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I can certainly see why you'd struggle 😅

Without a doubt. Although, you could argue at that point it's stopped being anecdotal and just become straight up lies.

@@thesciencelens My point is that the investigator has essentially no way to tell apart an honest anecdote from a lie. And this is the biggest weakness of anecdotal evidence. Faking an experiment is difficult, and the experiment can be repeated later to confirm or dismiss the alleged results. While faking an anecdote is much easier, and there's no standard way to confirm it.

Thanks for watching!

It's true that a lack of evidence doesn't disprove something's existence, and people are free to believe whatever they want. But in an argument you can't expect another person to accept that something exists unless you have evidence.

I try to be politically neutral when choosing my examples. Is there an example of a fallacy that you see from the other side of the fence that you think I should address?

I'm not sure I agree with you that this would be cherry picking data. Can you clarify a little more what you mean?

​@@thesciencelens My point is that accusing someone of cherry picking can itself be a rhetorical strategy. It can be used to evade addressing the actual data or argument presented. By calling a statistic cherry-picked, one might avoid discussing its relevance or the uncomfortable truths it might reveal. This shifts the focus from the data to the method of presentation, potentially preventing a meaningful discussion about the data itself. This tactic can be seen as a form of manipulation, where the accusation of cherry picking is used to undermine an argument without considering its merits. It's important to recognize when this is happening, as it can prevent the establishment of claims or charges that seek to bring attention to factual incidents, regardless of the sampling size.

Thanks so much!

Thanks so much. Really appreciate it.

Thanks! I appreciate you watching.

Thanks for watching!

You're too kind :)

You are so welcome!

It doesn't mean you're incorrect, but you shouldn't expect others to agree with you without evidence.

@@thesciencelens yeah but it’s also lazy to just dismiss everything without care because modern science only studies things that will give profit. So it’s very skewed in one direction. But if people question it just based on logic and assertions it gets dismissed. That’s why modern science is so stagnant.

From what you've described I would say no. You've been open to the idea of being contradicted, examined the evidence and found that it's not strong enough to change your mind. To me that's the right way to approach the situation.

Ha. I stand corrected :)

@@thesciencelens Seriously though, thanks for educating people on this important topic👍. Should be seen in every school.

Thanks for watching!

There's so much to think and learn about when it comes to critical thinking as a pursuit. Thanks for sharing!

@@thesciencelens yep definitely ^_^ sometimes my own bias can get the better of me like when it comes to codependency, but really it is just trivial a lot of the time - in concern to my folks and peers.

@@thesciencelens overall though, I believe conformation bias is neither always fundamentally good or bad, as it keeps us aware of our surroundings and events (like the pandemic or even global warming or climate change).

Thanks for watching!

Thanks! I'm glad you enjoy it. I'm on a break at the moment because I just started a new job but hoping to bring out a new video soon.

I know exactly what you mean! It's impossible to be bias free. I think the important thing is to practice critically thinking as much as we can so when it comes time to make big decisions we can have a better chance of making the right one. Thanks for watching!

Very true. We definitely need to be careful about that.

Glad you enjoyed it!

Thanks for the feedback! You make an interesting point. I'll have to read up on the gronding problem as I'm not familiar with it. And I'll definitely have a think about how I might be able to incorporate moral relativism into a future video. Cheers!

@@thesciencelens that would be awesome i would love to hear your take on it also your most recent video about memory is great keep it up man i think you might just blow up soon you make great quality content <3

I'm glad you liked it! If you're interested, I just made all of my worksheets available for free on my website at www.thesciencelens.com/resources.html. If you use them with your students or just one of the videos I'd be keen to hear how they go.

There are, of course, plenty of examples of when the scientific consensus was wrong. The problem is those examples are more salient that the times it was right, which are much more common. This is what I mean when I say it's about playing the odds. If you had gone against the scientific consensus in the 1900s it's unlikely you would have said that the Universe was expanding (because there was no available evidence to suggest so), so you would have been wrong. If you go against the scientific consensus today you would still be wrong. If you had believed the scientific consensus, on the other hand, you would have been wrong in the 1900s but right today. So, science doesn't always get it right, but it's a safer bet.

​@@thesciencelensso you agree that consensus can not establish truth

That particular phenomenon is not really about an appeal to authority it's about the general state of human knowledge. It has become a well-known fact that half the information medical students learn, for example, will be considered to be untrue within 10 to 20 years. It's actually referred to as the half-life of facts. And of course it is the case in any branch of knowledge.

That's why he said "more often than not".

Everything you said is true. But it's about playing the odds. A specialist's opinion on their area of expertise is more likely to be correct than a non-specialist. The consensus of 100 specialists is more likely to be correct that the opinion of 1. And a single expert is more likely to be biased than an entire group. Of course, it's important to remain vigilant because science can get it wrong and systems can be flawed. But as non-specialists we have to remain humble about our understanding of specific topics, which is why, in the absence of evidence to the contrary, it's safer to trust science.

​@@thesciencelensI think your argument is flawed, and i will try to showcase the problem here with an analogy. (I assume the premises you provided are true for example: ":And a single expert is more likely to be biased than an entire group." Although I don't see that you backed these claims up with anything, but for the sake of this argument i will look away from that for now). So the analogy: Lets imagine someone is brought into court for murder charges, and his lawyer says that only 0.001 of people are murderers (I just made this number up to showcase a very small percentage) and therefore its very unlikely that his client is indeed a murderer, and therefore the charges should be dropped. According to the logic you presented, where "it's about the odds" the lawyer's argument is correct, when in reality we obviously know its not. Actually in that case there were information available which indicated that in that specific case the percentage should be much higher (for example he was caught red handed). The main problem here is that a general rule is used as a basis, and while the general rule can be true in itself, after closer inspection there are other important factors which would greatly alter the odds and those factors are disregarded. I think it is kind of a "fallacy" related to "supression of evidence" or "cherry picking" or the "accident fallacy". I think when its abut trusting a scientists (or anything in general) its important to weigh in other factors, other than their expertise and the consensus (aka appeal to authority/popularity fallacy). An easy example for these factors would be to look after the interest of the scientist: who is supporting them with money (sorry for bad english), also an other one: to look for political interests behind it: if a controversial theory comes from a well known dictatorship (or something similar in some regards), who is advocating certain ideologies just like the nazi Germany was, or the USSR, than it automatically should raise doubt about the integrity of the theory.

Hey! Thanks for commenting and sorry for the delayed response. I would start by looking for their profile on the webpage of the company or university that they work for. There you should their qualifications and where they studied. If you see PHD after their name that's a good sign :) Next, I would jump onto Google Scholar and do a search for their name, to see if they've been published in any peer reviewed journals. Being peer reviewed means their work has been checked by other experts in the field so is held to a high standard. There's a channel called 'Smart Student' that has a few videos on using Google Scholar and checking credentials. This video might be a good place to start - ua-cam.com/video/t8_CW6FV8Ac/v-deo.html You could also check out my other videos on Checking for Peer Review or Appeal to Authority. Peer Review - ua-cam.com/video/Sk-csc5vjmY/v-deo.html Appeal to Authority - ua-cam.com/video/WsON5mGeVto/v-deo.html Thanks for watching!

I thought you'd like that one!

Thanks! I appreciate the support.

Oh man, I feel woefully unqualified to answer THAT question! But I think it's a great one.

A report of symptoms isn't anecdotal evidence. The doctor isn't extrapolating out what the patient reports to the general population which is why we don't use anecdotal evidence, they are just applying the symptoms to the patient.

It depends on what you mean by reliable. And compared to what else?

There's definitely value in anecdotal evidence. And when used correctly can yield some important insights. The logical fallacy is in taking one or a handful of examples thinking that they mean more than they do. I'm interested to see what AI will be able to do with a large set of anecdotes moving forward. For a human to find meaning in a set of 1000 stories would take years, but I can see the right AI model doing it in a fraction of the time.

@@thesciencelens As always, thanks for replying. I like these little YT discussions we're having.

​ If 1000 people are reporting a severe adverse reaction to something immediately after eating or taking something. Its legit ! Millions of dollars of food are removed from supermarket shelves from just a few negative reports sometimes. And only from a small sample. The system in this case is logical, because its better to be safe than sorry.

@@thesciencelens Let me help. Examples can't be extrapolated out to the general population because they are not representative of the general population. You can have specific populations like people with cancer or some other condition when performing clinical trials.

Yeah because a set of data is made up of individual data which themselves are anecdotes

Thanks! Glad you liked it :)