Cool Things You Can Do With AI & Surprising Insight in Chance, Probability & Risk

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Today on Something You Should Know, there's a common word you use that actually means the opposite of what you think it does. Then you'll hear a lot of cool uses for artificial intelligence that will make your life so much better.
I do this all the time. Give me a quick recipe.
I have chicken, asparagus, parmesan, and tomato sauce in my fridge. What can I make with this? It will generate back a recipe that will result in something tasty.
It may not be the best thing you've ever made, but it will get you there. Also, we need to talk about your shower and the fascinating world of risk, chance, and probability.
If I shuffle a pack of cards properly and give it a good shuffle, I can be absolutely confident nobody in the entire history of humanity has ever had the cards in that order before. It's not intuitive just how many shuffles there are.
The number is about the same as the number of atoms in our galaxy. All this today on Something You Should Know.
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Fascinating intel. The world's top experts.
And practical advice you can use in your life. Today, Something You Should Know with Mike Carruthers.
So there is a word in the English language, a fairly common word, that actually means the opposite of what you think it means. Hi, welcome to another episode of Something You Should Know.
When you hear the word overdrive, you think you know what it means. When you hear the phrase like kick it into overdrive, most people think it means something along the lines of warp speed or maximum power.
And it means just the opposite. It's an automotive term that refers to a gear ratio higher than one to one.
So after a certain speed is reached, that speed can be maintained with a minimum of engine effort and wear. So in your car, overdrive gives you a more relaxed, efficient ride.
The reverse definition has become so ingrained in people's mind that it is now an acceptable definition according to most dictionaries. And then there was the movie Maximum Overdrive, which helped continue the words misuse.
But technically, when you say, punch that baby into overdrive, what you're really saying is punch that baby into a leisurely cruising mode. Sounds a lot less cool now that you know what it means.
And that is something you should know. I will admit that I haven't dipped my toe too deep into the artificial intelligence waters.
I've played around with chat GPT and I've read a few articles and we've had guests on here talk about what AI is. But when I saw this book written by my next guest, I don't know, something clicked.
I realized I wasn't really understanding all of what AI could do for me in my life. And maybe more importantly, how to use it in a way that it really gives me what I want and uses more of its potential.

As you listen for the next several minutes,

I think you'll really start to understand some of the very cool things AI can do

to make your life better and how easy it is to navigate.

My guest is Celia Quillen.

She is an expert in artificial intelligence and has been featured in Time, the New York Post, the Wall Street Journal, and on the Today Show. She's the creator of the popular TikTok and Instagram channel at SmartWorkAI.
And she's author of the book AI for Life, 100 plus ways to use artificial intelligence to make your life easier, more productive, and more fun. Hi, Celia.
Welcome to Something You Should Know. Hi, Mike.
Thank you so much for having me. It's great to be here.
So I have a sense, because this is what I thought for a long time, I have the sense that people think of AI as kind of a really fancy search engine. Like you go to ChatGPT, you type in something,

and you get results back, much like you would do with Google,

even though, as you're about to explain,

it isn't really a search engine.

But don't you think that's what a lot of people think it is?

Absolutely.

I think many people think of it as a search engine,

which, especially in the early days,

might have been a detriment to them because at the time, many of these tools could not browse the web for you and do that search. Now they can.
But I do think that that is kind of the first and foremost thing that people think of them as. Yeah.
See, that's what I thought. And I've, you know, I've done that.
I've typed in things and gotten answers. But then I looked in your book and saw that you can do so

much more. And so what much more can you do? If you could give me like a little shopping list of things that AI can do that people may not realize.
I don't want to go deep. I just want to go wide.
Brainstorming. It's excellent at coming up with new ideas and helping you kind of creatively come up with new suggestions for how to accomplish tasks or how to name something.
It can help you create and generate effectively anything that is text-based. So if you needed to create a quick guide to a place that you're traveling, instead of searching one thing, you can search many things at once effectively by having it create a guide.
You can have it craft a shopping list according to your groceries that you have to accomplish for the week. You can turn it into your personal secretary, articulating out all the things you have to keep in mind and remember and have it jot it down and summarize it in a nice, concise way for you to refer back to later.
There is no limit to how it can help you, really. Anything that is text-based, it effectively acts as an intern, as a super advanced intern that can do anything for you.
Another use case that many people enjoy is meal planning. So you can put in your preferences for what your dietary preferences are, what you want to eat, how many meals you need prepped for, what your calorie intake you roughly want for each meal is.
And it can generate a list of ideas, recipes, grocery lists from there, and really help you outsource a lot of the menial tasks that take a lot of energy and mind space in your day-to-day. one of the things that's so amazing to me about it that I discovered after reading your book is that it isn't just that you ask it to do something and it does it and that's it.
You can refine and say, no, that's not what I was looking for. Or here's a document, read this and now tell me something that you didn't know before.
I mean, it's so malleable. You can, it's like clay, you can make it do almost anything.
Absolutely. And it is always better when you collaborate with it as well.
You can refine it to make it more personalized. You can give it feedback.
It's almost like a co-collaborator. And it really is, it's a magical tool when you first use it because I'm realizing that it can unlock this.
It's like having a second intelligence in the room with you. What is it doing when it's doing all these things? And I know that's a big question and I'm asking for a little answer, but give it a shot.
Yeah. Keeping to understand, unlike a search engine, these tools are not going and browsing a massive database of information, plucking out a paragraph or two and then pasting them back to you.
They're not doing what a Google search might, where it's browsing all the URLs on the web and finding the content that most matches your search. Instead, it is a predictive tool.
So it's predicting the best possible answer word by word, or more technically token by token, so fraction of a word to give you an answer based off of the words you put into it. And it's basically like a very, very advanced autocorrect.
How it's able to do this is these tools were trained off of a massive amount of data. So think about the contents of the entire internet, for example.
The computer is able to run a lot of complex calculations and notice different patterns within language. So it basically became very good at mimicking human language patterns.
It assigns weights to different words. So for example, it might know that the word kitten is more frequently associated with cat than puppy.
And over time, all those different things informs the model that allows us to interact with these tools, the large language model. But all you need to know is effectively, it's not retrieving information, it is predicting the best possible answer, word by word based off of this massive training model that it has developed.
There are different AI tools, chat GPT is the one that you know, I think a lot of us that comes to mind immediately is the one to go to but but there are others. What are the differences between them? Are they more or less interchangeable or not? Certainly.
I find them to be more or less interchangeable. So you have ChatGPT, kind of the leader, the most well-known, but there are countless tools in this arena.
If you're looking for a more general purpose AI that can

do kind of everything that I mentioned before, ChatGPT, Google Gemini, Clawed AI is another one, Perplexity, Microsoft Copilot, Meta has an AI now that also has a chat interface. All of these tools can do all of that text-based generation.
There's some subtle differences between the different tools in terms of the extra functionalities they have. But as these companies behind them are developing and trying to compete with each other, they are frequently introducing the same features and functionality that, you know, ChatGPT might have just released so they can keep up.
So some examples are attachments. For in the early days of ChatGPT and these other tools, many did not allow you to, say, attach a PDF to your question or query.
Now, ChatGPT can do that. Claude AI can do that.
Google Gemini, you can connect it with your Google Drive. Microsoft Copilot works in sync with your Microsoft 365 suite so that you can now communicate with those PDFs.
Other examples, as we mentioned earlier, web browsing. So all of these different tools, with the exception of Claude that I mentioned earlier, can now actually go and browse the web, generate a response summarizing what it finds, and then link back out to the source that it got that from.
So all of these tools have subtle differences, but by and large, I try and encourage people to, you know, if you have one that you like, and especially if it's free and you're just getting started, experiment, play around with it. In no time, if some competitor launches a new feature, it probably won't be long until they launch their own version of the same thing, because these tools are evolving so quickly, and they're all trying to stay competitive with each other.
If I were to ask an AI tool like ChatGPT, give me a snappier title for this, or give me a, like, how does it know what snappier means means or does it? So it doesn't really know anything, I guess is the one way to put it. It's not actually intelligent, but it is artificially so.
So snappier, you know, kind of how a thesaurus works really. Snappier is associated with other words like catchy, zingy, you know, all these other things.
And in its training data, it's associated, you know, snappy characters in a text it might have been trained off of, right? Maybe a character is described as snappy in their dialogue at some point in time, it starts to associate those words with different kinds of output. So it's hard to explain it exactly, but it does have a very advanced way of understanding human language patterns and human language context and meeting.
So if you ask it to be snappier, it will probably develop a response back to you that is more concise, maybe a little bit sassy. Maybe it has a, you know, rhyme to it, depending on what else is in your prompt.
But it, because it has become like an expert of mimicking human language patterns, it effectively is very good at understanding the meanings of words that you use. Now, if you use the gibberish word that had never existed before and said, can you make it more smergoblat? It would have no idea what you meant, but it might come up with something that's similarly silly sounding as smergoblat.
You and I are getting a great primer in artificial intelligence and how to use it to make your life better. My guest is Celia Quillen.
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So Celia, how do these AI tools like ChatGPT, how do they handle things like, like if you were to ask it, come up with a clever way to say, how does it know what clever means and does it come up with something clever? I mean, does it make an attempt to be clever? Yes, that's a good way to put it. It is definitely attempt to.
You'll see this with the earlier models from ChatGPT. It is slowly, these tools are slowly getting better at it.
But if you ask it to, for example, make something funny, make it funnier, it will have a little bit more trouble with that. It will kind of give you a response back that sounds like it could be a premise for a joke, but then it does the punchline falls flat.
And that's an important thing to understand about these tools is they don't have the same, you know, human experience that we have. They don't really know anything.
They're just guessing at the best answer. So I believe at some point I asked it to tell me a knock knock joke about the dentist.
And it was like, knock, knock, who's there? Dentist, dentist who? Cavity another? And it, you know, that doesn't make any sense to us, but it was in the structure of a joke. Right, right.
So, but for the most part, if there is, you know, I think humor is the one that really falls flat on, but cleverness, you know, if you ask it to create 10 clever headlines, maybe one of them, you pluck it out after you read it through as a human, is clever.

The other nine might not be so much, but one of those 10 is bound to get you a little closer to where you want to be.

And how do we know when, how accurate are these things? Like, when you ask it a question, how confident should you be that the answer you got back, assuming it's a factually based answer, is correct? That is a super good question. And the answer is you should be always a little skeptical with everything, especially if it's a super niche topic.
Because these tools do create, you know, their best, they're just predicting the next best answer, that prediction could be wrong. Just kind of like how the weather prediction might be wrong for the day if you're looking at your weather app.
But these tools are progressively getting better and better and trained and on more data sets, which are making them less likely to what we call hallucinate. Mathematics, they used to be terrible at predicting the best answer to a mathematical question.
Now, the more advanced models, especially those that are called deep reasoning models, where they kind of, when they generate a response to you, it takes a little bit longer because it's actually running through its response through itself over and over again to see if it's really getting to the best answer. Those will be more likely to be correct.
Now, when it comes to general questions about things that are likely, there's likely a lot of information about it on the internet, for example, therefore, it's likely trained on a lot of that data. Like, why is the sky blue? It's probably going to give a pretty solid answer to that.
If you ask it about a very niche disease that just appeared in the world that hasn't been heavily researched, it's probably going to give you an answer, but it may not be correct. The best thing I tell people to do is that when you use these tools as a jumping off point, because they can get you really far, and then do a quick Google search, see if there's a secondary source that backs that up.
You'll find that a lot of the time, it is totally right. It's wrong enough of the time that you should always do that extra step of fact checking.
If I Google, if I just search in a search engine, the best baked lasagna recipe there is, I'll get back results of 10 million lasagna recipes, none of which may or may not be the best. If I ask AI to give me the best, does it somehow put in a judgment that this one or these four are the best, or will I just get 10 million baked lasagna recipes? You will get one lasagna recipe back.
It will not necessarily be the best lasagna. Best is, you know, arbitrary, but you will get a recipe back that is most likely to result in a lasagna.
That's the best way I can put it. So if you truly want to have the vetted, you know, best ranked lasagna, lots of great ratings, Google might still be the best way to go.
But if you're looking to just get started, I want to try and cook something quick. I do this all the time.
How do I give me a quick recipe, I have chicken, asparagus, Parmesan and tomato sauce in my fridge, what can I make with this, it will generate back a recipe that will result in something tasty. It may not be the best thing you've ever made, but it will get you there.
And that is, again, because it's taking in all of the data it has of all of those on your recipes that are in its training data, which is likely a massive amount because they are effectively trained on the whole variety of things on the internet. One of the first things that struck me and that I noticed that makes it so different an experience than dealing with a search engine is if you ask for a baked lasagna recipe, you get one because you ask for one.
So why not ask for 10 if you really want to sort through them? But it takes you very literally, whereas a search engine will give you as many baked lasagna recipes as it can find, seemingly. But AI gives you exactly what you asked for.
You asked for one, here's one. That's correct.
You asked for one, you get one. Now, you can ask for five, and it'll give you five different ones.
I do say in the case of a recipe, if you're looking for a recipe, most of these tools have a certain text-based cutoff. after they generate a certain number of words, they'll finish the answer.
That way they don't go on for forever and you don't have 10 pages of content to read. So if you're looking for recipes, for example, sometimes you're better off asking for one and then saying, okay, that sounds okay, but could I have another? And then it generates another one.
But I like it, honestly, instead of having to scroll through endless pages of search results and then click through them, scroll past all of the ads and all of the recipe blogs tend to have a lot of extra context up front that has nothing to do with the recipe. ChatGPT will give you exactly what you want, nicely packaged, short and sweet.
And if you don't like it, you can ask for another one and it'll generate it just about as quickly. So tell me something that you've done with AI that I wouldn't have thought to do that was really, really cool.
A couple of years ago, I planned a whole trip to Puerto Rico with it. I did not know where I wanted to go.
I just knew I wanted to go on a vacation. I knew what the criteria that I wanted were.
My husband and I wanted to go on a nice romantic trip together, somewhere warm that we had never been before that, you know, maybe it was a little bit tropical, but was in a certain distance. I mean, I don't want to go to Hawaii.
It was too far away. And it generated a bunch.
I asked it to generate, you know, 10 recommendations based off of all that criteria, generated 10 recommendations, then I had it do some more research on okay, tell me more about Puerto Rico. Once we had landed on that trip within a basically 10 minutes, I had it make a table breaking down all the different activities that we could possibly do there based off of the price per person based off of a description, like describe it, give me a price per person, give me where it is relative to the hotel we're thinking about staying at.
And it just accomplished so much research tasks that I would have taken me, you know, hours and hours and hours on Google, popping through different travel blogs, trying to find responses. So that's, that's one thing, just everything related to travel planning.
And related to that, the vision capabilities on these tools, which is basically being able to take a picture and ask questions about it, is huge. You can snap a picture of a menu at a restaurant and ask, you know, I'm on this kind of diet, I'm looking for lower sodium, I'm trying to be gluten free, but I don't know what has gluten in it.
It's kind of one of those fancy menus that has menu items that I've never heard about listed on the menu. Could you describe what this dish probably is or go and describe in layman's term what this fancy menu means or translate this menu entirely in French into English? It can analyze data now.
ChatGPT has a data analysis feature. So I personally track all of my finances in a spreadsheet.
I can attach it into ChatGPT with all the different inputs of how much money is in what account and have it create graphs and charts and analyze what's going up, down, what I should be considering. There are so many things it can do.
I could go on forever. What I have found so interesting about it is, A, it is so easy to use.
And the more you use it, the more you want to use it. And the more you want to use it, the more things you find it can do.
It's just remarkable. Absolutely.
Yeah. And it's really great.
I mean, it is truly a collaborative tool. It is like engaging with a second person in the room.
So if you're trying to sort through a problem, that's another use case. If you're an interpersonal problem with a family member or friend, and you just need something to bounce ideas off of and get advice from, it's surprisingly good at delivering mature, thoughtful, somewhat objective advice as long as you ask for that.
And it's very, very collaborative and creative. It's just, it's an expert at mimicking how humans communicate.
I remember you said in the book, something about,

some of them may tell you it can't do something

and you can correct them

and say, no, you do have that ability.

That's correct.

Sometimes it will say,

sometimes these tools will say,

I'm sorry, I can't help you with that.

I don't have the ability

to browse the web.

But if you know it can browse the web

because either you've,

because you've tried it

probably in the past before,

then it will say,

okay, I'll go do it now. And then it will come back to you and you'll know it did it because you'll be able to see a link that you can click through on.
How are these things and at what rate are these things, like ChatGPT and the other ones, getting better? The level of progress they've made in the past two years, two and a half years since they released is insane. So they will be able to do more and more advanced things as time progresses.
Well, I love how you make this so easy and so accessible because, you know, I mean, AI at first glance might seem a bit intimidating and overwhelming, but you make it so not that. So thanks.
Celia Quillen has been my guest. She's an expert in artificial intelligence, and she is author of the book, AI for Life, 100 Plus Ways to Use Artificial Intelligence to Make Your Life Easier, More Productive, and More Fun.
There's a link to her book in the show notes. Well done, Celia.
Thanks. Thank you so much, Mike.
It was a pleasure. The PC gave us computing power at home, the internet connected us, and mobile let us do it pretty much anywhere.

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Uncertainty is a constant we live with every moment. We never know what's going to happen.
And sometimes that's fine. We don't always want to know what's coming.
But not knowing can also be problematic. I mean, some things we would really prefer to know before they happen.
Nevertheless, we live with uncertainty. And joining me to help make sense out of all the uncertainty that lies before you is David Spiegelhalter.
He is Emeritus Professor of Statistics at the University of Cambridge and author of the book The Art of Uncertainty, How to Navigate Chance, Ignorance, Risk, and Luck. Hey, David, thanks for being a guest on Something You Should Know.
No, it's a great pleasure to be here. So uncertainty is just part of life.
It's there. There it is.
So why do you study it? Oh, I think it's fascinating. I mean, it's just part of being human.
It's all around us. We don't know what's going to happen and we don't know what's happening.
We don't know what's happened and we don't know why. And we live with that all the time and we're happy with that.
I mean, I always ask people, would you want to know how a football match was going to end if you had recorded it? And would you want to know what you're going to get for Christmas? And even, and of course they say no, and even would you like to know when you're going to die? Which of course I can't tell them, but very few people actually say they would like to know. Some do, but very few.
And so I always think of uncertainty as a relationship between ourselves and the outside world. Somebody's called it the conscious awareness of ignorance,

which I really like, because it really puts that in as something we own,

you know, our personal ignorance.

And that can vary so much from person to person.

And so why doesn't the conversation end there?

Some things are uncertain.

You'll never know until you know.

And have a nice day.

That's it.

Well, I'm a statistician. So I've spent my entire career in a way, analyzing uncertainty, using data and evidence to try to reduce our uncertainty and even try to quantify our uncertainty to actually get a handle on what we don't know.
And I really strongly believe that we should, when possible, try to put our uncertainty into numbers. I mean, we all use words like could, perhaps, likely, and everything in our everyday language.
But actually, those can be very dangerous. And I always refer back to 1961, when Kennedy became president and found out about the CIA planned invasion of the Bay of Pigs at Cuba to topple Castro's government with 1,500 Cuban exiles.
And he commissioned the Joint Chiefs of Staff to do an intelligence report on that. And they thought it was not a very good idea at all and thought that it was about 30 to 70 chance of success.
In other words, 70 percent chance of failure. But in the report that went to Kennedy, the numbers got taken out and it got replaced by, bizarrely, the term a fair chance of success.
And they meant not very good, but I don't think that's how anybody else would interpret it. Of course, that's not the only reason he approved the raid, which of course was a complete fiasco.
But people have learned from that. And now in intelligence, people really try to put numbers on their judgments.
In the UK, if you're in MI5 or MI6 and you use the term likely, you mean between 55 and 75% probability. And if anyone assesses a 30% chance of success, they have to use the word unlikely to communicate that number.
So there's a sort of lookup table between words and numbers. Somewhere in this discussion has to come human nature because numbers don't tell you everything.
For example, it is much safer to fly than it is to drive in a car. But a lot of people don't live that.
They know it intellectually, but flying scares them to death. And so the probabilities don't mean much because they ignore them.
Yeah, I know. I mean, this has been studied for ages.
I'm not a psychologist, but, you know, I think it's well known that, you know, people do have an anxiety about, you know, not having control of their lives. They feel particularly bad when, you know, something risk might be imposed upon them by something else.
They're particularly scared of things that they don't understand very well or have really dread results giving people cancer and so on. And that makes people anxious about certain things where actually maybe they're not the main things they should be anxious about.
When people started doing this research in the 1980s, microwave ovens came very high on the risk index in terms of people's fears and anxieties. And that's gone down.
There's some fashions in risk in what people are anxious about and what they aren't. But it is true.
Our feelings come into how we feel about risk and uncertainty all the time. We can't just wave our fingers at people and say, oh, how silly you are that you're worried about this and you're not worried about something else.
I don't think we should do that. I think we should acknowledge people's concerns, but try to give them the best evidence in the clearest way, so that they can make an informed choice.
We shouldn't be propagandizing people, trying to manipulate their feelings, either to reassure them or to frighten them. And that's why in my work, I really push this idea of trustworthy communication.
Why should anyone trust scientists, experts, authorities and things if they feel they're being manipulated? And that means actually giving people information that's balanced and that does talk about the benefits and harms possibly of vaccines, for example. And, you know, perhaps don't use the phrase vaccines are safe and effective, but say, yeah, they're safe enough and effective enough to use in some people in some circumstances.
Talk about luck, because luck seems to throw a monkey wrench into everything. I mean, you know, people say, you know, it's really stupid to play the lottery.
Your chances of winning are just so ridiculous. Well, tell that to the guy that won $300 million, you know, turned out out to be a pretty good deal.
Yeah, I like the idea of luck. I mean, I don't believe that luck is some external force that operates in our life, but I do think it's quite useful as a description, looking backwards at things that happened to us that were out of our control and were unpredictable and yet had a big impact, like winning the lottery or being knocked down by a car.
So, you know, these are all things that could happen to us. And philosophers have identified, in fact, the most important type of luck, which is what's called constitutive luck, which is just who you're born as.
Actually, maybe even before that, there's existential luck, which is the luck of being born at all, because it's extraordinary that any of us are born, the chain of circumstances are required for that. But given you are born, who you're born as in the world is incredibly important for the rest of your life.
You know, who your parents are, the country, time of history, etc. Especially your genes, your early environment or so.
You've got no control over these at all, and yet they're staggeringly important for the rest of your life. So that's the biggest bit of luck that you have, just who you are.
And then, of course, you've got what's called circumstantial luck, which is being at the right place at the right time, meeting your wife on a train, as somebody I know did, or being like my grandfather, being at the wrong place at the wrong time and being blown up by a shell in 1918 in the Western Front. And then you've got outcome luck, which is just how it happens to work out for you at that particular moment.
Like, you know, I know a friend of mine was on a plane that crashed, seriously. Nearly everyone on board was killed.
Terrible circumstantial luck to be on that plane, but really good outcome luck because he survived. Similarly, my grandfather, actually, the shell blew him up, but only not severely enough.
He was taken off the front line and survived the war. Otherwise, I wouldn't be here.
Well, we're glad you are. Yeah, exactly.
So exactly so am i but i very nearly couldn't be just like all of us so it is amazing any of us are here at all really what about coincidences are are they a thing or it's just that's just there's just so many things going on that there's bound to be yeah i i again i is no i don't think there's some external force i mean people do talk about a force like synchronicity which young invented or seriality and things i don't believe that i think they just happen because there's so many opportunities for them to happen and uh and also i think it's very they happen because randomness true randomness is very clumpy indeed you Just because things are random, they're not equally spaced. So I know that if I've got 20 people and I ask them the last two digits of their cell phone number, there's an 87% chance that I'll get a match in that group of 20 people.
And some people would think, oh, wow, what a coincidence. And I think, no, it's utterly predictable that that'll happen.
So, you know, the clumpiness of randomness leads to coincidences occurring, and they're quite difficult to interpret. And that's why anybody who talks about a coincidence, they really need to get some expertise in there to try to evaluate that.
Our human intuition about it is terrible, absolutely awful, about probability in general. We're really bad at it.
What are some other things like that, like what you just said about if you had 20 people in a room and the last two digits of their phone number? Things like that, those kind of probabilities in everyday life that people probably have no idea are true. Well, the standard one is if you have 23 people, then there's 50-50 chance that two of them will share a birthday.
And that is something you find quite difficult. So on a soccer field, there's 23 players, 11 in each team, and the referee.
So in half of all soccer games, there's two people on the pitch with the same birthday and that I think people do find quite difficult to tell me and it's shown people have shown it again and again so it works and you can prove it mathematically fairly easily but it is something that doesn't correspond to our intuition but there are other things that go the other way that's we think is, whoa, that's surprising that happens so often. The other thing that actually happens is surprisingly rare is shuffling a pack of cards.
Now, if I shuffle a pack of cards properly and give it a good shuffle, I could be absolutely confident, bet you all the money in the world, that nobody in the entire history of humanity has ever had the cards in that order before.

And then I can shuffle them again into a good shuffle. And I say nobody in the entire history of humanity has ever had the cards in that order before.
And not just now, it's unbelievably unlikely that anyone ever, and no two people in the whole history of humanity,

have ever had a pack of cards in the same order after a good shuffle.

And people find that really difficult belief

because it's not intuitive just how many shuffles there are.

And you can do the sums.

It's sort of 52 for the first card and 51 choices for the second card and 50 for the third card. And you multiply all those numbers up together and you get a very good number.
In fact, the number is about the same as the number of atoms in our galaxy. It's, you know, it's got 78 zeros, I think, beyond it.
You know, it's an unbelievably massive number. And that's not intuitive at all.
Wait a minute. You're saying that if you shuffle a deck of cards, the number of, the different number of orders that you could come up with is a number with 78 zeros.
Yep. As many atoms as there are in the whole galaxy.
And so the shuffle you come up with after a good shuffle, nobody will ever have done before. You can be almost certain of it.
You can't prove it, of course. It's not logically true, but statistically it is just unbelievably unlikely.
Yeah, that's an amazing fact. Yeah, yeah, it is quite surprising.

What that reminds me of is when people say there are no two snowflakes alike,

well, how would you ever know that? How would you ever know that? How would you prove it? That's true. It is difficult because you can't prove it.
You can't look at every snowflake. I don't know every shuffle that's ever been done.
But you can do the sums and you can work out just how incredibly unlikely a match would be. What about the phenomenon?

It often happens in weather and whatnot.

It's called the perfect storm, where multiple things come together to create total havoc.

Yeah.

Taleb uses the frame black swan, which is essentially a really completely unpredictable event that occurs.

And then people find the excuse for it.

Perfect storm is different. It's just a very extreme example of something fairly familiar.
And, you know, the story I use is about this boat, the MV Derbyshire, which is twice the size of the Titanic, and disappeared without trace in 1974. And so they had no idea what happened uh and eventually they found about 12 years later they found the wreck and there was an inquiry and two statisticians um you know it took who i know took part in the analysis of that and they'd done simulations on wave tanks and things like this and they worked out that the boat it was in a typhoon went into a perfect storm and suddenly you know a wave they reckoned you know it could have been 25 meters high the entire weight of it went onto the front of the boat the front hatch and caved it in and then there was a chain reaction and all the all the chain reaction and all the containers in the ship just sort of exploded, just caved in and the ship went down in seconds.
They didn't even have time to send a distress call. And that was, they used this technical stuff of extreme value theory, but it was an example of a perfect storm in which an event happened that had never more extreme than anything that had ever been observed before.
But with the appropriate analysis, you can show that it's quite plausible that it happened. What did you say about what's a black swan? Oh, a black swan.
That was what the Taleb invented. A black swan is something that it's like, you know, people thought all swans were white.
And then they went to Australia and found a black swan. And so it's something that you never even crossed your mind.
A complete unknown unknown in Rumsfeld's language. You know, so you never even crossed your mind that it was there.
And then suddenly it's there. And usually, of course, people then very quickly find a reason to explain why it happened.
But it's a it's a qualitatively different event from something that has happened before. And again,

I think it's useful to distinguish that from a perfect storm, which is just an extreme version

of something that is familiar. So what do we do with all of this? I mean, knowing what you know,

on a day to day basis, like what? How does this fit into your life that you this? I mean, knowing what you know on a day-to-day basis,

like how does this fit into your life that you do that I don't do

because you know what you know?

I kind of, I go a few principles I do,

which is try to look at the possible futures,

you know, try to think of what might happen,

what might go wrong,

and without getting too anxious about it,

and then take some mitigating circumstances, you know, sort of buying insurance and stuff like that when you go traveling taking risks but not being reckless that's what i always say to kids when i talk about this stuff take risks but don't be reckless in others protect yourself against the severe downsides of what might happen but go for it because you know people have found that you are later who are considered lucky, well, actually, they've got particular personal characteristics of being bold, being taking advantage of opportunities for having a positive mindset of going for things, acknowledging it's not always going to work out. so i i i kind of think that i try to do that and i but without being right i won't get on a motorbike

for example i you know i always think i love i love it, but I'm not going to get on a motorbike. But I will go off and have other adventures, which I feel are okay.
So I kind of try to weigh things up, not always using numbers, but just trying to think about roughly what are the risks I'm concerned about. Do you sense people are overly worried about risk or do we have it kind of right? Oh, that's very difficult.
There's huge variation. You must know in the people you know, you'll know some people who are very cautious, rather anxious, always concerned, you know, one in a million chance.
Well, there's always the one and things like that. And others who are more gung-ho and go for it and kind of ignore, you know, are not too sensitive, are bold, possibly even reckless.
And so there's enormous variation in our reaction to it. I think what's more important, and that's how individuals are, people are different.
When it comes to sort of societies, when people are making judgments on behalf of us about what risks society is prepared to take, then I think, you know, it is interesting just how much cautious some, you know, some policies are compared with others just because actually people are really concerned about, for example, nuclear power or nuclear waste.

And so vast amounts of money is spent to possibly have negligible effect in reducing the risk as the risk is so small in the first place. And so, you know, I think when it comes to societal decisions, we should be expecting people to take, I wouldn't say a rational, but a balanced approach to actually looking at the important things and not, I personally feel, not following people's anxieties.
Yeah. Well, you know, it's funny because I think of myself as a fairly cautious person,

but I also know as I look back on my life, things have a way of working out for the most part. I mean, I have not been the victim of any huge disaster.
And, you know, we just had the fires here in California. We have friends that lost their home.
But they'll be okay. I mean, it will eventually, there will be a path to recovery and things work out.
This is the important thing, which I always emphasize, which is resilience. And the point is that, you know, we can't stop everything.
Stuff happens. We can't stop everything bad happening to us.
And we've got to die anyway. So the crucial thing is resilience, which is being able to deal with stuff as it comes along of you know recover as best as you can and it's resilience to things you never even thought of i mean you can protect yourself to some extent against things you you have thought of but in the end what needs is reserves both i think mental and uh and monetary if possible but certainly mental reserves to deal with unexpected things.
The illnesses are going to happen, the dramas, the things are going to happen to the people around you, people you love. You've got to be deal with it.
That is how things go. And so I don't know if you can train people into resilience, but it's certainly a characteristic that is, I think, the most valuable thing to have in an age of uncertainty.
I still can't believe that thing about shuffling cards. I mean, that is just unbelievable.
But it's all about this discussion of certainty and uncertainty.

David Spiegelhalter has been my guest. He is Emeritus Professor of Statistics at the University of Cambridge and author of the book, The Art of Uncertainty, How to Navigate Chance, Ignorance, Risk, and Luck.
And there's a link to his book at Amazon in the show notes. David, thanks.
Thanks for sharing. Thanks very much.
You would think there is one place where you would be safe from all the troubles in the world, and that would be in the shower. Yet there are hazards lurking in your shower.
For example, did you know showering in a thunderstorm is dangerous? It's actually dangerous to be near any plumbing or wiring inside your house when there are thunderstorms going on outside. This is according to the Lightning Injury Research Program at the University of Illinois at Chicago.
Lightning can hit a power line or the ground and then come right up through your water pipes. Using an old shower head can be trouble.
A lot of shower heads contain potentially dangerous bacteria, according to a study from the University of Colorado at Boulder. That's because they're full of these little nooks and crannies that provide an ideal home for microbes.
It's better to use a rain-type shower head or take the showerhead off altogether and go with a single stream of water. Yeah, I don't think I'm going to do that.
Using a dirty loofah or washcloth or brush. They may be good for exfoliating the skin, but those things are loaded with germs unless you wash them regularly.
You should soak them once a week in a diluted vinegar soak or run them through the dishwasher. And not having a bath mat is asking for trouble.
According to a report from the Center for Disease Control and Prevention, more than 230,000 accidental injuries occur in the bathroom or shower in one year. And almost 20% of those injuries are due to slipping and falling.
So it is best to have those non-slip strips or a non-slip bath mat in your tub. And that is something you should know.
You know, podcasting is a very competitive business. We're always competing for new listeners, and one of the best ways to get them is for you to recommend this podcast to people you know.

It really helps us, and then they become listeners, and hopefully they'll tell people, and our audience continues to grow.

So please share this podcast with people you know, and it's a great way to show your support. I'm Mike Herbrothers.
Thanks for listening today to Something You Should Know. Have you ever heard about the 19th century French actress with so many lovers that they formed a lover's union? Or what about the Aboriginal Australian bandit who faked going into labor just to escape the police, which she escape from them it was a great plan how about the french queen who murdered her rival with poison gloves i'm ann foster host of the feminist women's history comedy podcast vulgar history every week i share the saga of a woman from history whose story you probably didn't already know and you will never forget after you hear it sometimes we re-examine well-known people like Cleopatra or Pocahontas, sharing the truth behind their legends.
Sometimes we look at the scandalous women you'll never find in a history textbook. Listen to Vulgar History wherever you get podcasts.
And if you're curious, the people I was talking about before, the Australian woman was named Marianne Bug and the French actress was named Rochelle. No last name, just Rochelle.
And the queen who poisoned her rival is Catherine de' Medici. I have episodes about all of them.
Hello, I am Kristen Russo. And I am Jenny Owen Youngs.
We are the hosts of Buffering the Vampire Slayer once more with spoilers, a rewatch podcast covering all 144 episodes of, you guessed it, Buffy the Vampire Slayer. We are here to humbly invite you to join us for our fifth Buffy prom, which, if you can believe it, we are hosting at the actual Sunnydale High School.
That's right. On April 4th and 5th, we will be descending upon the campus of Torrance High School, which was the filming location for Buffy's Sunnydale High.

To dance the night away, to 90s music in the iconic courtyard, to sip on punch right next to the Sunnydale High fountain, and to nerd out together in our prom best inside of the set of Buffy the Vampire Slayer.

All information and tickets can be found at bufferingcast.com slash prom. Come join us.