Abstract

This report summarises the findings of a series of workshops carried out by The Alan Turing Institute, the UK’s national institute for data science and artificial intelligence (AI), in late 2020 following the 'AI and data science in the age of COVID-19' conference. The aim of the workshops was to capture the successes and challenges experienced by the UK’s data science and AI community during the COVID-19 pandemic, and the community’s suggestions for how these challenges might be tackled.

Four key themes emerged from the workshops.

First, the community made many contributions to the UK’s response to the pandemic, via national organisations, research institutes and the healthcare sector. Researchers responded to the crisis with ingenuity and determination, and the result was a range of new projects and collaborations that informed the pandemic response and opened up new areas for future study.

Second, the single most consistent message across the workshops was the importance – and at times lack – of robust and timely data. Problems around data availability, access and standardisation spanned the entire spectrum of data science activity during the pandemic. The message was clear: better data would enable a better response.

Third, issues of inequality and exclusion related to data science and AI arose during the pandemic. These included concerns about inadequate representation of minority groups in data, and low engagement with these groups, which could bias research and policy decisions. Workshop participants also raised concerns about inequalities in the ease with which researchers could access data, and about a lack of diversity within the research community (and the potential impacts of this).

Fourth, communication difficulties surfaced. While there have been excellent examples of science communication throughout the pandemic, participants highlighted the challenges of communicating research findings and uncertainties to policy makers and the public in a timely, accurate and clear manner.

In this report, we outline the workshop participants’ reflections and suggestions relating to each of these themes, with the aim of enabling the data science and AI community to respond better to the ongoing pandemic, and future emergencies.

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