Matthew Griffin, described as “The Adviser behind the Advisers” and a “Young Kurzweil,” is the founder and CEO of the World Futures Forum and the 311 Institute, a global Futures and Deep Futures consultancy working between the dates of 2020 to 2070, and is an award winning futurist, and author of “Codex of the Future” series. Regularly featured in the global media, including AP, BBC, CNBC, Discovery, RT, and Viacom, Matthew’s ability to identify, track, and explain the impacts of hundreds of revolutionary emerging technologies on global culture, industry and society, is unparalleled. Recognised for the past six years as one of the world’s foremost futurists, innovation and strategy experts Matthew is an international speaker who helps governments, investors, multi-nationals and regulators around the world envision, build and lead an inclusive, sustainable future. A rare talent Matthew’s recent work includes mentoring Lunar XPrize teams, re-envisioning global education and training with the G20, and helping the world’s largest organisations envision and ideate the future of their products and services, industries, and countries. Matthew's clients include three Prime Ministers and several governments, including the G7, Accenture, Bain & Co, BCG, Credit Suisse, Dell EMC, Dentons, Deloitte, E&Y, GEMS, Huawei, JPMorgan Chase, KPMG, Lego, McKinsey, PWC, Qualcomm, SAP, Samsung, Sopra Steria, T-Mobile, and many more.
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.