Hmm. That seems like a better example of the problem than either of the examples at https://en.wikipedia.org/wiki/Gettier_problem .

The cases cited in the article don't seem to raise any interesting issues at all, in fact. The observer who sees the dark cloud and 'knows' there is a fire is simply wrong, because the cloud can serve as evidence of either insects or a fire and he lacks the additional evidence needed to resolve the ambiguity. Likewise, the shimmer in the distance observed by the desert traveler could signify an oasis or a mirage, so more evidence is needed there as well before the knowledge can be called justified.

I wonder if it would make sense to add predictive power as a prerequisite for "justified true knowledge." That would address those two examples as well as Russell's stopped-clock example. If you think you know something but your knowledge isn't sufficient to make valid predictions, you don't really know it. The Zoom background example would be satisfied by this criterion, as long as intentional deception wasn't in play.

Biology makes it even more complicated. If you see your mother, you consider her to be imposter. While if you hear your mother's voice, you consider her to be real.

Ramachandran Capgras Delusion Case

https://www.youtube.com/watch?v=3xczrDAGfT4

> On the flip side, even if the knowledge is wrong, if everyone agrees it is true, does it even matter?

This is case of consensus reality (an intuition pump I borrowed from somewhere). Consensus reality is also respected in Quantum realm.

https://youtu.be/vSnq5Hs3_wI?t=753

while individual particles remain in quantum superposition, their relative positions create a collective consensus in the entanglement network. This consensus defines the structure of macroscopic objects, making them appear well-defined to observers, including Schrödinger's cat.

edit: Then there's the whole "what is a cow" thing. Like if you you stuffed a cow carcass with a robot and no one could tell the difference, would that still be a cow? Or what if you came across a horrifying cow-horse hybrid, what would you call that? Or if the cow in question had a unique mutation possessed by no other cow - does it still fit the cow archetype? For example, what if the cow couldn't produce milk? Or was created in lab? Which features are required to inherit cow-ness? This is an ambiguity covered by language, too. For example, "cow" is a pejorative not necessarily referring to a bovine animal.

edit: And also the whole "is knowledge finite or infinite?". Is there ever a point at which we can explain everything, science ends and we can rest on our laurels? What then? Will we spend our time explaining hypotheticals that don't exist? Pure theoretical math? Or can that end too?

I wonder if there is a law of coincidental succeeses too. (if you're an old timer, you might call this some sort of Mr. Magoo law, or maybe "it seems to work for me")

Yeah, good times. I just recently had one that was a really strong misdirection, ended up being 2 simultaneous other, non related things that conspired to make it look convincingly like my code was not doing what it was supposed to. I even wrote tests to see if I had found a corner-case compiler bug or some broken library code. I was half way through opening an issue on the library when the real culprit became apparent. It was actually a subtle bug in the testing setup combined with me errantly defining a hardware interface on an ancient protocol as an HREG instead of an IREG, which just so happened to work fine until it created a callback loop inside the library through some kind of stack smashing or wayward pointer. I was really starting to doubt my sanity on this one.

I often wonder if LLMs would have made Wittgenstein cry...

Dumb counterpoint: if it’s not a true belief, is it a false negative or a false positive? Any third option I can think of starts with “true”…

QED - proof by terminological convention!

False propositions are not knowledge, only true propositions are knowledge. Therefore you cannot know something true that is actually false, you can only believe something true that is actually false. Precisely describing how one moves from belief to knowledge is exactly what epistemology is about.

No, I think many people use a definition of "know" that doesn't include "knowing" falsehoods. Possibly you and they have fundamentally beliefs about the nature of reality, or possibly you are just using different definitions for the same word.

> "Knowing" falsehoods is something we broadly acknowledge that we all do.

Only in abstract discussions like this one. And in some concrete discussions on certain topics, not "knowing" seems to be essentially impossible for most non-silent participants.

> That's a problem right there. Maybe that made sense to the Greeks, but it definitely doesn't make any sense in the 21st century. "Knowing" falsehoods is something we broadly acknowledge that we all do.

I think the philosophical claim is that, when we think we know something, and the thing that we turns out to be false, what has happened isn't that we knew something false, but rather that we didn't actually know the thing in the first place. That is, not our knowledge, but our belief that we had knowledge, was mistaken.

(Of course, one can say that we did after all know it in any conventional sense of the word, and that such a distinction is at the very best hair splitting. But philosophy is willing to split hairs however finely reason can split them ….)

Could you elaborate what you mean by that?

I always thought of what I learned in some philosophy class, that there are only two ways to generate a contradiction.

One way is to reason from a false premise, or as I would put it, something we think is true is not true.

The other way is to mix logical levels (“this sentence is false”).

I don’t think I ever encountered a bug from mixing logical levels, but the false premise was a common culprit.

As long as "your assumptions" includes "I know what I am doing", then OK.

But most people tend not to include that in the "your assumptions" list, and frequently it is the source of the bug.

Alternative host [no paywall]: https://fitelson.org/proseminar/gettier.pdf

> How careful do you have to be to never be fooled?

This is where Contextualism comes into play. Briefly, your epistemic demands are determined by your circumstances.

https://plato.stanford.edu/entries/contextualism-epistemolog...

Yes, most likely. Rebase hides the fact the 2 changes happened separately, a merge would make it much easier to see the different avenues that may lead to the bug.

We purposefully try not to do rebases in my team for this reason.

You are defining valid steps in understanding of software, but attaching them to job titles is just going to lead to very deceptive perspectives. If your labeling was accurate, every organization I've ever worked at would at least triple the number of staff engineers than it does.

Yes, the paper itself is much more unambiguous (and very short): https://courses.physics.illinois.edu/phys419/sp2019/Gettier....

These are correct but contrived and unrealistic, so later examples are more plausible (e.g. being misled by a mislabelled television program from a station with a strong track record of accuracy).

The point is not disproving justified true belief so much as showing the inadequacy of any one formal definition: at some point we have to elevate evidence to assumption and there's not a one-size-fits-all way to do that correctly. And, similarly to the software engineering problems, a common theme is the ways you can get bitten by looking at simple and seemingly true "slices" of a problem which don't see a complex whole.

It is worth noting that Gettier himself was cynical and dismissive of this paper, claiming he only wrote it to get tenure, and he never wrote anything else on the topic. I suspect he didn't find this stuff very interesting, though it was fashionable.

I like the example of seeing a clock as you walk past. It says it's 2:30. You believe that the time is 2:30. That seems like a perfectly reasonable level of justification -- you looked at a clock and read the time. If unbeknownst to you, that clock is broken and stuck at 2:30, but you also just happened to walk by and read it at 2:30, then do you "know" that it's 2:30?

I think a case can't so much "disprove" JTB, so much as illustrate that adopting a definition of knowledge is more complex than you might naively believe.

I was thinking that one solution might be to specify that the "justification" also has to be a justified true belief. In this case, the justification that you see a cow isn't true, so it isn't a JTB.

Of course that devolves rapidly into trying to find the "base case" of knowledge that are inherent

I have similar belief, but only when it comes to bugs that make me look foolish.

The more likely a bug is to make me look dumb, it will only appear as soon as I ask for help.

I think those other two are also very useful. I've actually had a lot of traction with introducing "yak shaving" in everyday life situations to non-programmers -- it applies to all kinds of things.

EDIT: Deleted paragraph on DRY that wasn't quite right.

On a more serious note: populist politicians seem to like making gettier claims; they cost a lot of time to refute and are free publicity. Aka the worst kind of fake news.

I don't understand the Gettier problem. The example of the cow for example: You do not have a justified belief there is a cow there, all you can justify is that there is the likeness of a cow there.

To be able to claim there is a cow there requires additional evidence.

Yeah why did he rebase unreleased code?

And the “right” RC only has to be right enough to solve the issue.

I can understand 0 and 2, but what's 1? The "I don't know how to count" answer?

I’ve come across (possibly written) code that upon close examination seems to only work accidentally — that there are real failures which are somehow hidden by behavior of other systems.

The classic and oft heard “How did this ever work?”

This is horrifying, and needs a trigger warning lol. It gave me a sense of panic to read it. It’s always bad when you get so lost in the codebase that it’s just a dark forest of hidden horrors.

When this kind of thing tries to surface, it’s a warning that you need to 10x your understanding of the problem space you are adjacent to.