Since March 2020, the CDEI has been monitoring the use of AI and data-driven technology in the UK’s COVID-19 response through two distinct lenses. Firstly, through our COVID-19 repository, which is a database for novel use-cases of artificial intelligence and data specifically being used to counter and mitigate the effects of COVID-19. Secondly, through survey research, to understand what the public has made of this use of technology during the crisis. Have they supported the innovations captured in our repository? Have they felt that technology has been used well and in a timely manner? Do they believe there has been sufficient oversight of its deployment?
This blog provides an overview of our COVID-19 retrospective, highlighting key findings from our COVID-19 repository and survey research, as well as detailing next steps.
COVID-19 repository: What did we find?
The aim of the COVID-19 repository was to highlight innovations that were yet to be fully explored, encouraging researchers, the media, and policymakers to widen the scope of their analysis and pay attention to lesser known use-cases. While public attention largely centred on the roll out of high profile use-cases such as contact tracing apps, our research highlights the breadth of applications aimed at suppressing the virus and coping with its effects.
From the piloting of drones that delivered medical supplies to remote regions, to the creation of health equipment databases that monitored the availability of assets in the NHS, the private and public sectors alike have tested a wide range of data-driven interventions in the last 12 months. This technology has not only been used to combat the immediate public health crisis, it has also been deployed to mitigate the wider effects of lockdown.
Some of the data-driven innovations were to be expected, and a few of the themes that transpired were predicted as the pandemic unfolded at the start of 2020 - notably the central role that artificial intelligence would play in the discovery of vaccines and treatments for COVID-19. However, other themes were more surprising, such as the fact that, aside from in a healthcare setting, artificial intelligence did not play the outsized role many thought it would in relief efforts.
The 10 core themes that emerged from the COVID-19 repository were:
- Conventional data analysis has been at the heart of the COVID-19 response, not AI
- Existing datasets provided the basis for much of the pandemic response
- New methods of data storage were implemented to enable data sharing
- In the face of a public health crisis, community data sharing increased
- Local governments increasingly realised the importance and value of data
- Where AI is prevalent, it is often being used in a healthcare setting
- Many existing tools have been repurposed to solve COVID-19 related problems
- Data-driven tools are also being used to measure and understand the effects of new rules
- The focus is beginning to shift towards building future resilience
- Data sharing across borders facilitated the discovery of new vaccines and treatments
In the report, we’ve highlighted some of the use-cases that underpin these themes. Three case studies also provide a deeper look at some of the data-driven innovation we’ve seen across local government, the health sector, and public transport.
Survey research: What did we find?
By repeating a survey every month for six months, we have a unique longitudinal dataset of over 12,000 individuals, allowing us to see to what extent public attitudes changed over a period of six months as the UK’s COVID-19 response has evolved. We found significant public support for the use of data-driven technology to tackle the pandemic. Almost three quarters (72%) of the UK population felt that digital technology had the potential to be used in the response to the COVID-19 outbreak. This sentiment was shared by all demographic groups and was consistent over the 6-month period.
A majority of the public also showed support, in principle, for a number of specific use-cases taken from CDEI’s COVID-19 repository. These were used to test whether public attitudes towards applied hypothetical real world examples of data-driven technology echoed attitudes based on abstract statements about data-driven technologies. This includes technologies that have not been widely adopted, such as wearable technology to aid social distancing in the workplace.
However, many respondents also felt that the potential of data-driven technology was not being fully realised. Fewer than half (42%) said digital technology was making the situation in the UK better (although only 7% claimed it was making matters worse). This points to an “opportunity gap” - a chasm between technology’s potential and the perceived reality of how it has been applied.
Another key finding was the link between trust in governance and support for the use of data-driven technology in the UK’s COVID-19 response. When controlling for all other variables, we found that trust in the governance of technology is the single biggest predictor of whether someone believes that digital technology has a role to play in the COVID-19 response. This trust in governance was substantially more predictive than attitudinal variables such as people's level of concern about the pandemic, or belief that the technology would be effective; and demographic variables such as age and education.
While a reasonable proportion of the public (43%) trust that the right rules and regulations are in place to ensure that digital technology is used responsibly in the UK’s COVID-19 response, nearly a quarter (24%) disagree with the statement. This analysis suggests the critical importance of building and maintaining trustworthy governance, and ensuring this governance works for all citizens. When asked whether they would know where to raise their concerns if they felt this governance was failing, 39% of younger people would know where to raise these complaints. This falls to just 14% for older people. For younger people, 40% agreed with the statement ‘I feel well informed about how digital technology has been used during the crisis’. Only 22% of those aged 55+ agreed with the same statement.
What happens next?
It will take time to properly evaluate the impact of the initiatives documented in our COVID-19 retrospective, and as such we have deliberately chosen not to make an overall assessment of success or failure. Although we are highlighting positive aspects of the trends we have seen, that is not to say there aren’t lessons to be learnt.
We recommend that further research is taken into individual use-cases to assess their full impact, as well as the ethical implications associated with adoption, not least to help decision-makers determine which should be sustained in the wake of the pandemic, and which should be phased out. Use-cases that were acceptable during a national crisis may not be in its aftermath. Moreover, although we saw unprecedented innovation at pace in the last 12 months, we were also reminded of the many barriers to sharing data in a timely manner across sectors and organisations. Understanding how these barriers manifested during the pandemic and the limitations they created will be central to increasing cross-sector collaboration moving forwards.
The overall picture presented by our polling is one of a public that is largely sympathetic, and in some cases enthusiastic, about the idea of AI and data being used to tackle the pandemic. But that this has been in spite of, rather than because of, the way the technology has been deployed in different contexts. This suggests that public support is tenuous and dependent on trust in the governance of technology.
For organisations and policymakers looking to realise the benefits of greater data use, it will be important to build data governance mechanisms that are capable of building long-term trust. The CDEI’s Trust Matrix, designed to drive forward trustworthy data sharing in the public interest, is a helpful starting point for organisations that are looking to up their governance game. The CDEI is committed to playing its part in developing and refining governance approaches.
The raw data, which we collected when conducting our survey research, is available here, should you wish to explore the dataset in more detail. If you would like to have any follow up conversations on the data or our analysis, please get in touch at email@example.com.
Our COVID-19 repository has now been archived and we will no longer be publishing updates. We would like to thank all those organisations who have contributed to the repository over the last 12 months. For more information about our COVID-19 repository or the CDEI’s work more broadly, please get in touch at firstname.lastname@example.org.
About the CDEI
The CDEI was set up by the government in 2018 to advise on the governance of AI and data-driven technology. We are led by an independent Board of experts from across industry, civil society, academia and government. Publications from the CDEI do not represent government policy or advice.