by In the false religion of data, heresy is asking for data that is not being collected because it might reveal unpalatably unprofitable realities. Here’s how every modern con starts: let’s look at the data. Every modern con starts with an earnest appeal to look at the data because the con artist has assembled the data to grease the slides of the con. We have been indoctrinated into a new and false religion, the faith of data. We’ve been relentlessly indoctrinated with the quasi-religious belief that “data doesn’t lie,” when the reality is that data consistently misleads us because that is the intent. Nobody in the False Religion of Data ever looks at what we don’t measure because that would uncover disruptive truths. My latest book Will You Be Richer or Poorer?:
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In the false religion of data, heresy is asking for data that is not being collected because it might reveal unpalatably unprofitable realities.
Here’s how every modern con starts: let’s look at the data. Every modern con starts with an earnest appeal to look at the data because the con artist has assembled the data to grease the slides of the con.
We have been indoctrinated into a new and false religion, the faith of data. We’ve been relentlessly indoctrinated with the quasi-religious belief that “data doesn’t lie,” when the reality is that data consistently misleads us because that is the intent.
Nobody in the False Religion of Data ever looks at what we don’t measure because that would uncover disruptive truths. My latest book Will You Be Richer or Poorer?: Profit, Power, and AI in a Traumatized World looks at everything consequential that we don’t measure, and since we don’t measure it, we assume it doesn’t exist. That’s the end-game of the False Religion of Data: what’s actually important isn’t measured and therefore it doesn’t exist, while what is measured is artfully packaged to support a narrative that enriches those behind the screen of “objective data-based science.”
The data-based con can be constructed in any number of ways. A few data points can be cleverly extrapolated to “prove” some self-serving claim, a bit of data can be conjured into a model that just so happens to support the most profitable policy option, inconvenient data points can be covertly deleted via “filtering out the outliers,” statistical trickery can be invoked (with a wave of this magic wand…) to declare semi-random data “statistically significant,” and so on, in an almost endless stream of tricks.
While the official statistics on inflation claim an annual rate of 2.5%, unmanipulated estimates (the Chapwood Index for example) find inflation is north of 10% in major U.S. urban areas.
The official data soothsayers’ bag of tricks include completely bogus, made-up “hedonic adjustments” which magically lower the price of real-world goods and services. Autos are supposedly “cheaper” now because they’re so much safer and reliable. Perhaps, but can we be honest and admit they cost a lot more than they did a generation ago?
The poor fools giving hundreds of millions of dollars to the con artists of Big Data Marketing apparently don’t understand the flimsiness of the “science.” As Mark, Jesse and I discuss in our latest Salon, Algorithmic Guerrilla Warfare, a few purposefully misleading data points turn the entire Big Data Marketing “science” into the familar “garbage in, garbage out.”
And so here we are in the midst of a pandemic, and the battles over “what the data tells us” sound more like religious wars than science. Everybody’s in such a hurry to conjure up a profitable con or make grandiose claims for their narrative that what we aren’t measuring is ignored.
Here’s the raw data I’d like to see collected:
- What percentage of people under the age of 50 who do not have chronic health conditions who test positive end up with severe symptoms that incapacitate them for weeks or months?
- What percentage of these younger, healthier people who exhibit severe symptoms have organ damage that doesn’t heal in a few months?
- What percentage of people who had antibodies for the virus end up coming down with the illness again a few months later?
Collecting this data is non-trivial, and so it may never be collected–partly because the results might not support the approved narratives: whatever data we don’t collect doesn’t exist and can’t disrupt our models, profit centers, narratives, policies, etc.
In the false religion of data, heresy is asking for data that is not being collected because it might reveal unpalatably unprofitable realities. Much safer to burn heretics at the stake than let them question the cons.
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