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May release: COVID-19 repository

Posted by: , Posted on: - Categories: Artificial intelligence, Covid-19, Ethical innovation

One of the core building blocks of the CDEI’s COVID-19 response is our repository - a database for novel use-cases of artificial intelligence and data specifically being used to counter and mitigate the effects of COVID-19 around the world. The second release of the repository can be found here.

We will continue to update the repository on a regular basis, publishing an updated snapshot each month with any new use-cases that have been brought to our attention. To that end, we strongly encourage anyone who has visibility of developments we are yet to identify to contribute to the database. Further use-cases can be sent to, which will be monitored by members of the CDEI team. 

Key findings from the May repository

  • New use-cases continue to be broad in scope; from the deployment of machine learning (e.g. to recognise patterns in medical imaging and to enable insights from research papers), to the utilisation of novel data sources (e.g. online travel agency data to track the impact of COVID-19 on property rental markets).
  • The majority of our May use-cases relate to a pivot of existing AI or data activity to a new context, for example the development of an open-sourced COVID-19 vulnerability index which identifies people most at risk of severe complications. The index utilises an AI predictive model and is being used by healthcare organisations and insurance companies in the US to target assistive services. 
  • As expected, health and social care continues to dominate the sectoral composition of use-cases, but we are beginning to see growth in other sectors as they too adapt their activities in response to COVID-19. Within crime and justice, for example, cameras are being trialled in France that can detect face masks and therefore evaluate public adherence to government mandates.
  • A selection of the use-cases are relatively niche (e.g. the use of VR apps to facilitate virtual fieldtrips for teachers during lockdown), and thus the lifespan of such applications is uncertain. It is unclear whether demand will persist for these technologies post-COVID-19.
  • The speed and breadth of tech implementation varies across countries, with many of the May use-cases, allowing some exceptions, currently exhibiting low levels of adoption in the UK. 

Finally, the impact of AI and data-driven technology in mitigating the effects of the pandemic may still yet be overstated. Many of the most novel use-cases are either still being scoped or in the early stages of development, and so we cannot say how effective they will be moving forwards.

COVID-19 Repository - May 2020 (PDF) 

COVID-19 Repository - May 2020 (CSV)

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