Matthew Griffin, award winning Futurist and Founder of the 311 Institute is described as "The Adviser behind the Advisers." Recognised for the past five years as one of the world's foremost futurists, innovation and strategy experts Matthew is an author, entrepreneur international speaker who helps investors, multi-nationals, regulators and sovereign governments around the world envision, build and lead the future. Today, asides from being a member of Centrica's prestigious Technology and Innovation Committee and mentoring XPrize teams, Matthew's accomplishments, among others, include playing the lead role in helping the world's largest smartphone manufacturers ideate the next five generations of mobile devices, and what comes beyond, and helping the world's largest high tech semiconductor manufacturers envision the next twenty years of intelligent machines. Matthew's clients include Accenture, Bain & Co, Bank of America, Blackrock, Bloomberg, Booz Allen Hamilton, Boston Consulting Group, Dell EMC, Dentons, Deloitte, Deutsche Bank, Du Pont, E&Y, Fidelity, Goldman Sachs, HPE, Huawei, JP Morgan Chase, KPMG, Lloyds Banking Group, McKinsey & Co, Monsanto, PWC, Qualcomm, Rolls Royce, SAP, Samsung, Schroeder's, Sequoia Capital, Sopra Steria, UBS, the UK's HM Treasury, the USAF and many others.
WHY THIS MATTERS IN BRIEF
How long you have left to live is determined by a whole range of factors and scientists in Australia are trying to work backwards from death to use AI to predict when you’ll die, and so far the results are impressive.
Scientists, data scientists that is, from the University of Adelaide in Australia have announced that they have managed to build an Artificial Intelligence (AI) that can predict when people are going to die, and it’s 70 percent accurate, but unlike the AI’s I’ve talked about before that can predict how long people who have had heart attacks have left to live, more accurately than human doctors, this one is different – it can predict when you’re going to die irrespective of the state of your current health because it uses deep learning to analyse a range of different scans, such as CT scans, to search for the signs, and assess the severity of, heart disease, cancer, and other diseases.
For example, look at it this way – if I asked you how long you thought you were going to live, and you exercised every day, had the perfect diet and had no history of hereditary diseases in your family’s lineage then it’s likely you’d be able to tell me, with some degree of confidence, that your chances of living beyond eighty years old were good. On the other hand though, if you never exercised, had an awful diet of alcohol, lard and sugar, and your family had a history of hereditary diseases then you might tell me that the chances of you living beyond eighty could be slim.
See, in one fell swoop you’ve assessed the state of your overall health, roughly assessed the risk factors in your head and calculated the rough odds of how long you think you have left to live. And that’s what this AI is being trained to do, except for the fact that rather than relying on gut instinct it’s analysing real time scans and correlating the patterns it’s seeing against a huge dataset of patient information.
The team responsible for the new AI believe it could revolutionise healthcare and act as an early health warning system. They used a dataset of historical CT scans, and excluding other predictive factors like age, the system was able to predict whether patients would die within five years with a 70 percent accuracy rate. The work was described in an article published in the journal Scientific Reports.
“The goal of the research isn’t really to predict death, but to produce a more accurate measurement of health,” said Dr. Luke Oakden-Rayner, a researcher on the project, “a patient’s risk of death is directly related to the health of their organs and tissues, but the physiological changes associated with chronic diseases often build up for decades before we see the final, sometimes fatal, symptoms. By the time we recognise a disease is present it’s often quite advanced. So we can take a known outcome, like death, and look back in time at the patient’s medical scans to find patterns that relate to undetected disease. Our goal is to identify these changes earlier and more accurately so we can tailor our treatment to individuals.”
At present, this is still a proof of concept experiment, however, and Oakden-Rayner points out that there’s a lot more work to be done before this becomes the transformative clinical tool it could be. For one thing, the AI’s 70 percent predictive accuracy when looking at scans is in line with the “manual” predictions made by experts, and at worst that makes it a good time saving tool, or a good second opinion, but the hope is that it can one day be much more than that.
“Our next major step is to expand our dataset,” continues Oakden-Rayner, “we used a very small cohort of 48 patients in this initial study to show that our approach can work, but in general deep learning works better if you can give it much more data. We’ll be collecting and analysing a dataset of tens of thousands of cases in the next stage of our project and expanding the range of diseases and conditions it looks for.”
So can an AI really predict when you’ll die? Well, if it detects the early stages of cancer, or other chronic diseases then maybe, but that said I still doubt whether it can predict you being hit by a bus. Heaven forbid.