Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and other services that advance population health and wellbeing. However, the use of AI in healthcare also brings potential risks that may cause unintended harm. To guide future developments in AI, the High-Level Expert Group on AI set up by the European Commission (EC), recently published ethics guidelines for what it terms “trustworthy” AI. These guidelines are aimed at a variety of stakeholders, especially guiding practitioners toward more ethical and more robust applications of AI. In line with efforts of the EC, AI ethics scholarship focuses increasingly on converting abstract principles into actionable recommendations. However, the interpretation, relevance, and implementation of trustworthy AI depend on the domain and the context in which the AI system is used. The main contribution of this paper is to demonstrate how to use the general AI HLEG trustworthy AI guidelines in practice in the healthcare domain. To this end, we present a best practice of assessing the use of machine learning as a supportive tool to recognize cardiac arrest in emergency calls. The AI system under assessment is currently in use in the city of Copenhagen in Denmark. The assessment is accomplished by an independent team composed of philosophers, policy makers, social scientists, technical, legal, and medical experts. By leveraging an interdisciplinary team, we aim to expose the complex trade-offs and the necessity for such thorough human review when tackling socio-technical applications of AI in healthcare. For the assessment, we use a process to assess trustworthy AI, called 1Z-Inspection® to identify specific challenges and potential ethical trade-offs when we consider AI in practice.
This paper documents how an ethically aligned co-design methodology ensures trustworthiness in the early design phase of an artificial intelligence (AI) system component for healthcare. The system explains decisions made by deep learning networks analyzing images of skin lesions. The co-design of trustworthy AI developed here used a holistic approach rather than a static ethical checklist and required a multidisciplinary team of experts working with the AI designers and their managers. Ethical, legal, and technical issues potentially arising from the future use of the AI system were investigated. This paper is a first report on co-designing in the early design phase. Our results can also serve as guidance for other early-phase AI-similar tool developments.
AI will change many aspects of the world we live in, including the way corporations are governed. Many efficiencies and improvements are likely, but there are also potential dangers, including the threat of harmful impacts on third parties, discriminatory practices, data and privacy breaches, fraudulent practices and even ‘rogue AI’. To address these dangers, the EU published ‘The Expert Group’s Policy and Investment Recommendations for Trustworthy AI’ (the Guidelines). The Guidelines produce seven principles from its four foundational pillars of respect for human autonomy, prevention of harm, fairness, and explicability. If implemented by business, the impact on corporate governance will be substantial. Fundamental questions at the intersection of ethics and law are considered, but because the Guidelines only address the former without (much) reference to the latter, their practical application is challenging for business. Further, while they promote many positive corporate governance principles—including a stakeholder-oriented (‘human-centric’) corporate purpose and diversity, non-discrimination, and fairness—it is clear that their general nature leaves many questions and concerns unanswered. In this paper we examine the potential significance and impact of the Guidelines on selected corporate law and governance issues. We conclude that more specificity is needed in relation to how the principles therein will harmonise with company law rules and governance principles. However, despite their imperfections, until harder legislative instruments emerge, the Guidelines provide a useful starting point for directing businesses towards establishing trustworthy AI.
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