An article about how, supression prediction works, and how we can use it to protect ourselves. 


Before we start there's a subject I would like to  talk about the deffenition of today's subject: Prediction Supression according to the dictonary those two words mean the next two things. 

suppression

the act of ending something by force:

brutal police suppression of the riots

prediction

B2a statement about what you think will happen in the future:

Combinded  these words roughly mean the act of preventing a statement what you think will happen in the future. 

Now imagine, the following scenario:

You are about 8 years old and, are playing with a group of friends, for a school project you are asked to make a drawing about what you all think will happen at the next school trip. 

So you start to draw but, then one of your friends decide that you are not allowed to use the red crayon and, hide it. Even when with this crayon the picture you as a group will draw will become more accurate and, can add important detail. 

Now your friend hides this crayon for a couple of reasons. Which is not because, they forgot it our because, it is broken. No. It's because when it used it will reveal something disliked. Something scary our embaressing. That shows someone getting hurt because, without the colour red the colour of blood seems less worse. It can hide that someone was hurt our make someone powerful look bad. The red crayon can be used to X out and, write failure showing the plan was flawed. 

But, when you try to point this out your friend says: "I don't know, it's a stupid assigment, predicting the future is hard". 

This is exactly what prediction supression is. 

And it's important to us all because, it's important information that can influence important events our outcomes yet, be held back because it's socially forbiden. 

Now imagine, the drawing is done, and you give it to your teacher, then the school trip happens but, you all end up getting an F because, the picture left out and important part that could have been drawn with the red crayon. 

The teacher then asks: Why did it end up badly? 
Then one of your friends point out: The red crayon wasn't allowed. 
And, suddently the picture makes sense. 
The rainbow now has all it colours intact. 
The prediction was always obvious from the start, the bad outcome was obvious. 

You look around in your group and, everyone looks uncomfortable and, you realize they all knew the red crayon did belong when we where drawing the picture. They choice not to know, because no one wanted to be the rat, no one wanted to be uncomfortable. 


And why we can fix it later was a lie.


In the last 10 years the City of New York has dealt with several crisises and, the city goverment has taken several initatives. Only to fail in less then 3 years of time. 
Each time the newspapers wrote simulair lines. Something in the trend like: "This couldn't been forseen, unprecedent, unpredictable"
 

For example some of the articles I was talking about: (See sources)

CityTime payroll scandal
Early warnings vissible:
Early delays, missed milestones, officials framed it as "Unforseen Complexity
Citi Bike Service Expansion
Early warnings vissible:
Logical gaps and, software issues where downplayed to protect the public image
Stop and Risk Reform Programs
Early warnings vissible:
Early risk where documented, but where framed as "Novelty challenges"
NYC Public Housing Renovation Program
Early warnings vissible:
Budget cuts and, staffing shortages but, where ignored to keep the public image

Outside of NYC: Quaside/The sidewalk labs 
Early warnings vissible:
Early warning signs ignored. Framed as "Novelty"

All of them showing early warning signs, all of them ignored. Showing the working of Prediction Supression in it's working.

The connection to Base-Rate Blindness our Red Crayon: 

Study shows that: 75–80% of public-sector transformation our IT projects end up in failure. The examples from NYC proven that this is true as their failures could have been prevented. By not ignoring the early warning signs. 

If we look at the overal numbers and data it shows that the failure rate has a huge overlap with the data above. 

CityTime payroll scandal
Complexity: Large IT model accors several agencies
Outcome: Fraud, cost overun, no intervention
Connection: Matches the IT failure rate 80%

Citi Bike Service Expansion
Complexity: Mobility Tech
Outcome: Maintaince and docking issues. 
Connection: Fit's public-sector and, tech failure rates

Stop and Risk Reform Programs
Complexity: Policy implentation across large scale
Outcome: Violations, several of them. 
Connection: Matches social program rates 75%

NYC Public Housing Renovation Program
Complexity: Urban infrastructure/Housing
Outcome: Delays, underfunding and incomplete work
Connection:  Fit's the failure rate 75%

In every one of the above cases, reputational pressure just like, in our kids group was precedent and, visable. Ignored to protect public PR, safe face. 

The maths: 


If we use the next formula: $Success=1-BaseFailureRate\times e-k\cdot EarlyAction\times (1-ReputationalPressure)$

In where we use 80% as an early warning and,  reputational constrain, we will be able to predicte the failure rate. 

Conclusion
As shown the data was there, the social insenstives too, and yet instutitions around, you keep acting as if they don't know. 
If you want to know, the future and, what will happen next, pay attention to the variables, you where told not to count. 


Sources: 
Words: 
https://dictionary.cambridge.org/dictionary/english/prediction
https://dictionary.cambridge.org/dictionary/english/suppression

Failed projects: 
https://en.wikipedia.org/wiki/CityTime_payroll_scandal
https://www.crainsnewyork.com/transportation/citi-bike-service-unreliable-low-income-neighborhoods-nyc-comptroller-report
https://gothamist.com/news/nypd-says-plan-to-monitor-14th-amendment-stop-and-frisk-violations-is-finally-a-priority
https://nysfocus.com/2025/04/02/nypd-stop-and-frisk-eric-adams
https://www.thecity.nyc/newsletter/new-adams-twist-final-nycha-monitor-report-climate-law-failure
https://nyc.streetsblog.org/2023/12/28/2023-in-review-here-are-the-years-biggest-livable-streets-failures
https://www.thecity.nyc/2024/03/20/nycha-monitor-public-housing-management

https://www.mckinsey.com/industries/public-sector/our-insights/unlocking-the-potential-of-public-sector-it-project