Why the event-oriented structure of news doesn't help in understanding how the world works
In 2020, I significantly reduced the proportion of daily news consumption in my information diet. And I strongly recommend the same to others: less of news and more of books. There are many reasons why, and I will list them in a future post. Here is one compelling argument from the book Thinking in Systems (by Donella H. Meadows) about the fundamental limitation of incremental news stories:
Systems fool us by presenting themselves—or we fool ourselves by seeing the world—as a series of events. The daily news tells of elections, battles, political agreements, disasters, stock market booms or busts. Much of our ordinary conversation is about specific happenings at specific times and places. A team wins. A river floods. The Dow Jones Industrial Average hits 10,000. Oil is discovered. A forest is cut. Events are the outputs, moment by moment, from the black box of the system.
Events can be spectacular: crashes, assassinations, great victories, terrible tragedies. They hook our emotions. Although we’ve seen many thousands of them on our TV screens or the front page of the paper, each one is different enough from the last to keep us fascinated (just as we never lose our fascination with the chaotic twists and turns of the weather). It’s endlessly engrossing to take in the world as a series of events, and constantly surprising because that way of seeing the world has almost no predictive or explanatory value. Like the tip of an iceberg rising above the water, events are the most visible aspect of a larger complex—but not always the most important.
We are less likely to be surprised if we can see how events accumulate into dynamic patterns of behavior. The team is on a winning streak. The variance of the river is increasing, with higher floodwaters during rains and lower flows during droughts. The Dow has been trending up for two years. Discoveries of oil are becoming less frequent. The felling of forests is happening at an ever-increasing rate. The behavior of a system is its performance over time—its growth, stagnation, decline, oscillation, randomness, or evolution.
If the news did a better job of putting events into historical context, we would have better behavior-level understanding, which is deeper than event-level understanding. When a systems thinker encounters a problem, the first thing he or she does is look for data, time graphs, the history of the system. That’s because long-term behavior provides clues to the underlying system structure. And structure is the key to understanding not just what is happening, but why.
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