Petra Liverani
Registered Member
Are you aware of rules of critical thinking that guide you and do you see those rules broken by others?
These are two guideposts and two rules that guide my thinking. What do you think of them? I'm what many others would perceive as a hard-core conspiracy theorist and yet I don't see myself that way at all as I think that my thinking is 100% evidence-based (even if I'm mistaken in my interpretation sometimes) and follows the rules of critical thinking.
Guideposts
1. Every relevant piece of information will at least support if not favour the correct hypothesis
It is useful to constantly bear in mind that the nature of reality is that every single relevant piece of information will at least support if not favour the correct hypothesis. Any relevant item selected at random will show that it at least is consistent with the hypothesis if not favour it. If not, the hypothesis isn’t correct. Sometimes seeming anomalies might contradict the correct hypothesis but on closer inspection will be revealed to be only seeming anomalies not real anomalies.
2. Internal consistency and consistency with expectations
Where all the evidence is both internally consistent and consistent with expectations, unless a good reason is put forward for doubt we should accept an hypothesis as correct.
Rules
Rule 1: Aim to prove your hypothesis wrong
This rule applies generally to the validity of the hypothesis you hold.
When I came across the statement by Kary Mullis, the Nobel-prize winning inventor of the PCR technique, in an interview with Gary Null, "The scientist aims to prove their hypothesis wrong," I thought, "Bingo! That's what I do.” If ever what I believe is challenged by anyone or anything I review my hypothesis against the challenge to see if it still holds. I also go out of my way to investigate the opposing arguments sufficiently to ensure I can respond to them … and if I can’t respond with a good argument, I change my mind or at least “park” the challenge for later review. Richard Feynman effectively said the same thing as Kary Mullis in his commencement address at Caltech in 1974 entitled, Cargo Cult Science.
Rule 2: Confine your analysis to the most relevant and unarguable-with data in the first instance
This rule applies to the best way to approach evidence in order to get to the truth.
If the nature of reality is that every single piece of evidence will at least support if not favour the correct hypothesis then if there is a reasonable amount of unarguable-with data and all of it supports your hypothesis if not favours it over any other then it's going to be rather difficult for another hypothesis to be correct.
People get carried away with claims on subject matter about which they have insufficient understanding, for which there is not good evidence and that do not align with all the evidence. They also focus on irrelevant information which creates confusion and clouds the issue. Even if certain facts are unarguable-with are they necessarily the most relevant? Considering the most relevant and unarguable-with data first sets you on a good path to the truth. In essence it’s Occam's Razor, shaving away the unnecessary.
These are two guideposts and two rules that guide my thinking. What do you think of them? I'm what many others would perceive as a hard-core conspiracy theorist and yet I don't see myself that way at all as I think that my thinking is 100% evidence-based (even if I'm mistaken in my interpretation sometimes) and follows the rules of critical thinking.
Guideposts
1. Every relevant piece of information will at least support if not favour the correct hypothesis
It is useful to constantly bear in mind that the nature of reality is that every single relevant piece of information will at least support if not favour the correct hypothesis. Any relevant item selected at random will show that it at least is consistent with the hypothesis if not favour it. If not, the hypothesis isn’t correct. Sometimes seeming anomalies might contradict the correct hypothesis but on closer inspection will be revealed to be only seeming anomalies not real anomalies.
2. Internal consistency and consistency with expectations
Where all the evidence is both internally consistent and consistent with expectations, unless a good reason is put forward for doubt we should accept an hypothesis as correct.
Rules
Rule 1: Aim to prove your hypothesis wrong
This rule applies generally to the validity of the hypothesis you hold.
When I came across the statement by Kary Mullis, the Nobel-prize winning inventor of the PCR technique, in an interview with Gary Null, "The scientist aims to prove their hypothesis wrong," I thought, "Bingo! That's what I do.” If ever what I believe is challenged by anyone or anything I review my hypothesis against the challenge to see if it still holds. I also go out of my way to investigate the opposing arguments sufficiently to ensure I can respond to them … and if I can’t respond with a good argument, I change my mind or at least “park” the challenge for later review. Richard Feynman effectively said the same thing as Kary Mullis in his commencement address at Caltech in 1974 entitled, Cargo Cult Science.
Rule 2: Confine your analysis to the most relevant and unarguable-with data in the first instance
This rule applies to the best way to approach evidence in order to get to the truth.
If the nature of reality is that every single piece of evidence will at least support if not favour the correct hypothesis then if there is a reasonable amount of unarguable-with data and all of it supports your hypothesis if not favours it over any other then it's going to be rather difficult for another hypothesis to be correct.
People get carried away with claims on subject matter about which they have insufficient understanding, for which there is not good evidence and that do not align with all the evidence. They also focus on irrelevant information which creates confusion and clouds the issue. Even if certain facts are unarguable-with are they necessarily the most relevant? Considering the most relevant and unarguable-with data first sets you on a good path to the truth. In essence it’s Occam's Razor, shaving away the unnecessary.