CDC data are disappearing

> Data isn’t the ultimate fact check

But it is. Numbers can be twisted, but it they can easily be verified. Bias, bad sources and cherry picking can allow you to tell stories, but the data will allow you to verify those stories are indeed facts. Brain can’t really fact check things that don’t have any data.

I'm not sure I agree.

Even if the numbers are accurate, nearly any situation has a nearly infinite number of potential data points, and deciding which ones are relevant isn't as straightforward as people act like it is.

This is easy to see play out; you can look at the same stories being reported on both Fox News and MSNBC. Usually both sources' raw facts will be basically "correct" in the sense that they're not saying anything explicitly false, but there can be bias in determining which facts are actually useful or how they're categorized.

You can see how the reporting of the January 6th stuff varied between news outlets.

Can data, or AI, tell me definitively who the MVP of the NFL was this season? Allen, Lamar, Saquon? The numbers certainly help when making comparisons, but they aren't the entire story, different people will come to different conclusions based on the exact same set of facts.

Who cares about the NFL? The issue here is that, and mark my words this almost this exact conversation will play out in the very near future:

Scientists: X number of people died of Covid in the US according to CDC data.

US Government: you can't prove that number. That data doesn't exist on government servers, the data in the copies is fake and can't be trusted.

Numbers alone will always lack context. You can absolutely verify where the numbers came from, weren't altered, and the math was done right. What you can't do is verify the numbers alone accurately portray what was happening in the real world, or what has happened in the real world since the snapshot of those numbers was taken.

Numbers are extremely useful, but numbers alone mean absolutely nothing.

Disagree. Numbers don't exist in a vacuum - they are collected, framed, and interpreted by humans with biases, agendas, and limitations. Verification isn't just about checking numbers; it's about scrutinizing methodologies, sources, and context. Data can affirm falsehoods when selectively presented or measured poorly. Brains aren't secondary to fact-checking; they are the ultimate tool for discerning whether data reflects reality or is merely a well-dressed distortion.

> Who cares about the NFL?

It's a simple example, that's why it's relevant. All the facts are available for anyone to see, to process, to analyze. There is no disputed or hidden data. And yet nobody, including any AI, can produce a "true" answer to the question, because it's reliant on one's personal biases.

Even with Covid, did a 92-year old die because of Covid, or because of a multitude of existing conditions that Covid triggered? Probably impossible to know medically, and AI isn't going to tell you definitively one way or the other.

You are proving my point. The CDC has faced several instances where its data was inaccurate or misrepresented:

- COVID-19 Death Overcount: In 2022, a coding error led the CDC to overcount 72,277 COVID-19 deaths across 26 states. Source: https://www.theguardian.com/world/2022/mar/24/cdc-coding-err...

- Maternal Mortality Data: Changes in death certificate reporting, particularly the addition of a pregnancy checkbox, resulted in overcounts of maternal deaths due to false positives. Source: https://www.theatlantic.com/podcasts/archive/2024/08/materna...

- Lead Exposure Report: A 2004 CDC report underestimated the impact of lead-contaminated water in Washington, D.C., leading to criticism over its data accuracy. Source: https://en.wikipedia.org/wiki/Morbidity_and_Mortality_Weekly...

- Property System Data: An audit revealed that the CDC's property system data was neither accurate nor complete, with an estimated $29.2 million of property at risk of being lost or misplaced. Source: https://oig.hhs.gov/reports/all/2016/centers-for-disease-con...

These instances highlight that data, even from reputable sources, can be subject to errors, misinterpretation, or manipulation, underscoring the need for critical analysis beyond face-value acceptance.

It's not relevant because the person who is MVP in a sport is an opinion. Or, to put it more bluntly, it's a marketing scheme to keep people talking about it. There's no correct answer when it comes to opinions.

If the question was who scored the most points in the year, that can be answered factually by data.

If the NFL was deleting all their data at the end of the season with the goal of creating arguments and sowing disinformation, that would be a more relevant example.

True, though in order for brains to do that at all, they need data to analyze. Data is a necessary prerequisite for trying to understand things at all. Removing said data means there is not even the chance to achieve understanding or change. Which is kinda the point.

Barring said data being fabricated, deleting data seems to be a sign of bad faith.

True, numbers alone mean nothing. And the surrounding context alone also doesnt paint a sufficient story. You need both, for without both you can't be effective. Unless said data/context is fabricated, trying to suppress either seems like a clear case of acting in bad faith.

Lol - "cause of death" is often an opinion as well. Or no opinion at all - "natural causes."

In theory, yes. But we're more approaching philosophy with Laplace's demon at this point.

A more realistic example: we can theoretically predict the weather weeks in advance. In reality, it's pointless because there so much data needed to collect for that, and so many events to away the weather, that's its impractical past a few days in the future.

No, cause of death is objective. Whether or not we have the data to figure out the truth doesn't deny the truth.

That's the point of data. To get us closer to the truth. Gravity will keep making you cling to the earth no matter your opinion. Even though as we speak we are still trying to develop models to properly understand the particles or forces behind gravity.

Sure, I didn't mean to say data is unimportant or not needed at all. My point was just that data solves nothing without context (among other things, pike discernment and critical thinking).