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Mental Models

Iatrogenics of Data

Frequent observation of data increases the noise-to-signal ratio, leading to overreaction and harmful interventions. This principle explains why too much information—from medical data to news—can be toxic and cause iatrogenic harm.

THE IDEA

If you want to accelerate someone’s death, give him a personal doctor. I don’t mean provide him with a bad doctor: just pay for him to choose his own. Any doctor will do.

This may be the only possible way to murder someone while staying squarely within the law. We can see from the tonsillectomy story that access to data increases intervention, causing us to behave like the neurotic fellow. Rory Sutherland signaled to me that someone with a personal doctor on staff should be particularly vulnerable to naive interventionism, hence iatrogenics; doctors need to justify their salaries and prove to themselves that they have a modicum of work ethic, something that “doing nothing” doesn’t satisfy. Indeed, Michael Jackson’s personal doctor has been sued for something equivalent to overintervention-to-stifle-antifragility (but it will take the law courts a while to become directly familiar with the concept). Did you ever wonder why heads of state and very rich people with access to all this medical care die just as easily as regular persons? Well, it looks like this is because of overmedication and excessive medical care.

Likewise, those in corporations or in policy making (like Fragilista Greenspan) who are endowed with a sophisticated data-gathering department and are therefore getting a lot of “timely” statistics are capable of overreacting and mistaking noise for information—Greenspan kept an eye on such fluctuations as the sales of vacuum cleaners in Cleveland to, as they say, “get a precise idea about where the economy is going,” and of course he micromanaged us into chaos.

In business and economic decision making, reliance on data causes severe side effects—data is now plentiful thanks to connectivity, and the proportion of spuriousness in the data increases as one gets more immersed in it. A very rarely discussed property of data: it is toxic in large quantities—even in moderate quantities.

The previous two chapters showed how you can use and take advantage of noise and randomness; but noise and randomness can also use and take advantage of you, particularly when totally unnatural, as with the data you get on the Web or through the media.

The more frequently you look at data, the more noise you are disproportionally likely to get (rather than the valuable part, called the signal); hence the higher the noise-to-signal ratio. And there is a confusion which is not psychological at all, but inherent in the data itself. Say you look at information on a yearly basis, for stock prices, or the fertilizer sales of your father-in-law’s factory, or inflation numbers in Vladivostok. Assume further that for what you are observing, at a yearly frequency, the ratio of signal to noise is about one to one (half noise, half signal)—this means that about half the changes are real improvements or degradations, the other half come from randomness. This ratio is what you get from yearly observations. But if you look at the very same data on a daily basis, the composition would change to 95 percent noise, 5 percent signal. And if you observe data on an hourly basis, as people immersed in the news and market price variations do, the split becomes 99.5 percent noise to 0.5 percent signal. That is two hundred times more noise than signal—which is why anyone who listens to news (except when very, very significant events take place) is one step below sucker.

Consider the iatrogenics of newspapers. They need to fill their pages every day with a set of news items—particularly those news items also dealt with by other newspapers. But to do things right, they ought to learn to keep silent in the absence of news of significance. Newspapers should be of two-line length on some days, two hundred pages on others—in proportion with the intensity of the signal. But of course they want to make money and need to sell us junk food. And junk food is iatrogenic.

There is a biological dimension to this story. I have been repeating that in a natural environment, a stressor is information. Too much information would thus be too much stress, exceeding the threshold of antifragility. In medicine, we are discovering the healing powers of fasting, as the avoidance of the hormonal rushes that come with the ingestion of food. Hormones convey information to the different parts of our system, and too much of them confuses our biology. Here again, as with news received at too high a frequency, too much information becomes harmful—daily news and sugar confuse our system in the same manner. And in Chapter 24 (on ethics) I will show how too much data (particularly when it is sterile) causes statistics to be completely meaningless.

Now let’s add the psychological to this: we are not made to understand the point, so we overreact emotionally to noise. The best solution is to only look at very large changes in data or conditions, never at small ones.

Just as we are not likely to mistake a bear for a stone (but likely to mistake a stone for a bear), it is almost impossible for someone rational, with a clear, uninfected mind, someone who is not drowning in data, to mistake a vital signal, one that matters for his survival, for noise—unless he is overanxious, oversensitive, and neurotic, hence distracted and confused by other messages. Significant signals have a way to reach you. In the tonsillectomies story, the best filter would have been to only consider the children who were very ill, those with periodically recurring throat inflammation.

When to use it

  • Investors: Check stock performance quarterly or annually instead of daily to avoid overreacting to short-term volatility.

  • Managers: Evaluate employee performance based on long-term trends rather than weekly fluctuations to reduce noise.

  • Media consumers: Limit news consumption to once a week or only for major events to avoid information toxicity.

  • Medical patients: Avoid unnecessary frequent checkups and tests; only seek medical attention when symptoms are significant.

FROM THEORY TO EVERYDAY LIFE

In practice

01

Personal Doctor and Overmedication

Giving someone a personal doctor can lead to overintervention and harm, as illustrated by Michael Jackson's death, where his personal doctor overmedicated him. The doctor's need to justify his salary and prove work ethic led to excessive treatment that stifled antifragility.

02

Greenspan's Reliance on Detailed Data

Alan Greenspan used detailed data like vacuum cleaner sales in Cleveland to gauge the economy, leading to overreaction and micromanagement that caused chaos. Mistaking noise for signal in policy-making can cause harm.

03

Tonsillectomy Filtering

In the tonsillectomy story, only very ill children (with periodically recurring throat inflammation) should have been considered for surgery. Filtering by severity reduces the noise of unnecessary interventions.

04

Yearly vs. Daily Data Observation

Observing stock prices yearly yields a 50% noise-to-signal ratio, but daily observation yields 95% noise, and hourly yields 99.5% noise. Frequent observation drowns out the real signal.

✳

A MOMENT TO REFLECT

Put it to work.

  1. How does the frequency of data observation affect your decisions in your field? Provide a specific example where you might have overreacted to noise.

  2. Think of a situation where you had access to a lot of data. Did you mistake noise for signal? How could you have filtered the information better?

  3. Why might having a personal doctor or constant monitoring be harmful, according to this concept? Can you apply this to other areas of life?

Connected ideas

Another lens can bring the same problem into focus.

Often confused with

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Source texts

  • Antifragile (Nassim Nicholas Taleb)
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