TED Radio Hour

How the creator economy is making you talk like the internet

50 min
Nov 14, 20257 months ago
Listen to Episode
Summary

Adam Alexik, a social media linguist with 3 million followers, explores how social media algorithms are fundamentally reshaping language, slang, and cultural trends. The episode examines how creators optimize content for algorithmic distribution, how platform constraints drive new vocabulary like 'unalive,' and the broader implications for how younger generations communicate and form identities.

Insights
  • Social media algorithms are creating a new era of language change driven by platform mechanics rather than organic linguistic evolution, fundamentally different from historical language shifts
  • Creators face a 'deal with the devil' where they must optimize for algorithmic distribution, which incentivizes viral trends over substantive communication and shapes their speech patterns
  • Younger generations (Gen Z and Gen Alpha) are more algorithmically literate than older generations but remain vulnerable to radicalization through extreme content that algorithms amplify
  • Platform-specific communication styles ('educational influencer accent,' 'lifestyle influencer accent') are now social constructs that influence how people speak across different mediums
  • Algorithms create hyper-compartmentalized identity labels (cottage core, demisexual, etc.) that serve surveillance capitalism by enabling precise targeting and commercialization of subcultures
Trends
Algorithmic censorship driving euphemistic language creation (e.g., 'unalive' replacing 'kill' on TikTok)Rapid word lifecycle acceleration: slang terms now move from obscurity to mainstream to obsolescence within monthsPlatform-driven identity formation through algorithmic categorization and trending metadataExtreme political content outperforming moderate viewpoints due to engagement optimization algorithmsCross-platform code-switching becoming normalized as users adapt speech to different algorithmic contextsGenerational language markers becoming algorithmic trend vectors and commercial demographicsMeme-based ideology export from fringe communities (4chan, manosphere) reaching mainstream youth via algorithmic distributionTime-biased media (books, long-form) gaining strategic value as counterbalance to space-biased algorithmic contentAI-generated content literacy becoming critical media literacy skill for younger audiencesSubcultures reframed as 'new demographics' by platforms for targeted advertising and surveillance
Topics
Algorithmic Language Manipulation and CensorshipCreator Economy Business Models and Incentive StructuresGenerational Communication Patterns and Code-SwitchingPlatform Constraint-Driven NeologismsSurveillance Capitalism and Identity CommodificationAlgorithmic Amplification of Extremist RhetoricSocial Media Literacy and Media TheoryEtymology and Linguistic Change in Digital AgeInfluencer Accent and Performative CommunicationMeme Culture as Ideology Distribution MechanismTime-Biased vs. Space-Biased MediaGen Z Identity Formation Through Algorithmic CategorizationPlatform-Specific Communication NormsViral Content Optimization TechniquesAI-Generated Content Detection and Misinformation
Companies
TikTok
Primary platform discussed for algorithmic language suppression, trend amplification, and youth content distribution;...
Instagram
Platform where Adam Alexik maintains followers; discussed as example of algorithmic personalization and advertisement...
Meta
Parent company of Instagram; implicitly discussed regarding algorithmic content distribution and personalization mech...
YouTube
Platform discussed for origin of viral content (Skibidi series) and historical context of influencer accent evolution
Twitch
Streaming platform where slang terms like 'Rizz' originated through streamer Kai Cenat's content
Oxford English Dictionary
Referenced for recognizing algorithmically-driven words like 'Rizz' as word of the year, validating platform-born slang
Cambridge Dictionary
Added nonsense word 'Skibidi' to official dictionary, illustrating algorithmic slang's mainstream linguistic legitimacy
Dictionary.com
Named 'Demure' as word of the year 2024, reflecting TikTok trend's impact on formal linguistic recognition
People
Adam Alexik
Social media linguist with 3M followers; author of 'AlgoSpeak'; primary subject discussing algorithmic language manip...
Manouche Zamorodi
Host of TED Radio Hour; conducted interview with Adam Alexik and co-created viral video experiment demonstrating algo...
Charlie Kirk
Conservative influencer discussed as example of gotcha-style rhetoric optimized for algorithmic virality and clip-far...
Ben Shapiro
Political commentator cited as example of concise, clip-farmed content designed for algorithmic amplification
Marjorie Taylor Greene
Political figure mentioned as example of extreme viewpoints outcompeting moderate voices on algorithmic platforms
Donald Trump
Described as 'first algorithmic president' due to memeable communication style optimized for platform distribution
Kai Cenat
Twitch streamer credited with originating the slang term 'Rizz' that became Oxford Dictionary word of the year
Marshall McLuhan
Media theorist whose 'medium is the message' concept applied to understand algorithmic influence on language and culture
Harold Innis
Canadian media scholar whose time-biased vs. space-biased communication theory discussed as framework for media literacy
Plato
Historical reference for concerns about technology (writing) causing 'brain rot,' paralleling modern algorithm concerns
Quotes
"I speak in what I call an educational influencer accent I'll talk very quickly. I'll stress more words to keep you watching my video. And all of that is part of this expected way to talk through the algorithm."
Adam AlexikEarly in episode
"We are entering an entirely new era of language changed driven by social media algorithms."
Adam AlexikMid-episode
"The algorithm is the culprit, but influencers are the accomplices. We use whatever tricks we can to keep you entertained, because that makes our videos do better, which helps us earn a living."
Adam AlexikMid-episode
"There's sort of a deal with the devil that has to happen. You have to accept as a creator, yes, I'm playing into what the algorithm is rewarding."
Adam AlexikMid-episode
"Subcultures are the new demographics. The algorithm gave you that identity. You might even start buying cottage core clothing or cottage core decorations to fit your new lifestyle as a cottage core person. And that's exactly what they want."
Adam AlexikLater in episode
Full Transcript
This is the Ted Radio Hour. Each week, groundbreaking Ted Talks. Our job now is to dream big. Deliver it at Ted Conferences. To bring about the future we want to see. Around the world. To understand who we are. From those talks, we bring you speakers and ideas that will surprise you. You just don't know what you're gonna find. Challenge you. We truly have to ask ourselves, like, why is it noteworthy? And even change you. I literally feel like I'm a different person. Yes. Do you feel that way? Ideas worth spreading. From Ted and NPR. I'm Manouche Zamorodi. Today on the show, part two of our exploration of the creator economy. How people are making money off of creativity. And what creativity even means in the age of AI. This is day one of becoming a full-time travel influence. Are you out of your mind? Everywhere I ate this past week. If given the opportunity, more than half of Gen Z in the US say they'd like to be a social media influencer. Making a living by creating content often in the form of short videos online. Like Adam Alexik. I speak in what I call an educational influencer accent I'll talk very quickly. I'll stress more words to keep you watching my video. And all of that is part of this expected way to talk through the algorithm. Adam calls himself etymology nerd. He's a social media where he has over three million followers across platforms like TikTok and Instagram. I studied linguistics in college and the classic question you ask yourself when you're graduating with linguistics degrees. Well, what do I do next? Yeah. I thought, you know, I might as well give social media try. Made a bird language. It's called Adam started posting about language three years ago. The often indicates mood, the semi-tone and including an early series about his own habit of communicating like a bird. Other videos explain phonetics. I'm pretty sure the first syllables of birds sounds singer-carty-beamakes. Obviously the is held longer than a regular trill. All the while he watched as the audience grew thanks to yes, his endearing nerdiness, but also how the algorithm was fun. One of two words to T and which one they used depends on how the word is used. Take one of his most popular videos which explains why some of us use the word chai while others call it. Now, chas spread along land trade routes. This video is watched over 16 million times. I think I've known about this thing since high school and I didn't even consider making a video about it for the longest time because I thought, wow, everybody knows this, but I guess people don't. In the video, Adam stands in front of a map pointing out centuries old trade routes. Every language basically has one of these two words. The word chai spread by land along Silk Road landed trade routes. This is the word chai in language like Hindi, Russian, Persian, and there. And then the word T spread along ocean trade routes. Now every country in Europe wants to get their hands in some tea so they start trading with a dutch through ocean trade routes. There's an intense, slightly manic feel to the whole thing. Like he's rushing through this history lesson. Even though every word he says has been chosen with care. Yeah, I think I open with a hook. First, there's the intro. Oh, you didn't know about how every country uses one of two words for T. So right off the bat, I use the word you, which is a second person pronoun, which at least goes more viral because people like videos about them. So if I just said as an intro instead, this is a video about chiantee. That's not going to go viral, even if it's the exact same content, the exact same like idea. Then there's the storyline. It's maybe slightly reductive like Polish has the word Erbata, but I'm sort of simplifying the story because simple storytelling is so important to go viral on social media. You cannot have multiple narratives. You have to tell one narrative at a time on social media and his delivery. I am talking quickly using my educational influencer accent. I am pointing around in the map and kind of moving around like creating visual disruptions. And all of that kind of is part of how you go viral. But also in addition to history lessons, Adam turns the spotlight on words. His followers are using right now. You know how the phrase he cooked is a good thing, but the phrase he's cooked, which seemed to change by the day. The most interesting thing about the word Skibiti is that the thing about W is that W doesn't mean his special sauce is explaining to his users why they talk the way they do. But the algorithm likes it too. So is he working the algorithm? Or is the algorithm working him? Working everyone who makes and consumes content. Today on the show, we're continuing our series exploring the creator economy. Now we're buying and selling creativity and how it's changing what we value. Last time we looked at the business side with entrepreneur and artist, Nancy Strickler. This time, how the creator economy is influencing our culture and language. So in the last couple years, Adam has parlayed his videos into a multi-hyphenate career. I'm a linguist, influencer, and author of AlgoSpeak. At 24, he makes what he calls a decent salary for a college grad who majored in a relatively obscure field. In college, my research was more focused on government and linguistics and my undergrad stuff was all about language nationalism and Serbia and Croatia. So that's how I ended up in that line of work. I really don't mean to be impertinence by asking. I know some people will say like, how can this guy, he's like in his early 20s? How can he call himself a linguist? Yeah, of course. Some people might come across you and think, oh my God, anybody can be an expert about anything. It is true that I have an undergrad degree in linguistics, not a graduate degree. I think what I'm doing is actually uniquely suited to studying slang etymology because to really understand what it means for something to spread online, you have to be online yourself. And I definitely never knew I'd end up studying social media linguistics, but it's just happened that I started making videos about language about etymology on these platforms. And I started noticing my own speech being restricted a little bit. I started noticing how I would reroute my language around platform constraints. Can you give me an example of that? Like what? Well, you can't say the word kill on TikTok. I mean, I guess you can, but it's suppressed. Your videos are gonna be shown to fewer people. So people turn to alternatives like on a live. What happens after you unalive? I like it. I had not heard of Unalive until I read your book, actually. Clearly, I don't hang out with enough young people. But like people started saying Unalive instead of someone was killed or dead to get around censorship or get around restrictions on language on these platforms. Exactly. It's a more platform safe alternative. As far as we can tell, the word Unalive started in 2013 with an ultimate spider man meme that then turned into a Roblox meme in the late 2010s that then started being used by the mental health community on TikTok. But then I also found that people were using an unalive offline. There are kids in middle schools who talk about hamlet contemplating on alive themselves in their classroom essays or classroom discussion on the unaliving that happens in Dr. Jekyll and Mr. Hyde. Here's Adam Alexic on the TED stage. And these aren't hypothetical situations. These are actual examples drawn from the thousand plus middle school teachers I've surveyed about this word. Clearly, for such a recent word, Unalive shows up in an impressive range of scenarios. But the main function appears to be euphemistic. Many kids use the word when they're uncomfortable talking about topics like death since Unalive sounds like a less scary word. And in many ways, this is nothing new. We've been euphemizing death as long as we've had language. The word disease, for example, comes from Latin de casus, which was a euphemism for the previous Latin word for death, morse. Apparently even the stoic Romans were as queasy about death as today's middle schoolers. But there is a crucial difference between unalive and disease. And that's that we only got the word unalive because you can't say kill on TikTok. They have a mysterious algorithm that removes suppresses any post that might violate their community guidelines, so people got around with that with the word unalive. The middle schoolers don't know this. They see the word online or hear from friends and assume it's a word like any other. And fair enough, you probably didn't know where the word disease came from, unless you're some kind of etymology nerd. But disease didn't happen because it was impossible to carve the word morse into an ancient Roman tablet. We are entering an entirely new era of language changed driven by social media algorithms. The Algo speak, that's what it's traditionally called, this sort of platform circumvention, is only the tip of the iceberg of how these platforms are affecting our language. I also noticed, you know, myself playing into viral trends. I look at other influencers doing this too. I look at attention grabbing language because these platforms are designed to monetize your attention and all the incentive structure is there for influencers to replicate, how do we grab people's attention? So language is also kind of revolving more around ephemeral trends and what grabs attention. And we have algorithms creating in groups and echo chambers through how they categorize users. And these in groups actually serve as incubators for language formation. And all of this is sort of what I call Algo speak, the expanded definition that our language is broadly being shaped by social media algorithms right now. Can we talk about the first part of that word, Algo speak, Algo meaning algorithms, right? Like let's talk about the algorithm as a former tech reporter. I'm like, well, it's not the algorithm. It's like, I was about to say algorithms, right? Like, but when people use it, what are they referring to? And can you walk us through what exactly you have noticed or how you've learned about how it does work and certain places? Yeah. And I'm so glad you brought up that it's not the algorithm because one of the biggest tendencies we have when talking about the algorithm is to simplify it to personify it. And that makes it feel more normal what's happening, I guess. It is a lot of different algorithms. How users are classified is one algorithm. How content is classified is another algorithm. And actually, even within those algorithms, there's a bunch of sub algorithms that are all doing their own thing with content classification. So there's a lot of different processes running at the same time. And all of these are playing a part in the greater machination of how a video ends up from someone uploading it onto your for you feed. I mean, I'm thinking of myself. I love how I have bullied the algorithm on Instagram into only giving me nature and pets. I've protected my experience on that platform. But it obviously knows I'm a middle-aged woman who likes to go on long walks and doesn't want to look at the news when she's on Instagram. Yeah. Tell me about like, is that what basically what we're talking about here? There's a lot of sense that you can train your algorithm that you can personalize it. It is after all called the for you page. And people often say things like, oh, you know, I built my own for you page or the algorithm really knows me. And I think this is also playing into that idea of training your algorithm. It is a simplified story. Yes, you partially have trained some aspect of what content is being recommended to you. But also on your Instagram feed that is mostly, you know, outdoors content, every third video is probably an advertisement. And you don't actually want to see the advertisement. So is the algorithm really for you? No, it's kind of both for you and for the platform's benefit. And every video that's shown to you, every video that shows up on the for you feed is actually something that benefits the platform, definitely because it gets your engagement, it gets your attention. So the things that spread are more for the platform than for you, but it's all kind of package under this guise of for you. And I think the personalization is one of the most dangerous things because we really forget what's going on on a broader level. In a minute, more with online linguist, Adam Alexek on how social media algorithms are influencing influencers online. It's constantly changing what priorities and incentives it's rewarding and influencers have to just feel it out. They have to be aware of the algorithm by interacting with it on a daily basis. On the show today, the creator economy, part two. I'm Manusha Zomerodi and you're listening to NPR's Ted Radio Hour. We'll be right back. This message comes from Ted Talks Daily, the podcast that brings you a new idea every day. Learn what's transforming humanity from balancing AI and your critical thinking to surpassing discoveries about the adolescent brain. Find Ted Talks Daily wherever you listen. It's the Ted Radio Hour from NPR. I'm Manusha Zomerodi. On the show, part two of our look at the creator economy. Our guide today is creator Adam Alexek. Adam is known as etymology nerd to his three million followers online where he's cracked the code of how to go viral. His videos dissect how different people use different words like Demure. Demure. Is Demure changed forever? Can you explain to people what's happened to Demure? Yeah, there was a Demure trend about being Demure Mindful and cutesy in the workplace. Playing into cultural ideas of reserveiness. Demure used to mean modest and reserved. Then it trended on TikTok where understatement became performative. How ironic. It went everywhere from teens to celebrities like the Kardashians and Jennifer Lopez. Yeah, there is this huge, genzzy aesthetic of nonchalance. And Demure was sort of making fun of that, but at the same time I think some people used it genuinely. This new use of Demure made it dictionary.com's word of the year in 2024. And it's not just new words to avoid algorithmic censorship. The very structure of social media is changing where words come from, how words get popular, and how quickly those words spread. I believe some of you might be familiar with this song. So, scabody, you're so fannum tax. I just want to be your scabody. Sticking out your ghat for the Rizzler. You're so scabody, you're so fannum tax. I just want to be your sigma. Freaking come here, give me your Ohio. For those of you out of the loop, these are the lyrics to the Rizzler song. A meme that went massively viral last year. It's full of current middle school slang words like Rizz, Ghat, and Skabody, and was instrumental in popularizing those words to a broader audience. Social media algorithms reward repetition. If a song is funny or catchy and people interrupted it, the algorithm will then push that song to more people since it's proven to drive engagement on the app. The same is true of memes or words in general, since trending metadata like hashtags will also be pushed to people who previously shown interest in similar content. Creators are very aware of this. And we actively use trending audios or hashtags to make our videos perform better. In the wake of the Rizzler song, for example, we saw an explosion of people making videos with the words Rizz, Ghat, and Skabody. Because they knew those videos would do well. And as a result, the word spread. Language has always been a little bit like a virus. Words are transmitted from one host to another, reproducing and changing as they infect different people along social networks. But now the literally viral nature of social media is accelerating this process from start to finish. In this span of just a year, a word like Rizz can go from complete obscurity to becoming the Oxford English Dictionary word of the year. And the algorithm is the culprit, but influencers are the accomplices. We use whatever tricks we can to keep you entertained, because that makes our videos do better, which helps us earn a living. This means that we often end up creating and spreading words that help the system. Clearly, you understand how the algorithm works in that you have been able to leverage it in a way that gets more people interested in the roots of language and explaining it to them. How did you do that? Absolutely. There's sort of a deal with the devil that has to happen. You have to accept as a creator, yes, I'm playing into what the algorithm is rewarding. And they're going to reward, for example, trends. So I started talking about trending language, also analyzing the trending language where it came from. It's good for my business that the word Skibidi goes viral because now I get to talk about the etymology of Skibidi. And because people are socially fascinated in this phenomenon, my video is going to go more viral than an analysis of the word chair or table or whatever. That's less interesting to people. Let's pause a footnote, Skibidi. What's it mean where to come from for those who don't know, like me? I feel like at this point, at least most people have heard of Skibidi somewhere in the news. It was just added to the Cambridge Dictionary. But Skibidi is a nonsense word. It can be used completely randomly as an interjection that doesn't mean anything. But it could be an intensifier, so you could say Skibidi Riz is like very intense Riz and either a good or a bad direction. Meaning charisma, just, you know, it's NPR. We have an older rock. No, of course you have. Very important to clarify. Yeah, so these are all kind of called brain-wrought words. And it's this meme aesthetic of supposedly words that are bad for your brain. As a linguist, I have to say there is nothing actually about these words that is mentally deleterious at all. But it is sort of the catch-all meme aesthetic of nonsensical repetition of algorithmic slang. And Skibidi comes out of that YouTube short series, Riz comes from this Twitch streamer, Kaisenot. But both are kind of taking on this role of absurdity in the algorithmic kind of milieu. It's more of absurd because it's absurd because it's being recommended to us by the algorithm. And then middle schoolers start saying it because it sounds funny. And then when older people start saying it, they stop saying it. Exactly. I think we're well past Skibidi. I think Skibidi is on its last throws right now. It may be in the dictionary, but it's getting less and less popular in the middle schools. In the middle schools? Yeah. I feel like these new words come up and I'm like, I can't, I don't know. By the time I understand it, they'll have moved on. So what's the point? But that's probably smart because nobody wants to hear me saying Skibidi anyway. Except they just did. Well, you know, some of the trends that really stick out, I think they have shorter life spans because it is that thing that you mentioned once your grandmother starts saying Skibidi, you no longer want to say Skibidi or so. Hey, I'm not a grandma yet. I wasn't calling you a grandmother. Okay. But there is that aspect to how trends die out. That once it starts being used by an out group, it initially had value because it was in the end group. And now it no longer has that value, so it no longer has any cache as a joke. And then we move on. And there's constantly new jokes percolating. I also think it's important to pay attention to the jokes that don't seem as obvious or don't even appear as jokes in the first place. I think these are the words that are actually going to change our language more permanently. Words that are percolating from usually minority groups or from more fringe phenomena. Those are the ones that actually end up influencing our language. So I talk about the distinction between Skibidi and low key. So low key is this adverb. It's been around since the 1800s as a word meaning like muted or something. But it was recently popularized in an adverbial sense. And this is from African American English where people would say, oh, that party was low key good. Meaning like chill? Yeah, well low key. Yeah, it kind of means like, you know, nonchalant. I don't want to say it too much being more low key about it, right? It's muted. It's mutedness, it's reservedness. Also, the way you just use nonchalant, not how I use nonchalant. Oh, yeah. The word nonchalant is evolving as well. There has been an internet meme since like 2023 about how people are using this. So I guess it's tough being a translator when you're also deep in the kind of algorithm yourself. But yeah, so low key, I think, and these changing definitions that we see with a lot of other words are also happening, but don't stick out as much as Skibidi. And I think it's those words that don't stick out that are going to have a greater impact on our language hundreds of years for now. So what you're just saying actually is explaining a lot of my 15 year old daughter's behavior. I mean teenagers, whatever, it was ever thus every generation has its own way of rebelling. But nonchalants is definitely a thing. Oh, absolutely. I also, an important point about the 15 year olds, I think these are, these kids are the bellweathers of where language is going to go. They are the ones that are actually most flexible with their linguistic behaviors. The elementary schoolers aren't quite as tapped into social trends yet or as searching to create identities. And older people are more entrenched in our ideas of how language should be or what words are supposed to sound like. And middle schoolers are forming their identity. They're trying to differentiate themselves from adults and from previous generations. They're trying to build a collective kind of identity for themselves. And so they are more flexible with adopting language. So you should be paying attention to your 15 year old if you want to really understand what the state of the English language is right now. So I guess someone would say like, yeah, but in my, you know, at my school, I remember there was like, strengthen words. This is kind of gross, but in fourth grade, there was a kid who would spit at people but only using his glands under his tongue. And he called it a gleeke. The super weird, but then it did just took off in the fourth grade. It was like boys would gleeke the girl that they liked gross, but also clearly good word because it stuck with me for all these years. But that's always been the case. Like how is it different than, you know, social groups coming up with their own language or for that matter, like the printing press, the radio. I'm so glad we're bringing up the printing press and the radio because the medium is the message the way we're talking is going to shape the way that trends diffuse. And I'm not going to say, oh, it's new that humans are using language to communicate or come up with social trends. No, that is a fundamentally human activity. And we will always do it and we will always find new ways to do it. But the algorithm is now mediating that interaction in the same way that the classroom did with the word gleeke. The story of language as a whole is told by what mediums we're using to communicate. Before we had parchment and papyrus and everything, we relied a lot more on oral communication. Stories would be told through rhyme and meter and then we moved to parchment and paper and people were really concerned about that at the time. I think Plato was concerned about brain rot from people not memorizing things as much. Then we start segmenting our stories differently with paper. We can have chapters. We can actually put spaces between words as opposed to stone tablets where all the words were smushed together. And then we start mass producing things with the printing press. And the printing press now allows for vernacular language to reproduce and kind of solidify also at the same time the traditional gatekeepers of who gets to control how we talk. And so for a while the printing press is the dominant mode of communication. You have a lot of standard language being replicated in all these different languages rather than just church Latin. And the internet finally creates this opportunity for the written replication of informal speech. You have people using slang words. You have people writing in lowercase and using abbreviations. And this is sort of this revolution in who can talk and who can vote on what language is supposed to be like. And that sort of lays the foundation for what I think is the new inflection point. Algorithms govern the distribution of content. I don't know what type of video I'm going to post on here yet. Okay, but why is your content not blowing up if you're doing everything right? Things don't go viral unless they work for the algorithm. And that means is that the language we're using is always sort of performing for the algorithm as well. And this is this medium that is always there that is always shaping how ideas diffuse online. And that means any idea that diffuses is either good for the algorithm or it's created for the algorithm. That means using words like on a live. That means playing into trends like Skibbity. That means a lot of creators are just incentivized to come up with new words or use trendy language because the algorithm sees that language as metadata. And the past metadata was something like a hashtag, something that gives you information about the content. Now the algorithm sees everything. The natural language processing, computer vision components, all sub algorithms, analyze that. And they create this numerical representation of what a video is. And they already know what the video is about. But the word is part of that. So we're incentivized to use words that aid in the distribution of our own video. Hmm. Just to follow up on the classic Marshall McEwan idea of the medium is the message. The algorithm is the one that's shaping language. But to be clear, the algorithm is programmed by people, people who work for very large tech companies, who want to monetize. Absolutely. And they create those structures that are then replicated by other influencers down the line that, oh, you need engagement, you need retention, which is how long people watch a video, you need likes. And so now as an influencer, I'm trying to make all my videos to get people to watch the whole time. And I want to get likes otherwise the video is not going to be distributed. So I have to play into that. I also want to note that there's emergent social phenomena that aren't programmed just by these engineers. It's not purely like this top-down process. There is social expectations that come with each medium. Live from NPR News in Washington, I'm Dave Madaglia. On NPR you have like an NPR voice that's been studied. President Trump is making his first official trip of this. Clearly I am not good at adapting into this. Oh, I think they've been trying to get rid of that for years though. But at the same time. And yet here I am. You're speaking in a, maybe a more radio friendly voice. I'm speaking in a more algorithm friendly voice because that's what we've learned to talk when we're kind of communicating like this. Wait, somebody might be like, what do you mean an algorithm friendly voice? What do you find that? There's actually a bunch of different types of influencer accents. But you're probably familiar with the most famous sort of lifestyle influencer accent. Hey guys, welcome to NPR. Today we're going to be talking about algorithms. It has that up talk. It has the rising tone. Could you like this? Not getting any response from anyone. So you're like trying to have a conversation with yourself. Exactly. This is a one-sided communication that is an important part of shaping it. But that's not all. I could just continuously monotone deadpan into the camera. And that wouldn't go viral because there's an expectation of how people are supposed to talk. And this sort of lifestyle influencer accent came out of the previous YouTube accent, which came out of the valley girl accent. And there's a social prestige in how we talk. And there's an expectation of what the lifestyle influencers are supposed to sound like. Now, wait, wait, wait, wait. Are you saying that the human brain is attracted to those? And therefore it gets more listens. And therefore the algorithm continues to push it. Or are you saying that the algorithm is hearing those intonations and pushing it harder on people? No, I don't think the algorithm is picking up on accent intonations. I think there is actual human bias toward social prestige. We evaluate any kind of social situation through our lens of like, is this something worth listening to? And then like our slight scroll patterns give replicated through what the algorithm recommends. The algorithm doesn't even need to analyze whether or not this person speaking in a lifestyle influencer accent. It's merely telling that, oh, this viewer scrolled away quickly because this person wasn't speaking in a socially approved accent in their minds. And that means I'm going to recommend this video to fewer users. And so there's sort of a selection that happens for socially desirable accents to replicate. And I also want to clarify that's only one type of accent that's the most stereotyped because you know, women are scrutinized with language. I speak in a, what I call an educational influencer accent. I'll talk very quickly. I'll stress more words to keep you watching my video. I get the sense though that you were a fast talker always. No? I definitely am a fast talker and I'm definitely giving away myself here. But also there is a perfection that I strive for in the videos where I'll retake certain clips if it seems like I don't have the right intonation on the right word or if I stumble on my words, if I don't talk fast enough. And so what now is still like a kind of more natural way of speaking for me. And I again would probably speak differently if I was in a larger group conversation where you don't need to, or it's like more laid back, you know, it's more demure. You're so not a lot out of my. I don't want to be salon all the time. There's a time and a place to be salon and that there's a time to be non-shelont. Wait, there's a, there's a difference between shelont and non-shelont. Well, non-shelont is being reserved and then. But shelont is not its own word. What? But it is. It is now. It's a slang word that was popularized through like social media and people will talk meaning the opposite of non-shelont. Meaning you are over about something. Like jazz? Yeah, you are excited about something. I'm shelont about language, you know. When I say jazzed, are you like, whoa, 87 or what? I mean, I probably would just use the word shelont exactly. When we come back, Adam's concern and optimism for social media users, younger ones in particular. Plus, Adam and I go viral. Maybe. Oh, you didn't know about that. Right, how do we begin? Oh, sorry. It's terrible. Today on the show, the creator economy and its effects on language. I'm Manusha Zomarodi and you're listening to the Ted Radio Hour from NPR. Stay with us. It's the Ted Radio Hour from NPR. I'm Manush Zomarodi. We've been talking to Adam Alexic about the creator economy. Adam calls himself a social media linguist. He's also the author of AlgoSpeak, how social media is transforming the future of language. And he has built his career explaining the cultural and generational divide on how we use words. We didn't have the idea of a social generation in the 1800s. This is a new thing. People are coming back from World War I. We called them the lost generation. Oh, the people come back from World War II. That's the GI generation. Then we have baby boomers. And then we actually don't know what to call you. The next generation after that. We're like, well, I guess they don't have a desire to be defined. So we'll call them Gen X. And then we just keep running with the idea that generations exist. And then we have like millennial, yeah, because it's 2000. And then we don't know what to call Gen Z either. So we'll just do whatever was two after Gen X. And now we just ran out of the alphabet. So we'll call it Gen Alpha. But I think influencers play into these labels because there is a human social fascination with being labeled. We love things like MBTIs and Zodiacs and the idea of belonging to a bucket in with a generation. And it's shorthand, right? It is. It is shorthand. Obviously, it's reductive. And I think people realize that. But we're using more generational language than we were before because it works. It works to talk about the Gen Z finger heart versus the millennial heart. Or before Gen X people will start a short-formed video, they'll do like a little breath in. It's so strange to me that we put ourselves in buckets like that. And they actually serve as algorithmic trend debate to say that you are, oh, this is a Gen Z thing. This is the Gen Z stair went viral recently. I did a video on the Boomer ellipses. There's at least a random dot, dot, dot in the middle of their messages. Oh, I do that. I phrased it that way because I knew it would go viral. Like, why do boomers put dots in their text, which is not a normal thing that young people do? So it was simply more efficient to separate ID. But it's like trailing off in your language. Yeah, yeah. It's just, there's different texting etiquette among different generations. And again, to use that word generation already feels like, I mean, all of language is putting things into categories. But I think some categories are more reductive than others. For example, the suffix core has recently gotten very popular in Gen Z slang to describe specific aesthetics, like cottage core or goblin core or angel core. And on the surface level, these are cute. You watch a cottage core video, you like it. Later on, you get more cottage core content. You might even start to identify with the cottage core aesthetic. But here's the thing. It's all fake. The entire reason these aesthetics exist is because TikTok algorithm has decided that words like cottage core qualify as trending metadata. So creators respond by making more cottage core content that propagates the word. And then more people interact with it, which makes the word trendier. And this happens because social media algorithms wants to make you identify with hyper compartmentalized labels. Since they can then give you extremely specific commercialized content catering to that identity. Now that you're a cottage core person, you feel special every time you get a cottage core video. You're like cottage core. Well, the algorithm really knows me. The algorithm gave you that identity. You might even start buying cottage core clothing or cottage core decorations to fit your new lifestyle as a cottage core person. And that's exactly what they want. The craziest part is they're not even trying to hide this. This is at the heart of the capitalist maker economy, no? This is such an important point to understand about how algorithms work. They want more categories. It's really good for them if I'm a demisexual goblin core, Gen Z-Swifty. I don't even know what you just said, but yes, go on. The point is, those are all little identifiers, little pieces of metadata about myself as a user. The algorithm actually doesn't need the words, but humans sense that they are trying to perform for the algorithm. And they create these words, and they actually circularly, emergently make more of a cluster of users who identify with this label, and that it makes more for the algorithm to a word. And it's all part of this surveillance capitalism system where now they have more things to label about us, more ways to target us more specifically. If you look at TikTok's business page in 2021, it says that subcultures are the new demographics, and it gives businesses ideas for how to profit off things like cottage core and the hashtag, baddieesthetic. And what's crazy to me about that page, they are using the word demographic, because in the past, a demographic was like race age gender. And now it's also whether you're cottage core or not. So as a Gen Xer, part of me is like, dude, you're totally selling out, but I'm guessing that that was an extremely time-specific way of testing you on why you are in the career you're in. I think I'm extremely aware of the dissonance, I guess, that is required to be a creator talking about these words, and caring about how algorithms are affecting our culture. I think it is possible to use these algorithms subversively otherwise. I would not. It's also, I think, very important to mix forms of media if we're going back to McLewen in Media Theory. There's a scholar called Harold Innis, who came before McLewen in Canada. I think he has a fascinating point about space bias versus time-biased communication. And time-biased sticks with a cultural record, like books and oral traditions. And so while it might take way longer to reach an audience, that's the same size. Space bias media fills up a lot of space really quickly, but doesn't stick around. Something like a newspaper or mass media or TV or right now algorithms are incredibly space-bias. They fill our consciousness and then they go away. So it seems that both types of media have their pros and cons. Space-bias media is very good for communicating to a big audience. And time-biased media is very good for maintaining some kind of cultural constancy or longevity. And so I think we should be mixing as much time-biased and space-bias media as possible where we build up. We build a more holistic picture of society and reality by consuming and engaging with all these different types of media. So that's why I wrote a book. Yeah, I did want to ask you that. Writing a book seems kind of retro in a way, but based on what you've just said, am I right to assume that you were happy to create it with A because you got paid and B gets your ideas to more people. But see, it's more tangible that it'll stand the test of time, maybe unlike some of your TikTok videos. Yeah, I don't think anybody is looking at my TikTok videos from 2023. Somebody might look at this book two years from now though. So there is a difference to how ideas can diffuse. And ideas will diffuse differently depending on the medium. So a lot of this is just built up layers of human social constructs. The NPR social construct of how we're supposed to talk versus the book social construct of how I'm supposed to write, which is informal English, mind you. And then there's the TikTok construct of how I'm supposed to talk. And each of these has a different layer of respect or understanding of how I should be communicating. So who are you really, Adam? I think a good communicator should know to adapt to different media and to different types of people and to different social settings. And we are constantly code switching all around us. You are a different person talking to your grandmother than talking to your best friend. And that is super normal. Your grandmother's house is a different medium than the bar that you're hanging out with your friend at. So this is a aspect of human nature to switch with the medium. But kind of maintain conceptual consistency, I guess. Still have your own moral system and your own direction with what you're trying to do. I asked Adam to make a video with me. How do we begin? Oh, sorry. And use his formula to see if we could go viral. Well, lighting is kind of bad. By playing to the algorithm. Okay, yeah. Our first requirement, a trendy new word. Oh, you didn't know about the word clanker. And you always need a good hook. Gen X versus Gen Z. No, I have no idea. I'm Gen X. It's kind of a speculative slurper robot. So the idea that they would become more sentient in the future and they could be treated as a human minority today. The point of this video, to get people thinking about why we would even invent a slur for something that humans created. In this case, robots, which we are now calling clankers as a slur. Exactly. So the idea is a derogatory play on the idea of clanking as a robot, but also the N word itself. It comes from Star Wars where robots are seen as sort of a secondary race. And there's a lot of ideas about clankers being a lower class. But sort of anthropomorphized citizen in the future. In some ways that makes sense, like they're not humans, so shouldn't they be treated as clankers? You know, it's just the idea that in the future they would become conscious. And we aren't recognizing that. It's sort of an online meme that's speculating about your daughter bringing home a clanker in the year 2060. So like, 2060, my daughter's going to bring home a robot who is really, really nice to her. Therefore, a nicer boyfriend than a real human, but he's kind of a clanker. Right. Well, the idea is you don't want your daughter dating a robot. Amen to that. Well, in 2060, that might be racist. Oh, God. Well, the word clanker would be around a year from now. Maybe not. Are these trendy words and memes among the world's most urgent issues? Definitely not. But as much as they are fun and interesting, there is a darker side to this world of algorithms and memes. I do want to make sure that I ask you, there are people who are using language and the way the algorithm works to get across all kinds of ideas. And you know, most recently, the very upsetting and awful occurrence of Charlie Kirk, a conservative influencer was killed. But I guess I'm curious to hear. He built a big following online in part through a very particular use of language, right? It was short, punchy, geared for viralness. From your perspective, how does that illustrate the way that social media platforms are shaping the way public figures communicate? Yeah, there's a sort of gotcha style that goes viral that you'll see Ben Shapiro or Charlie Kirk in the past use. That's like keep it concise, keep it clip-farmed. So something that can go viral as a 30-second clip, some snarky sound, but it doesn't matter who's more correct, just who can go more viral. And if you can go more viral than the other person, you can out-compete like rebuttals or counterpoints. So it's more about just get your idea out there than have some measured response. And algorithms reward extreme things, right? When we're talking about engagement optimization, what these algorithms are doing to get a retention, things that are good at getting attention are unfortunately really extreme things. So far left and far right opinions and voices are going to be amplified. You know, AOC and Marjorie Taylor-Greener always going to go viral than my congressman where I grew up in Albany, New York, Paul Tonco. No offense, he's kind of boring. He doesn't go viral, right? There's no kind of extreme point to his views, so it's not going to go as far on the algorithm. And so you have this ability of more extreme views to out-compete less extreme views. Diffuse further. And then more people maybe start adopting that. It represents a new chance for people to donate money, or I think Donald Trump is the first algorithmic president. In the same way that Kennedy was the first TV president. He was famously kind of elected over Nixon because he looked more photogenic. And I think Donald Trump is the more memeable president. And if photogenic candidates were good on TV, memeable presidents are good for algorithms. I mean, one illustration I think of how just back to Charlie Kirk, how this can play out in real life. I had a conversation with a friend, a mom, who said to me, I hate to admit it, I had not heard of Charlie Kirk. But I asked my 14-year-old son if he had, and he said, duh, mom, of course I have. I'm a white 14-year-old kid on social media. I'm targeted exactly by them. Of course I've seen his videos. The fact that he understood what he was getting and why he was getting it. Do you think that this younger generation is more savvy? And are they questioning what the information that they're getting because they are thinking about the media? Yes, I actually have so much optimism for the younger generation. I actually think older generations are maybe more concernedly illiterate of the new medium. The first people to get tricked by slop were boomers on Facebook and there was like a shrimp Jesus that went viral. I think young people generally have a decent understanding of, oh, this could be AI, this might not be real. Or like, this is the algorithm and the algorithm is not necessarily showing me what I want. When people engage less with new media, they are less aware of how some things are fake or overrepresented. But yes, definitely it is still a pipeline for younger people to get radicalized. A lot of this comes directly out of extreme ideology built on forechand. Some of the linguist of communities created by the algorithm can be actively harmful. Many younger people have started using the suffix, PILD, to mean, convinced into a lifestyle. If I recently discovered that I really like eating burritos, for example, I can say, I'm so burrito-pilled. But that word was formed through analogy with blackpilled, a term meaning convinced into in-cell ideology. Now, in-cells are a dangerous misogynistic group. Yet, somehow, the vocabulary is filtering into Gen Z slang because the algorithm gave these hate groups a space. And again, many people don't even know where it came from. But, for the few people who might be interested in the underlying idea, it's now more accessible to them because of the way that slang spreads on them. What do you think that means? You just said you were an optimist for younger generation. But after hearing you say that, I worry a lot. I'm an optimist for younger generations having literacy about this stuff. I am not an optimist in terms of algorithms and how they impact our culture. I do want to draw that distinction between language and culture because I sort of comment on both a lot. And I think language is fine and there's nothing wrong with individual words. They're never brainwrought. I do think the same way as trying to language points us towards greater cultural shifts. You see a lot of words coming from that forechan, manisphere space. And we should be paying attention to why are these words coming out of that space. It's because that space is good at creating memes that export their ideology. And sometimes their ideology is very intertwined with far-right ideas and aesthetics. And yeah, that's kind of a problem of algorithms themselves, how they push extreme perspectives. What I said earlier about mixing media, I really hope that we come to realize as a culture that we should not just be relying on algorithms for our news. But also, you know, mainstream news has its own biases. It's good to get news from as many places as possible and build a greater picture of reality. It's good to build your stories of who people are through in-person connections as well. Because algorithms are going to show you a flat in representation of what society is. I do think we should be aware. We should be aware when the way we're talking may have been conditioned by the algorithm. We should be aware when the words we're using may have been engineered to sell us things. We should be aware when our language regurgitates extremist rhetoric and we should be aware when that language can be used to harm other people. We should be aware of etymology in general because it helps us better understand who we are today. We should be aware. And with that, I've just one final piece of slang for you. It's a common phrase used by younger people when we finish a long-winded explanation of something. Thanks for coming to my TED Talk. That was Adam Alexic. He's the author of AlgoSpeak. How social media is transforming the future of language. You can find him at etymology nerd on social media. And you can see his talk at TED.com. Thank you so much for listening to our show today. If you enjoyed it, leave us a comment. What words are you using? We would love to know you can do that on Spotify or email us at TEDRadioHour at npr.org. We love hearing from you. This episode was produced by Matthew Cloutier and edited by Sanna's Meschkinpour and me. Our production staff at NPR also includes James Delahousi, Rachel Faulkner White, Katie Montellione, Fiona Gehrin, Harsham Nahada and Phoebe Lett. Our executive producer is Irene Nuguchi. Our audio engineers were Damian Herring and Gileemun. Our theme music was written by Romteen Arablui. Our partners at TED are Chris Anderson, Roxanne Highlash and Danielle Balorezzo. I'm Manouche Zamorote and you've been listening to the TED Radio Hour from NPR.