# AI, Data Science and the Covid19 Pandemic

The Stokes Society, Pembroke College

There are three types of lies: lies, damned lies and statistics

??

There are three types of lies: lies, damned lies and statistics

Benjamin Disraeli

There are three types of lies: lies, damned lies and statistics

Benjamin Disraeli 1804-1881

There are three types of lies: lies, damned lies and ‘big data’

Neil Lawrence 1972-?

## Embodiment Factors

Table: The embodiment factor is the ratio of compute to communicate in the model.

 compute $\approx 100 \text{ gigaflops}$ $\approx 16 \text{ petaflops}$ communicate $1 \text{ gigbit/s}$ $100 \text{ bit/s}$ (compute/communicate) $10^{4}$ $10^{14}$

## DELVE Overview

DELVE will contribute data driven analysis to complement the evidence base informing the UK’s strategic response, by:

• Analysing national and international data to determine the effect of different measures and strategies on a range of public health, social and economic outcomes
• Using emerging sources of data as new evidence from the unfolding pandemic comes to light
• Ensuring that the work of this group is coordinated with others and communicated as necessary both nationally and internationally

## Delve Timeline

• First contact 3rd April
• First meeting 7th April
• First working group 16th April

## Data at the Heart

• Use data to answer policy questions.
• Make international comparisons for input.
• Challenges: around getting data.

## What is Machine Learning?

$\text{data} + \text{model} \stackrel{\text{compute}}{\rightarrow} \text{prediction}$

• We collect more data, but we understand less.

## Wood or Tree

• Add complexity to the model to make it realistic.
• Move model “beyond human intuition”
• But model still falls well short of mark in terms of representing reality

## Increasing Need for Human Judgment

The domain of human judgment is increasing.

How these firms use knowledge. How do they generate ideas?

## Data as a Convener

• Data allows externalisation of cognition.
• Even when not existing, can ask: What data would we want?

## Delve Reports

1. Facemasks 4th May 2020 (The DELVE Initiative, 2020a)
2. Test, Trace, Isolate 27th May 2020 (The DELVE Initiative, 2020b)
3. Nosocomial Infections 6th July 2020 (The DELVE Initiative, 2020c)
4. Schools 24th July 2020 (The DELVE Initiative, 2020d)
5. Economics 14th August 2020 (The DELVE Initiative, 2020e)
6. Vaccines 1st October 2020 (The DELVE Initiative, 2020f)
7. Data 24th November 2020 (The DELVE Initiative, 2020g)

## Delve Data Report

• Surveillance data situation.
• REACT Study (Imperial)
• ONS Coronavirus (COVID-19) Infection Survey
• RECOVERY Trial (Dexamethasone)
• Happenstance data.
• Our report’s focus (The DELVE Initiative, 2020g)

## Delve Data Report: Recommendations

• Update statutory objective of ONS to accommodate happenstance data.
• ONS and ICO to collaborate on data driving license to standardise access processes.
• Nowcasting of economic metrics
• Movement of populations (mobile phone data).

## Conclusions

• Bandwidth constraints of humans
• DELVE Data Report Recommendations

## References

Lawrence, N.D., 2017. Living together: Mind and machine intelligence. arXiv.
The DELVE Initiative, 2020g. Data readiness: Lessons from an emergency. The Royal Society.
The DELVE Initiative, 2020e. Economic aspects of the COVID-19 crisis in the UK. The Royal Society.
The DELVE Initiative, 2020a. Face masks for the general public. The Royal Society.
The DELVE Initiative, 2020c. Scoping report on hospital and health care acquisition of COVID-19 and its control. The Royal Society.
The DELVE Initiative, 2020d. Balancing the risks of pupils returning to schools. The Royal Society.
The DELVE Initiative, 2020b. Test, trace, isolate. The Royal Society.
The DELVE Initiative, 2020f. SARS-CoV-2 vaccine development & implementation; scenarios, options, key decisions. The Royal Society.