The Real and False Promises of AI & What They Really Ate at the First Thanksgiving
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Today on Something You Should Know, some fascinating facts you never knew, including one weird one about Wild Bill Hickok, then a top AI expert on the amazing things AI can do, and the false promises, the things AI cannot do.

These ideas about AI developing an agency of its own and deciding to do stuff, these are pure sci-fi scenarios. Based on the way that AI is currently built today, those speculative scenarios really have no basis in reality.

Also, the real reason printer ink is so expensive and a look back at what they really ate at the first Thanksgiving. One of the things that they always ate and ate to excess is pumpkin. Pumpkin was hugely important. New England was the pumpkin dominion and the first American folk song was written in 1620 and it was about how they ate too much pumpkin all the time. All this today on Something You Should Know.

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Something you should know. Fascinating Intel, the world's top experts and practical advice you can use in your life today. Something you should know with Mike Carruthers.

You know, I don't know why, whether it's because I have this job or I have this job because I like to do this, but I love to uncover fascinating facts about things that I never knew before. And I have uncovered some and would like to share them. And these first facts are all about photography.

In 2024, by the time this year is over, an estimated 1.94 trillion photographs will have been taken worldwide. Globally, we capture 5.3 billion photographs daily. That's 61,400 per second.

The average American takes 20 photos a day. And there are now approximately 14.3 trillion photographs in existence. And now to completely change the subject, you've heard of Wild Bill Hickok, right? The cowboy? Well, Wild Bill Hickok had a brother. And you know what his name was? Tame Bill Hickok. When George W. Bush was president...

He and Saddam Hussein both had their shoes made by the same Italian shoemaker. And there is a Mexican language. It's called Zouk. But the language died out in the mid-20th century. Only two people on the planet can speak it. And those two people are feuding and refuse to speak to each other. And that is something you should know. Music

There is so much talk today about artificial intelligence, AI. And my sense is that AI has been around long enough that the people, the experts who talk about it, presume we all know what it is and how it works. But I'll tell you, and maybe it's just me, but my understanding of AI is pretty elementary. I get it, but I don't really understand how it works or what it does or what it doesn't do on any kind of deep level.

In other words, there's a lot more about AI and the different kinds of AI that I don't know compared to what I do know. And I suspect I'm not the only one.

So, given how much AI seems to be creeping into our lives, I wanted to find someone who could help bring us up to speed on the latest in what AI is, what it does, and what it cannot do. And here to do that is Arvind Narayanan. He's a professor of computer science at Princeton and director of its Center for Information Technology Policy. He was named one of Time Magazine's 100 Most Influential People in AI –

and he's co-author of a book titled AI Snake Oil, What Artificial Intelligence Can Do, What It Can't, and How to Tell the Difference. Hey, Arvind, welcome to Something You Should Know. Hi, Mike. Thank you for having me. So on a very fundamental, simple level, what is AI?

AI is an umbrella term for a loosely related set of technologies. You have on the one hand generative AI like chat GPT. On the other hand, you know, you have self-driving cars and you have predictive AI, AI that's used in the criminal justice system, for instance, to make enormously consequential decisions.

decisions about people, AI that's used in healthcare, these types of AI generally have very little to do with each other. And it's true that some types of AI, notably generative AI, are rapidly advancing. But we should be careful about, I think, the snake oil salesmen in the AI world who like to just slap the AI label on whatever tech product they're selling to try to get us to think that it is some remarkable technology that's going to solve all our problems for us.

So you mentioned some different kinds of artificial intelligence just now. Can you go through and just explain what each one of them does? Or is that just too complicated to do? Oh, not at all. And I would say to listeners that if someone tells you it's too complicated, you should be skeptical. They're probably trying to hide something. But in broad strokes, so let's take a couple of different types of AI. So what's happening in ChatGPT is...

that it's simply a machine, and some of you may have heard this, a machine for predicting the next word in a sequence of words. What is the most likely next word? And it turns out, and this was largely a surprise to AI researchers as well, that the way for...

AI to be really good at predicting the next word in a sequence of words is to have some quote unquote understanding of language, of grammatical rules and patterns and understanding of facts about the world because

If you have a sentence like the capital of France is blank, it helps to know what the capital of France is so that you can complete that sentence with a high probability word instead of a low probability word. So it turns out that's really the secret behind it, and it might seem a little bit

disappointing to hear that that's all it is. And in a sense, that's all it is. But I think it is truly remarkable that developers are able to create something useful with this really brute force approach. And so when it's predicting the next word in a sequence, where is it? Where is it getting the info? Where is it pulling from to come up with that word?

Chatbots have been trained on essentially all of the text on the internet, approximately speaking, and a lot of books and so on. So that's what it's pulling from, right? So what trading means is that it has learned the statistical patterns that allow it to say,

For example, you know, something you should, the bot would know that no is a likely next word because there are many discussions of this podcast online. And so it has learned that statistical pattern.

So that's primarily what it's learning from. To a lesser extent, these bots learn from their conversations with us, but it's not in the way that a person would learn. It's not automatic. There's a cumbersome process by which companies have to filter these chat conversations and feed that back into the training data. But to a first approximation, it's learning from text on the web.

And so now talk about predictive AI and what that is and how it's different and how it works and all that. Sure. Yeah. So predictive AI, on the other hand, is statistics that we've had for a century almost that's been rebranded into quote unquote AI. So this is used, for example, in the criminal justice system to determine if a defendant should be jailed before their trial, you know, which could be months or years away.

It's used in healthcare to detect sepsis in a hospital context, for instance, by looking at various indicators. It's often used in hiring to try to predict which employee might be a fit for the role or who's going to be a good employee and that sort of thing. Now,

What's happening in all of these cases is that the system is just picking up crude statistical patterns. So in criminal justice, the system learns that younger defendants are more likely to re-offend if they're released before their trial, and so recommends treating them more harshly. So these kinds of, again, fairly crude statistical patterns that we've known how to do for a long time, but it's not the same kind of technology behind ChatGPT

It is not something that's advancing quickly, and it is something that I think we should be pretty skeptical about. But all it's doing is it's predicting based on the past, right? I mean, that's pretty much it. Exactly. It's making decisions about the future based on the past. So no matter how accurately it works, I think, you know, kind of on a fundamental philosophical level, we should think about

Is this a just way to treat people, right? Should you deny someone their freedom in the criminal justice system because of the behavior of people like them in the past? So that's, yeah, something that's deeply questionable as well.

What about this whole idea, though? We hear about AI and people throw that term around so much that AI can, you know, fake things and it can create images of people that aren't real. It can replace, you know, actors in a movie. I don't get all that.

Yeah, image generation AI has been advancing very quickly. And over the last year or so, companies have been working on video generation AI. So yes, I think to some extent, the hype around this is rampant.

real. I think deep fakes are already a problem. Specifically, the thing I'm most concerned about is deep fake nudes. And this is affected from what I can tell, you know, hundreds of thousands of people, primarily women, as you can imagine, around the world. And I think we desperately need regulation to curb some of the damage here.

Now, in the political sphere, there's also concern that deepfakes can be used to trick voters and that sort of thing. I'm less convinced of that. There has been a lot of alarmism about that.

But I think something we should think about is that in a world where we're online and we have no easy way to tell what's real and what's not, what does that mean for the erosion of trust in the online environment? And how easy that makes it for powerful people, politicians and others to evade accountability by claiming that even real videos are actually deepfakes. So we see that happening over and over. And that is something I'm worried about.

There have been very prominent people who have sounded the alarm that AI is dangerous, and we've heard things about how, you know, what if it

develops a mind of its own. There's all this stuff that's very scary sounding and I just don't know, is that real? What is the big concern that people like Elon Musk and others have? What are they worried about? What's the problem? First of all, with Elon Musk and other CEOs of AI companies, it's a very self-serving thing to say, right? So this is incredibly powerful technology. It's going to change the world either mechanically

bring about a utopia or destroy humanity. And we're the only ones in a position to ensure that this technology doesn't get out of control. We and many others in the AI community have spent a lot of time looking at the evidence behind these AI fears. And we've come up short, basically. So let's take some of the concerns that have been brought up.

that AI could help bioterrorists, for instance, by finding information about how to create bioweapons. Now, the funny thing about the sphere is that finding that information is not the hard part. For the most part, that's readily available on Wikipedia, right? And so if a chatbot, you know, makes it easier and makes it, you know, 10 seconds faster for someone to access that information, that's not the end of the world.

And there have been concerns in cybersecurity, for instance, that AI could be used to hack critical infrastructure and that could bring about catastrophic risk. But here's the funny thing.

If the ability to use AI to find bugs in software and attack systems that way, if that is a critical capability for hackers, then we've already lost. Because for the last 10 or 20 years, automated ways to find bugs have been readily available even before AI, yet the world hasn't ended.

And in fact, it's turned out that these methods primarily help defenders over attackers. They help software developers because those developers can use these automated tools, including AI, to find and fix bugs in their software before they ship it out, before hackers even have a chance to take a crack at it. And we think the same thing is happening with AI, and we think some of these fears are vastly overblown.

And then these ideas about AI developing, you know, an agency of its own and deciding to do stuff. These are pure sci-fi scenarios based on the way that AI is currently built today. You know, those speculative scenarios.

really have no basis in reality. Yeah. So quick break here. I'm speaking with one of the smartest guys I've ever met when it comes to AI. His name is Arvind Narayanan. He's one of Time Magazine's 100 most influential people in AI. And he's author of a book called AI Snake Oil, What Artificial Intelligence Can Do, What It Can't, and How to Tell the Difference.

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in a way that would be really helpful? So it's not this one big thing that AI is going to do for everybody. I mean, that might happen in the future, but so far, I don't think there has been this one killer application. But it's 100 little things. So in my work, for instance, it's been enormously useful in helping me write code. Frankly, it's hard for me to imagine going back to a time before I had AI assistance in writing code because it's just so much faster, but also more fun, frankly.

And, you know, for lawyers, I'm hearing there are so many ways in which legal tech is making their lives better, making it easier to find information. Of course, it's not going to replace a lawyer. There have been, you know, many overblown claims of companies building a robot lawyer and things like that. I think that sort of stuff is a little bit silly for now, at least.

But I think in every profession, you know, that involves basically dealing with knowledge in some way, AI can be a creativity enhancer or a way to automate certain mundane tasks in your everyday life. I think it can also be a good learning tool. There are pitfalls here because, you know, AI can hallucinate, that is, generate incorrect information and not even be aware that it is hallucinating.

That said, again, once one spends a few hours learning to work around these pitfalls, I think it can be a very good learning tool. I use AI a lot for learning about new topics. I haven't stopped using books for learning.

But, you know, I can't ask a book a question and I can't summarize my understanding of a topic to a book and ask it if I have gotten it right. These are things that I can do with chatbots. So those are a few of the ways in which I've been using it in my own work and in my own life. And I think each person has to figure it out for themselves. And so when you say that, you know, it would be worthwhile to use some of these tools and see what they can do.

Like what? Like, if I type a question into Google, am I using AI or is that a different technology? Like, what are the AI tools or are they embedded into everything? There are broadly two different ways to use AI. One is you can use a specific AI app. You know, ChatGPT is the most well-known one. Or...

You can use AI that's embedded into the other apps or other physical products that you use. And I think both of those are interesting and both of those are worth trying out. So specifically, if you do a Google search, there are relatively simple types of AI

that have existed even in traditional Google search. But more recently, Google has started creating these AI overviews, which can often be wrong. So I think it's caveat emptor to actually verify that information. But I think it can be more enlightening to play with a standalone AI tool like ChatGPT or Gemini or whatever people want to use.

and explore the kinds of things that it can do, as well as learn how it gets things wrong. And I think that's going to give you a much better understanding of AI's powers and limitations. And so I think when people use like ChatGBT or Gemini, there is an assumption that whatever it tells you is probably right. Is it probably right? What's the accuracy rate?

That's a great question. We should not assume that whatever AI tells us is probably right. I think the accuracy rate varies greatly depending on the kind of topic. When I use AI with my kids, you know, when I ask it science questions, it's very good at explaining those things in a way that a five-year-old can understand and almost never makes mistakes. But if you ask it questions on a very specialized topic, there have been papers looking at the accuracy of AI

AI in the legal sphere or medical sphere, right? Here it's much more dodgy and obviously these are areas where accuracy is much more important.

So one might wonder, you know, if it's going to sometimes make mistakes, should you use this tool at all? I would argue still probably yes, because I think it can still, you know, enable you to do things that would otherwise be very hard. So one example of this is when I'm exploring a new topic, I don't even know how to frame my question. And if I don't know the right terms to put into Google search, I can't find the authoritative sources on that topic.

But with chatbots, it's very easy. I just describe it in a fuzzy way in which

I think of it in my head and it, you know, it rephrases it for me and then it gives me information about that topic. Sometimes it's reliable, sometimes it's not. So it's just a very different way of interacting with information. It's just really hard to understand it in terms of previous ways of interacting with information. I can't give you a number saying, you know, 90% of the time it's going to be right. It just really varies depending on one's use case.

So I think, you know, each of us has to put a little bit of trial and error into adapting it for our own specific purposes. So where is the snake oil? What's the what's the snake oil part of this that has you most concerned? Criminal justice, for instance. Right. So I don't think that's.

you know, we should be making decisions about people based on these crude statistical formulas with some caveats, like I was saying earlier, if it's the judge who is empowered to make that decision, that's a different story.

There is a lot of the same coil in hiring. There are companies that claim that by analyzing a 30 second video of a candidate, of a job candidate, not even talking about their skills for the job, but about their hobbies or whatever, that they can do video analysis and look at the candidates facial expressions and body language and that sort of thing and use that to drive a personality score, which companies should do their hiring based on.

There's so much more. There is AI for detecting which students in a school or college might be at risk of suicide or mental health difficulties. There have been investigations of all these kinds of AI tools and they barely work better than the flip of a coin. So I think these are the kinds of things we should be very suspicious of. And unfortunately, these are the kinds of things that are often used

in order to make very high stakes decisions about people. Is it just a matter though of over time it will kind of work itself out, it'll get better because the more people use it and the more practice it gets basically that the better it gets?

For ChatGPT, yes. But here's the difference between ChatGPT and trying to predict if someone will commit a crime. You know, ChatGPT is just trying to do things like, you know, some typical thing you might use ChatGPT for is to translate text from one language to another, right? That's not like a fundamentally impossible task. It's something that humans can do. And AI over time is learning to do it better, right? Or write code or whatever it is. On the other hand,

Predicting, you know, what's going to happen in the future, no one knows. The universe doesn't know. It doesn't matter how much data you can throw at it. What we're seeing is that these technologies are not really getting better. They haven't got better in decades. And, you know, it should be common sense that...

We can't really predict the future, or at least not with anything close to perfect accuracy. And yet a lot of companies are telling us to suspend our common sense because AI, right? And that's what we're trying to push back on.

Well, I appreciate all you've said. It's helped me get a better understanding of what AI is and what it does and doesn't do. And I'm sure other people listening feel the same way. My guest has been Arvind Narayanan. He is a professor of computer science at Princeton and director of its Center for Information Technology Policy.

And he is author of a book called AI Snake Oil, What Artificial Intelligence Can Do, What It Can't, and How to Tell the Difference. And there's a link to that book at Amazon in the show notes. And thank you again for coming, Arvind. Ah, and here we have travelers in their natural habitat enjoying guaranteed 4 p.m. checkout at fine hotels and resorts booked through Amex Travel. And they don't even see what's coming at them.

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Most of us learned in school about the first Thanksgiving. How pilgrims and Native Americans came together for this big feast. And they ate turkey and pumpkin something or other. And they gave thanks. And I have to admit, I don't remember too much of what I learned about the first Thanksgiving. And in fact, I wonder how much of what I did learn was in fact fact or fiction.

Here to talk about what really went on at the first Thanksgiving and how some of our customs around this holiday actually came later is Leslie Landrigan. She's been writing about New England history for over 10 years, and she's author of a book called Historic Thanksgiving Foods and the People Who Cooked Them, 1607 to 1955. Hi, Leslie. Welcome to Something You Should Know. Thanks, Mike. I'm happy to be on.

So it seems like there's always been this fascination about what they ate at the first Thanksgiving. I'm not sure why that is, but is it a mystery? Is it a theory? Do we really know what they ate? We know two things. We know that they had four deer that the natives brought, the 90 natives. And we know that the men went out shooting birds, right?

With the natives and the Englishmen. So birds, deer, probably shellfish, probably corn. That's what we know for sure. Lobster, maybe. And do we know why that first Thanksgiving, like how these people came together and did they call it Thanksgiving? And like, what's, briefly as you can, what's,

What's the quick story of why these people came together? What's interesting to me, if you call the meeting of indigenous people and English colonists in, you know, the early 17th century to eat food in autumn, if you're going to call that a Thanksgiving, then the pilgrims in 1621 were not the first Thanksgiving. Right.

The first Thanksgiving would have been in 1607 in Phippsburg, Maine, where a failed colony was established for about a year. But the circumstances were very, very similar. The two groups came together basically together.

It was more of a state dinner than it was a Thanksgiving. They were negotiating alliances. They would trade with each other and they would defend each other against common enemies. The food that they ate, which we'll get into very soon here, but is it the food that they always ate or was this some real special kind of food? It was the food they usually ate.

They may have dressed it up a little bit and it would have been plentiful because of the time of year. But it was pretty much what they ate. I was going to say one of the things that they always ate and they ate to excess and they have eaten it since 1620 and they're still eating it is pumpkin. Pumpkin was hugely important. And you know how we call people in Wisconsin cheeseheads?

People used to call New Englanders pumpkin heads. New England was the pumpkin dominion. And the first folk song was written in, the first American folk song was written in 1620, and it was about how they ate too much pumpkin all the time. And what was the magic of pumpkin, just because there were so many? I mean, that wasn't something that came over from England, right? No.

Actually, they did know a pumpkin in England and pumpkin pie was really popular. The Spanish had brought it over and then it kind of fell out of favor. But it the it grew well. It it was more resistant to deer and insects and fungus and things like that. So I think it's it was just its hardiness. And, you know, it kept for a while.

In addition to a pie, what do you make out of pumpkin? They tended to stew it. They would do a lot with it, but mostly they'd chop it up and stew it and mix it up with other stuff. I don't know that it was terribly appetizing. Well, if you ever eat pumpkin, because we feed our dog pumpkin on recommendations of the vet, and it isn't much. I mean, without spicing it up, it doesn't really...

No. It's pretty bland. It's pretty nutritious, though. Right. That's why the dog eats it. Well, you know, the natives, they grew what was called the three sisters, the pumpkin or squash, beans and corn.

Which, for some reason, having to do with amino acids or carbohydrates or something, I don't know, makes for a very nutritious diet. At the center of today's Thanksgiving dinner is typically a turkey. Was it their center of the table? No, it wasn't for a long time. It didn't.

They may have had turkey at the first Thanksgiving. Wild turkeys are really stupid birds. They roost in the same place all the time. So, you know, if you want dinner, you just go get yourself a turkey. But in fact, they were so easy to kill that they were obliterated from New England, probably by the Civil War. Turkey, it was a part of the meal and it was something they ate.

But chicken pie was the big thing for a long time. And it was a woman named Sarah Josepha Hale, who was a widow with five kids and needed money. So she wrote a book in 1827. It was a novel. I can't think of the name of it, but it's

She described a Thanksgiving dinner in New England, a classic New England Thanksgiving, which was really at the time only celebrated in New England. And the book sold well and she got a job as the editor of what became Godey's Lady's Book, which was this tremendously influential magazine. It was way more influential than Martha Stewart.

And she she was an American influencer and she was the one who made turkey the centerpiece of the American meal. And she was also the one she lobbied for a long time to make Thanksgiving a national holiday. And finally, Abraham Lincoln was the one who said, yeah, OK.

So can you run down, without going into, you don't have to stop at any of them and go into any detail. We can do that later. But just like, what's the menu look like at these early Thanksgiving-y kind of dinners? What's on the menu? Well, for the pilgrims, it would have been something called nasamp, which was a native kind of a porridge made with cornmeal and nuts and

berries and maybe a sweetener. They probably would have had striped bass, which was a fish that was easy to catch, and that was also sustaining them. Probably would have had shellfish. They would have had deer, probably. And I'm guessing a lot of different kinds of wildfowl. They

I don't know that they would have had dessert, but they did develop this thing called Indian pudding, which was cornmeal with milk and a sweetener. What about potatoes, stuffing, and gravy? Oh, potatoes. Well, in 1620, we're talking about that first Thanksgiving, that first alleged Thanksgiving, they would have known about potatoes, but the potato they would have known about was the sweet potato.

which the Spanish had brought to Europe. And it was highly prized because it was believed to be an aphrodisiac and it was a luxury item. So some of the pilgrims who were of the gentry would have been familiar with the sweet potato. But the sweet potato didn't come to America, I think, until 1764, right?

The Irish potato didn't come to the United States until 1718 when a bunch of, there were five shiploads of Scots-Irish who came to Boston. And the Boston Puritans didn't want to have anything to do with them, so they sent them to the New Hampshire frontier. And in what is now Derry, New Hampshire, they planted the first potato there.

the first Irish potato, and it was viewed as a food for the poor, for pigs, and for the Irish. You just didn't eat the potato. And the French hated the white potato even more. They banned its harvesting or they banned the planting of the potato because they thought that it caused leprosy.

But then during the Seven Years' War, around 1755 or so, there was a French pharmacist who was captured by the Germans. And while he was in prison, they made him eat potatoes. So after he got released, he got really interested in nutrition and he rehabilitated the potato. And the French came to embrace the noble spud.

And they served Thomas Jefferson French fries in Paris when he was minister to France. And Thomas Jefferson liked the French fries. So he served them at the White House when he was president.

And that's how the white potato became a popular menu item at Thanksgiving. You said the sweet potato didn't come here until the 1700s, but I thought you said that it was at the first Thanksgiving, which would have been before then, so...

No, no, no. They would have known about the sweet potato, but they wouldn't have had them here. It was something, you know, it was like a really fancy food. So there are some foods that I think of as New England-y foods that are often associated with Thanksgiving. Were they, and those would be cranberries, apples, things like that. Were those there or not? Oh, they would have had cranberries, definitely. The natives...

revered the cranberry. In fact, there is a, there are some Wampanoag people who live on Martha's Vineyard and they, their Thanksgiving is the second, second Thursday, I think, in October.

And it's Cranberry Day, and the kids get out of school and they eat cranberries. It was very, very useful. It was used as a dye. It was used as a sweetener. It had medicinal properties. Were the early settlers here, the pilgrims, were they big on vegetables, meaning did they have peas and celery and carrots and things like that?

they would have eaten the three sisters, the pumpkins, the beans, and the squash. Celery is kind of an interesting vegetable because it didn't really come to America until the American Revolution, the 1770s. And it was kind of a fancy food. But think about it. You're celebrating Thanksgiving in

late fall and vegetables are mushy, but there's this nice green crisp vegetable. And for many years, it was the most popular item on U.S. restaurant menus next to coffee and tea.

So talk about the people, because you mentioned this, the one woman who was kind of the Martha Stewart of her, or bigger than Martha Stewart. But I imagine that there are other people in this story that kind of steer the menu a bit or the legend of the menu. Yes? Well, the people who stick in my mind are the first four women who cook Thanksgiving.

Because after that first winter, there were only four adult women left in Plymouth Colony. And there would have been some 48 others who survived and 90 Native Americans. So that's cooking for 140 people. Here are these four women who survived.

have to pluck all the birds that the men caught. They probably have to cut up the deer. They have no running water. They've got to cook outside. It just would have been a nightmare. I can't even imagine it. But I can tell you who they were. There was Mary Brewster, who was older. She was in her 50s, and she was the wife of...

William Brewster, the spiritual guide. There was Susanna Winslow, who was the wife of Edward Winslow, who was one of the leaders. And those two were saints, which means they were the Puritans who came for religious reasons. So the other two women were Elizabeth Hopkins and Elizabeth Billington. And the Billingtons were bad news. Her husband, John Billington, was hanged for murder and

Her son was a troublemaker who got lost and nearly started a war between the pilgrims and the natives, and she was whipped for slander. But the one who really interests me is Elizabeth Hopkins. Her husband was Stephen Hopkins, who was in a Shakespeare play.

He had come over to North America one time previously as an indentured servant, and his ship got wrecked, and they lived on Bermuda for nine months, and rebuilt the ship and went to Jamestown. And Shakespeare...

heard the story and wrote The Tempest. And so Stephen Hopkins, who came back to North America after returning to England, he was Stefano in The Tempest. He was the power-mad butler. So you have this image that we got in school of, you know, the Native Americans and the pilgrims coming together as some sort of like community dinner and that they're all getting together and

and sharing their food. Is that what this was? Was there a lot of, let me help you cook that, or here's how we do it here as Native Americans, or was there that kind of relationship? I think there would have been. One thing I'm really unclear about is whether

the native women came because, you know, they might have brought some nasamp or some cornbread or something. There were servants and there were children. And so I think everybody would have been pressed into service. They'd been working together for over a year. You know, the pilgrims had things that the Indians wanted, guns, for example, or, you

you know, trade goods, pots. And the natives had something that the pilgrims wanted, which was fur. There was a huge, huge market for beaver fur in Europe.

And the natives taught the pilgrims how to fish. So I think it would have been a cooperative effort. So the natives and the pilgrims have this big meal together. But was this like a special occasion? They came together, had this meal, and then they went their separate ways? Or did these people mingle together all the time? No, they intermingled a lot. As a matter of fact...

Edward Winslow, who was the husband of Susanna Winslow, who cooked that dinner, he saved the chief's life at one point. Massasoit had some illness and Edward Winslow came and I think, honestly, I think he fed him something like chicken soup and did something to save his life. So, yes. And of course, Squanto, the native who breeded them,

Taught them how to grow corn. So they were they were they mingled a lot What else about this holiday or the or the first Thanksgiving anyway, or the early? traditions of Thanksgiving do you find people still don't understand or maybe is a bit of a myth or Or anything like that. It wasn't really Thanksgiving until the 19th century

It was kind of forgotten. And Thanksgiving was something that the English celebrated in England and here. It wasn't a harvest meal. A real Thanksgiving was getting the community together because you were thankful for something. It could be rain after a drought or a military victory.

So after the Battle of Saratoga and the Revolution, Sam Adams in Massachusetts declared a day of Thanksgiving. You could have Thanksgiving in April. Your town could have a Thanksgiving. Thomas Jefferson actually declared Thanksgiving when he was governor of Virginia. And it didn't really become a national holiday until Abraham Lincoln declared it.

But the idea of Thanksgiving, as you say, came later. So what did they view it as? When they came together, they're coming together saying, hey, thanks for coming to our what? I think it would have been like a state dinner.

You know, they didn't sign any treaties, but that would have been the point of it. Well, it sounds like the Thanksgiving we have today that we celebrate in our homes with our family and friends is very different than those early Thanksgivings and frankly seems a lot tastier.

But it is fun to hear you talk about what those real Thanksgiving meals were like. I've been speaking with Leslie Landrigan. She is author of a book called Historic Thanksgiving Foods and the People Who Cooked Them, 1607 to 1955. And there's a link to her book at Amazon in the show notes. Leslie, thank you. Terrific. Thanks so much, Mike. Thank you.

Why is printer ink so expensive? A lot of people ask that question, and according to Consumer Reports, there are actually some good answers to that question. You might not like them, but they're good answers.

For one thing, the engineering that goes into printer ink today is really expensive. Today's printers have to fire thousands of drops of ink per second, representing four different colors with tremendous accuracy, and that ink needs to be quick-drying, water and smear resistant, and avoid making the page curl up. It also has to prevent the tiny little ink jets from getting clogged. All of that costs a lot of money.

Turns out that a lot of ink gets wasted. Well, it's not wasted, but it's not for printing. Printers use ink in two ways. First, of course, the ink is used to print documents and images, but the inkjets also use ink just to clean the printheads. According to one expert, it's typical for an inkjet printer to waste as much ink on maintenance as it does on printing documents.

Another reason is, in essence, you're paying off the printer. Think of the price of the printer as a down payment. It's theorized that some printers cost more to make than the price they sell for. But the printer companies make up the difference by marking up the ink. And that is something you should know. For a successful podcast like this to stay successful, we always need new listeners because...

As you can imagine, listeners come, listeners go, and so we constantly need to attract new listeners, and you can help by telling people you know about this podcast and suggesting they give a listen. I'm Micah Ruthers. Thanks for listening today to Something You Should Know.

Hey, hey, are you ready for some real talk and some fantastic laughs? Join me, Megan Rinks. And me, Melissa Demonts, for Don't Blame Me, But Am I Wrong? We're serving up four hilarious shows every week designed to entertain and engage and possibly

And don't blame me. We dive deep into listeners' questions, offering advice that's funny, relatable, and real. Whether you're dealing with relationship drama or you just need a friend's perspective, we've got you. Then switch gears with But Am I Wrong?, which is for listeners who didn't take our advice and want to know if they are the villains in the situation. Plus, we share our hot takes on current events and present situations that we might even be wrong in our lives. Spoiler alert, we are actually...

Quite literally never wrong. But wait, there's more. Check out See You Next Tuesday, where we reveal the juicy results from our listener polls from But Am I Wrong? And don't miss Fisting Friday, where we catch up, chat about pop culture, TV and movies. It's the perfect way to kick off your weekend. So if you're looking for a podcast that feels like a chat with your besties, listen to Don't Blame Me, But Am I Wrong on Apple Podcasts, Spotify or wherever you get your podcasts. New episodes every Monday, Tuesday, Thursday and Friday.

Do you love Disney? Do you love top 10 lists? Then you are going to love our hit podcast, Disney Countdown. I'm Megan, the Magical Millennial. And I'm the Dapper Danielle. On every episode of our fun and family-friendly show, we count down our top 10 lists of all things Disney. The parks, the movies, the music, the food, the lore. There is nothing we don't cover on our show. We are famous for rabbit holes, Disney-themed games, and fun facts you didn't know you needed.

I had Danielle and Megan record some answers to seemingly meaningless questions. I asked Danielle, what insect song is typically higher pitched in hotter temperatures and lower pitched in cooler temperatures? You got this. No, I didn't. Don't believe that. Witch coming true? Well, I didn't either. Of course, I'm just a cicada.

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