You're assuming causality there which hasn't been proven.
"When the data and the anecdotes disagree, the anecdotes are usually right."
-Jeff Bezos https://lexfridman.com/jeff-bezos-transcript/#chapter6_amazo...
"When the data and the anecdotes disagree, the anecdotes are usually right."
-Jeff Bezos https://lexfridman.com/jeff-bezos-transcript/#chapter6_amazo...
What is the context or background for this statement? It's completely insane to think something like this
> It's pretty wild for a random HN user to label one of the top 10 most successful technology leaders of our time as "insane"
Here, let me go. I think it is insane that Elon Musk took so much ketamine that he kept peeing his pants and then kept telling people about it. I think it is insane he's been promising that FSD is <2 years away for the past decade.
Given two sets of data: The statistics and your anecdotal evidence.
The probability of anecdotal evidence being correct must be lower than than the anecdotal evidence being incorrect when it conflicts with the statistics since the statistics come from anecdotal evidence.
Therefore, all other things being equal, if you are presented with data that conflicts with your anecdotal evidence the data has the higher probability of being correct.
After all nothing is more trustworthy than statistics. They should never be conflated with lies or damned lies.
You shouldn't trust your perception, and shouldn't trust statistics. You should question both.
My personal perception can be right as well as statistics the issue is when I use my own limited experience to generalize.
Why would these be in conflict unless you take your personal experience and draw a conclusion beyond that?
>After all nothing is more trustworthy than statistics. They should never be conflated with lies or damned lies.
Why can't I trust statistics if they are sometimes lies?
It's not a dig against math or statistics. It's a dig against the people using statistics. What do you do when, statistically, the majority of statistics you're given are lies, wrong, irrelevant, misleading, or out of context? You ground yourself in direct experience.
Even simple events are difficult to evaluate. One podcaster I've listened to for a decade had an issue on a flight. He bumped into a passenger in front of him and words were exchanged. Eventually he was deplaned by the pilot. In his telling of the story, it was completely outrageous and unwarranted. But obviously to others involved, he was completely in the wrong, enough to be deplaned.
So no, "direct experiences" are definitely filtered.
For another example, my daughters feel unsafe walking alone at night in my city's downtown area. Whereas I, walking at the same time in the same area, don't feel any danger at all. Every human experience is mediated by our past history.
Also by others who may have an agenda.
What's more likely. That a person is afraid of walking alone in your city at night because of a personal experience (like being the victim of a crime) or what they heard from other people?
We can redefine this with more statistical language. The claim would then be "When the likelihood of a sample is low, the sample is likely correct." Which is nonsense.
It is worth noting when you continuously are getting low likelihood samples, but the usual conclusion is that you have biased sampling. Maybe the model is bad, but in some sense that's not so different.
Let's go back to normal language. Anecdotally, a HN user might think a $100k/yr salary is not very much. But the data suggests that it is. Is the anecdote right?! No, we are just biased because we're comparing incomes in tech and often around the Bay area.
I think it is no surprise that one of the richest men in the world is out of touch. He is, by definition, a statistical anomaly. ¯\_(ツ)_/¯
Let's redefine it with this language:
"When statistics are used as PR, data gathering is a joke, state and police competence is cratering, and direct experience and observation tells you things are getting worse, things are getting worse".
The problem is the claim doesn't distinguish biased sampling from a biased model. The former is far more likely.
Just ask yourself which is more likely: "my experience is abnormal" or "everyone is experiencing the same thing I am"? In your friend group the latter might be more likely because you're similar locally and culturally. But across the state? Across the country? Across the globe? No, you'd be crazy to think experiences are typical. There's way too many variables at play and even if we were clones we should expect differences.
So no, it doesn't make sense