Chapter 1: Why do companies still invest in junk mail marketing?
Today on Something You Should Know, why some companies still send physical junk mail and who actually likes to read it? Then AI, what's behind this new wave of technology? What is powering this wave is not major breakthroughs in technology. What is powering the rate wave is enormous amounts of capital and these companies aren't making money.
They are basically telling us we have to use it because they have invested so much money in it. Also, why razor blades are so expensive and the story of alcohol and why so many people drink it. The production of alcohol, dating back 15,000 years, coincides with when we first started to live in groups, having to socially interact with other people.
One wonders whether alcohol's fulfilled a purpose really since that early time. All this today on Something You Should Know. Ah, the Regency era. You might know it as the time when Bridgerton takes place, or as the time when Jane Austen wrote her books. The Regency era was also an explosive time of social change, sex scandals, and maybe the worst king in British history.
Vulgar History's new season is all about the Regency era, the balls, the gowns, and all the scandal. Listen to Vulgar History, Regency era, wherever you get podcasts. Something you should know.
Chapter 2: What are the potential risks of trusting AI technology?
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 you probably get junk mail and you may have wondered why? Who reads junk mail? Well, you'd be surprised. And that's why we're going to start by talking about junk mail on this episode of Something You Should Know. Hi, I'm Mike Carruthers.
And yeah, people often complain about junk mail, and you might assume that younger generations, Gen Zs and Millennials, really hate junk mail. But marketing research shows that Gen Z and Millennials often pay more attention to physical mail than older generations do, largely because they grew up in a world flooded with digital ads.
When everything online is competing for your attention, a physical piece of mail can actually stand out. In fact, surveys from the US Postal Service found that younger consumers are more likely to read advertising mail and view it as more trustworthy than digital ads. One reason is simple. Digital ads feel disposable.
Chapter 3: What drives the hype surrounding artificial intelligence?
But a physical catalog or a postcard feels more tangible. And it tends to stick around on the counter or the table longer than an email stays in your inbox. So, while junk mail may seem like an outdated marketing tool, for many companies it's actually a way to cut through the digital noise. And that's why you still get junk mail. And it's something you should know.
It seems like everyone is talking about AI, artificial intelligence, what it can do, what it might become, how it's going to change the world. But the conversation you are about to hear looks at artificial intelligence from a very different angle. The concern isn't that AI will suddenly become conscious and take over the planet. The concern is almost the opposite.
that AI isn't actually thinking at all, at least not the way many people believe it is. And misunderstanding that may be where the real risk lies. My guest argues that much of the excitement around artificial intelligence is built on a fundamental misunderstanding of what these systems actually do, and what they don't do, and what's driving all the hype.
And essentially, what's driving all the hype is money. Emily Bender is professor of linguistics at the University of Washington. She was named in the inaugural Time 100 list of the most influential people in AI. She's co-author of a book called The AI Con, How to Fight Big Tech's Hype and Create the Future We Want. Hi, Emily. Welcome to Something You Should Know. I'm so glad to be here.
Thank you for having me on.
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Chapter 4: How has alcohol consumption changed in modern society?
So first, I think we need to define what AI hype is, because I'm not sure it's a term that people hear a lot, or I don't actually think I've heard it before I saw the cover of your book. So what is AI hype in a couple of sentences?
Yeah, so it is hype about AI, and I'd love to try to define AI as well, but hype is this like salesmanship, the sense that if you don't get on board, you are going to be missing out. You've got to jump on the train with everybody else without necessarily there being a real there there. Well, there certainly has been a lot of AI hype. I mean, there's a million books and podcasts.
I mean, we've had several guests on who've written books about AI and how to use it and what it's good for and all of that. And we hear a lot that it's taking over jobs. But there does seem, from people who use it, there does seem to be some sense that it really is pretty wonderful, that some of the things it seems to do are great.
Well, so we have to talk about what it is, though, because the term artificial intelligence doesn't refer to a coherent set of technologies. The main thing that everyone is super excited about right now is chatbots, or you might call them conversation simulators. And they are systems designed to mimic the way we use language in many different domains of activity.
And so it seems like we have systems that can do many different things, but actually what we have is a system that mimics the way we use language. Well, it may do that, but it seems like the experience of using it is that it's more than that, that it's deeper than that, that it's doing a lot of things. Well, so what do you have in mind?
Well, from my own experience of using it and the way I use it, it seems as if it's looking for information that can help me. It's synthesizing that information. It's writing it in a way, if I ask it to, to make it more effective. It seems like it's doing a lot of things, not just mimicking language. Unfortunately, it's designed to look like it's doing that.
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Chapter 5: What are the psychological and social reasons behind drinking?
There's a system addition called RAG, which is retrieval augmented generation, where you put a query into one of these systems. And the first thing that happens is that your input is turned into a web search. And then documents come back just the way web searches work in general.
And then the system is prompted to basically produce something that looks like a summary of the documents that came back to you. But there's no accountability there. There's no reliability there. And it's not searching the whole Internet any more than an old fashioned search engine does.
But it's certainly giving me information, it would seem, that I would have trouble coming up with myself or would certainly take a lot longer because it seems to be able to understand what I mean when...
when I want to find out this information, whereas Google, if I'm not using the right words in the right order, I could get a completely different set of websites to look at, and Google doesn't synthesize the websites, it just gives me a list of websites. Yeah, well, actually, unfortunately, now they do the synthesis thing in their AI overview. That's true, yes.
But if we want to distinguish sort of old-fashioned web search from the so-called AI search or chat interface, the big difference is that, yes, the way you interact with it is instead of putting in some keywords that you hope will match the documents you're looking for, you phrase the question the way you might ask a person who could understand you.
And that helps create the illusion that the system you are interacting with does understand you. But fundamentally, these systems are just set up to repeatedly answer the question, what is a likely next word?
And what is a likely next word given that question as input and the various documents that the web search returned produces something that looks like an answer and is very easy to accept as an answer, but we are then cut off from really important sense-making work where we understand where information is coming from
why somebody may have put those particular pieces of information together and how to situate all of that in our understanding of the information landscape. And is that really all bad? Unfortunately, yes. One of the examples I like to use is imagine you have a medical query and let's say you're expecting a child and you discover that they are likely to have clubfoot. So how do I treat clubfoot?
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Chapter 6: What are the health implications of alcohol consumption?
And if you put that into an old-fashioned web search and you got back answers, or not answers, but actually links to the Mayo Clinic and a local university medical center and something called WebMD and Dr. Oz's website and a chat room, you probably already have opinions about many of those sites.
And if like me, the Mayo Clinic to you is associated in your mind with cancer, you might go, wait, what's this got to do with cancer? But also I think of them as like a respectable institution. So I'm gonna go see why they might be talking about Clubfoot.
And anything in the chat room, I'm gonna take with a grain of salt, but it is extremely valuable to connect with other parents who are going through the same thing, right? If instead I put this into a chat bot and I get back something that might have come from one of any of those sources, I don't know where it came from, so I don't know how to situate it.
I am cut off from my ability to sort of continually build up my understanding of these different sources and cut off from the chance to connect with those other people. In your query, though... You could tell ChatGPT, please source all your information, please give me links to those sources, and then you get the summary from ChatGPT, and now you can go look at all the links to where it came from.
So there's no guarantee that the summary is an accurate representation of those links, so you are better off not reading it and just doing the old-fashioned source, old-fashioned search. Rather than getting the idea of in the summary where it might have dropped a negation or put some word emphasis or whatever it is because there's no accountability there.
It has no understanding of what it is processing. It is just giving you likely next words given that input. But you're making the assumption that if I read it, I believe it and therefore I shouldn't read it. But it seems to me I should read everything and then make my own determination.
I believe it is important to read many different things, but I think it is dangerous to read things that nobody has any accountability for. So go read those different sources. Go read a summary that a person has produced. But this synthetic output that we actually can't locate in the information landscape because it comes from nowhere is just misleading.
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Chapter 7: How do personal experiences shape our relationship with alcohol?
Well, I like that. It does. It comes from nowhere. Like, you can't point out, well, where did you, how did you arrive at that? In fact, you could ask the same question tomorrow and get a completely different answer. Exactly. And you can input into the chat bot, how did you get to that? And it will give you an answer, but that answer is not truthful, right? It's just more likely next words.
And so you can go down a big rabbit hole that way. But most likely next, it's most likely next words and not truthful aren't mutually exclusive. It could be truthful and it could be just next words. Exactly. So if what comes out is truthful or valuable, that is also by chance. If what comes out is incorrect, harmful, or just misleading, equally by chance.
And in neither case is there any accountability. And so do you then dismiss all of this technology? Do you not use ChatGPT or any of the other chatbots because of what you're saying? For many reasons, I do my very best not to consume any synthetic media. And define synthetic media.
Chapter 8: What factors contribute to the high cost of razor blades?
So synthetic media is text extruded from one of these chatbots or the images that someone has produced using a text-to-image system, the fake videos that are made. I don't want to spend time on things that don't reflect the either artistic effort of a person drawing an image or the thought processes and accountability of someone writing text.
So I want to explain how I use ChatGPT and get your views on that. If Bravo drama, pop culture chaos, and honest takes are your love language, you'll want All About TRH podcast in your feed. Hosted by Roxanne and Chantel, this show breaks down Real Housewives reality TV and the moments everyone's group chat is arguing about. Roxanne's been spilling Bravo tea since 2010.
And yes, we've interviewed Housewives royalty like Countess Luann and Teresa Giudice. Smart recaps, insider energy, and zero fluff. Listen to All About TRH podcast on Apple Podcasts, Spotify, or wherever you listen. New episodes weekly. Thank you. Hey, it's Hillary Frank from The Longest Shortest Time, an award-winning podcast about parenthood and reproductive health.
We talk about things like sex ed, birth control, pregnancy, bodily autonomy, and, of course, kids of all ages. But you don't have to be a parent to listen. If you like surprising, funny, poignant stories about human relationships and, you know, periods, The Longest Shortest Time is for you. Find us in any podcast app or at LongestShortestTime.com.
So, Emily, when I do this podcast, one of the things I do is I write introductions to the segments, usually after the segment is over, so I know what I'm introducing. And sometimes, you know, some days I just don't have it. It just doesn't come out right or I'm not explaining it well.
So I'll write a pretty crappy intro and then feed it into Chat Sheet BT and say, make this better, make this more compelling, make this more... intriguing, make this snappier, whatever I say. And sometimes, man, it comes out with something that is really good. And I think, wow, I wish I had thought to say that, but didn't. And so I'll use it. I'll use some of it.
Sometimes I don't use any of it because I think mine was better. But boy, sometimes it really hits it out of the park. Yeah. As you might guess, I have some objections to that. And I sure hope that you don't do it for this segment. And by the time listeners are hearing this, they will have heard whatever it was. Right. But I so for one thing, you've been doing this show for a long time.
You didn't use ChatGPT before November 30th, 2022, because it wasn't there. So, this is something you can do, but it's also a practice skill. And I think every time we do the cognitive offloading of using some system to do something instead of doing it ourselves, we lose that opportunity to practice.
We also lose the opportunity to really hone our own unique voices and sort of end up towards this average, which I think is really quite bland. On top of that, every time we use these systems, we help build the case for training the next large model, for building the next hyperscale data center with all of the economic, labor, and environmental impacts that those entail.
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