Preprint Announcement – Guide to Regulating Medical AI

One year ago, I left the start-up where I had been working on an AI-driven companion to accompany patients through their cancer treatments.

When I left, I was deeply frustrated with the start-up environment surrounding AI in Healthcare. I was still convinced that AI could help in this space, but all I was seeing was teams going down what I considered to be the wrong paths.

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New article: My experience of the BIA Pulse accelerator

I wrote recently about my experiences of the Pulse leadership and entrepreneurship training program for the blog of the UK BioIndustry Association (BIA). The Pulse course is organised jointly by the BIA and the Francis Crick Institute. I joined the three-day course, in its first year of operation, in 2018.

I felt that I benefited enormously from the course. I had left my postdoc position 3 months previously and I was researching ideas for setting-up a company. I subsequently took my learnings from Pulse and elsewhere, and established my first company Simmunology. So when I was contacted earlier this year I was particularly keen to write something and say thanks.

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Managing People

I really love dealing with people. I come from a culture which highly prizes human interaction and communication skills. But I also love technical work, and this tends to attract people who prefer to work alone. In this article I want to discuss my progression through different styles of management and leadership throughout my life.

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Modelling the Modeller

Something I’ve struggled with on and off over the 20 years that I have been making mathematical models is explaining those models to others. I have tried to bring people along and develop their understanding. But mainly what I observed was that, some people just got it and others did not.

I have certainly improved my own skill at explaining. This comes down to having streamlined stories and simpler take-home messages. Telling a clearer story certainly improves my audiences’ self-satisfaction, but ultimately some of them get the whole message and others do not.

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Predictive Models

I have mentioned, in the past, that I am a huge fan of Nate Silver. Something which he used to repeat quite frequently, on their podcast, is a sort of predictive modelling tautology:

The best prediction of the future is no change.

Nate Silver [Paraphrasing]

This concept has even got a probabilistic and philosophical theory behind it. All other things being equal, over the long history of time, the next moment from now is not likely to be any different from right now. If we repeat this process often enough then we will be right more often than we are wrong. In essence, we are accepting that there is continuity (and perhaps causality) in our experience of the natural world. Political scientist David Runciman even explored the concept in his recent work of political theory.

I originally took this statement in the manner in which, I hope, it was intended. But behind every great phrase there is often an enticing problem. Thinking over this phrase has led me to realise that there are three basic types of predictive models and each one of them has a fundamentally different purpose and indeed parameterisation.

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Narrative and Decision Models

Since I managed to break my writers’ block on decision making models last week I want to follow-up with a brief discussion on the use of Narrative in presenting decision models to an audience.

In my first article on decision making models I emphasized that a model must serve a purpose. In explaining our models to others I want to highlight that there are two purposes behind explaining a model; the first is to convince the audience; the second is to convey insights into the model. This is the opposite ordering of how scientifically-trained modellers typically think about communicating results, but it is by far-and-away the prioritisation of most top scientific communicators around the world.

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