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- Dykstra, Pearl, et al.
(författare)
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Improving pandemic preparedness and management : Lessons learned and ways forward : independent expert report
- 2020
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Epidemics and pandemics have shaped human history and will continue to do so. The COVID-19 crisis has shown that there is need to understand how Europe can ensure better management of and preparedness for them. This joint advice builds on lessons learned from the current and from previous pandemics. It analyses their complexity, drawing on insights from research and scholarship and taking Europeanvalues and respect for fundamental rights as critical orientation. It is developed jointly by the European Commission’s independent Group of Chief Scientific Advisors, the European Group on Ethics in Science and New Technologies (EGE) and Peter Piot, Special Advisor to the President of the European Commission on the response to COVID-19. Their recommendations include strengthened European and global solidarity and coordination in governance, research and community efforts to improve pandemic preparedness and management. This should address all aspects and causes of pandemics in their complex interplay, from biomedical and health to social and environmental ones. The advice covers efforts to prevent and pre-empt future pandemics; more coordinated response structures and mechanisms; the strengthening of essential systems, including healthcare, supply chains, public health, information and education; and protecting fundamental rights and social justice.
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- Zicari, Roberto V., et al.
(författare)
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On assessing trustworthy AI in healthcare : Machine learning as a supportive tool to recognize cardiac arrest in emergency calls
- 2021
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Ingår i: Frontiers in Human Dynamics. - : Frontiers Media S.A.. - 2673-2726. ; 3
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Tidskriftsartikel (refereegranskat)abstract
- 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.
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