Research

A socio-technical framework for digital contact tracing

A socio-technical framework for digital contact tracing

In their efforts to tackle the COVID-19 crisis, decision makers are considering the development and use of smartphone applications for contact tracing. Even though these applications differ in technology and methods, there is an increasing concern about their implications for privacy and human rights. Here we propose a framework to evaluate their suitability in terms of impact on the users, employed technology and governance methods.

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#Standards4Quantum: Making Quantum Technology Ready for Industry

#Standards4Quantum: Making Quantum Technology Ready for Industry

The Joint Research Center (JRC) in cooperation with the European Committee for Standardization (CEN) and the European Committee for Electrotechnical Standardization (CENELEC), European Commission’s Directorate General Communications Networks, Content and Technology (DG CNECT), and the German Institute of Standardisation (DIN), organised in Brussels on 28-29 March 2019 the Putting-Science-Into-Standards (PSIS) workshop on Quantum Technologies.

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Artificial Intelligence and Machine Learning in Software as a Medical Device: discussion Paper and Request for Feedback

Artificial Intelligence and Machine Learning in Software as a Medical Device: discussion Paper and Request for Feedback

Artificial intelligence and machine learning technologies have the potential to transform health care by deriving new and important insights from the vast amount of data generated during the delivery of health care every day. Medical device manufacturers are using these technologies to innovate their products to better assist health care providers and improve patient care. The FDA is considering a total product lifecycle-based regulatory framework for these technologies.

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The need for a system view to regulate artificial intelligence/machine learning-based software as medical device

The need for a system view to regulate artificial intelligence/machine learning-based software as medical device

FDA need to widen their scope from evaluating medical AI/ML-based products to assessing systems. This shift in perspective—from a product view to a system view—is central to maximizing the safety and efficacy of AI/ML in health care, but it also poses significant challenges for agencies like the FDA who are used to regulating products, not systems. We offer several suggestions for regulators to make this challenging but important transition

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When Autonomous Vehicles Are Hacked, Who Is Liable?

When Autonomous Vehicles Are Hacked, Who Is Liable?

Who might face civil liability if autonomous vehicles (AVs) are hacked to steal data or inflict mayhem, injuries, and damage? How will the civil justice and insurance systems adjust to handle such claims? RAND researchers addressed these questions to help those in the automotive, technology, legal, and insurance industries prepare for the shifting roles and responsibilities that the era of AVs may bring.

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ICT security certification opportunities in the healthcare sector

ICT security certification opportunities in the healthcare sector

Digital solutions for healthcare open a plethora of new possibilities in this area. They provide a technical base for easy testing, they improve significantly the quality of service by allowing immediate access to medical data – results of tests, history of treatment; they facilitate correct diagnosis by easier analytics and correlation of data and easier monitoring of patients’ health parameters. They facilitate setting up appointments with appropriate doctors at a convenient time

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