That was fake news:
In May 2020, Jones was terminated from her position managing the team that created Florida's ArcGIS COVID-19 dashboard after being repeatedly reprimanded for sharing the department's work online without authorization. Jones alleged instead that she was told to manipulate the dashboard's data and that her firing was retaliation for her refusal. The OIG exonerated state health officials, finding her allegations to be unsubstantiated and unfounded. Jones later posted on social media a forgery of the dismissal letter from the Florida Commission on Human Relations, such that it appeared that her complaint had been validated.
In December 2022, she signed a deferred prosecution agreement admitting guilt to unauthorized use of the state's emergency alert system on November 10, 2020, which resulted in her home being searched under warrant by state police in December 2020. The execution of the warrant with armed police, widely referred to as a raid, was due to a 2016 battery charge against Jones by the Louisiana State University police. In 2023, Jones pled no-contest to a 2019 charge of cyberstalking a former Florida State University student. She was fired from both institutions.
When all they see is it being used to push narratives, they'd rather not have it at all.
Also, "There Are Three Kinds of Lies: Lies, Damned Lies, and Statistics" dates to the 1800s. This is nothing new.
That quote is solely used to add thin validation to simply rejecting critical consideration of every evidence.
Statistics are, first and foremost, a set of techniques for summarizing and simplifying data by reducing a large amount of raw facts to a few easily grasped parameters. They can be very powerful when used for good (e.g. to help you answer your own questions about the data) but that very power can even more readily be abused for evil when they are used to persuade others. This is what the quote refers to. Statistics are a powerful way to lie. That's what it says, and it is true.
Examples: p-hacking, Anscombe's quartet, all manner of chart crimes, the numerology of quants (there's some magical thinking for you), the isolated, uncontextualized "significant numbers" so loved by journalists, etc.
As for your claim that it is "solely used to add thin validation to simply rejecting critical consideration of every evidence"... do you have anything to back that up? Note that as worded it is clearly false, since I am using it in the original sense and it only takes a single exception to refute such a broad claim.
They're LARPing. There are no gag orders.
>I find it fascinating that all the discussion about climate change has largely disappeared after LLMs became mainstream, and the idea that state actors may be suppressing data is equally fascinating/terrifying.
It's just not as popular to virtue signal over. Everyone is discussing the wars.
I think the reliability problem is very bad. It's not just that the US government is encouraging fraud, it's also that the average American hates AI and data science. Usually, the public would prefer reliable data, but in this case, Americans seem to prefer corruption just to spite the AI.
We're certainly living in a post-truth country. By vilifying higher education, the assumption that Americans can interpret data is challenging. Therefore, Americans are consuming biased information in their online bubbles because their media is comfortable with fraudulent data.
A concrete example of what happens whenUS economic data becomes unreliable is employment numbers. At the end of 2025, the government couldn't produce any data because of the government shutdown. Most quants and analysts utilized ADP numbers instead. A few years ago, the ADP payroll numbers and the projections by the government were perceived as aligned. This is no longer the case, and most traders rely more on ADP indicators for things like the unemployment rate.
Speculating on what other data is fraudulent, I suspect that real Gross Domestic Product (GDP) will become meaningless. It was supposed to be an indicator for economic wellbeing but now best describes wealth inequality. Nominal GDP is a slightly better measure because it adjusts for things like inflation but it's based on government produced data.
Lastly, there is widespread fraud in climate data in order to deny climate change. The data feeds into economic models and affects property values and insurance rates. I have personally received gag orders from government agencies from both the US and Europe for publishing environmental data.