Abstract
ObjectivesWhile ethicists have largely underscored the risks raised by digital health solutions that operate with or without artificial intelligence (AI), limited research has addressed the need to also mitigate their environmental footprint and equip health innovators as well as organisation leaders to meet responsibility requirements that go beyond clinical safety, efficacy and ethics. Drawing on the Responsible Innovation in Health framework, this qualitative study asks: (1) what are the practice-oriented tools available for innovators to develop environmentally sustainable digital solutions and (2) how are organisation leaders supposed to support them in this endeavour?MethodsFocusing on a subset of 34 tools identified through a comprehensive scoping review (health sciences, computer sciences, engineering and social sciences), our qualitative thematic analysis identifies and illustrates how two responsibility principles—environmental sustainability and organisational responsibility—are meant to be put in practice.ResultsGuidance to make environmentally sustainable digital solutions is found in 11 tools whereas organisational responsibility is described in 33 tools. The former tools focus on reducing energy and materials consumption as well as pollution and waste production. The latter tools highlight executive roles for data risk management, data ethics and AI ethics. Only four tools translate environmental sustainability issues into tangible organisational responsibilities.ConclusionsRecognising that key design and development decisions in the digital health industry are largely shaped by market considerations, this study indicates that significant work lies ahead for medical and organisation leaders to support the development of solutions fit for climate change.
Funder
Canadian Institutes of Health Research
Fonds de la recherche en santé du Québec
International Observatory of the Societal Impacts of Artificial Intelligence and Digital Technologies
Subject
Strategy and Management,Health Policy,Leadership and Management
Reference42 articles.
1. Goldacre B , Morley J . Better, broader, safer: using health data for research and analysis. A review commissioned by the secretary of state for health and social care. 2022.
2. The global landscape of AI ethics guidelines;Jobin;Nat Mach Intell,2019
3. Fjeld J , Achten N , Hilligoss H , et al . Principled artificial intelligence: mapping consensus in ethical and rights-based approaches to principles for AI. SSRN Journal 2020. doi:10.2139/ssrn.3518482
4. The ethics of AI in health care: a mapping review;Morley;Social Science & Medicine,2020
5. Murphy K , Di Ruggiero E , Upshur R , et al . Artificial intelligence for good health: a scoping review of the ethics literature. BMC Med Ethics 2021;22:14. doi:10.1186/s12910-021-00577-8