authors conducted a descriptive and thematic analysis of the collected data. RESULTS: After reviewing 1108 papers, 94 were included in the final analysis. Our results show a growing interest in the academic community for ELSI in the field of AI. The main issues of concern identified in our analysis fall into four main clusters of impact: AI algorithms, physicians, patients, and healthcare in general. The most prevalent issues are patient safety, algorithmic transparency, lack of proper regulation, liability & accountability, impact on patient-physician relationship and governance of AI empowered healthcare. CONCLUSIONS: The results of our review confirm the potential of AI to significantly improve patient care, but the drawbacks to its implementation relate to complex ELSI that have yet to be addressed. Most ELSI refer to the impact on and extension of the reciprocal and fiduciary patient-physician relationship. With the integration of AIbased decision making tools, a bilateral patient-physician relationship may shift into a trilateral one.
Keywords:
Artificial intelligence; Decision-making; ELSI; Ethics by design; Medical ethics; Transparency; bioethics; decision-making; digital health; medical AI
Authors: Malvika Sharma; Carl Savage; Monika Nair; Ingrid Larsson; Petra Svedberg; Jens M Nygren Journal: J Med Internet Res Date: 2022-10-05 Impact factor: 7.076
Authors: Martin Mullins; Martin Himly; Isabel Rodríguez Llopis; Irini Furxhi; Sabine Hofer; Norbert Hofstätter; Peter Wick; Daina Romeo; Dana Küehnel; Kirsi Siivola; Julia Catalán; Kerstin Hund-Rinke; Ioannis Xiarchos; Shona Linehan; Daan Schuurbiers; Amaia García Bilbao; Leire Barruetabeña; Damjana Drobne Journal: Environ Syst Decis Date: 2022-07-24