{"id":103063,"date":"2023-05-22T11:24:21","date_gmt":"2023-05-22T15:24:21","guid":{"rendered":"https:\/\/www.shortform.com\/blog\/?p=103063"},"modified":"2023-05-28T13:18:05","modified_gmt":"2023-05-28T17:18:05","slug":"you-cant-predict-the-future","status":"publish","type":"post","link":"https:\/\/www.shortform.com\/blog\/you-cant-predict-the-future\/","title":{"rendered":"The Top 3 Reasons Why You Can’t Predict the Future"},"content":{"rendered":"\n

Why is it hard to make predictions? How can you tell what the future has in store for you?<\/p>\n\n\n\n

According to The Signal and the Noise<\/em> by Nate Silver, prediction is an inherently challenging endeavor. He explores how insufficient information, system complexity, and the tendency of small errors to compound all limit the accuracy of predictions.<\/p>\n\n\n\n

Here’s why you can’t predict the future<\/a> and the challenges you’ll face when attempting to.<\/p>\n\n\n\n\n\n\n\n

1. We Often Lack Sufficient Information<\/strong><\/h2>\n\n\n\n

The first reason why you can’t predict the future is that you might be lacking sufficient information. To make good predictions, Silver says, you need information about the phenomenon you\u2019re trying to predict as well as a good understanding of how that phenomenon works<\/strong>. For example, today\u2019s meteorologists have abundant information about atmospheric conditions as well as a good understanding of the physical laws by which those conditions develop. Accordingly, Silver says, they can make reasonably accurate predictions about the weather. <\/p>\n\n\n\n

(Shortform note: Though Silver regards meteorology as a relatively successful field when it comes to predictions, some scientists suggest that climate change may have affected the accuracy of weather forecasts since The Signal and the Noise<\/em> was published in 2012. Specifically, one study suggests that shifting temperature patterns have made it harder to predict summer precipitation<\/a>\u2014which could in turn make it harder to predict catastrophic floods<\/a> such as those that afflicted large portions of Europe in 2021.)<\/p>\n\n\n\n

The problem is that in many situations, we don\u2019t have much useful data to go on<\/strong>. Silver illustrates this point by comparing meteorology to seismology, explaining that seismologists have no way to predict the timing, location, or strength of specific earthquakes. That\u2019s because earthquakes happen rarely and on a geological timescale, which makes it hard to discern any patterns that might be at play. And whereas meteorologists can directly observe atmospheric conditions, there\u2019s no way to measure factors such as the pressures currently at work on a given fault line nor to foresee future tectonic activity.<\/p>\n\n\n\n

(Shortform note: Seismology also highlights a related problem\u2014sometimes we\u2019re not even sure how to interpret the data<\/a> we do have because we don\u2019t have a sufficient theory<\/em> about how a given phenomenon works. For example, though geologists agree that earthquakes result from ruptures along tectonic fault lines, they\u2019re still not sure why some ruptures release energy more quickly (and dangerously) than others<\/a>. So even if we suddenly had much more information <\/em>about earthquakes and the forces that drive them, it might take a while to develop a workable theory that could turn that information into reliable predictions.)<\/p>\n\n\n\n

2. Many Systems Are Too Complex to Fully Understand<\/strong><\/h2>\n\n\n\n

Also, Silver argues that even when we have rich data and a good understanding of the underlying principles, many systems still defy accurate prediction because of their inherent complexity. Silver discusses economic forecasts\u2014which he says are notoriously unreliable\u2014to lay out several ways complex systems<\/a> hinder forecasting:<\/p>\n\n\n\n