a day ago
What I learnt … from the dangers of bad data
Ben Warner, 38, is the co-founder of Electric Twin, which creates synthetic populations to give instant results to survey questions for businesses. He gained his physics PhD from University College London in 2013, before becoming a research fellow. In 2015 he joined Faculty, a data science and AI consultancy co-founded in 2014 by his brother, Marc Warner. He was also a key figure in the modelling program used by Vote Leave's EU referendum campaign in 2016, and in the 2019 election, his model predicted that the Conservatives would win, off by only one seat. Warner joined No 10 in 2019 before holding a central role in data predictions for Covid. He launched Electric Twin in 2023 after his experiences during the pandemic highlighted a gap in the market for data modelling.
I joined No 10 in late 2019. In early 2020, Covid struck. At that point in time, we really needed to understand how people were going to behave, what policies were going to be important.
When we were trying to make the decisions in Covid, we tried our best to get the best possible data, the best possible information. But fundamentally, the tools and the systems didn't exist to actually do that, which meant that although we were trying our hardest, we obviously made decisions that weren't good enough.
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When it came down to it, in March 2020, we were sitting in the prime minister's office and slowly walking through that our current plan meant that the NHS would be overrun. That tens or hundreds of thousands of people might needlessly lose their lives.
The tool we did that with was the whiteboard. Given all the modern technology, all the AI that exists in the world, I just felt there had to be a better way to solve these problems. Since leaving No 10, I've been thinking about it and I think Electric Twin is the way to do that.
The prime minister [during Covid], was reliant on essentially the educated guesswork of lots of people. The data being run at him was saying 'if we flatten the sombrero', as was said, 'we can pass through'. And actually, that was wrong. If we flattened the sombrero, the NHS would still be overrun, we'd still not have the beds in intensive care that we needed for people who have heart attacks, etc. So it's a combination of the data and the modelling all together and it comes down to that decision making.
Lots of companies in the world today are reliant on that guesswork. The idea of Electric Twin is that companies aren't reliant on that guesswork. They can quickly get the answers to the questions that they want, so that they can make better decisions. Rather than having to sit there with a pencil and paper, or trying to draw it out in their head, they can actually use a top-level system that uses the world's best AI to put it together and make a more substantive estimate of what's going to occur and be able to test different courses of action before they make a decision. So that decision will be better.
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We spent six months making sure that our experimental engine is the cutting edge of this type of work. We spent a lot of time validating to demonstrate to customers that our accuracy is 95 per cent.
We use large language models that are trained on the entirety of the internet to co-create synthetic populations with our companies. Most of the internet is not people talking about how to code or how to write a business report. It's people talking about their thoughts, their beliefs, their reactions to different things. So the large language model can represent some areas of that human experience.
Then what we do at Electric Twin is we make sure that the output is reflective of the audience and the population that we're trying to model, so that decision-makers and business people have these tools they can really trust and rely on.
It's all about trying to make sure that we deliver value to that business and allow them to make sure that they can get accurate answers in five, ten seconds to address their business problem. Whether that's being able to understand their current audience that they're trying to build a better product for, or starting to build out a new proposition for maybe an audience that they're not so used to seeing.
At the moment, we don't have any policymakers using the tool. We're already helping companies, and we could help governments make better decisions for people.
I think a lot of the wrong decisions we make are avoidable — avoidable if we truly understand the people they affect. Too often, we talk past each other without understanding someone's lived experience. Electric Twin helps close that gap — it lets you test ideas quickly, with a deeper understanding of real people. Ultimately, when you make more informed decisions, you can create better outcomes.
Ben Warner was talking to Niamh Curran, reporter at the Times Entrepreneurs Network
