The challenges of deploying artificial intelligence models in a rapidly evolving pandemic

The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2, emerged into a world being rapidly transformed by artificial intelligence (AI) based on big data, computational power and neural networks. The gaze of these networks has in recent years turned increasingly towards applications in healthcare. It was perhaps inevitable that COVID-19, a global disease propagating health and economic devastation, should capture the attention and resources of the world's computer scientists in academia and industry. The potential for AI to support the response to the pandemic has been proposed across a wide range of clinical and societal challenges, including disease forecasting, surveillance and antiviral drug discovery. This is likely to continue as the impact of the pandemic unfolds on the world's people, industries and economy but a surprising observation on the current pandemic has been the limited impact AI has had to date in the management of COVID-19. This correspondence focuses on exploring potential reasons behind the lack of successful adoption of AI models developed for COVID-19 diagnosis and prognosis, in front-line healthcare services. We highlight the moving clinical needs that models have had to address at different stages of the epidemic, and explain the importance of translating models to reflect local healthcare environments. We argue that both basic and applied research are essential to accelerate the potential of AI models, and this is particularly so during a rapidly evolving pandemic. This perspective on the response to COVID-19, may provide a glimpse into how the global scientific community should react to combat future disease outbreaks more effectively.Comment: Accepted in Nature Machine Intelligenc

AI reflections in 2020

We invited authors of selected Comments and Perspectives published in Nature Machine Intelligence in the latter half of 2019 and first half of 2020 to describe how their topic has developed, what their thoughts are about the challenges of 2020, and what they look forward to in 2021.Postprint (author's final draft

Crime in the time of the plague: fake news pandemic and the challenges to law-enforcement and intelligence community

The Paper explores the problem of fake news and disinformation campaigns in the turmoil era of the COVID-19 coronavirus pandemic. The Author addresses the problem from the perspective of Crime Science, identifying the actual and potential impact of fake news propagation on both the social fabric and the work of the law-enforcement and security services. The Author covers various vectors of disinformation campaigns and offers the overview of challenges associated with the use of deep fakes and the abuse of Artificial Intelligence, Machine-, Deep- and Reinforcement-Learning technologies. The Paper provides the outline of preventive strategies that might be used to mitigate the consequences of fake news proliferation, including the introduction of counter-narratives and the use of AI as countermeasure available to the law-enforcement and public safety agencies. The Author also highlights other threats and forms of crime leveraging the pandemic crisis. As the Paper deals with the current and rapidly evolving phenomenon, it is based on qualitative research and uses the most up-to-date, reliable open-source information, including the Web-based material

EXAMINING THE ADOPTION OF ARTIFICIAL INTELLIGENCE FOR DIGITAL TRANSFORMATIONS

Digital transformation (DT) is considered to be a core priority for organisations and a strategy to strengthen their survival. With a myriad of new and evolving digital capabilities to initiate a DT process, it is often unclear how multi-stakeholders engage in exploring and exploiting new digital technologies and capabilities such as artificial intelligence (AI) during the early adoption phase. This study adopts the theory of organisational ambidexterity to examine how a higher education institution (HEI) adopted AI as part of its DT strategy. Our findings indicate that although multi-stakeholders set out with a shared high-level common vision, at an operational-level tensions emerge around defining DT and AI, realising value from AI, and determining their success. We identified how such tensions can both help or hinder a DT process in the early adoption process and we present recommendations to overcome these. We also present avenues for future research around AI in DT

A new framework for global data regulation

Under the current regulatory framework for data protections, the protection of human rights writ large and the corresponding outcomes are regulated largely independently from the data and tools that both threaten those rights and are needed to protect them. This separation between tools and the outcomes they generate risks overregulation of the data and tools themselves when not linked to sensitive use cases. In parallel, separation risks under-regulation if the data can be collected and processed under a less-restrictive framework, but used to drive an outcome that requires additional sensitivity and restrictions. A new approach is needed to support differential protections based on the genuinely high-risk use cases within each sector. Here, we propose a regulatory framework designed to apply not to specific data or tools themselves, but to the outcomes and rights that are linked to the use of these data and tools in context. This framework is designed to recognize, address, and protect a broad range of human rights, including privacy, and suggests a more flexible approach to policy making that is aligned with current engineering tools and practices. We test this framework in the context of open banking and describe how current privacy-enhancing technologies and other engineering strategies can be applied in this context and that of contract tracing applications. This approach for data protection regulations more effectively builds on existing engineering tools and protects the wide range of human rights defined by legislation and constitutions around the globe.Comment: 15 pages, 2 figure