AI "Accurately" Predicts Your Death

If you’re looking for an incredible example of journalists over-hyping the capabilities of AI (sometimes referred to by it’s synonym of  “Big Data”), you need look no further than this article talking about AI predicting death “Accurately.” 

You can rest assured that a bunch of geeks in a lab somewhere haven’t used a computer to crack the code of time and space. And no, it can’t tell you with certainty whether or not you’re going to die next Tuesday at 3:52pm local time. Dissecting this one takes some critical thinking and it helps if you have some experience with predictive analytics. 

First of all, the writer/editor are having a bit of fun here being somewhat loose with the definition of the word “accurately.” Webster defines accurate as “Free from error or defect; Consistent with a standard, rule, or model; precise; exact.”  The definition is vague, because the same word can be used to mean either “perfect” or “right more than half the time.” When you deal with predictive analytics on a large scale, the results are almost never perfect. Hence, the article may be guilty of using the accurate to mean “right more than half the time", but gleaning disproportionate amounts of attention and web traffic from people who read accurate to mean nearly “perfect."

A second convenient detail about the article is the nature of the prediction. Given enough time, there's a 100% probability that everyone alive today will die. So if I build a model to predict death, I can cheat and always predict “Yes, you will die” and I’ll be right… eventually.

Once the hype is peeled back a bit, you can look at what the article is really saying and make a strong case that this is really nothing new. Actuaries  (a.k.a. “Data Scientists”) have known for decades (centuries?) that while you can’t predict specifically what will happen with any one person, you can make reasonable assumptions for a group of people. It’s effectively an example of the Central Limit Theorem, one of the core principles underpinning modern statistics. In fact, the math has long been accurate enough to underpin some very valuable companies that sell life insurance. 

Mark Twain famously said that "there are three kinds of lies: lies, damn lies, and statistics.” This article feels like yet another example of how slight tweaking of definitions and statistical models can really go a long way toward distorting reality.