Fallibilism and Induction Preconceptions
Fallibilism
Fallibilism is the idea that we can always make mistakes. It says that there are no guarantees against making mistakes. No matter what you do there could always be a mistake that you’re not aware of.
Infallibilism attempts to prove ideas as certainly true. It’s problem is that whatever arguments is given in order to prove that the idea is true must also be proved true themselves. And so you have to make sure ad infinitum that every supporting argument in the proofs don’t contain any mistakes. This is an infinite regress which means we can never get to the bottom of it.
Infallibilist propose axioms as a way to escape the infinite regress. Axioms are fundamental ideas that we can be certain are true without giving proof that they are. Many of ideas held as axioms are knowledge, but there really is no way we can be 100% certain they are true. Any axiom which you use reasoning to establish must have the reasoning be proved true as well, so those cannot escape the infinite regress. The other option is to claim that the axioms are simply self-evident. They say we don’t need any reasoning we just know they are true because of their simpleness, obviousness or something else. But ideas once held as self-evident have later been found to be wrong. There isn’t anything that’s truly obvious; anything can be doubted. Claiming self-evidence is arbitrary and is never a rational reason to accept any idea.
If we view truth as correspondence with reality then theoretically we can express the truth perfectly (however there could be issues with language or other thinking tools in getting perfect correspondence). Fallibilism doesn’t necessarily say this is impossible. However it says that if we did manage to match reality perfectly then we can’t be certain that we did. Any idea that claims that we know for certain that it’s true suffers from infinite regress. Still we can hold the true idea.
Fallibilism says we can’t have certainty, but it doesn’t say we can’t have knowledge. According to JTB, fallibilism would amount to denying knowledge, but according to evolutionary epistemology certainty isn’t necessary for knowledge. CR says you have to start with guesses. It then says that we can improve upon the guesses by criticizing the guesses and then coming up with new guesses that don’t have the same flaw. The possibility of the improvement of our ideas is what let’s us say we have knowledge. For each time we reject ideas and come up with alternatives that are better we have come closer to the truth. It is also always possible that what thought was an improvement was actually a regression.
We can also view attempted refuted ideas as true and useful in some limited context. Refuted ideas is still information which is not random. They will have a definite structure and an appearance of design for some purpose. And so we can think of them as less useful and/or true knowledge. Because if something was designed then that means knowledge had to be used in order to create it. Either that could be a watchmaker using his knowledge to create watches, or it could be nature using the process of evolution to create genes, which contain knowledge, to create the appearance of design in animals.
Fallibilists are often accused as being skeptics because the accuser thinks that we need certain ideas for knowledge or at the least that we need some certain ideas to base the less certain ideas on. But what is the danger of being a skeptic? Pyrrho, a skeptic, was said to have to be pushed out of the way from a carriage since he would not move himself because he could not be certain that the carriage was real. Whether or not the story was true it shows that the problem with skeptics is that they’re indecisive. With certainty you would be absolutely decisive, so infallibilists fear that without certainty you would be like Pyrrho not knowing what to do. But so long as we have a method to figure out what our best idea that we know is, then we can be decisive and follow that idea. With CR we can use critical preference and choose the ideas that have best survived criticism. With CF we can refute ideas and come up with new selection criteria until we are left with one non-refuted idea to follow.
Fallibilism can also mean that mistakes are common. Which they in fact do seem to be. Given that we improve our knowledge by fixing mistakes, that mistakes are common and that we can never be certain there is no mistake in our knowledge, then we really ought to always be on the look out for mistakes.
I wanted to say:
Because we can never be certain that we are correct then there is always room for infinite progress
But that doesn’t follow. I think the infinite progress idea has to do with fallibilism, but I can’t really connect them. Here’s one way:
Since we can never perfectly define our all of our knowledge without making circular definitions, we can always add definitions and thus improve our body of knowledge as a whole.
Hmm. Just adding definitions doesn’t necessarily improve our knowledge. We could have already added all the useful definitions.
Review
I can’t find any contradictions.
I think the biggest thing I missed out on was not talking more about being open to criticism. I only said we should always be on the look out for mistakes.
Induction
Induction is the (false) idea that you can extrapolate patterns from observations to create theories and/or validate them. Induction is a justificationist theory which says we can justify theories by making repeated observations.
Induction relies on the premise that the future will resemble the past. It says that patterns we observe now and have observed will continue into the future. But only some patterns will continue into the future while others won’t. For induction to work we would need some epistemological technique to know which patterns are going to continue and which won’t. We can make (fallible) explanations for why certain patterns will continue or won’t, but induction can’t use those since induction is supposed create such explanations. It would be a stolen-concept. Induction has no way of telling which patterns will continue and which won’t.
For any sequence of observations we have observed so far there logically exists infinitely many patterns that fit these observations. The sequence of observations may repeat again, but it could just as well be followed by any different observation afterwards. There are infinite logical possibilities for what observation will follow. If the next observation breaks what looks like our previous pattern then a new pattern has actually emerged, just repeat the sequence we have seen up until now. If we look at the observations we have now and imagine the logically possible patterns they could follow we can see that there are an infinite amount patterns that logically fits.
I have a concern with the above. Shouldn’t we only count what is logically possible as things following non-contradiction and the laws of physics. So when I say there are infinite amount of logically possible observations that could follow any sequence of observations, then that’s false because I’m counting observations which would not follow the laws of physics and non-contradiction? Maybe there aren’t infinite amount of possible observations that could follow, but if there multiple logically possible observations then that could make infinitely many different patterns. You can make infinite patterns with 1’s and 0’s so long as there doesn’t stop being a possibility for either observation after some point of time.
Induction also faces the problem of determining how well a pattern fits a situation. When you’re making observations how does induction tell you that the situations are similar enough for the pattern to hold? For example you may find that water boils at different temperature at different altitudes. That can be explained by the different atmospheric pressure at different altitudes, but induction can’t tell you that. Over time the world changes, and sometimes relevant changes are made to the situation for the theory. Induction says to make multiple observations for similar enough situations in order to confirm the theory. But induction cannot tell you when the situations are similar enough and how well the pattern fits the situation.
Induction assumes that observations can be understood directly. It says pure impressions of observations can generate ideas and verify them. It says that truth is manifest, just repeatedly observe nature and the truth will occur to you. But in reality what you get from observations is just sense data. And the data doesn’t make sense unless you interpret it. The idea you get from making observations is what you interpret it to be. There is no mechanism for sense data to automatically generate true ideas in your mind.
Induction also assumes that observation takes the leading role, guiding the mind towards true theories. It says that after making repeated observations the pattern underlying the phenomena becomes apparent to you. But we have already explained that there are an infinite amount of possible patterns that are compatible with our observations. So, how does the method of induction pick out the correct pattern among them? It can’t. In order to discover the correct pattern you have to already have it in mind, otherwise you cannot recognize it in your observations. When we have a pattern or theory in mind we can observe to see if they are compatible with nature. So it is the mind which guides the observations towards theories and patterns such that we can look for ways nature might contradict our ideas. You need to have a theory in mind in order to focus your attention towards the correct observations.
Review
Induction is an attempt to use evidence without arguments or intelligent thoughts.
That’s a good sentence. I said induction couldn’t use explanation since that would be a stolen-concept and that induction is supposed to explain how explanations are made. But the quote above said it more explicitly.
I didn’t say anything about how evidence can only provide contradiction or non-contradiction.
I didn’t criticize induction for not trying to explain and understand the world conceptually.
I spent somewhere around 3 to 3.5 hours on this.