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Idk. When I see something like that in real life my conclusion is that people have different levels of intelligence. Also I don't know what or how to teach som

Idk. When I see something like that in real life my conclusion is that people have different levels of intelligence. Also I don't know what or how to teach someone who falls into this pitfalls.

GTP 2y ago
I think it is easy to highlight the mistake by rephrasing the argument as OP did. By rewriting it that way, I think it is easy to see that the fallacy lies in taking some specific observations and saying that those are valid in general, without providing a solid explanation as of why that should be the case. Another way of rephrasing it could be, "I have evidence of some statistics-based decisions that were wrong, therefore all statistics-based decisions are wrong". If a person still doesn't get it, put it as "I have evidence of you being wrong once, therefore you must be always wrong (including in this specific case :D )".
- fc417fc802 2y ago
  I believe that is a misunderstanding of what the other party is expressing in this case. It's not "wrong once, so always wrong" but rather "intentional deception in the past, therefore might intentionally deceive again, and I don't know how to verify, therefore I shouldn't trust it".
  - GTP 2y ago
    Uhm, but then, it would work only if applied to the same entity that was deceptive in the past. Applying this to some other party would still make little to no sense, unless you've got some reason to believe this other party wants to deceive you as well.
    - fc417fc802 2y ago
      Unless someone obviously shares common goals with you they are a potential adversary. When faced with a tool that you are confident can be used to deceive you, and a potential adversary who you are confident is aware of this fact, you should then clearly distrust that tool in that context.
    - nickpsecurity 2y ago
      In science, we're required to take a default deny approach. The scientific method treats everything as wrong or a lie by default. Then, a combination of independent review and replication add confidence to the claims. Assuming you trust that person. Later on, media reported pervasive problems in reviewer independence (especially drug studies), statistical claims (especially p hacking), and replication ("replication crisis"). So, we now have more reason to not trust scientific claims without independent replication. That's double true for statistical claims. If I read one, I say "maybe true, maybe not." At least brings me above a random guess in a belief on that topic. If they're highly biased, I ignore their claims on that topic entirely since cherry-picking evidence is so common. Certain sources have enough independent betting or positive outcomes to trust by default in a probabilistic sense. A person whose chips work is fairly trustworthy on basic, chip design and their own product designs. I default on believing their essential claims but know they might be disproven later. That's how empiricism works. Anyone doing less is probably using some combo of faith, testimony, logic, or feelings. They can also dress these up with scientific language or mathematical formulas, too. But was it rigorously reviewed by someone who doubted everything about it? Often not for statistical or scientific-sounding claims.
      - GTP 2y ago
        > The scientific method treats everything as wrong or a lie by default No, the scientific method requires proof both for a positive and for a negative answer. If we can't prove neither, all we can say is that we don't know whether something is true or false. Think i.e. about Riemann's hypothesis or the Collatz conjecture: should we say those are wrong because no one so far proved them to be correct?
- randomNumber7 2y ago
  But what could I do to help people get better in the __act__ of spotting this or doing what you desribe themselves. Idk for me it is subconcious, I just "feel" it or know that it is logically faulty. Also the rephrasing doesnt always work imo, you could have a logic statement, that is totally valid in some context and not valid in others. And you also need to think about the validity of the premise and if it is legit to draw the conclusion in natural language.
  - avodonosov 2y ago
    The paper proposes to use automated tools to help people avoid logic errors. :) I doubt anyone is completely free from logic errors. I am certainly not. But while seeing logic errors other make, we are often blind to our own errors logic - if we were aware of them we would correct them. Just recently while considering a logical fallacy in somebody's argument I realised that on another occasion I myself used similar argumentation. So only when noticed the problem in somebody else I was able to recognize my own error. There are many reasons people make logic errors. For example, if they like the conclusion they easier accept even flawed argumets in support.

Idk. When I see something like that in real life my conclusion is that people have different levels of intelligence. Also I don't know what or how to teach someone who falls into this pitfalls.

GTP 2y ago

I think it is easy to highlight the mistake by rephrasing the argument as OP did. By rewriting it that way, I think it is easy to see that the fallacy lies in taking some specific observations and saying that those are valid in general, without providing a solid explanation as of why that should be the case. Another way of rephrasing it could be, "I have evidence of some statistics-based decisions that were wrong, therefore all statistics-based decisions are wrong". If a person still doesn't get it, put it as "I have evidence of you being wrong once, therefore you must be always wrong (including in this specific case :D )".

fc417fc802 2y ago
I believe that is a misunderstanding of what the other party is expressing in this case. It's not "wrong once, so always wrong" but rather "intentional deception in the past, therefore might intentionally deceive again, and I don't know how to verify, therefore I shouldn't trust it".
- GTP 2y ago
  Uhm, but then, it would work only if applied to the same entity that was deceptive in the past. Applying this to some other party would still make little to no sense, unless you've got some reason to believe this other party wants to deceive you as well.
  - fc417fc802 2y ago
    Unless someone obviously shares common goals with you they are a potential adversary. When faced with a tool that you are confident can be used to deceive you, and a potential adversary who you are confident is aware of this fact, you should then clearly distrust that tool in that context.
  - nickpsecurity 2y ago
    In science, we're required to take a default deny approach. The scientific method treats everything as wrong or a lie by default. Then, a combination of independent review and replication add confidence to the claims. Assuming you trust that person. Later on, media reported pervasive problems in reviewer independence (especially drug studies), statistical claims (especially p hacking), and replication ("replication crisis"). So, we now have more reason to not trust scientific claims without independent replication. That's double true for statistical claims. If I read one, I say "maybe true, maybe not." At least brings me above a random guess in a belief on that topic. If they're highly biased, I ignore their claims on that topic entirely since cherry-picking evidence is so common. Certain sources have enough independent betting or positive outcomes to trust by default in a probabilistic sense. A person whose chips work is fairly trustworthy on basic, chip design and their own product designs. I default on believing their essential claims but know they might be disproven later. That's how empiricism works. Anyone doing less is probably using some combo of faith, testimony, logic, or feelings. They can also dress these up with scientific language or mathematical formulas, too. But was it rigorously reviewed by someone who doubted everything about it? Often not for statistical or scientific-sounding claims.
    - GTP 2y ago
      > The scientific method treats everything as wrong or a lie by default No, the scientific method requires proof both for a positive and for a negative answer. If we can't prove neither, all we can say is that we don't know whether something is true or false. Think i.e. about Riemann's hypothesis or the Collatz conjecture: should we say those are wrong because no one so far proved them to be correct?
randomNumber7 2y ago
But what could I do to help people get better in the __act__ of spotting this or doing what you desribe themselves. Idk for me it is subconcious, I just "feel" it or know that it is logically faulty. Also the rephrasing doesnt always work imo, you could have a logic statement, that is totally valid in some context and not valid in others. And you also need to think about the validity of the premise and if it is legit to draw the conclusion in natural language.
- avodonosov 2y ago
  The paper proposes to use automated tools to help people avoid logic errors. :) I doubt anyone is completely free from logic errors. I am certainly not. But while seeing logic errors other make, we are often blind to our own errors logic - if we were aware of them we would correct them. Just recently while considering a logical fallacy in somebody's argument I realised that on another occasion I myself used similar argumentation. So only when noticed the problem in somebody else I was able to recognize my own error. There are many reasons people make logic errors. For example, if they like the conclusion they easier accept even flawed argumets in support.