The problem with conspiracies is they keep expanding till well the whole damn planets in on it to make them work logically but the logic like a rusty bucket full of holes
It's actually surprising how many people claim to be "open minded" but then quickly retreat back to their comfort zones once presented with a radical new perspective.
It's a hard task to be open minded 24*7..sometimes it can be exhausting being too perfect or even attempting to be. I think we are mostly open minded to accept the opposing ideas when it doesn't affect us that much.
If you accept everything as being true, you are setting yourself up for bullshit. Only scientific, objective physical reality is true. Semantics, contemporary philosophy, they are bullshit mental clownery created to deceive.
Humans are built for survival, and only the truth where it is accidentally conducive to survival Confirmation bias is a cognitive bias underlying fallacious lines of reasoning. By definition, cognitive biases need to be common. Common likely because it is partly perpetuated by our biology. I imagine that believing something that everyone in the tribe does would allow them to work well together and reduce conflict? That's my guess
Bayes' Theorem is an important tool in probability, but my statistics book was terrible in its attempt to verbalize it. Basically, it is very much as Julia described it: we think we know (with some degree of certainty) how an event will occur. However, we often learn in the future that our belief was wrong, so we go back and revise our beliefs (posterior probabilities). My book gives a very boring example having to do with credit cards and the probability that someone will default, so I won't bore anyone with those details. The implications are important, though: if something more accurate comes along than what we believe to be right and correct, we must be willing to change our paradigm in order to have a better understanding of the way the world works.
+Powerdriller Power The formula is useful because it is often easier to get the probabilities on the LHS of the equation. Maybe you find it "discouraging and too cryptic" because you have not read the proof, which is very short and easy. Think for a minute and you will understand it. That joke is crap and tells you very little about Baysian reasoning.
Any time you are going to give a lecture on something you should explain it first. And when I googled at the time of watching the video I didn't find anything. It so doesn't intuitively make sense after seeing the formula and watching the video. There should be a better explanation, that's all in saying.
That's because this is horseshit, and this video is the "thinking" equivalent of "BOSTON SCIENTISTS HAVE DISCOVERED A REVOLUTIONARY NEW PERFORMANCE SYSTEM. TRY THIS ONE WEIRD TRICK TO BUILD MUSCLE FAST..."
Matthew Van Helden she said that beliefs are greyscale, and that level of confidence changes as new evidence comes. She explained the relevance without giving out a formula. You were waiting for the formula and thus missed the explanation that mattered more.
@@Mr96akaal And what gives you the perception of being? your senses? all of which susceptible to illusions. "Cogtio ergo sum" is a good sentiment but what is perceiving you perceiving yourself?
JoeBlu That’s the point. The only knowledge that is certain is this very experience. Alan watts said “just how a knife can’t cut itself, you can’t out be being.”
Male humans solving disagreements by display of strength via varying degrees of violence is also natural. Just because something is natural does not necessarily mean it makes sense in today's society.
Realizing most people didn't already think like this is what ended my rebellious teen phase. Learning that my parents had gifted me something from infancy most people require years of schooling to obtain.
It's a very good informative video. I'm amazed by how much dislike it got. Maybe the prerequisites to understand this video is beyond those who have disliked.
She states some of the principles of Korzybski's General Semantics. Look up the book "Language in thought and action" by Hayakawa, or "Language habits in human affairs" by Irving J. Lee
It seemed interesting but at one point I was wondering if she really knew what Bayes theorem means. My guess is not,otherwise she could have given one example.
There is a flaw in this. If you are too excessive in trying to get all the facts, you will never get anything done. Sometimes you need to charge in headlong with limited information. It's a balancing act between bravery and patience. Too much patience, and nothing gets done. Too much bravery and you ruin yourself and whatever you're working on.
Nice , but what I think is that patience is more important than bravery cause the great things are made with it and not with bravery, Even if (like you say) bravery is necessary, bravery is like a surface (a shape of something:the first impact of an action) , patience is something more deep
itsiwhatitsi The mind will always come up with excuses to, "do a little more research". Jeff Bezos didn't spend 7+ years planning. He spent 7+ years *acting*.
manictiger The creator of Amazon? Is him? Ok anyway I agree with you.. what I just try to say is that patience is a value that you must have if you go true years in which not necessary happen something (like in the internet business). Also a brave man without patience , is superficial and can't really improve. What I think is that it's necessary to be brave but the patience is a very strong value that can really open your mind, in the process of improving yourself. I agree anyway: do with bravery, but think with patience
itsiwhatitsi The mind plays games on itself. Patience is important, but cowardice will mask itself as patience, if you let it. Once you conquer your own mind, then nothing can really stop you.
and yet "the way" is not described or explained. Just many words with little meaning. One could compare to political debates. The only thing described in this video was sound and sequential reasoning. One does not require Bay's theorem to comprehend logically.
Well, part of the problem is that to go into Bayes requires more time than is alloted to this Big Think introduction video. As far as I can extrapolate, Julia only had time to talk about the benefits of using Bayes Theorem, not necessarily what it is or how to use it in everyday thinking. But about those equations: (A|B) is the probability that B is true given that A is true. That's what the symbol "|" means. I've found this out very recently. Relevance: ....hard to talk about in 500 chars
Still sounds like a bunch of obvious statements to me. Maybe I should review Bayes' formula (which I've studied but forgot long ago...). Or maybe she could have provided a quick recap of it. Just sayin'
That is the thing with probability. Things seem pretty obvious at first but can quickly become unintuitive very quickly. If you have studied stochastic processes, you will see this time and time again. Especially when considering expected times, etc. I think you are right, maybe you should review Bayesian statistics. And more importantly, apply it and see for yourself.
Thanks. For the record, I was not implying that Bayes' formula itself is obvious. Only her words in this video seemed to me not that insightful. Anyway there are quite a bit of videos of her talking about these same concepts more extentensively, so I guess I'll just have to go check them out...
Since she didn't actually state Bayes's Formula for those of us who didn't remember what it's about, I went and looked it up myself. Basically, the most important application of the rule is when it comes to the possibility of false positives, and how we apply probabilities.
I was about to burst a blood vessel towards the end when she STILL HADN'T TOLD US WHAT BAYES RULE IS!!! Would have appreciated a simple "here's what bayes rule is. NOW let's discuss what it means for your every day life". /sigh/
She's trying to explain math. If she rattled off what Bayes Rule was p(A|B)=(p(B|A)*p(A))/p(B), you probably would have clicked away. Bayes rule is kind of like shaping a blob of clay into a recognizable shape. The clay is your current opinion and recognizable shape is someone else's opinion. The more info and supporting evidence for that other person's opinion is like molding the clay into the shape. But may or may not convince you in the end, since it doesn't look completely like the shape.
Bayes' rule is where there is a higher chance of probability. too many people will cherry pick their dissent to an argument throwing out strawman and ask improbable scenarios to discredit. Bayes' rule counters those who bring up the rare of the rare that can occur saying that since 0.000001 percent chance something won't happen means it we can't judge. but in fact we can judge based on reasonable probability.
She said at the start of the video, that she wasn't going to go into the mathematics of Baye's equation, just a way to use the concept of updating one's beliefs based on new information. She implies at least, that a lot of the time we walk around with a beliefs as though they are black and white (1 and 2). However, when we apply Baye's rule we find that our beliefs arn't as bullet proof or as infallible as we previously thought; Rather, the degree of certainty behind our beliefs is more grey scaled, as she said, (between 0%-100% - a probability if you will) meaning that given enough evidence for a belief other than our own, we can make a more rational decision. I think you also have to take into account, the video is only 3 minutes, so it would be hard to go into depth of the mathematics that are operating within Baye's equation. This is a simplified explanation for those who are laymen in mathematics.
Caleb I'm a fan of Julia's work, but even though I enjoyed the video, I agree with Will the this was not her best. She told us about some of her *conclusions* and perspective changes after *she* understood Bayes' Theorem, but she didn't explain what the theorem *is*, nor the process of using it (at least not well), nor how she reached those conclusions. She wouldn't have had to go into the mathematics, but a conceptual description would've been in order.
I don't think the idea of updating our estimate of the chance of something based on new evidence is the worst hand-wavy description of Bayes' Theorem. At least for a nontechnical audience.
Earl Warren somewhat had good reason to be suspicious of the Japanese after what they did to infiltrate Singapore prior to the War... Anyway so I take it Baye's rule is about being open minded.
Okay hold your horses. Don't let Galef's video persuade you just yet of the power of what she calls “Bayes's rule”. Given Galef is clearly influential within online discussions of rationality, here are two reasons why Galef's attempt is problematic as an attempt to convince people to adopt Bayes's rule. (1) @ 0:59 - "Bayes's rule is provably the best way to think about evidence." (Galef). Bayes's Rule states: P(A|B) = {P(B|A) * P(A)} / P (B) Furthermore, P(A|B) is defined as = P(A & B)/P(B) First off, Galef doesn't acknowledge that a mere proof of a theorem is not sufficient evidence of its epistemic worth. Proofs are always relative to axioms and a theorem proved from controversial axioms is controversial too. Note that Bayes's rule presumes the truth of a formalism with the structure of the Kolmogorov axioms for probability. Writing several hundred years before Kolmogorov, and writing as a contemporary of Thomas Bayes himself, the prominent 18th-century natural philosopher Jean d'Alembert (famous for the d'Alembert wave equation in mathematics) would go on to deny as elementary aspects of the Kolmogorvian framework as the claim that P(A & B) = P(A) * P(B), for independent A and B. He argued instead that all events are conditionally dependent (Daston, 1979). So while committing oneself to the Kolmogorov axioms may prevent you from being Dutch-booked, this is merely one epistemic standard and is not necessarily “the best”. Absent an argument for this formalism's superiority over all competitors, there is no reason to agree with her that Bayes's rule is some kind of catch-all solution to problems of reasoning. (2) @ 1:13 - "And I don't think that the math behind - the math of Bayes's rule is crucial to getting benefit out of it in your own reasoning or decision making." (Galef). Considering she has a statistics degree from Columbia, this is a puzzling claim for her to make. Remember that Bayes's rule states the following: The probability of a proposition A conditional upon B (A|B) is equal to the probability of B conditional upon A (B|A) multiplied by the unconditional (sometimes known as 'priori') probability of A (A) divided by the probability unconditional probability of B. Furthermore, since P(A|B) = P(A & B)/P(B) it follows that all the probabilities used in Bayes's rule are based on unconditional (prior) probabilities. It is contentious though what is meant by the unconditional probability of an event's occurrence. After all, when I think that it is probable that the sun will rise tomorrow, I am formulating this belief based upon my probabilistic assignments of the truth about other background beliefs (.e.g - that my memory of past days is sound, that the sun somehow spotaneously cease to exist, etc.) So it seems even such basic beliefs as my belief that he sun will rise tomorrow is itself conditional argument. In fact, according to historian of probability Lorraine Daston, when Bayes was writing his 'An essay towards solving a problem in the doctrine of chances' (1763): “Section II contained the scholium that apparently caused Bayes himself doubts grave enough to withhold the essay from publication...Bayes had had misgivings about the postulate that permitted his theorem to be generalized to cases where nothing is known about the prior probability of A and B.” (Daston, 1988, p. 258). Even the great 20th-century economist John Maynard Keynes, in his influential 'Treatise on Probability' (1921), argued that all probabilistic judgments should be understood as partial entailment relationships between at least two propositions: “A great deal of confusion and error has arisen out of a failure to take due account of this relational aspect of probability...[I]f 'a' is so related to 'b', that a knowledge of it renders a probable belief in 'b' rational, we cannot conclude anything whatever about 'b' which has not reference to 'a'” (Keynes, 1921, p. - 6). While Galef is clearly a well-intentioned person, her hasty claims about Bayesianism and its history aren't helpful, and possibly harmful, for viewers trying to learn about epistemology and probability theory. Instead, she should avoid using such ideological language as “Bayes's rule is provably the best way to think about evidence." I agree with a comment below that what she is describing is simply just a certain form of common sense that isn't necessarily better than other kinds of common sense. It also doesn't follow that common sense needs to be Bayesian in method nor that Bayes's rule will help you out in your everyday life. After all, it takes a lot of time to explicitly calculate one's priors. References Daston, Lorraine. (1979). D’Alembert’s Critique of Probability Theory. Historia Mathematica. 6, pp. 259 - 279. Daston, Lorraine. (1988). Classical Probability in the Enlightenment. Princeton, NJ: Princeton University Press. Print. Keynes, John Maynard. (1921). A Treatise on Probability. London, UK: Macmillan and Co. Print.
Your post is a giant hock of sh*t. Bayes theorem, like all theorems, derive from axioms. There's nothing special about that. If you don't like it, then you don't like the entirety of probability theory. So don't try to use aspects of the theory you do like to b*tch about aspects of it you don't like.
I don't think there is a way to put it politely, but it saddens me to see people having opinions about things they do not comprehend, like statistics. I explained somewhere what is Bayes' Rule, which is a mathematical theorem, and how is it used. Mrs. Galef's video isn't only unrelated to any mathematical theorem, (those things derived from axioms, and/or other theorems, which aren't formalisations), but it's also 100% inane. I don't have any more time for this. Peace!
Bayes' Rule is the equation :P And incidentally, we're using it in every day life when we do pools. For example, if you know how many men will vote for X, and how many college educated people will vote for X, you can calculate how many man who are college educated will vote for X, without doing a specific pool. Second, Math is basically a language. It's nice to know it before you talk about it. Now please continue to be rude and wrong at the same time :). Peace!
Lol, no. Bayes' Equation allow you to calculate a marginal probability when you know a general probability and another marginal probability. But yes, it's not your fault that on a channel that have Lawrence Krauss, there is also Julia Galef. I won't continue this ad nauseam, but it would be nice if you'd just be true to yourself and admit that you don't know what you're talking about. Peace!
Thanks for explaining the obvious (to people who think). Facts and evidence over emotion and feelings! Wow! What a concept! BTW, how is that hope and change working out? "Youth is easily deceived because it is quick to hope” - Aristotle. Where was Aristotle when we needed him? And cheering wildly at fundamentally transforming the greatest country in history? But thanks for taking on trillions in debt and ruining the futures of you, your children, and grandchildren.
What she points out in the end of the video is that we tend to stick with our beliefs very much. What you do with Bayesian reasoning, is to make sure that every piece of evidence will affect your beliefs about things, not just very large pieces of evidence. If for example there was very small signs of subterfuge amongst japanese americans, you would shift your beliefs slightly to be more suspicious. You get closer to "I'm a 100% sure they are tricking us" but might still be far away from it.
The way it's phrased makes bayes rule seem like something that gives rise to conspiracy theories rather than work as a tool against such faulty reasoning... In the case of the japanese-americans for example, the fact that no sign of subterfuge amongst the japanese-americans was found, would (with bayesian resoning) update your prior belief to one that is less suspicious of japanese-americans. if however there was evidence, you would update your prior belief to one that is more suspicious.
Probably there are at least two human characteristics working against each other. One is "my team" People tend to pick their team, and to greater or lesser degrees remain faithful by fending of any challenges to that way of thinking or set of "truths" Another is the need for an objective assessment of reality. but the group instincts most often prevail even when contra evidence is overwhelming.
Isn't that just Occam's Razor? Hell, just read David Hume... Idiot drops loses keys, finds them later in unlikely place - "Praise Jesus, its a miracle!" David Hume sees this and asks; "what is more likely? That the very laws of nature have suspended themselves in YOUR FAVOR (Imaginary Jesus/God returns your keys indirectly), or that you simply failed to retrace your steps and, by chance, merely stumbled upon them again later?" This isn't revolutionary thinking, it's just an amalgamation.
It makes more sense to stop calling it Bayes rule and just call it objectivity because when you lose attachment to your ego and allow yourself to see the objective perspective rather than being fully immersed in your subjective perspective you have genuinely grown as a person and its not some thing a guy came to understand its a stage in human growth. Not a stage every human reaches even upon old old age.
...part 3 what the woman in the video describes as changes in thinking when "seeped in" bayes rule for a while, is just dedicating more attention/time/resources to updating our believes, doing more of what we already do, by consciously being more focused on doing it. probably due to realizing that our current level of updating is not as good as it could be, after thinking about it (due to thinking about it after learning about the bayes rule) ...
the only info we are completely oblivious to is the info that we don't process (IE the brain doesn't process all info that the sense get, it "chooses" only the info that it deems worthwhile, to save energy/resources) and the info that we forget (the brain forgets things that are deemed not as worthwhile as other info competing with the limited brain space); so yes, we ignore/forget info that the brain considered not worthwhile to get/have ...
... tip over to the other side of 50%, which is when we change our behavior most drastically. If I predict it's not worth it to take my umbrela, and new info providing stronger evidence that it'll rain but not enough to make me believe that it's worth it to bring the umbrella, no noticeable change happens in my behavior; only when there's strong enough new evidence that changes my belief enough that makes me belief it's worthwhile, do I "change my mind" and bring the umbrela.
So, Bayes' rule is a formalization of how to change your mind. So... formalized how? Is it a process like some sort of mental organization technique? A mathematical analog for the logical process? This video feels like the first 3 minutes of a 15 minute video. Pragmatically, what is Bayes' rule and how would one use it? These two questions are missing from the explanation. All I gleaned is that there is a thing called Bayes' rule and it would be useful to use if I ever learned how.
Baye's Rule or Bayesian inference is pretty basic in the introductory concept. She explained it in the first minute just fine. All it states is that the likelihood of an event is easier to predict as you gather more evidence. It seems obvious, but in practice we tend to ignore evidence in favor of our preconceived assumptions. Non-Bayesian - "If she weighs the same as a duck, then she floats, and is therefore a witch!" Bayesian - "If she weighs the same as a duck, then she is probably a duck."
Bayes' Rule is pretty math-y, which is probably why she doesn't explain what it means. From what I've gathered though, in layman's terms Bayes' Rule is a rule used to "update" your prior beliefs of some fact/event in light of new evidence. If anyone reading these comments who knows Bayes' Rule sees this and agrees with how I put it, please like this comment so more people can see it!
"if men don't paint their faces, there's no good reason women should." That's just nonsense. Here's one possible reason: Men are biologically wired care a lot more about the looks of females than females care about the looks of males. You seem to want to reduce this crusade of yours against makeup to a question about logic, when in fact it's not about logic, it's about accomplishing things in reality. In this case, enhancing one's sexual attractiveness.
"I would be a hypocrite if I denied people their religious delusions." There's a difference between saying "I prefer to think about gravity as fairies pulling things together, because I find the science related to gravity distasteful" and "Yahweh tells me that homosexuals, adulterers and people working on the sabbath should be put to death". The latter delusion can cause severe harm and is not a personal matter.
Science has taught me that love is purely chemical and brought on by millions of years of evolution and yet I allow myself to be delusional about it. I get off on the feeling of being in love and loving family and friends. I prefer to think that love is some magical and mystical force than animal instinct and chemical rushes. Belief in a deity is natural. It sprang up independently all over the globe. I would be a hypocrite if I denied people their religious delusions.
I dont see how hes off putting. Religious people can take pretty much any information that contradicts their beliefs and turn it around to confirm their beliefs. Just like Julia Galef is talking about staticians who dont use Bayes' rule in their everyday life. The point is anyone can have delusional beliefs. Beliefs only create biases that prevent people from seeing things the way they actually are. What if someones "right to their beliefs" infringes on others right to live in a sane society?
She does explain what Bayes' rule is (though it seems to come clear only at the very last moment of the video) I think it says that when encountering new information in the world one should not simply ask "does my theory explain this", like the conspiracy theorists who always find a way to maintain their theory Instead, one should also ask "does another theory explain this better", which is a different question, that apparently most people don't ask themselves I hope she marries me for this
Bayes' Rule basically means that the probability of something to be true is the prior probability of it being true without some piece of evidence multiplied by the probability that it's true when you do consider the new evidence. This is not disputed even by non-Bayesians. What Bayesians say is that after you've made this determination you should change your prior probability to now equal the result that you just arrived in. It's a way of iterating beliefs to be more accurate with evidence.
So the chance that you think you're right, even though you're wrong, depends on the chance that you're right in the first place and the chance that you're wrong even though you think you're right. Equally, the chance that you're wrong even when you think you're right will be proportional to the chance that you might think you're right, even though you're actually wrong. It can be applied in alot of ways I guess, Bayes' rule.
P(A|B) proportional to P(A)*P(B|A) The probability that you're actually a good driver, if you've been in a car crash, is proportional to the chance that you're actually a good driver multiplied by the probability that you would get into an accident even though you're a good driver. So if you've been in a car crash, the chance that you're still actually a good driver depends greatly on the chance that even good drivers get into accidents.
I am not familiar with it but based on the limited hints in the video it seems to be a way of thinking that involves assessing your way of thinking and other ways of thinking, then critiquing them and figuring out which one makes the most sense and relies on the least assumptions in order to be true. Sounds like a bunch of common sense to me... Then again i am a sciences university undergrad ;b
If you don't get it, then you're must likely a bit intellectually lazy. She explicitly says that the math is not necessary in order to understand Bayes' rule, but the general principle: when new information comes along adjust your views - can be picked up and used by anyone. This big think required you to think a little, I guess that is what you should expect and WANT from this channel.
A newborn sees his 1st sunset, and wonders if the sun will rise again. He assigns equal probabilities to both outcomes by placing 1 white and 1 black marble in a bag. When the sun rises, a white marble goes in the bag. The chance that a random marble from the bag will be white (belief in future sunrises) has gone from 1/2 to 2/3. The next day, the child adds 1 white marble, and the probability goes from 2/3 to 3/4. The belief is modified to become near-certainty that the sun will always rise.
That doesn't make any sense. If the content of the video is supposed to be exactly what the title says, then you're wrong too. It shouldn't be a video about where it should be applied. The title is not "Where to apply Bayes' Rule". It should literally be an instruction telling you to "Think Rationally with Bayes' Rule". Her previous video on the channel explains the Sunk Cost fallacy. Explains it, not just tells you to look it up. Why is it unreasonable to expect the same here?
I google all the time. The answers I'm finding are expressed as math I don't understand. I think I found a word description, but I wasn't sure I understood it. Either way, since she brought it up, she ought to provide a definition as part of her talk as a matter of form, otherwise, who is she talking to? The choir? You have to already agree with her to even understand what she's saying.
As an example, say A is "I'm a scientist" and P(A) = 0.2 because about 20% of people have a job in science. Now say B is "I know Bayes' rule", then P(B|A) might be about 0.9 because most scientists (should) know it. Lastly, say 25% of people (overall) know Bayes' rule: P(B) = 0.25. Then the probability that you're a scientist, given that you know Bayes' rule, is P(A|B) = P(B|A) * P(A) / P(B) = 0.9*0.2/0.25 = 0.72, so 72%.
Explaining Bayes' theorem is extremely easy - you look at each possible outcome, you look at how likely that outcome is, and you choose the path that leads you to the outcome with highest likelihood of success (whatever success is in this situation). This being said, I too feel Julia should've at least mentioned this. The explanation, along with another 20 seconds of talking or so, would've made for a far better (and more concrete) advice, I think... =\
To everyone who doesn't know, Bayes' Theorem is this: the posterior (conditional) probability P(A|B) for A, given B, is equal to the prior probability P(A) multiplied by the conditional probability P(B|A) and divided by P(B). So P(A|B) = P(B|A) * P(A) / P(B) which is big if e.g. the chance of A, irregardless of B, is large AND the chance of B, given A, is also large. Or if e.g. the prior probability of B is very small.
If there were such a good explanation I should not need a great base in economics. She simply did not explain what (Bayes Rules) are. I use decision theory in my work all the time. As a result I am very familiar with Bayesian mathematics. That said, the vast majority of people won't have any prior knowledge of the work of Reverend Bayes. No reason they should. Without that prior knowledge her talk cannot deliver the titles implied meaning. Nor can it be understood.
Actually the title does not mention where Bayes rules should be applied. More it seems to give the command to "Think Rationally via Bayes' Rule". This of course implies that a complete guide on how to follow said command is forthcoming. Given both linguistic and cultural norms here in the U.S. The expectation of a description of how to think rationally (Bayes Rules) would be included in the video. I am glad you can read the title, though I am concerned with your lack of comprehension.
No she did not explain "generalized Bayes rules" in specific she did not even mention them. She simply stated that they are a means of changing a belief based on new evidence. Without explanation she could be referring any process in which the input changes the output. Her statement is therefore so general as to be useless. The admissible decision rule and Bayes rules are very specific processes used in applications like decision theory.
(h t t p : //) yudkowsky (dot) net/rational/bayes Don't be intimidated by the size. Its mostly made up of different (optional) examples of the theory. When you understand one well enough that it clicks, that's usually enough Remember the prior probablity. Remember the data can switch from talking about a % of a specific population (women who used breast cancer tests), OR a general one (women in general) Like how Earl Warren not observing the odds of any civilian actually becoming terrorist
lol she literally said what Bayes' rule is. It's when you rationally change your belief based on new evidence that is provided. In fact that's what an entire side of statistics known as Bayesian statistics is based on. It can be explained mathematically using conditional probability but that's not necessary for you to understand what it is. So in my opinion, this was not a "waist" of time.
I disagree, Scott Ritter, former Chief Weapons inspector laid the whole case out. He stated that the inspectors accounted for like 95 % of Sadaam's weapons as being destroyed. I heard Scott and realized this guy is genuine, also went to one of his lectures. Those in power wanted the war, and the democrats being cowards, went along with it.
Pls. tell me, if I have no information about the probability of a star in Andromeda Galaxy to turn into a supernova, does it mean that it has less chances to do so, as this woman is saying? Do you understand Bayes' equation? I feel like I'm talking to creationists about evolution through natural selection.
Lol, again nonsense. What value have P(B) in your equation? Don't tell me, 0 :P If you have 0 information about an event, that doesn't say anything about the probability of that event. Ffs, Bayes' Rule deals with statistical information, not with evidence, or lack of it. It's a theorem derived from statistical axioms, not a substitute for logic.
How about defining Baye's rule from the statistical equation FIRST and THEN transform it into a set of reasoning. Would suddenly make the video usefull, but instead we are stuck with a brad who doesn't guite know what she is talking about. And the existence of an applied rationality centre blows my mind. Trying to take ownership over common sense is just stupid....
She kind of did explain what Bayes rule is. It's process for finding out what your best bets are when it comes to believing something based on the given evidence, and when it's time to change beliefs. She didn't explain the mechanics of it because mathematical models are bloody impossible to explain without writing and illustration. Google it ya lazy sods!
reading a few comments here makes me feel ashamed to be human. BIG think is a brilliant channel and this lady knows her stuff, she makes good points and good examples. SOme comments here are akin to the chicken or egg argument, when you start explaining it in depth ppl simply zone out cause they dont hear the answer they want.
Actually , she did present a general explanation of Baye's Rule . The problem is , how much of the general public would be willing to apply that logic ? According to Michel Foucault's dismal conclusion , nobody would - we all interiorize our existence to such an extent , that no one listens to anyone else , unless it suits them .
Apparently understanding the power of Bayesian reasoning makes you completely oblivious to everything that you are not consciously applying the reasoning to. Namely, you completely neglect the fact that big think reads the comments and complaints are a necessary form of feedback. But you know, enjoy your high horse.
Problem: Bayes' rule no longer applies in QM. (although, to be fair, I should mention some people have tried to make it work) We would not benefit from making Bayes' rule an intuition, because then the whole of QM becomes even less intuitive. Also, she makes Bayes' rule sound like statistical hypothesis testing, which it isn't. But I understand what she's getting at.
Don't bother having a conversation with corcoos. I've tried explaining it to him/her but it's obviously way beyond his/her understanding. Corcoos is stuck in the land of statistics unable to understand the implications of Bayes Rule in any situation that doesn't concern figures and polls.
... (IE info that it considers false due to it not making sense with regards to the rest of it' "world view") but only because of limited time/energy/resources, not because of not using the bayes rule. and as I said, the calculations are not perfect, we make the best calculation we can. ...(again)
Unfortunately, that's not how human minds work. The world might be a much nicer place if it were. We can be completely oblivious to information that doesn't fit in with our biases. A really great book related to this topic is 'Thinking, Fast and Slow' by Daniel Kahneman.
I agree that three minutes and twenty three seconds for Bayes' Rule is way too little for such an important topic. Bayes' Rule captures a mathematically demonstrable and provable truth at which humans are usually intuitively bad at. Which is why we would need extra time with it.
Bayesianism is great, it can be incredibly helpful in making people think more rationally and consider more alternative explanations that they might not otherwise consider. But Bayesianism does have some problems. For instance it's not clear how one would judge evidence collected in the past with it.
One of the most if not the most decorated military unit in American history was 442nd regiment in ww2. They were all Japanese American fighting Nazis while their families were in American concentration camps. That's fact, your bayes rule would not be able to argue true character.
In fact many things weigh the same as a duck without being a duck and anyway how much does a duck weigh? Is it a young duck or a fully grown mature duck. Is it a fat duck or a thin duck? This leaves us just as we started without a clue.
Completely meaningless to say you're using Bayes Theorem without actually doing the calculations. Which you can almost never do on a day to day basis. Everything she's said reduces to just saying "Watch out, human's are prone to confirmation bias."
Please tell me that someone pointed out the obvious logical fallacy of: "If Japanese Americans are conspiring, because they are being quiet, than all Americans that are quiet (which is easily 99% of them) are therefore conspiring".
Seriona1, false. She did not define bayes rule only gave examples of what its not and hinted that it's somthing to do with realistic thinking. In truth people who dont already know what it is will not learn what it is with this video.
If something weight the same as a duck, then it's probably not a duck, since the weight of a duck is pretty common. That being said, what you're saying isn't only nonsense, but it has nothing to do with Bayes' Rule.
Clearly this woman does not know what Bayes rule says or is. Why do you let her speak? It is just a shallow marketing-blurp of shiny words and zero content. Just go to 1:00 and try to find out what Bayes Rule _is_.
Do not waist your time watching this. At no point does she go to the trouble of explaining what Bayes rule is or even describing it in broad terms. If you would like to know what it is you can look at the Thomas Bayes wiki.
Also, can you give me, pls, the Bayes' Equation for the probability of an American Japanese to be a threat to US security during WW2? Pls. enlighten me, since I'm too stupid to understand.
Lol, where did you get that, really? It's a formulae to calculate the probability of an event, when you have statistical data to work with. When you don't operate with probabilities, you use logic.
but all evidence makes a dent in how strong our belief about things are. it just transpires (on things that can only be taken 2 different actions) into observable behaviour when it tips the balance.
So you are saying someone is not "intellectual" because she uses makeup? I would say that your belief that appearance somehow contributes to intellect is a sign that you are not an intellectual.
Perhaps It is explained well if you know what Bayes rule is, but the closest I got out of the video is that you should not only revise your view of the world when you find. Contradicting evi
Actually she explained it very well and how it affects you on a daily basis. But obviously you can't transfer that onto your own life. So you are angry on how she didn't explain it simpler.
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The problem with conspiracies is they keep expanding till well the whole damn planets in on it to make them work logically but the logic like a rusty bucket full of holes
It's actually surprising how many people claim to be "open minded" but then quickly retreat back to their comfort zones once presented with a radical new perspective.
It's a hard task to be open minded 24*7..sometimes it can be exhausting being too perfect or even attempting to be. I think we are mostly open minded to accept the opposing ideas when it doesn't affect us that much.
Frankness, not openness is the key.
@@sanjarcode please explain your argument if you want people who encounter this reply section to take your opinion seriously, I can't be guessing
If you accept everything as being true, you are setting yourself up for bullshit. Only scientific, objective physical reality is true. Semantics, contemporary philosophy, they are bullshit mental clownery created to deceive.
Humans are built for survival, and only the truth where it is accidentally conducive to survival
Confirmation bias is a cognitive bias underlying fallacious lines of reasoning. By definition, cognitive biases need to be common. Common likely because it is partly perpetuated by our biology. I imagine that believing something that everyone in the tribe does would allow them to work well together and reduce conflict? That's my guess
Better yet, actively try to poke holes in the things that you believe the most.
My lost bro😁
100%
That’s just called “science”. Not sure what Bayes’ rule has directly to do with it.
Bayes' Theorem is an important tool in probability, but my statistics book was terrible in its attempt to verbalize it. Basically, it is very much as Julia described it: we think we know (with some degree of certainty) how an event will occur. However, we often learn in the future that our belief was wrong, so we go back and revise our beliefs (posterior probabilities). My book gives a very boring example having to do with credit cards and the probability that someone will default, so I won't bore anyone with those details. The implications are important, though: if something more accurate comes along than what we believe to be right and correct, we must be willing to change our paradigm in order to have a better understanding of the way the world works.
The best presentation I know of can be found in "Probability Theory: The Logic of Science" by Edwin T. Jaynes.
You neglected to explain Bayes' rule.
+Matt Van Helden because it is so basic and a quick google gives you P(A|B) = P(A) P(B | A) / P(B)
+Powerdriller Power The formula is useful because it is often easier to get the probabilities on the LHS of the equation.
Maybe you find it "discouraging and too cryptic" because you have not read the proof, which is very short and easy. Think for a minute and you will understand it.
That joke is crap and tells you very little about Baysian reasoning.
Any time you are going to give a lecture on something you should explain it first. And when I googled at the time of watching the video I didn't find anything. It so doesn't intuitively make sense after seeing the formula and watching the video. There should be a better explanation, that's all in saying.
That's because this is horseshit, and this video is the "thinking" equivalent of "BOSTON SCIENTISTS HAVE DISCOVERED A REVOLUTIONARY NEW PERFORMANCE SYSTEM. TRY THIS ONE WEIRD TRICK TO BUILD MUSCLE FAST..."
Matthew Van Helden she said that beliefs are greyscale, and that level of confidence changes as new evidence comes. She explained the relevance without giving out a formula. You were waiting for the formula and thus missed the explanation that mattered more.
"Is there any knowledge in the world which is so certain that no reasonable man could doubt it?"
-Bertrand Russell.
Your own conscious experience.
@@Mr96akaal What IS your conscious experience?
JoeBlu I’m being. Being is just perceiving. You see how I can perceive being.
@@Mr96akaal And what gives you the perception of being? your senses? all of which susceptible to illusions. "Cogtio ergo sum" is a good sentiment but what is perceiving you perceiving yourself?
JoeBlu That’s the point. The only knowledge that is certain is this very experience. Alan watts said “just how a knife can’t cut itself, you can’t out be being.”
My last name is a rule! :O
you rule!
@El Pacificador are you talking about those guys who believe in reincarnation?
hey are you gonna tell us what Bayes' rule is or do we have to pay for that?
Here she explains... th-cam.com/video/BrK7X_XlGB8/w-d-xo.html
LOL
@@HakWilliams Nice that a video was created to address this - eventually....
Male humans solving disagreements by display of strength via varying degrees of violence is also natural. Just because something is natural does not necessarily mean it makes sense in today's society.
This is all great and awesome but then confirmation bias comes in and destroys everything in our daily thinking.
would be nice to explain what they bayes' rule actually is.
It's hard to concentrate on what she is saying .....
Speed it up a bit or two 😂
Realizing most people didn't already think like this is what ended my rebellious teen phase. Learning that my parents had gifted me something from infancy most people require years of schooling to obtain.
Duck.
Duck@@demonetizedz1001
Duck
she's very easy on the eyes.
It's a very good informative video. I'm amazed by how much dislike it got. Maybe the prerequisites to understand this video is beyond those who have disliked.
A video about Bayes' Rule that doesn't say what Bayes' Rule is 🤔
She states some of the principles of Korzybski's General Semantics. Look up the book "Language in thought and action" by Hayakawa, or "Language habits in human affairs" by Irving J. Lee
It seemed interesting but at one point I was wondering if she really knew what Bayes theorem means. My guess is not,otherwise she could have given one example.
i'd like to rule that bey, know what I mean
There is a flaw in this. If you are too excessive in trying to get all the facts, you will never get anything done. Sometimes you need to charge in headlong with limited information.
It's a balancing act between bravery and patience. Too much patience, and nothing gets done. Too much bravery and you ruin yourself and whatever you're working on.
Nice , but what I think is that patience is more important than bravery cause the great things are made with it and not with bravery, Even if (like you say) bravery is necessary, bravery is like a surface (a shape of something:the first impact of an action) , patience is something more deep
itsiwhatitsi
The mind will always come up with excuses to, "do a little more research".
Jeff Bezos didn't spend 7+ years planning.
He spent 7+ years *acting*.
manictiger The creator of Amazon? Is him? Ok anyway I agree with you.. what I just try to say is that patience is a value that you must have if you go true years in which not necessary happen something (like in the internet business). Also a brave man without patience , is superficial and can't really improve. What I think is that it's necessary to be brave but the patience is a very strong value that can really open your mind, in the process of improving yourself. I agree anyway: do with bravery, but think with patience
itsiwhatitsi
The mind plays games on itself. Patience is important, but cowardice will mask itself as patience, if you let it.
Once you conquer your own mind, then nothing can really stop you.
manictiger That's interesting
Now I am no expert... but sounds to me like you're confusing logical and reasonable thinking with a formula used for conditional probability.
not really, there is a way to use bay's theorem as a basis for a new way to do logical reasoning.
and yet "the way" is not described or explained. Just many words with little meaning. One could compare to political debates. The only thing described in this video was sound and sequential reasoning. One does not require Bay's theorem to comprehend logically.
True, yet bayesian reasoning des exists, even if Julia made a poor job explaining it.
aven871 It's not like the internet wouldn't provide you the facts about it.
Jaqxone Don't be a tool... She was just talking in circles period. Most Big think guests are incredible. She wasn't.
Religious people , watch and learn
Well, part of the problem is that to go into Bayes requires more time than is alloted to this Big Think introduction video. As far as I can extrapolate, Julia only had time to talk about the benefits of using Bayes Theorem, not necessarily what it is or how to use it in everyday thinking.
But about those equations: (A|B) is the probability that B is true given that A is true. That's what the symbol "|" means. I've found this out very recently.
Relevance: ....hard to talk about in 500 chars
She explained the rule just fine...
Still sounds like a bunch of obvious statements to me. Maybe I should review Bayes' formula (which I've studied but forgot long ago...). Or maybe she could have provided a quick recap of it. Just sayin'
That is the thing with probability. Things seem pretty obvious at first but can quickly become unintuitive very quickly. If you have studied stochastic processes, you will see this time and time again. Especially when considering expected times, etc. I think you are right, maybe you should review Bayesian statistics. And more importantly, apply it and see for yourself.
Thanks. For the record, I was not implying that Bayes' formula itself is obvious. Only her words in this video seemed to me not that insightful.
Anyway there are quite a bit of videos of her talking about these same concepts more extentensively, so I guess I'll just have to go check them out...
Since she didn't actually state Bayes's Formula for those of us who didn't remember what it's about, I went and looked it up myself. Basically, the most important application of the rule is when it comes to the possibility of false positives, and how we apply probabilities.
why is she so magneticc ughhh
Love this: the use of mathematical principles outside mathematics :) awesome
Yes!
I was about to burst a blood vessel towards the end when she STILL HADN'T TOLD US WHAT BAYES RULE IS!!! Would have appreciated a simple "here's what bayes rule is. NOW let's discuss what it means for your every day life". /sigh/
She's trying to explain math. If she rattled off what Bayes Rule was p(A|B)=(p(B|A)*p(A))/p(B), you probably would have clicked away.
Bayes rule is kind of like shaping a blob of clay into a recognizable shape.
The clay is your current opinion and recognizable shape is someone else's opinion. The more info and supporting evidence for that other person's opinion is like molding the clay into the shape. But may or may not convince you in the end, since it doesn't look completely like the shape.
Bayes' rule is where there is a higher chance of probability.
too many people will cherry pick their dissent to an argument throwing out strawman and ask improbable scenarios to discredit.
Bayes' rule counters those who bring up the rare of the rare that can occur saying that since 0.000001 percent chance something won't happen means it we can't judge.
but in fact we can judge based on reasonable probability.
you didn't actually introduce Bayes' Rule
تا وتاواوزتظ.ططجطج
She said at the start of the video, that she wasn't going to go into the mathematics of Baye's equation, just a way to use the concept of updating one's beliefs based on new information.
She implies at least, that a lot of the time we walk around with a beliefs as though they are black and white (1 and 2). However, when we apply Baye's rule we find that our beliefs arn't as bullet proof or as infallible as we previously thought; Rather, the degree of certainty behind our beliefs is more grey scaled, as she said, (between 0%-100% - a probability if you will) meaning that given enough evidence for a belief other than our own, we can make a more rational decision.
I think you also have to take into account, the video is only 3 minutes, so it would be hard to go into depth of the mathematics that are operating within Baye's equation. This is a simplified explanation for those who are laymen in mathematics.
Caleb I'm a fan of Julia's work, but even though I enjoyed the video, I agree with Will the this was not her best.
She told us about some of her *conclusions* and perspective changes after *she* understood Bayes' Theorem, but she didn't explain what the theorem *is*, nor the process of using it (at least not well), nor how she reached those conclusions. She wouldn't have had to go into the mathematics, but a conceptual description would've been in order.
I don't think the idea of updating our estimate of the chance of something based on new evidence is the worst hand-wavy description of Bayes' Theorem. At least for a nontechnical audience.
Here she explains: th-cam.com/video/BrK7X_XlGB8/w-d-xo.html
Big think is losing it,
I prefer Julia Galef's video on Bayes' Rule on her own channel: watch?v=za7RqnT7CM0
Earl Warren somewhat had good reason to be suspicious of the Japanese after what they did to infiltrate Singapore prior to the War...
Anyway so I take it Baye's rule is about being open minded.
It's just me and Julia, down by the schoolyard.
Okay hold your horses. Don't let Galef's video persuade you just yet of the power of what she calls “Bayes's rule”. Given Galef is clearly influential within online discussions of rationality, here are two reasons why Galef's attempt is problematic as an attempt to convince people to adopt Bayes's rule.
(1) @ 0:59 - "Bayes's rule is provably the best way to think about evidence." (Galef).
Bayes's Rule states: P(A|B) = {P(B|A) * P(A)} / P (B)
Furthermore, P(A|B) is defined as = P(A & B)/P(B)
First off, Galef doesn't acknowledge that a mere proof of a theorem is not sufficient evidence of its epistemic worth. Proofs are always relative to axioms and a theorem proved from controversial axioms is controversial too. Note that Bayes's rule presumes the truth of a formalism with the structure of the Kolmogorov axioms for probability. Writing several hundred years before Kolmogorov, and writing as a contemporary of Thomas Bayes himself, the prominent 18th-century natural philosopher Jean d'Alembert (famous for the d'Alembert wave equation in mathematics) would go on to deny as elementary aspects of the Kolmogorvian framework as the claim that P(A & B) = P(A) * P(B), for independent A and B. He argued instead that all events are conditionally dependent (Daston, 1979). So while committing oneself to the Kolmogorov axioms may prevent you from being Dutch-booked, this is merely one epistemic standard and is not necessarily “the best”. Absent an argument for this formalism's superiority over all competitors, there is no reason to agree with her that Bayes's rule is some kind of catch-all solution to problems of reasoning.
(2) @ 1:13 - "And I don't think that the math behind - the math of Bayes's rule is crucial to getting benefit out of it in your own reasoning or decision making." (Galef).
Considering she has a statistics degree from Columbia, this is a puzzling claim for her to make. Remember that Bayes's rule states the following: The probability of a proposition A conditional upon B (A|B) is equal to the probability of B conditional upon A (B|A) multiplied by the unconditional (sometimes known as 'priori') probability of A (A) divided by the probability unconditional probability of B. Furthermore, since P(A|B) = P(A & B)/P(B) it follows that all the probabilities used in Bayes's rule are based on unconditional (prior) probabilities.
It is contentious though what is meant by the unconditional probability of an event's occurrence. After all, when I think that it is probable that the sun will rise tomorrow, I am formulating this belief based upon my probabilistic assignments of the truth about other background beliefs (.e.g - that my memory of past days is sound, that the sun somehow spotaneously cease to exist, etc.) So it seems even such basic beliefs as my belief that he sun will rise tomorrow is itself conditional argument.
In fact, according to historian of probability Lorraine Daston, when Bayes was writing his 'An essay towards solving a problem in the doctrine of chances' (1763): “Section II contained the scholium that apparently caused Bayes himself doubts grave enough to withhold the essay from publication...Bayes had had misgivings about the postulate that permitted his theorem to be generalized to cases where nothing is known about the prior probability of A and B.” (Daston, 1988, p. 258).
Even the great 20th-century economist John Maynard Keynes, in his influential 'Treatise on Probability' (1921), argued that all probabilistic judgments should be understood as partial entailment relationships between at least two propositions: “A great deal of confusion and error has arisen out of a failure to take due account of this relational aspect of probability...[I]f 'a' is so related to 'b', that a knowledge of it renders a probable belief in 'b' rational, we cannot conclude anything whatever about 'b' which has not reference to 'a'” (Keynes, 1921, p. - 6).
While Galef is clearly a well-intentioned person, her hasty claims about Bayesianism and its history aren't helpful, and possibly harmful, for viewers trying to learn about epistemology and probability theory. Instead, she should avoid using such ideological language as “Bayes's rule is provably the best way to think about evidence." I agree with a comment below that what she is describing is simply just a certain form of common sense that isn't necessarily better than other kinds of common sense. It also doesn't follow that common sense needs to be Bayesian in method nor that Bayes's rule will help you out in your everyday life. After all, it takes a lot of time to explicitly calculate one's priors.
References
Daston, Lorraine. (1979). D’Alembert’s Critique of Probability Theory. Historia
Mathematica. 6, pp. 259 - 279.
Daston, Lorraine. (1988). Classical Probability in the Enlightenment. Princeton, NJ: Princeton University Press. Print.
Keynes, John Maynard. (1921). A Treatise on Probability. London, UK: Macmillan and Co. Print.
Best discussion on this matter on this thread. Thanks
Your post is a giant hock of sh*t. Bayes theorem, like all theorems, derive from axioms. There's nothing special about that. If you don't like it, then you don't like the entirety of probability theory. So don't try to use aspects of the theory you do like to b*tch about aspects of it you don't like.
You're what I call Crippled Smart.
I don't think there is a way to put it politely, but it saddens me to see people having opinions about things they do not comprehend, like statistics. I explained somewhere what is Bayes' Rule, which is a mathematical theorem, and how is it used. Mrs. Galef's video isn't only unrelated to any mathematical theorem, (those things derived from axioms, and/or other theorems, which aren't formalisations), but it's also 100% inane. I don't have any more time for this. Peace!
Bayes' Rule is the equation :P And incidentally, we're using it in every day life when we do pools. For example, if you know how many men will vote for X, and how many college educated people will vote for X, you can calculate how many man who are college educated will vote for X, without doing a specific pool. Second, Math is basically a language. It's nice to know it before you talk about it. Now please continue to be rude and wrong at the same time :). Peace!
Lol, no. Bayes' Equation allow you to calculate a marginal probability when you know a general probability and another marginal probability. But yes, it's not your fault that on a channel that have Lawrence Krauss, there is also Julia Galef. I won't continue this ad nauseam, but it would be nice if you'd just be true to yourself and admit that you don't know what you're talking about. Peace!
Thanks for explaining the obvious (to people who think). Facts and evidence over emotion and feelings! Wow! What a concept! BTW, how is that hope and change working out? "Youth is easily deceived because it is quick to hope” - Aristotle. Where was Aristotle when we needed him? And cheering wildly at fundamentally transforming the greatest country in history? But thanks for taking on trillions in debt and ruining the futures of you, your children, and grandchildren.
What she points out in the end of the video is that we tend to stick with our beliefs very much. What you do with Bayesian reasoning, is to make sure that every piece of evidence will affect your beliefs about things, not just very large pieces of evidence.
If for example there was very small signs of subterfuge amongst japanese americans, you would shift your beliefs slightly to be more suspicious. You get closer to "I'm a 100% sure they are tricking us" but might still be far away from it.
The way it's phrased makes bayes rule seem like something that gives rise to conspiracy theories rather than work as a tool against such faulty reasoning...
In the case of the japanese-americans for example, the fact that no sign of subterfuge amongst the japanese-americans was found, would (with bayesian resoning) update your prior belief to one that is less suspicious of japanese-americans. if however there was evidence, you would update your prior belief to one that is more suspicious.
Probably there are at least two human characteristics working against each other. One is "my team" People tend to pick their team, and to greater or lesser degrees remain faithful by fending of any challenges to that way of thinking or set of "truths" Another is the need for an objective assessment of reality. but the group instincts most often prevail even when contra evidence is overwhelming.
Isn't that just Occam's Razor? Hell, just read David Hume...
Idiot drops loses keys, finds them later in unlikely place - "Praise Jesus, its a miracle!"
David Hume sees this and asks; "what is more likely? That the very laws of nature have suspended themselves in YOUR FAVOR (Imaginary Jesus/God returns your keys indirectly), or that you simply failed to retrace your steps and, by chance, merely stumbled upon them again later?"
This isn't revolutionary thinking, it's just an amalgamation.
It makes more sense to stop calling it Bayes rule and just call it objectivity because when you lose attachment to your ego and allow yourself to see the objective perspective rather than being fully immersed in your subjective perspective you have genuinely grown as a person and its not some thing a guy came to understand its a stage in human growth. Not a stage every human reaches even upon old old age.
...part 3
what the woman in the video describes as changes in thinking when "seeped in" bayes rule for a while, is just dedicating more attention/time/resources to updating our believes, doing more of what we already do, by consciously being more focused on doing it. probably due to realizing that our current level of updating is not as good as it could be, after thinking about it (due to thinking about it after learning about the bayes rule)
...
the only info we are completely oblivious to is the info that we don't process (IE the brain doesn't process all info that the sense get, it "chooses" only the info that it deems worthwhile, to save energy/resources) and the info that we forget (the brain forgets things that are deemed not as worthwhile as other info competing with the limited brain space); so yes, we ignore/forget info that the brain considered not worthwhile to get/have
...
...
tip over to the other side of 50%, which is when we change our behavior most drastically.
If I predict it's not worth it to take my umbrela, and new info providing stronger evidence that it'll rain but not enough to make me believe that it's worth it to bring the umbrella, no noticeable change happens in my behavior; only when there's strong enough new evidence that changes my belief enough that makes me belief it's worthwhile, do I "change my mind" and bring the umbrela.
So, Bayes' rule is a formalization of how to change your mind. So... formalized how? Is it a process like some sort of mental organization technique? A mathematical analog for the logical process? This video feels like the first 3 minutes of a 15 minute video. Pragmatically, what is Bayes' rule and how would one use it? These two questions are missing from the explanation. All I gleaned is that there is a thing called Bayes' rule and it would be useful to use if I ever learned how.
Baye's Rule or Bayesian inference is pretty basic in the introductory concept. She explained it in the first minute just fine. All it states is that the likelihood of an event is easier to predict as you gather more evidence. It seems obvious, but in practice we tend to ignore evidence in favor of our preconceived assumptions.
Non-Bayesian - "If she weighs the same as a duck, then she floats, and is therefore a witch!"
Bayesian - "If she weighs the same as a duck, then she is probably a duck."
Bayes' Rule is pretty math-y, which is probably why she doesn't explain what it means. From what I've gathered though, in layman's terms Bayes' Rule is a rule used to "update" your prior beliefs of some fact/event in light of new evidence.
If anyone reading these comments who knows Bayes' Rule sees this and agrees with how I put it, please like this comment so more people can see it!
"if men don't paint their faces, there's no good reason women should."
That's just nonsense. Here's one possible reason: Men are biologically wired care a lot more about the looks of females than females care about the looks of males. You seem to want to reduce this crusade of yours against makeup to a question about logic, when in fact it's not about logic, it's about accomplishing things in reality. In this case, enhancing one's sexual attractiveness.
"I would be a hypocrite if I denied people their religious delusions."
There's a difference between saying "I prefer to think about gravity as fairies pulling things together, because I find the science related to gravity distasteful" and "Yahweh tells me that homosexuals, adulterers and people working on the sabbath should be put to death". The latter delusion can cause severe harm and is not a personal matter.
Science has taught me that love is purely chemical and brought on by millions of years of evolution and yet I allow myself to be delusional about it. I get off on the feeling of being in love and loving family and friends. I prefer to think that love is some magical and mystical force than animal instinct and chemical rushes.
Belief in a deity is natural. It sprang up independently all over the globe. I would be a hypocrite if I denied people their religious delusions.
I dont see how hes off putting. Religious people can take pretty much any information that contradicts their beliefs and turn it around to confirm their beliefs. Just like Julia Galef is talking about staticians who dont use Bayes' rule in their everyday life. The point is anyone can have delusional beliefs. Beliefs only create biases that prevent people from seeing things the way they actually are. What if someones "right to their beliefs" infringes on others right to live in a sane society?
She does explain what Bayes' rule is (though it seems to come clear only at the very last moment of the video)
I think it says that when encountering new information in the world one should not simply ask "does my theory explain this", like the conspiracy theorists who always find a way to maintain their theory
Instead, one should also ask "does another theory explain this better", which is a different question, that apparently most people don't ask themselves
I hope she marries me for this
Bayes' Rule basically means that the probability of something to be true is the prior probability of it being true without some piece of evidence multiplied by the probability that it's true when you do consider the new evidence.
This is not disputed even by non-Bayesians. What Bayesians say is that after you've made this determination you should change your prior probability to now equal the result that you just arrived in. It's a way of iterating beliefs to be more accurate with evidence.
So the chance that you think you're right, even though you're wrong, depends on the chance that you're right in the first place and the chance that you're wrong even though you think you're right.
Equally, the chance that you're wrong even when you think you're right will be proportional to the chance that you might think you're right, even though you're actually wrong.
It can be applied in alot of ways I guess, Bayes' rule.
P(A|B) proportional to P(A)*P(B|A)
The probability that you're actually a good driver, if you've been in a car crash, is proportional to the chance that you're actually a good driver multiplied by the probability that you would get into an accident even though you're a good driver.
So if you've been in a car crash, the chance that you're still actually a good driver depends greatly on the chance that even good drivers get into accidents.
I am not familiar with it but based on the limited hints in the video it seems to be a way of thinking that involves assessing your way of thinking and other ways of thinking, then critiquing them and figuring out which one makes the most sense and relies on the least assumptions in order to be true. Sounds like a bunch of common sense to me... Then again i am a sciences university undergrad ;b
If you don't get it, then you're must likely a bit intellectually lazy. She explicitly says that the math is not necessary in order to understand Bayes' rule, but the general principle: when new information comes along adjust your views - can be picked up and used by anyone. This big think required you to think a little, I guess that is what you should expect and WANT from this channel.
A newborn sees his 1st sunset, and wonders if the sun will rise again. He assigns equal probabilities to both outcomes by placing 1 white and 1 black marble in a bag. When the sun rises, a white marble goes in the bag. The chance that a random marble from the bag will be white (belief in future sunrises) has gone from 1/2 to 2/3. The next day, the child adds 1 white marble, and the probability goes from 2/3 to 3/4. The belief is modified to become near-certainty that the sun will always rise.
That doesn't make any sense. If the content of the video is supposed to be exactly what the title says, then you're wrong too. It shouldn't be a video about where it should be applied. The title is not "Where to apply Bayes' Rule". It should literally be an instruction telling you to "Think Rationally with Bayes' Rule".
Her previous video on the channel explains the Sunk Cost fallacy. Explains it, not just tells you to look it up. Why is it unreasonable to expect the same here?
I google all the time. The answers I'm finding are expressed as math I don't understand. I think I found a word description, but I wasn't sure I understood it.
Either way, since she brought it up, she ought to provide a definition as part of her talk as a matter of form, otherwise, who is she talking to? The choir? You have to already agree with her to even understand what she's saying.
As an example, say A is "I'm a scientist" and P(A) = 0.2 because about 20% of people have a job in science. Now say B is "I know Bayes' rule", then P(B|A) might be about 0.9 because most scientists (should) know it. Lastly, say 25% of people (overall) know Bayes' rule: P(B) = 0.25. Then the probability that you're a scientist, given that you know Bayes' rule, is P(A|B) = P(B|A) * P(A) / P(B) = 0.9*0.2/0.25 = 0.72, so 72%.
Explaining Bayes' theorem is extremely easy - you look at each possible outcome, you look at how likely that outcome is, and you choose the path that leads you to the outcome with highest likelihood of success (whatever success is in this situation).
This being said, I too feel Julia should've at least mentioned this. The explanation, along with another 20 seconds of talking or so, would've made for a far better (and more concrete) advice, I think... =\
To everyone who doesn't know, Bayes' Theorem is this: the posterior (conditional) probability P(A|B) for A, given B, is equal to the prior probability P(A) multiplied by the conditional probability P(B|A) and divided by P(B). So
P(A|B) = P(B|A) * P(A) / P(B)
which is big if e.g. the chance of A, irregardless of B, is large AND the chance of B, given A, is also large. Or if e.g. the prior probability of B is very small.
If there were such a good explanation I should not need a great base in economics. She simply did not explain what (Bayes Rules) are. I use decision theory in my work all the time. As a result I am very familiar with Bayesian mathematics. That said, the vast majority of people won't have any prior knowledge of the work of Reverend Bayes. No reason they should. Without that prior knowledge her talk cannot deliver the titles implied meaning. Nor can it be understood.
Actually the title does not mention where Bayes rules should be applied. More it seems to give the command to "Think Rationally via Bayes' Rule". This of course implies that a complete guide on how to follow said command is forthcoming. Given both linguistic and cultural norms here in the U.S. The expectation of a description of how to think rationally (Bayes Rules) would be included in the video. I am glad you can read the title, though I am concerned with your lack of comprehension.
No she did not explain "generalized Bayes rules" in specific she did not even mention them. She simply stated that they are a means of changing a belief based on new evidence. Without explanation she could be referring any process in which the input changes the output. Her statement is therefore so general as to be useless. The admissible decision rule and Bayes rules are very specific processes used in applications like decision theory.
(h t t p : //) yudkowsky (dot) net/rational/bayes
Don't be intimidated by the size. Its mostly made up of different (optional) examples of the theory. When you understand one well enough that it clicks, that's usually enough
Remember the prior probablity. Remember the data can switch from talking about a % of a specific population (women who used breast cancer tests), OR a general one (women in general)
Like how Earl Warren not observing the odds of any civilian actually becoming terrorist
lol she literally said what Bayes' rule is. It's when you rationally change your belief based on new evidence that is provided. In fact that's what an entire side of statistics known as Bayesian statistics is based on. It can be explained mathematically using conditional probability but that's not necessary for you to understand what it is. So in my opinion, this was not a "waist" of time.
I disagree, Scott Ritter, former Chief Weapons inspector laid the whole case out. He stated that the inspectors accounted for like 95 % of Sadaam's weapons as being destroyed. I heard Scott and realized this guy is genuine, also went to one of his lectures. Those in power wanted the war, and the democrats being cowards, went along with it.
Pls. tell me, if I have no information about the probability of a star in Andromeda Galaxy to turn into a supernova, does it mean that it has less chances to do so, as this woman is saying? Do you understand Bayes' equation? I feel like I'm talking to creationists about evolution through natural selection.
Lol, again nonsense. What value have P(B) in your equation? Don't tell me, 0 :P If you have 0 information about an event, that doesn't say anything about the probability of that event. Ffs, Bayes' Rule deals with statistical information, not with evidence, or lack of it. It's a theorem derived from statistical axioms, not a substitute for logic.
How about defining Baye's rule from the statistical equation FIRST and THEN transform it into a set of reasoning. Would suddenly make the video usefull, but instead we are stuck with a brad who doesn't guite know what she is talking about. And the existence of an applied rationality centre blows my mind. Trying to take ownership over common sense is just stupid....
She kind of did explain what Bayes rule is. It's process for finding out what your best bets are when it comes to believing something based on the given evidence, and when it's time to change beliefs. She didn't explain the mechanics of it because mathematical models are bloody impossible to explain without writing and illustration. Google it ya lazy sods!
reading a few comments here makes me feel ashamed to be human. BIG think is a brilliant channel and this lady knows her stuff, she makes good points and good examples. SOme comments here are akin to the chicken or egg argument, when you start explaining it in depth ppl simply zone out cause they dont hear the answer they want.
Actually , she did present a general explanation of Baye's Rule . The problem
is , how much of the general public would be willing to apply that logic ?
According to Michel Foucault's dismal conclusion , nobody would - we all
interiorize our existence to such an extent , that no one listens to
anyone else , unless it suits them .
Apparently understanding the power of Bayesian reasoning makes you completely oblivious to everything that you are not consciously applying the reasoning to. Namely, you completely neglect the fact that big think reads the comments and complaints are a necessary form of feedback.
But you know, enjoy your high horse.
Problem: Bayes' rule no longer applies in QM. (although, to be fair, I should mention some people have tried to make it work) We would not benefit from making Bayes' rule an intuition, because then the whole of QM becomes even less intuitive. Also, she makes Bayes' rule sound like statistical hypothesis testing, which it isn't. But I understand what she's getting at.
Don't bother having a conversation with corcoos. I've tried explaining it to him/her but it's obviously way beyond his/her understanding. Corcoos is stuck in the land of statistics unable to understand the implications of Bayes Rule in any situation that doesn't concern figures and polls.
...
(IE info that it considers false due to it not making sense with regards to the rest of it' "world view") but only because of limited time/energy/resources, not because of not using the bayes rule. and as I said, the calculations are not perfect, we make the best calculation we can.
...(again)
Unfortunately, that's not how human minds work. The world might be a much nicer place if it were. We can be completely oblivious to information that doesn't fit in with our biases. A really great book related to this topic is 'Thinking, Fast and Slow' by Daniel Kahneman.
I agree that three minutes and twenty three seconds for Bayes' Rule is way too little for such an important topic. Bayes' Rule captures a mathematically demonstrable and provable truth at which humans are usually intuitively bad at. Which is why we would need extra time with it.
Bayesianism is great, it can be incredibly helpful in making people think more rationally and consider more alternative explanations that they might not otherwise consider.
But Bayesianism does have some problems. For instance it's not clear how one would judge evidence collected in the past with it.
One of the most if not the most decorated military unit in American history was 442nd regiment in ww2. They were all Japanese American fighting Nazis while their families were in American concentration camps. That's fact, your bayes rule would not be able to argue true character.
In fact many things weigh the same as a duck without being a duck and anyway how much does a duck weigh? Is it a young duck or a fully grown mature duck. Is it a fat duck or a thin duck? This leaves us just as we started without a clue.
Completely meaningless to say you're using Bayes Theorem without actually doing the calculations. Which you can almost never do on a day to day basis. Everything she's said reduces to just saying "Watch out, human's are prone to confirmation bias."
Please tell me that someone pointed out the obvious logical fallacy of: "If Japanese Americans are conspiring, because they are being quiet, than all Americans that are quiet (which is easily 99% of them) are therefore conspiring".
Seriona1, false. She did not define bayes rule only gave examples of what its not and hinted that it's somthing to do with realistic thinking. In truth people who dont already know what it is will not learn what it is with this video.
If something weight the same as a duck, then it's probably not a duck, since the weight of a duck is pretty common. That being said, what you're saying isn't only nonsense, but it has nothing to do with Bayes' Rule.
Clearly this woman does not know what Bayes rule says or is. Why do you let her speak?
It is just a shallow marketing-blurp of shiny words and zero content.
Just go to 1:00 and try to find out what Bayes Rule _is_.
Do not waist your time watching this. At no point does she go to the trouble of explaining what Bayes rule is or even describing it in broad terms. If you would like to know what it is you can look at the Thomas Bayes wiki.
Also, can you give me, pls, the Bayes' Equation for the probability of an American Japanese to be a threat to US security during WW2? Pls. enlighten me, since I'm too stupid to understand.
Lol, where did you get that, really? It's a formulae to calculate the probability of an event, when you have statistical data to work with. When you don't operate with probabilities, you use logic.
but all evidence makes a dent in how strong our belief about things are. it just transpires (on things that can only be taken 2 different actions) into observable behaviour when it tips the balance.
So you are saying someone is not "intellectual" because she uses makeup? I would say that your belief that appearance somehow contributes to intellect is a sign that you are not an intellectual.
Perhaps It is explained well if you know what Bayes rule is, but the closest I got out of the video is that you should not only revise your view of the world when you find. Contradicting evi
Actually she explained it very well and how it affects you on a daily basis. But obviously you can't transfer that onto your own life. So you are angry on how she didn't explain it simpler.