Operationalising ethics in artificial intelligence for healthcare: a framework for AI developers

Abstract

Artificial intelligence (AI) offers much promise for improving healthcare. However, it runs the looming risk of causing individual and societal harms; for instance, exacerbating inequalities amongst minority groups, or enabling compromises in the confidentiality of patients’ sensitive data. As such, there is an expanding, unmet need for ensuring AI for healthcare is developed in concordance with human values and ethics. Augmenting “principle-based” guidance that highlight adherence to ethical ideals (without necessarily offering translation into actionable practices), we offer a solution-based framework for operationalising ethics in AI for healthcare. Our framework is built from a scoping review of existing solutions of ethical AI guidelines, frameworks and technical solutions to address human values such as self-direction in healthcare. Our view spans the entire length of the AI lifecycle: data management, model development, deployment and monitoring. Our focus in this paper is to collate actionable solutions (whether technical or non-technical in nature), which can be steps that enable and empower developers in their daily practice to ensuring ethical practices in the broader picture. Our framework is intended to be adopted by AI developers, with recommendations that are accessible and driven by the existing literature. We endorse the recognised need for ‘ethical AI checklists’ co-designed with health AI practitioners, which could further operationalise the technical solutions we have collated. Since the risks to health and wellbeing are so large, we believe a proactive approach is necessary for ensuring human values and ethics are appropriately respected in AI for healthcare.

Economics of Artificial Intelligence in Healthcare: Diagnosis vs. Treatment

“…Solanki et al [ 185 ] presented go-beyond approaches that provide guidelines based on principles such as adherence to “fairness” and adopting a framework based on solutions that AI programmers can use to operationalize ethics in AI for healthcare across all phases of the AI lifecycle, including data management, model development, deployment, and monitoring. The authors strongly emphasize actionable, technical, or quasi-solutions that AI developers can use.…”

Artificial Intelligent Tools: Evidence-Mapping on the Perceived Positive Effects on Patient-Care

“…The current study opposes earlier ones [10,12] suggesting that AI tools could seriously compromise data privacy. In addition, AI tools are vulnerable to attack by computer hackers who could misuse patient-records [9,24]. Although these concerns are legitimate, some previous studies [2,25] suggest that AI tools have inherent security mechanisms against data leak and theft.…”

“…The other continents, including Australia, Asia, and Africa have also recorded modest successes in the application of AI tools in their healthcare systems [7,13,15,22]. Though records exist about AI application in invasive and non-invasive procedures in these continents, especially in Africa, their use is more associated with smart devices aided by applications such as AiCure and a gamut of AI ChatBots [15,23,24].…”

“…Regardless of the level of AI use in patient-care across the globe, these intelligent machines appear to be supersupportive and could rede ne the future of healthcare and change its face for the better [10,16,25]. While at this, the patient remains the ultimate "subject" in this whole discourse and in whose best interest AI tools are deployed in the healthcare system [2,24,26].…”

“…Moreover, most of the studies involving AI use in health were conducted in non-clinical circles and devoid of the views of patients and other key stakeholders in healthcare [2]. As primary stakeholders in the healthcare system, the opinions of patients, especially, are key to determining the level of acceptability of AI tools in patient-care, which could help in ensuring their cooperation [2,24,26]. Meanwhile, the SDG 3.4 provides for the attainment of universal health coverage, including access to quality essential healthcare services, medicines and vaccines for all, by 2030 [3,7,8].…”