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.
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.
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.
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.
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.
- 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...
- 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.
