Why science based on induction is flawed

Probability doesn't reduce uncertainty, it measures it.

I mean, if you have probability, you are less uncertain. I am more certain about outcome which has 90% chance of happening than outcome which I have no idea what's the chance of happening.

We don't always have clean numbers to make precise calculations, and we are forced to use intuition to guess at the uncertainty

I never quite understood the intuition, mainly because so many people get the wrong intuition about something. From my point of view, if you don't have probability nor deduction, I don't know what do you draw conclusion from. Maybe some people have a stronger sense of a priori premise, so they don't need probability nor deduction to get that premise. But such people are usually rare. I get that when you don't have probability nor deduction, the only thing you can rely on to begin with is the intuition. My issue tho is, that intuition is a mystery to me. I don't really get how someone can know something based on intuition, because it's not really a form of logic. It's more like sixth sense.

Deduction doesn't operate on probabilities and chance

Deduction operates on deriving conclusion. What that conclusion is, is another thing.

You can quite perfectly make deductive argument that something has higher chance of happening.

P1. If there are more black cards in deck than white cards, then it is more likely to draw black card.

P2. There are more black cards in deck than white cards

C. It is more likely to draw black card

This is deductive reasoning. As long as premises are true, conclusion certainly follows.

Yes, I agree, but I dont understand your objection to induction I guess. I mean, let's say only one card has been drawn from the deck and it was black. Your syllogism is 100% true, but the level of certainty regarding pulling another black card is functionally ~50%. Is it the pretense of certainty that you like?

I prefer certainty, and I do think deductive reasoning reaches it better. I have no problem relying on induction when certainty or probability cannot be established by deductive logic. My issue with inductive logic is that establishing probability based on it is extremely difficult in some cases. Because its different from probability established by deductive logic. there are some probabilities in inductive logic which are almost certain, such as "sun will rise tomorrow". Its the constant repetition of something which establishes higher probability of further repetition. However, when we are dealing with probabilities which are not high, inductive reasoning gives a lot of false conclusions. If probability is 60%, then we are faced with problem that 40% of our conclusions are wrong, and from those conclusions, more incorrect conclusions are derived. However, we dont even know what probability exactly is when we are dealing with situation where observed world is smaller than non-observed world. It is true that in theory, induction produces 100% certainty when everything is observed, and higher certainty when most things are observed. However, in any situation where non-observed world is like 2x of observed world, issue rises with inductive logic. I think science doesnt even observe 50% of Earth, let alone universe. Its reason why science such as sociology and psychology is terribly unreliable, and whats worse is that other science which are considered hard science also face issue that we just dont know if our current knowledge even applies outside the tiny portion of the universe we observe.

These aren’t problems for science

Lack of certainty or known probability is a problem.

Absolute certainty is itself impossible to logically maintain unless you begin with the presumption that you are infallible

I mean, deductive logic is literally certainty of conclusions from premises. Math which works on deductive logic is literally certainly true. I don't really see why you even bother to respond if this will be your response.

What are you advocating? ...changing science so it doesnt allow more information to hone accuracy, or, what, getting rid of science?

What I advocate for is greater focus on deductions, observations and probabilities made by those.

I really dont think science which are based entirely on inductions have any great future, because their whole rule for logic they use is fundamentally flawed and proved false by countless examples in countless scenarios. there is a reason why sociology and psychology are called "soft science", because they rely on induction and its pretty much universal knowledge in scientific world that induction is not just uncertain, but sometimes even blatantly misleading.

there are only few areas where inductive logic is good, and those are always consistent repetition of conclusion. Because inductive reasoning doesnt use deduction, its conclusion entirely depends on observations to be proved likely true over and over in each observation.

However, in any case where observations are inconsistent or largely incomplete, conclusion made by induction resembles more of an assumption than reasoning.

I say, sure, if you have nothing else, use induction. But really, order of work should be deduction > observation > explanation exhaustion testing > induction. I guess definition deduction also have their place, and some science is based entirely on definition deduction, like math. However, definition deduction rarely applies to other forms of science, because it does require definitions based on primitives as opposed to arbitrary definitions. Math definitions are based on primitives. Even if you changed definition of "2", the primitive rule of addition would actually still be true. So definition deduction mainly deals with definitions made from primitive concepts. It descends into inconsistency if definitions arent based on some fundamental rule of logic. Which also does bring us to starting premises being laws of logic, and other than "A = A", the basic rule of logic is deduction (All A are B means "single A" is B).

As I said before, induction goes contrary to deduction, and its basic rule is that "Some A are B means All A are B". this rule is proved easily false, even in case of probabilities where "In some cases, probability is 50% = In all cases, probability is 50%" is also proved false.

In other words, induction uses a form of logic which can be true, but at same time, it can be false, so it takes a lot of observations to establish probability, and right now humans arent really in position to observe everything there is, to increase chances of induction logic being correct.

As Savant mentioned, extrapolation based on known distribution is unreliable even for AI or computers. Interpolation is more reliable. However, inductive reasoning based on small percentage of observed world is basically extrapolation. Interpolation allows deductive reasoning, because it's usually just filling gaps in training data. But the greater the unobserved world compared to observed, greater the gap.

Extrapolation induction is about as unreliable as it gets in science. The only next step would be making predictions based on dice roll.

Even AI agrees with me:

"Yes, extrapolation is generally considered the least reliable method for making predictions because it estimates values outside the range of your actual measured data"

AI should know, given that it's main issue AI faces today. They try to solve this issue by increasing training data, and increasing parameters count to make AI smarter so it doesn't hallucinate as much due to this issue.

Don’t use you4 past to predict your future.

Causation science is pretty much based on past predicting future. the only issue is when a lot of causes mix, so prediction is messy.

The goal being to improve accuracy, right? You must recognize deduction can yield absolute certainty in a faulty conclusion. All it takes is a bad premise.

If we are talking of actual deduction, then the foundational premise must be generally true claim.

It's true people can use deduction to arrive at incorrect conclusion, but that's only if their premises are incorrect and also not themselves deductions. It's actually possible to use deductive reasoning in flawed form, most famous one being "if, then" form, which is actually more often misused than used accurately.

The basic idea around deduction is to take part from the whole.

The classic example is:

"All A are B, so some A are B".

This is logic moving from general to specific.

And as far as I know, this logic cannot produce false conclusion unless "All A are B" is false.

How one comes to premise "All A are B" is a different thing. It can happen by definition, logical law, exhausting options, or observation(induction).

But when it happens by induction, you are again looking at weaker argument unless it's a strong constantly repeated observation.

Yes, the goal is to improve accuracy, and we can say for sure proper deduction is true as long as premises are true. Induction on the other hand can be false even if premises are true. Induction presented in form of deductive logic suffers from unproved premise from start.

Induction to spot the patterns and make the premise, and deduction to predict what happens if its true

You are correct that induction is often needed to make a premise. Not always. Sometimes starting premise can merely be logical law or exhausting options and exhausting explanations to see which explanation remains both internally consistent and not contradicting some true theory elsewhere, and which explanation is absurd.

My issue isn't with strong induction. My issue is more with relying too heavily on induction to the point where it's used even in cases where it has decently high chance to be wrong.

I don't deny that laws of physics which were generalized by induction are true. Maybe they are not true everywhere in universe, because they were derived by induction, but the chance of them being true is more likely than not in some area.

My issue is more with using induction beyond it's probable limits. We also know there are cases where induction is terribly uncertain. We know that AI uses induction to produce hallucinations.

I can agree that induction can be useful. My point of disagreement would be that induction should really be a last resort, especially in cases of extrapolation, which is least reliable formal form of reasoning there is.

Science which prefers induction over all other forms of reasoning is basically guaranteed to make bunch of false conclusions. And we have seen that with pretty much any science which relied on induction, be it psychology, sociology, pharma drug testing, social studies...ect.

We see flaw of these sciences because they are using form of reasoning which is considered nonsense in formal logic.

This is not to be confused with strong induction. Strong induction is basically something which repeats as exactly true each time when observed, even with expansion of observation.

Soft induction is area where results vary, so claim is sometimes true, sometimes not true. A lot of social science suffers from this issue.

Strong induction does have its own problems, such as assumption that what we observed so far follows same laws as remaining 99% of things we didn't observe.

However, at least in case of strong induction, we assume it's 100% true in areas we observed so far, so we can apply it there, and I don't think it's likely that laws of physics will stop working tomorrow.

However, even strong induction, when applied to non-observed areas, becomes flawed. I mean, black holes are still partly a mystery despite all strong induction we had so far.

Also, I have to make clear difference between deductions based on observations and induction based on observations.

Deduction based on observation is:

"this applies in all areas we observed, so it applies to this observed area as well"

this logic is always true, because specific observed area is part of "all observed areas". Conclusion must follow from premise.

Induction goes beyond observed area and says:

"this applies in all areas we observed, so it applies to all non-observed areas as well"

this is a leap of faith. conclusion doesnt follow from premise.

Inductive arguments arent valid deductively

Hence science based on them isn't valid deductively.

which isnt the same thing as completely invalid

Nothing is completely invalid. If you threw dice roll to guess answers, sure, you would get something right.

I think even you as a critic of induction wouldn't put it on the level of dice divination...

In any case where you don't have exact probability, that's what it comes down to.

If something is 60% true in observed cases, and most cases are not observed, there is no telling what probability would be if most cases were observed.

And these situations happen often in social science. I mean, the polls were at some point suggesting Trump will lose elections. Problem lies in the potential error.

You cannot be absolutely certain in everything

That’s exactly the point I’m trying to make to SL

So your point is a self-defeating statement?

That's amazing.

How is it self defeating? Please enlighten me.

Are you certain that you are uncertain?