Artificial Intelligence against COVID-19: An Early Review

Introduction

COVID-19 disease, caused by the SARS-CoV-2 virus, was identified in December 2019 in China and declared a global pandemic by the WHO on 11 March 2020. Artificial Intelligence (AI) is a potentially powerful tool in the fight against the COVID-19 pandemic. AI can, for present purposes, be defined as Machine Learning (ML), Natural Language Processing (NLP), and Computer Vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction.

These functions can be useful to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. Since the outbreak of the pandemic, there has been a scramble to use and explore AI, and other data analytic tools, for these purposes. Hover over me for tooltip

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In this article, I provide an early review, discussing the actual and potential contribution of AI to the fight against COVID-19, as well as the current constraints on these contributions. It aims to draw quick take-aways from a fast expanding discussion and growing body of work, in order to serve as an input for rapid responses in research, policy and medical analysis.

The cost of the pandemic in terms of lives and economic damage will be terrible; at the time of writing, great uncertainty surrounded estimates ofjust how terrible, and of how successful both non-pharmaceutical and pharmaceutical responses can be. Improving AI, one of the most promising data analytic tools to have been developed over the past decade or so, so as to help reduce these uncertainties, is a worthwhile pursuit. Encouragingly, data scientists have taken up the challenge (which implies that the shelf-life of this paper is likely to be brief).

The key take-aways are as follows. I find that AI has not yet been impactful against COVID-19. Its use of AI is hampered by a lack of data, and by too much noisy and outlier data. Overcoming these constraints will require a careful balance between data privacy and public health concerns, and more rigorous human-AI interaction. It is unlikely that these will be addressed in time to be of much help during the present pandemic.

Instead, AI may “help with the next pandemic”. In the meantime, gathering diagnostic data on who is infectious will be essential to save lives and limiting the economic havoc due to containment.

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