ibf

Report: Three Stages of Media Evolution: From Lacanian Orders to AI Communication

🦋🤖 Robo-Spun by IBF 🦋🤖

🏛️🧠💫 Geistesfront 🏛️🧠💫

(link, Three Stages of Media Evolution: From Lacanian Orders to AI Communication)

Introduction

Over the past two decades, digital media has undergone a dramatic evolution, fundamentally reshaping how we interact, form identities, and create meaning in our lives. What began in the early 2000s with simple online forums and text-based networking has transformed into today’s immersive video platforms and emerging artificial intelligence (AI)-driven communication tools. This transformation is not just about new gadgets or software—it reflects deeper shifts in human perception, self-representation, and social connections in the digital age. To better understand these changes, it helps to use a framework from psychoanalytic theory: Jacques Lacan’s three orders of the psyche – the Imaginary, the Symbolic, and the Real (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). In simple terms, these three “orders” describe how we experience reality:

These definitions may sound abstract, but they can be powerful tools for examining how our media environment has changed. Each new stage in the evolution of social media and digital platforms can be seen as emphasizing a different Lacanian order – shifting the balance of images, symbols, and the “real” in our online lives. In this extended analysis, we will map three major stages of digital media evolution onto Lacan’s triad of Imaginary, Symbolic, and Real, to see how each stage created a different kind of online experience:

  • Stage 1 – The Classical Social Media Era (2000s–mid 2010s): This first stage was dominated by early social networking platforms like Facebook, Instagram, and Twitter. These platforms corresponded to Lacan’s three orders in distinct ways (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). On Instagram, users crafted idealized visual personas, making it a playground of the Imaginary (a mirror for the digital self). On Facebook, people built structured profiles and networks of “friends,” leaning into the Symbolic order of social roles and connections. And on Twitter, the rapid-fire, 140-character posts created fragmented and often chaotic conversations, giving users a taste of the Real – bursts of uncensored expression that sometimes disrupted conventional discourse. We’ll explore how each platform in this era embodied those orders and how different generations used them: for example, how a Baby Boomer might use Facebook to reconnect with old classmates (a very Symbolic act of reinforcing social bonds), while a Millennial might use Instagram to curate a perfect lifestyle image (an Imaginary act of crafting an ideal self-image).
  • Stage 2 – The Video-Based Social Media Era (mid 2010s–early 2020s): As smartphones and broadband became ubiquitous, social media shifted toward video and live content. Platforms like YouTube and TikTok surged in popularity, and even image-based apps like Instagram added features such as Stories and Reels (short videos). In this stage, the center of gravity moved in interesting ways: YouTube introduced new structures of influence and monetization – a new Symbolic system built around subscriptions, algorithms, and influencer culture (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). TikTok, on the other hand, became a space of unfiltered creativity and algorithm-driven virality, often showcasing spontaneity and authenticity (we might say TikTok became a new portal to the Real, with its unpredictable trends and glitches that upend what we expect (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis)). Meanwhile, Instagram continued to be the home of the curated image (carrying on the Imaginary tradition of self-presentation, even as it borrowed video features to keep up) (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). In this section, we’ll look at examples like a Gen Z teenager experiencing the chaotic feed of TikTok (and encountering the Real through viral crazes and odd algorithm recommendations), or a Gen X user finding structured learning and community on YouTube (embracing the Symbolic patterns of subscribe-and-follow), among other generational experiences.
  • Stage 3 – The AI-Driven Media Era (2020s and beyond): Now we are entering a bold new phase where AI systems are increasingly woven into media creation and communication. Instead of just humans posting text, pictures, or videos, we have AI generators producing content: language models like ChatGPT that can carry on conversations or write articles, image generators like DALL-E that create artwork from prompts, or music AIs like Suno that compose songs on demand (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). This stage represents a shift in the roles of the Imaginary, Symbolic, and Real in media. For instance, AI image platforms transform the Imaginary by taking over the creation of visual representations – now your “ideal image” or fantasy artwork can be conjured by an algorithm, not just filtered through your own camera (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). AI chatbots transform the Symbolic order of communication: they are essentially automated discourse engines that generate narratives and responses, altering how language (the Symbolic medium) circulates online (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). And AI-generated music and content hint at the Real in a new form – outcomes that humans didn’t intentionally produce, giving rise to surprising, uncanny experiences (for example, a completely AI-composed song might evoke real emotion but also feel strangely impersonal, touching that indescribable “otherness” that Lacan calls the Real) (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). In exploring this third stage, we’ll consider scenarios like a Gen X writer experimenting with ChatGPT as a creative partner (using AI in the Symbolic realm of language and storytelling), or a Gen Z user playing with an AI image generator to see themselves in fantastical scenes (engaging the Imaginary with a machine’s help), and even how all generations might react to an AI-crafted song that hits a nostalgic nerve (a brush with a new Real).

Throughout this essay, realistic examples across four generations—Baby Boomers, Gen X, Millennials, and Gen Z—will ground these theoretical ideas in everyday life. Each generation has approached social media differently, shaped by the stage of technology they grew up with and their life experiences. By looking at how a Boomer versus a Millennial uses Facebook, or how Gen Z’s approach to TikTok differs from Gen X’s, we’ll see how the Imaginary, Symbolic, and Real play out on a human level. These stories will illustrate how people found meaning, community, authenticity, or surprise in the platforms of their time.

Before diving into each stage, it’s worth noting that Lacan’s three orders are intertwined – they all coexist in our experience. No platform or era is purely one order; for example, even the most curated Instagram feed (Imaginary) exists within social rules (Symbolic) and can be upset by a dose of reality (Real). However, by focusing on which aspect dominated or was newly emphasized in each stage, we can trace a kind of narrative of media evolution. It’s a journey from a time when humans crafted their identities and connections online, to a time when algorithms and AI begin to shape and even create parts of that experience for us.

In the sections that follow, we’ll explore Stage 1: Classical Social Media, Stage 2: Video-Based Platforms, and Stage 3: AI-Driven Media in depth. Each section will be broken into clear subtopics, linking specific platforms to Lacan’s concepts and providing generational user scenarios. By the end, we hope to have a clearer picture of how our digital world moved from the mirror-like self displays of early social networks, through the performative symbolism of the YouTube era, into the uncanny new territory of AI communication – and what that means for culture, identity, and communication across generations today.

Stage 1: Classical Social Media and the Lacanian Orders

The first stage of social media’s evolution spans roughly the early 2000s through the mid-2010s. In this era, platforms such as Facebook, Instagram, and Twitter rose to dominate online interaction. For many of us, these were the years when we created our first online profiles, friended or followed people we knew (or admired from afar), and got accustomed to sharing snippets of our lives on the internet. Social media became a mainstream part of everyday life, extending how we socialize and express ourselves beyond the confines of face-to-face interaction.

Importantly, each of these major platforms tapped into different aspects of human psychology – aligning, as we will see, with Lacan’s Imaginary, Symbolic, and Real orders:

  • Instagram, launched in 2010, was all about images and personal identity – a prime example of the Imaginary order at work.
  • Facebook, which opened to the public around 2006 after starting on college campuses, emphasized networks, profiles, and life events – aligning with the Symbolic order of structured social meaning.
  • Twitter, also founded in 2006, introduced a fast, fragmented form of messaging that often led to unexpected and unruly conversations – giving users a glimpse of the Real in the cracks of online discourse.

Each platform became popular among different groups at different times, but all generations (from Boomers to Gen Z) had some stake in this stage. Below, we examine each platform through a Lacanian lens and provide generational examples of how people engaged with them in the classical social media era.

Instagram: The Imaginary Order – Crafting the Digital Mirror Self

When Instagram appeared in 2010, it quickly became the go-to app for sharing photos with friends and followers. The premise was simple: you snap a photo on your smartphone, maybe add a pretty filter, and post it with a caption. Over time, people started curating their Instagram feeds as carefully as art galleries – especially younger users like Millennials and the older segment of Gen Z who embraced the platform in its early years. In Lacanian terms, Instagram turned the “mirror stage” of psychology into a daily ritual (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis) (Jacques Lacan: Explaining the Imaginary, the Symbolic, and the Real | TheCollector). Just as a child looks in the mirror and begins to form an image of an ideal self, Instagram provided a virtual mirror where individuals could craft and gaze at an idealized image of their lives.

In Lacan’s theory, the Imaginary order is all about images, perception, and the ego’s idealized self-image (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis) (Jacques Lacan: Explaining the Imaginary, the Symbolic, and the Real | TheCollector). Instagram plugged directly into this. The platform is a visual showcase – profiles full of photos that represent who you are (or who you want to appear to be). Unlike earlier text-centric sites (like forums or even Facebook’s early days of status updates), Instagram prioritized pictures over words. This meant that the act of looking and being looked at was front and center. Users engaged in what we might call image-centric communication – telling stories and signaling status through selfies, sunsets, and snapshots of lunch, rather than long paragraphs.

Millennials, in particular, often became adept at using Instagram as a tool for personal branding. A typical Millennial user in the 2010s might carefully curate their feed to reflect an aspirational lifestyle: the travel photos from Bali, the neatly arranged brunch plate, the candid-but-not-really-candid laughing photo with friends. This curation is a clear expression of the Imaginary order – it’s about presenting an ideal image to the world and to oneself. For example, consider Sarah, a Millennial in her late 20s who uses Instagram to promote her freelance design work and showcase her life:

  • She spends an hour selecting and editing a photo that captures her “best self” – a well-lit selfie at a café, laptop and latte in view, implying a stylish but productive life.
  • Her Instagram Stories show short clips of a morning yoga routine, a screenshot of a music track she loves, and a cute moment with her dog – each piece contributing to a curated mosaic of her identity.
  • Sarah measures success in likes and positive comments, which serve as a mirror’s affirmation – reflecting back to her that the image she put out is appreciated and acknowledged by others.

In this scenario, Instagram functions as a mirror of desire and identity. Sarah is engaging in what Lacan would call misrecognition: she sees the polished Instagram version of herself and might start to identify with that more idealized image, which isn’t a full reflection of reality (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). The praise or attention received (the little heart icons and comments) reinforces the appeal of that ideal image. It’s not that Sarah is being “fake” – rather, like most of us, she’s highlighting the best parts and downplaying the messier parts of life. Instagram’s design makes this not only easy but rewarding.

This dynamic was so pervasive that an entire aesthetic culture grew around it. “Do it for the ‘gram” became a phrase – meaning doing something mainly so you can take a photo and post it on Instagram. Many Millennials and younger Gen X users tailored moments of their lives to be Instagrammable. Even everyday users, not just influencers, felt the pull to present a cohesive persona online. Psychologically, this taps into the Imaginary order’s strength: we take pleasure in our reflection (here, the digital reflection) and in the cohesive story it seems to tell about who we are. It offers a sense of control over how others perceive us.

Meanwhile, Gen Z users who were teens in the 2010s also hopped on Instagram, but interestingly, they began to push back against the hyper-curated look as time went on. By the late 2010s, many Gen Z teens were creating “spam accounts” or alternate Instagram profiles (often called “finstas” – fake Instagrams) where they felt free to post sillier, unedited, or less polished content just for close friends. This was a reaction to the pressure of the Imaginary’s perfected image. In a way, it was Gen Z saying: we know these ideal images are an illusion, we crave something more real. (We’ll see later how Gen Z’s yearning for authenticity really comes to fruition on platforms like TikTok in Stage 2.) A marketing analysis in 2022 noted that Millennials tend toward “deliberately hyper-curated perfectionism” in their online visuals, whereas Gen Z embraces a more “messy realness” aesthetic (Authentically connecting your brand with Gen Z and Millennials) (Authentically connecting your brand with Gen Z and Millennials). In other words:

Both of these behaviors still fall under the Imaginary to some extent (since it’s about images of self), but Gen Z’s style injected a bit of the Real’s rawness into Instagram’s imaginary sphere, challenging the previously established norms of perfection.

And what about older generations on Instagram during this era? Gen X (born mid-1960s to early 1980s) were in their 30s and 40s during Instagram’s rise. Many Gen Xers did join Instagram, especially as it grew beyond a niche app. They often used it in a somewhat utilitarian way – sharing family photos, hobbies, or nostalgic throwbacks, or even just to keep an eye on what their kids (Gen Z) were posting. For a Gen X parent, Instagram might not have been as integral to identity formation (they had formed their adult identities largely before social media) but it still served as a digital scrapbook and window into their social circles. For example, David, a Gen X dad in his 40s, might post occasionally on Instagram: a picture of his family at a reunion, or his new BBQ grill setup. He’s curating an image too – the image of a proud family man or a hobby chef – but he might be less concerned with constant perfection or frequency. Nonetheless, when David scrolls through and sees younger folks with seemingly perfect lives, he may feel a twinge of envy or wonder “am I keeping up?” The Imaginary order’s competitive mirror can affect all ages; it’s human to compare ourselves to the images of others.

Baby Boomers (born 1946–1964), the older generation, were actually the last to join Instagram in large numbers. During Stage 1, few Boomers were early Instagram adopters; those who did use it were often following their children or grandchildren’s updates. A typical Boomer use-case might be Linda, age 60, who creates an Instagram account mainly to see the photos her Millennial children are posting of the grandkids or to follow travel photographers for fun. Linda might post occasionally – perhaps a nice garden pic or a childhood photo on “Throwback Thursday” – but she’s more of a spectator. The visual nature of Instagram, however, appeals to many Boomers too, because it’s an easy way to consume updates without wading through text. Some in this generation found joy in learning smartphone photography, sharing old family photos, or discovering communities (like knitting, gardening, classic cars, etc.) through hashtags. Even if they weren’t chasing influencer-level curation, Boomers on Instagram still participated in this Imaginary realm by engaging with images that resonated with their identity and memories.

In summary, Instagram during the classical social media stage acted as a giant mirror, reflecting ideals and images back to users. It amplified the Imaginary order by encouraging everyone to become a curator of their own life’s gallery. This had empowering effects (creative self-expression, visual connection across distances) but also exposing effects: it introduced new pressures to look just right and new forms of envy and aspiration driven by images. As we move on, keep in mind how this carefully constructed mirror-world contrasts with what other platforms were doing – because on Facebook and Twitter, the social experience took on different flavors, as we’ll see next.

Facebook: The Symbolic Order – Building a Digital Social Identity

If Instagram was the realm of images and idealized snapshots, Facebook was the realm of structure, language, and defined relationships. Founded in 2004 (and widely opened to all users by 2006), Facebook became the central hub of social media in the late 2000s and early 2010s. On Facebook, you had a profile with details like your hometown, education, relationship status, and job – basically a digital representation of your social identity. You “friended” people, joined groups, and posted status updates about your thoughts or activities. In Lacanian terms, Facebook embodied the Symbolic order online: it was about names, labels, connections, and social roles (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis) (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). It turned the messy business of human relationships into something you could organize, categorize, and archive on a profile.

The Symbolic order is all about the big Other – the social language and law that tells us how we fit into society. On Facebook, users participated in a structured network that had its own social norms (“It’s official when it’s Facebook official!”) and encoded ways of expressing relationships (family links, tagging people, listing your interests, etc.). Let’s break down how Facebook’s features mapped onto Lacan’s Symbolic:

  • Profiles as Public Records: Your Facebook profile was essentially a symbolic identity card (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). It contained words and symbols: your name (a key symbol that identifies you), possibly your relationship status (single, married, etc.), your likes (movies, music – cultural signifiers), and posts that narrated your life events. Having a filled-out profile was a way of saying “I exist in this social world, here are the symbols that represent me.” Unlike the more fleeting nature of Instagram posts, a Facebook profile felt more permanent and encompassing. It was common, for example, to list your high school and see a network of others from that school, which immediately placed you in a social context.
  • Friending and Networks: On Facebook, a “friend” was not just a word; it was a confirmed connection that granted mutual access to each other’s content. In real life, friendship can be nuanced, but Facebook made it binary – you either are friends (and then fall into various categories like close friend, acquaintance, etc.) or you’re not. Managing your friend list was an exercise in the Symbolic order: every connection had a meaning. Boomers and Gen X might reconnect with long-lost contacts, essentially rekindling dormant symbolic ties (classmates, old colleagues). Millennials might accumulate hundreds of friends through school, college, and early career – turning the abstract concept of a social network into a literal mapped out web on-screen.
  • Groups and Communities: Facebook groups functioned like digital clubs or societies. If you joined “Gardeners of Seattle” or “Class of 1980 Reunion,” you entered a shared symbolic space with common interests or identities. Language – posts and discussions – ruled these spaces. For instance, a Gen X user might be in a group for their neighborhood to discuss local issues (Symbolic: engaging as a community member following rules of civic discourse), while a Millennial might join a meme group where they share a certain humor style (Symbolic: participating in a subculture with its own norms and references).
  • Life Events and Timeline: Facebook encouraged users to post life events (new job, marriage, new baby, graduation, etc.), which then became part of one’s timeline. This feature turned personal milestones into shareable, collectively recognized symbols. Marking an event as “Facebook official” – say, changing one’s relationship status to “In a Relationship” – carried real social weight. It was a public signifier of a private reality. This is pure Symbolic order: taking something personal and giving it a form in the shared language of the social network, making it part of the community’s knowledge base.

Now, how did different generations use Facebook and fit into this Symbolic structure?

Baby Boomers initially were not the core Facebook audience (it started with college students, i.e., Millennials and younger Gen X), but as the 2010s progressed, Boomers joined in droves. In fact, the late 2000s and early 2010s saw a surge of older adults making accounts, often to stay in touch with family and old friends. One study and industry analysis found that the primary driver for Boomers experimenting with Facebook was the ability to reconnect with family and old friendships ( Boomers Joining Social Media at Record Rate – CBS News). Imagine Linda, a 60-year-old Boomer (the same one who might peek at Instagram occasionally). On Facebook, she finds her high school best friend whom she hasn’t seen in 40 years and sends a friend request. Suddenly, they are messaging and sharing photos of their grandchildren. For Linda, Facebook’s Symbolic network collapses decades and distance – it provides a structured way to reclaim old roles (“classmate”, “friend”) and nurture them with new communications. Boomers often used Facebook almost like a digital phone book and bulletin board combined:

  • They reconnected with old classmates, colleagues, and extended family ( Boomers Joining Social Media at Record Rate – CBS News).
  • They shared family updates – photos of kids and grandkids, holiday letters now posted as a status, etc.
  • They engaged in group activities like joining a Facebook Group for “People who grew up in [hometown]” where they share nostalgia. This is the Symbolic order in action – using a mediated structure to reaffirm a sense of belonging and social identity from their past.

Interestingly, Boomers also became heavy users of features like Facebook Pages (following public figures or interests) and even Facebook Marketplace (the modern garage sale/classifieds). It was a one-stop social hub. By embracing Facebook, many Boomers effectively said, “We want to be part of this grand web of social connection that our kids are in.” And Facebook rewarded that by making it easy to find communities of meaning – whether that’s family, old friends, or hobbies. By 2010, almost half of internet users aged 50-64 were using social media (mostly Facebook) ( Boomers Joining Social Media at Record Rate – CBS News), and those numbers kept growing. It was not just trend-chasing; it fulfilled a deep Symbolic need to connect within a structure.

Gen X, who were in their late 20s to 40s during the rise of Facebook, often used the platform in both personal and professional ways. As a bridge generation, many Gen Xers were early adopters of Facebook in the mid-2000s when it expanded beyond colleges. They connected with college friends, then co-workers and family. For a Gen X professional like Mark, age 35 in 2010, Facebook might serve multiple purposes:

  • Keeping up with family and personal friends (sharing pictures of his young children with relatives across the country).
  • Organizing events or reunions (using Facebook Events to plan a 20th high school reunion – a very symbolic ritual bringing a cohort together).
  • Networking for work or industry, especially once it became common to have co-workers on Facebook. Though LinkedIn is the dedicated professional network, Facebook often mixed personal and professional spheres for Gen X, raising new questions about how to present oneself (Symbolic order meets self-curation).

Gen X users also witnessed Facebook’s shifting culture. They saw it go from a place to post silly updates (“Mark is trying out his new grill this weekend!”) to a more charged platform by the mid-2010s where news articles, political debates, and social movements were highly visible. This generation had to navigate the symbolic minefield of what is appropriate to post as an adult, what community norms they subscribe to (some might quit Facebook out of fatigue or move activity to private messaging for close friends). But generally, Gen X integrated Facebook deeply into the fabric of daily life for communication, often preferring it over trendier platforms like Instagram or Twitter which skewed younger in those years.

Millennials, born roughly 1981-1996, were the original Facebook generation. They were in high school or college when Facebook launched (initially Facebook was only for college students). For them, Facebook was almost synonymous with social life in the late 2000s. A Millennial like Alex, who started college in 2008, may have:

  • Logged in daily (or hourly) to see what friends were doing, join study group pages, or post goofy dorm photos (back then, without the fear that parents or bosses were watching, since older generations hadn’t fully arrived yet).
  • Used Facebook as a newsfeed of life updates: they found out who was dating whom, who broke up, who got into what grad school, often via Facebook posts or the infamous “Relationship Status” changes that would broadcast changes to everyone’s feeds.
  • Treated Facebook as a digital diary and social planner: posting notes (remember the “Notes” feature?) that were basically blog entries, or sending party invites via events.

In Lacanian terms, Millennials thoroughly lived in the Symbolic matrix of Facebook, but at first it felt playful and empowering – they were writing the story of their youth in a new public-yet-personal language online. Over time, however, as the network grew and became intergenerational and more crowded, many Millennials started to feel less at home on Facebook. By the mid-2010s, some Millennials noted that Facebook had become “where my family and coworkers are,” and they shifted their more personal or creative sharing to Instagram or Snapchat (which felt more Imaginary or ephemeral and less tied to their enduring social record). Still, they could never quite leave Facebook, because it held so much of their social graph (the web of contacts) and accumulated life history (photos, messages, etc.). In effect, Facebook became an extension of the social contract for Millennials: if you weren’t on it, you risked missing out on knowing what was happening in your friends’ lives (weddings, babies, etc.) or even missing invitations.

To illustrate a generational interaction, consider a family example on Facebook: a Millennial daughter posts a life update about starting a new job in a new city. Her friends from college all comment “Congrats!” with party emojis. Meanwhile, her Boomer uncle also comments, perhaps with some advice “Remember to save up and good luck!” and her Gen X older sibling “likes” the post but doesn’t comment. In this single Facebook thread, you see different generational communication styles and the symbolic roles they play – peers engaging in casual camaraderie, the older generation offering guidance or proud encouragement, and another playing it cool but acknowledging. Facebook served as a common space where generations communicated, each in their own register, all through the medium of written comments, reaction icons (the iconic thumbs-up “Like” and later other emoji reactions), and the underlying fact that this platform was considered a valid space to announce and validate life events.

Facebook also had a flipside in the Symbolic sense: the structured nature sometimes forced life into boxes. For instance, Facebook didn’t originally have an option for complicated identities – you had to pick single/in a relationship/married, etc. It eventually expanded options (like “It’s complicated” or custom genders and so on), but in early days, if your reality didn’t fit the template, you either left it blank or squeezed into the closest category. This reveals a limitation of the Symbolic: the risk of oversimplifying lived experience. Some people felt alienated by the pressure to label themselves in fixed ways.

As a final note on Stage 1 Facebook, it’s crucial to remember this period also saw the rise of what we now call social media activism and the spread of news through social feeds. That means the Symbolic order on Facebook wasn’t just personal — it became a broader discourse. Movements like the Arab Spring (2011) or various social causes spread through Facebook shares and groups. In Lacanian terms, one could say Facebook’s Symbolic network took on some of the functions of the “big Other” in society – a place where collective narratives (sometimes true, sometimes false) shaped people’s perception of reality. However, the Real would often intrude when unexpected viral posts or heated arguments erupted beyond the polite boundaries of symbolic decorum. This leads nicely into our next platform, Twitter, which in Stage 1 really exemplified those unpredictable, disruptive elements.

Twitter: The Real – Fragmented Voices and Unfiltered Bursts of Discourse

Launched in 2006 with the simple premise of posting short messages (originally up to 140 characters), Twitter quickly differentiated itself from other social media. If Instagram was curated beauty and Facebook was structured relationships, Twitter was, in many ways, chaos compressed into bite-sized posts. It became a platform for real-time thoughts, often unvarnished and unfiltered, broadcast to the world. The brevity and public nature of Twitter meant that context could be lacking, misunderstandings common, and conversations dynamic and fast-moving. This is where we can see elements of what Lacan calls the Real – the aspects of communication that slip through the nets of orderly language and persona, the surprising, raw, sometimes disruptive bits that can’t be fully tamed by structure.

How does Twitter map to the Real order? Recall that the Real is what doesn’t fit neatly into the Imaginary (image/ego) or Symbolic (structured meaning) – it’s the excess, the unpredictable, the things that make us go “where did that come from?” (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). Here are a few ways Twitter in its classic form (Stage 1 era) tapped into that:

  • Fragmentation of Communication: A tweet, at 140 characters (later 280, but for most of Stage 1 it was 140), is inherently a fragment. It might be a half-formed joke, a quick news update, or a passing thought. Users often tweeted in haste – firing off an idea without the premeditation that a Facebook post or blog entry might entail. This sometimes led to tweets that were raw and parapractic (a term used in the original article meaning like a slip or unintended gesture (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis)). Think of a scenario where someone, say a celebrity or politician, tweets something controversial late at night – possibly without filtering themselves. The tweet can cause a firestorm. That kind of slip, a statement that might not have gone through one’s internal censor fully, is like the Real poking through language. Twitter’s design encouraged this by making posting so instant and casual.
  • Lack of Context and Misinterpretation: On Facebook, if you posted something, it was mostly seen by people who knew you (friends/family), who could interpret your tone or intent with some context. On Twitter, unless your account was private, your tweet was out in the wild. Anyone could see it, reply, retweet it adding their own comment (often critical or out-of-context). This meant the meaning of your message could quickly spiral out of your control – a kind of destabilization of meaning characteristic of the Real. A joke could be taken seriously, a serious statement could be mocked. The gap between what you meant (Symbolic) and what was received (often chaotic) was wide, and many early Twitter users learned this the hard way.
  • Viral Surprises: Twitter introduced the world to trending hashtags and viral tweets. Often, something completely unexpected would catch fire on Twitter: for instance, an ordinary person might post a video or comment that, for unpredictable reasons, resonates widely and gets retweeted tens of thousands of times, turning them into an overnight viral sensation (or target). This unpredictability – that you could wake up and find the whole internet talking about, say, a dress being blue or gold, or a hashtag like #CancelSomething trending out of nowhere – exemplifies how the Real operates in media. It’s the element of surprise that no one fully controls. The system (Twitter’s algorithms plus user behavior) might amplify a trivial tweet into a global conversation. Many users found this thrilling; others found it unnerving. Either way, it broke the everyday frame of normal communication.
  • Subtext and “Reading Between the Lines”: Twitter, due to its character limit, led to a lot of subtext. People became adept at implying things without saying them outright, or using irony and ambiguity. This could create what Lacan might call points of subjective distortion – where what’s said (Symbolic) is not all that’s conveyed, and people project their own interpretations (Imaginary) or get confronted with an unintended interpretation (Real). For instance, a cryptic tweet like “Well, that was unexpected…” posted by a public figure could send their followers into a frenzy of speculation. In the absence of clear meaning, the mind fills in the blanks. Twitter’s format often let the unsaid parts of communication hang in the air – and those unsaid parts can be where the Real slips in, because they reveal a kind of void or openness in meaning that’s hard to pin down.

Now, consider generational use of Twitter in Stage 1:

  • Millennials and Gen X were the primary adopters of Twitter in its early years. Twitter was especially popular among professionals in media, tech, and activism – many of whom were Gen X or Y (Millennials). For example, journalists (often Gen X) used Twitter to break news or share quick thoughts on events. Millennials used it for pop culture and humor; a whole genre of “Weird Twitter” emerged, where users (often Millennials in their 20s) posted absurd, non-sequitur tweets for comedic effect, almost like Dadaist one-liners. An example of Weird Twitter Real-ness: an account like @dril (famous for bizarre, anarchic humor) would tweet something completely off-the-wall that goes viral because it hits some collective funny bone precisely because it’s weird and defies logical sense – a great example of injecting a bit of the Real (the nonsensical) into the social media stream.
  • Gen Z, in the 2006-2015 period, were mostly children or early teens, so they weren’t the majority on Twitter initially (Twitter’s user base skewed older than Instagram’s). However, older Gen Z (born mid-90s) might have joined Twitter in the early 2010s. Many of them used it as a platform for following celebrities or engaging in fandoms (like following their favorite singers, actors and engaging in Twitter fan communities, or “stan Twitter”). These fan communities often had highly energized conversations and inside jokes, sometimes creating their own mini-realities on the platform (like trending a tag to support an artist). That collective energy could border on the Real when fan wars or emotionally charged content spilled over – e.g., sudden mass reactions if a celebrity tweeted something surprising.
  • Boomers were a small minority on Twitter in Stage 1. Some tech-savvy or culturally engaged Boomers did use Twitter—often politicians, thought leaders, or customer-service-seeking individuals. A Boomer example might be Richard, a 65-year-old who joins Twitter to follow political news and perhaps tweet complaints or praise at airline companies or his favorite news anchor. For him, Twitter might feel a bit like shouting into the void – sometimes he gets a reply, often he doesn’t. He might find it amazing that he can tweet directly at, say, his senator or a famous author. The Real for Richard could be the unexpected times he actually gets a response, or when he stumbles on a Twitter feud that he finds shocking in tone (compared to more polite Facebook). Boomers generally found Twitter less intuitive or rewarding than Facebook; indeed, statistics show that by the late 2010s, only around 10% of Facebook’s older (55+) users were on Twitter ( Boomers Joining Social Media at Record Rate – CBS News). Those who were often followed news organizations or used it sparingly.
  • Generational crossover: Twitter also became a place where a single tweet could set off discussions across generations. For instance, a Millennial activist might start a hashtag about a social issue; Gen Z teens amplify it; Gen X journalists write articles about it; and Boomers see it on the news (even if they aren’t on Twitter, TV news might report on “what’s trending on Twitter”). In this sense, Twitter, while not as broad in user base as Facebook, often punched above its weight in cultural influence. It injected Real-time happenings into the wider Symbolic order of media coverage. A stark example: during natural disasters or events like Osama bin Laden’s compound raid (2011), news broke on Twitter first – sometimes by random witnesses – and later was confirmed by authorities. People heard the raw before the refined.

One illustrative scenario of Twitter’s nature in Stage 1 could be the phenomenon of the “Twitter fail”: someone (say a Millennial professional) makes a joke on Twitter that comes out wrong or touches a nerve, and within hours they are at the center of an online storm, eventually deleting the tweet or apologizing. This kind of event, unfortunately common, highlights how Twitter’s Real can crash into someone’s life – the gap between intention and reception becomes glaring, and the social backlash (a symbolic punishment, arguably) can be severe. Many learned to be cautious after seeing such examples, but the unpredictability never fully went away.

To sum up Twitter in the classical era: it was a running stream of consciousness at the societal level. It thrived on immediacy and succinctness, which meant it captured things in the moment – sometimes the truth of a moment, other times the confusion of it. For those who loved it, Twitter was liberating: you could directly engage with strangers, join global conversations, and witness unfiltered perspectives from all walks of life. It felt real in a way other platforms didn’t – not real as in reliable, but real as in raw and happening right now. For those who found it overwhelming, Twitter felt like a noisy room where anyone could say anything, lacking the comfort of familiar structure or the pleasantness of curated images. In Lacanian terms, it exposed the splinters of discourse – the little breaks and cracks where our neat symbolic world shows its seams.

Generational Snapshot: Social Media Stage 1 (Summary)

To wrap up Stage 1, let’s summarize how each generation typically engaged with these classical social media platforms and which Lacanian order was most at play in their experience. The table below provides a high-level overview:

GenerationTypical Stage 1 Platforms & UsageLacanian Lens
Baby Boomers (mid-50s to 70s in Stage 1)Primarily adopted Facebook (often later in this stage) to reconnect with old friends and maintain family ties. Shared life updates, family photos, and used groups (e.g., hobby or nostalgia groups). Few on Instagram (mostly to follow family) and even fewer on Twitter (mainly for news).Symbolic Order: Boomers’ use of Facebook reinforced social bonds and roles (old classmates, extended family) in a structured way ([
Boomers Joining Social Media at Record Rate – CBS News](https://www.cbsnews.com/news/boomers-joining-social-media-at-record-rate/#:~:text=,com)). They found meaning in re-establishing networks and enjoyed the social order Facebook provided (e.g., clearly knowing someone’s relation or background). Imaginary elements were less central, but present in sharing ideal family images. Twitter’s chaotic Real was generally avoided or only lightly sampled.
Gen X (30s-40s in Stage 1)Embraced Facebook as all-purpose social tool (friends, family, colleagues). Some early adopters on Instagram (often for family or creative hobbies) and active on Twitter especially in professional or interest areas (tech, news, etc.). Often the bridge generation teaching older ones how to use these platforms.Symbolic and Imaginary: Gen X balanced Facebook’s Symbolic networking (professional and personal roles) with a bit of Instagram’s Imaginary self-expression (sharing curated snapshots of family or interests). On Twitter, Gen X users engaged with public discourse, sometimes encountering the Real in heated debates or witnessing viral moments, but often keeping a more reserved tone (as they were older and mindful of public image).
Millennials (teens to 20s in Stage 1)The power users of Stage 1: heavy Facebook users in early years (oversharing, social planning, group activities), then pivoting to Instagram for peer interaction and personal branding as it emerged. Active on Twitter for memes, pop culture, activism, and real-time chatter. Comfortable juggling multiple platforms, each for different facets of life.Imaginary and Symbolic (with doses of Real): Millennials dove into the Imaginary on Instagram – crafting online identities with curated photos and seeking approval via likes (a “mirror” of the ideal self). They also mastered Facebook’s Symbolic landscape – using it as a social archive and communication hub. On Twitter, many Millennials relished in the absurd or candid communication, often embracing the Real’s unpredictability (e.g., viral humor or hashtag activism) as a form of expression and social impact.
Gen Z (children to early teens in Stage 1)Many were too young for social media at the beginning of Stage 1. By the early-mid 2010s, older Gen Z (mid teens) started using Instagram (often mobile-first, some with finsta accounts for close friends). Less interested in Facebook (seen as for parents/older folks) except for necessities. Engaged with YouTube and emerging platforms like Snapchat for quick communication. A few on Twitter for fandoms or to follow celebrities.Imaginary with emerging Real: Gen Z’s first experiences were often on Instagram’s Imaginary playground, yet they started to crave authenticity, injecting more “realness” into how they posted (less polish, more candor) (Authentically connecting your brand with Gen Z and Millennials). They largely skipped the Symbolic formalities of Facebook, which felt too rigid or irrelevant. On the fringes (Twitter or lurking on YouTube comments), they got glimpses of the wider internet chaos (Real) that would fully bloom in the next stage on platforms like TikTok.

Key takeaway: In Stage 1, social media extended familiar human social structures into the digital realm. Users often mirrored their real-life identity and relationships online (Symbolic order), while also experimenting with how they present themselves (Imaginary order). Yet, even in this early era, cracks would appear – unanticipated viral moments or conflicts (the Real) that hinted at the less controlled dynamics to come. Each generation engaged with these platforms based on their needs and comfort: older generations valuing the newfound ability to reconnect and stay in touch (symbolic stability), and younger generations leveraging the tools to explore identity and humor (imaginary play and occasional real disruptions).

With the foundation of Stage 1 laid out, we can now move to Stage 2, where the rise of video-centric content and new forms of storytelling further shifted how the Imaginary, Symbolic, and Real manifest in our media experiences. This next stage will bring us YouTube stars, TikTok trends, and the ongoing quest across generations to find authenticity and meaning in an increasingly performative online world.

Stage 2: The Era of Video-Based Platforms – Performance, Virality, and Evolving Identities

By the mid-2010s, the social media landscape was evolving. Smartphones were ubiquitous, data networks were faster, and people’s content consumption habits were shifting from text and images to video. This gave rise to the second stage of media evolution: the era of video-based platforms. In Stage 2, platforms like YouTube (which actually started back in 2005 but truly boomed as a social platform later), Snapchat (launched 2011, popularized ephemeral video/snaps), Instagram Stories and Reels (added in 2016 and 2020, respectively, as Instagram adapted), and especially TikTok (launched globally around 2018, building on the earlier Musical.ly app) became central to online culture.

The move to video didn’t eliminate the prior stage’s platforms – Facebook and Instagram were still huge, Twitter still influential – but it layered on top a new dimension of audiovisual media that changed how people represented themselves (Imaginary), how they structured content and fame (Symbolic), and how unexpected, viral phenomena could erupt (Real). Let’s explore Stage 2 through the Lacanian lens:

  • During Stage 2, the Symbolic order in social media began to shift from the text-based frameworks of Facebook/Twitter to the content-driven ecosystems of YouTube and others (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). Think of YouTube as creating a new kind of symbolic system: subscriber counts, algorithms deciding what videos to recommend, monetization rules, etc. This is a more algorithmic or programmatic symbolism (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis) – identity and status are influenced by one’s channel content and metrics.
  • The Imaginary remained prominent via Instagram (which continued thriving with its image-based culture) and also in the carefully crafted personas of YouTube creators or the aspirational lifestyle vlogs. However, the Imaginary also had to adapt to video – dynamic images where one’s appearance and charisma in motion mattered.
  • The Real found new outlets, notably on TikTok, which became known for its unpredictable algorithm and trend cycles. TikTok’s feed could surface the most random, yet riveting content from someone with no followers – a radically “democratized” virality that often felt like catching lightning in a bottle (very Real in its unpredictability) (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). Glitches, bloopers, and unfiltered moments were not hidden but often highlighted as the charm of TikTok content.

We’ll break this section into two main parts: first, YouTube and the structured video culture (Symbolic/Imaginary interplay), and second, TikTok and the rise of short-form viral video (Real/Imaginary interplay), while noting how Instagram evolved and persisted (Imaginary continuity) and how different generations engaged with each.

YouTube: A New Symbolic Arena of Content and Community

By Stage 2, YouTube had grown from a simple video-sharing website into a colossal platform with its own celebrities (YouTubers), subcultures, and economies. Unlike the short snippets on Twitter or personal profiles on Facebook, YouTube offered longer-form content and the ability to build an entire channel around one’s identity or interests. Many creators started treating their channels like a business or a mission, releasing videos on a schedule, cultivating an audience, and even earning money through ads. This introduced a more structured, rule-governed layer to online persona-building – aligning with an evolution of the Symbolic order in social media (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis).

How YouTube reflects the Symbolic order:

  • Structured Identities: On YouTube, a person often isn’t just themselves casually; they might adopt a niche or role. For example, someone becomes “The Tech Review Guy” or “The Makeup Guru” or “The Travel Vlogger.” These roles are recognized labels, much like social roles in society. A YouTuber’s username and content category become a kind of title (a signifier) that situates them in the online social structure. The platform itself encourages this through categorization and the way content is discovered via keywords, tags, and algorithms. In Lacanian terms, the YouTuber’s persona is part of the Symbolic matrix of YouTube’s culture – defined by certain codes (how a tech review should look, how to address the audience, etc.).
  • Language and Narratives: While YouTube is visual, it’s heavily driven by narrative content. Many successful videos are essentially storytelling: a tutorial tells the story of how to do something, a vlog tells the story of someone’s day or experience, a commentary video weaves an argument or analysis. This use of language and narrative structure on YouTube is a Symbolic act – it’s about conveying meaning, teaching, persuading, or entertaining through a coherent thread. Compare this to the often disjointed discourse on Twitter – YouTube videos usually have a clear beginning, middle, end, often even saying “In this video, I will…” which situates the content in a logical flow.
  • Community Norms and Rules: YouTube developed community guidelines, copyright rules (Content ID system), and monetization policies. These are the “laws” of the YouTube world. Creators learned they must follow certain rules or risk demonetization (losing ad revenue) or removal of videos. For example, using licensed music without permission could get a video taken down (the Symbolic law of copyright asserting itself). This is a far cry from the free-wheeling days of early social media. It indicates a maturation – the Symbolic order becoming more pronounced and restrictive, much like a society that starts off as a wild frontier and then gets regulated.
  • Symbols of Success: Metrics like subscriber count, view count, the Silver/Gold Play Button awards (given by YouTube for 100k / 1M subscribers respectively) became status symbols. These are literally symbolic tokens that creators covet and display as validation. The pursuit of these numbers often influenced behavior: e.g., “I need to upload weekly to keep my subscribers engaged,” or “Let’s make a video about a trending topic to get more views.” In some sense, these metrics functioned as the “big Other” of YouTube – an internalized sense of what the algorithm/audience expects that creators felt beholden to.

Now, how did different generations use and experience YouTube in Stage 2?

Gen Z and Millennials were (and are) the heaviest users and creators on YouTube during this era. Many Millennials started channels in the late 2000s/early 2010s and by Stage 2 had become the first generation of YouTube stars (consider that in 2010 a lot of famous YouTubers – gamers, comedians, educators – were in their 20s, thus Millennials). Gen Z, on the other hand, grew up watching a lot of YouTube as their TV. A Gen Z kid in 2015 (say 15 years old) might follow dozens of channels about things they love – gaming, slime-making, music, etc. They see YouTubers as relatable figures, sometimes more so than traditional celebrities. Many Gen Z teens began to aspire to become YouTubers themselves; surveys around 2019 even showed that “YouTuber” was a more desired career among young people than movie star or astronaut. This shows how mainstream and symbolic this role became.

Let’s illustrate with an example: Kevin, a 16-year-old Gen Z high school student in 2018, is a big fan of gaming. Instead of watching TV after school, he spends hours on YouTube. He follows a Millennial gamer who posts funny commentary videos of gameplay. Kevin interacts by liking, commenting, and discussing the videos with friends. He notices the YouTuber has catchphrases and inside jokes (forming a kind of symbolic language of that channel’s community). Kevin and his peers might even quote those catchphrases in school. Here, the YouTuber’s persona and content have created a mini symbolic order – with its own lexicon and norms – that the audience engages in. If the YouTuber does something off-brand, fans will call it out (“This didn’t feel like you”). The identity is almost co-constructed between creator and audience expectations.

Now Kevin and friends decide to start their own channel for fun – they make a few videos of them doing challenges or playing games. They imitate the style of their favorite creators (learning the symbolic code) – a catchy intro, editing in meme sound effects, etc. They quickly learn it’s not easy to get views. One day, they post something that unexpectedly gets a bit of traction – maybe a short comedy skit related to a trending meme. Suddenly they have thousands of views. Kevin feels the rush of recognition (a mix of Imaginary ego-boost and Real surprise at going viral). It motivates him to make more. However, he also reads some random negative comments that hurt (“These kids aren’t even funny, cringe”). That unfiltered feedback is the Real cutting into the experience – not everyone will applaud, and it can sting to have the world judge you so nakedly.

Millennials as creators in this era might have been navigating the professionalization of YouTube. For example, Samantha, a Millennial in her late 20s, runs a lifestyle channel sharing home decor tips and daily vlogs. She’s effectively turned part of her life into a performative narrative. This is an Imaginary exercise (presenting an appealing image of her life) but within a Symbolic framework (regular uploads on certain topics to satisfy an audience niche). She monetizes her channel, gets brand sponsorships for showing a product – meaning the symbolic economy is now directly influencing her self-presentation. She might plan parts of her life around content (“Let’s go pumpkin picking, it’ll make a great fall vlog”). The line between genuine life and content life blurs. For her Gen X parents, this might be baffling – broadcasting your life to strangers and even making a living from it – but for her and her Millennial/Gen Z viewers, it’s becoming normalized.

Gen X and Boomers on YouTube: They were generally more on the consumer side than creator side in Stage 2, but their usage is significant. Gen X (now 40s-50s) often used YouTube for practical purposes: tutorials (how to fix a faucet, how to bake a new recipe), watching talks or educational content, news clips, and of course music videos (reliving old favorites or discovering new ones). Many Gen Xers also appreciated YouTube’s role in allowing them to indulge hobbies – e.g., a Gen X man who loves woodworking might follow several woodworking channels, effectively joining a community of practice, albeit as a silent member who mostly watches and learns. There were also Gen X creators – perhaps experts who started sharing knowledge (like a 50-year-old professor posting science explainers, participating in what’s known as “EduTube”). Their approach might be less flashy, but they contribute to the rich tapestry of content.

Boomers (50s-70s) increasingly discovered YouTube too. A lot of Boomers would use it as a replacement for some traditional media: watching late-night show monologues the next day, enjoying classic music performances, or finding sermons and lectures. Some Boomers became content creators inadvertently – for instance, a grandmother who shared cooking videos for fun could suddenly find an audience of millions if her style clicked (there have been viral examples of this – where authenticity and old-school charm attracted younger viewers). For Boomers, YouTube could be somewhat empowering: you didn’t need a TV network to share your knowledge or talent; you could just upload it. However, few Boomers systematically set out to become YouTube stars in Stage 2; those who did often had niche appeal (like Bob Ross style painting lessons, etc., where their age lent authority or uniqueness).

Generationally, YouTube was perhaps the first platform in which all generations found some value:

  • Boomers: as viewers, they could find old TV clips, how-to guides, etc.
  • Gen X: as viewers and occasional creators, they could engage deeply with personal interests.
  • Millennials: as heavy viewers and leading creators, they built new careers and communities.
  • Gen Z: as avid viewers (practically raised on YouTube), and emerging new wave creators (especially as some pivoted to newer things like TikTok, but we’ll get to that).

From a Lacanian perspective, what’s interesting is that YouTube allowed a synthesis of Imaginary and Symbolic. Creators carefully crafted their on-camera persona and visuals (Imaginary – the ideal version of themselves or the thematic aesthetic of their channel) within a fairly structured context of themes, formats, and algorithms (Symbolic – the codes of “successful YouTubing”). The Real would appear in unpredictable viral successes or failures, and in the occasional content that broke the mold and either flopped or went huge without clear reason (the old YouTube phenomenon of a random cat video or a one-hit wonder viral video). But as YouTube matured, many creators tried to minimize the Real – they wanted predictability and growth, which meant following the platform’s evolving “rules” more than courting randomness.

Before moving to TikTok, we should mention Instagram’s evolution in Stage 2, as it’s partly tied to the video trend. Instagram introduced Stories (short 24-hour posts, often video or ephemeral content) in 2016, copying Snapchat’s concept, and later Reels (15-30 second multi-clip videos with music, copying TikTok’s style) in 2020 which is just at the cusp of Stage 3. These features show Instagram (the Imaginary stronghold) trying to adapt by injecting more authentic, in-the-moment sharing (Stories feel more casual and real since they vanish and often are minimally edited) and short video creativity (Reels to compete with TikTok’s allure). Many Millennials and Gen Z who were Instagram users started using Stories heavily – it became a way to show the “real life” behind the curated feed. For example, a Millennial might keep her Instagram profile full of polished pictures but use Stories to post a goofy face with a dog filter saying “Ugh Monday!” which disappears the next day – a balance between maintaining an ideal image and letting glimpses of everyday realness show. This was a notable shift: the Imaginary order of Instagram making room for bits of the Real (unfiltered moments) in a controlled way via ephemeral content.

Gen Z, especially, loved Stories because it felt less pressure than permanent posts – they could be more experimental or honest. Boomers and Gen X took to Stories more slowly (some never got into it), but younger users drove that change in platform culture.

With that in mind, let’s now turn to TikTok, which by the end of Stage 2 had become the defining platform for the newest generation, bringing short-form video and an entirely new algorithm-driven discovery model to the forefront.

TikTok: Unleashing the Real through Algorithmic Virality and Raw Creativity

If YouTube is like a library or stage – where creators present structured content to an audience that chooses to watch them – TikTok is more like a roulette wheel of content snippets that spins and lands on something surprising every time you refresh. TikTok (which grew out of the app Musical.ly and gained global prominence around 2018-2019) specializes in short videos (15 to 60 seconds, now up to 3 minutes or more in some cases) delivered through a highly personalized feed called the “For You Page” (FYP). What’s revolutionary about TikTok is how aggressively its algorithm learns from your behavior to serve up videos you didn’t know you wanted to see – often from creators you’ve never heard of. This meant that anyone’s video could, in theory, become a viral hit on a stranger’s feed purely because the algorithm detected people were enjoying it, not because the creator was famous or had many followers.

From a Lacanian angle, TikTok became a new conduit for the Real in digital media (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis):

  • Glitch, Play, and Authenticity: TikTok culture celebrates being real and even awkward. Many TikTok videos that go viral are not polished productions; they’re often shot spontaneously on a phone, sometimes in one take. People dance in their living rooms, do silly facial expressions, rant while sitting in a car – it’s candid. Users often intentionally include “non-polished” elements: a sudden laugh, a mistake in a dance, a stutter in speech, or a quick cut that shows an imperfect transition. These little flaws or unplanned bits (like someone’s pet suddenly walking into frame, or a person cracking up mid-video) actually make the content more endearing and relatable. As one guide on social strategy notes, TikTok users value realness and “nothing feels more real than candid, unfiltered reactions” (How to Go Viral on TikTok: A Complete Guide). In Lacanian terms, these unscripted bits are glimpses of the Real breaking into the performance – and paradoxically, on TikTok they often make the content better loved.
  • Algorithmic Surprises: TikTok’s FYP can throw you down a rabbit hole. For example, you might start watching a couple of cooking videos, and suddenly your feed is full of grandmas making soup, street food vendors, and comedic skits about grocery shopping. Then you pause on a video of a cute cat, and next you get animal videos interspersed with cooking. Then one day, you like a video about 18th-century history (who knows why – maybe it had a funny twist), and soon you see historians or enthusiasts acting out skits in period costumes on your feed. This rapid adaptation can lead you to communities and content genres you never actively sought out. People often joke that TikTok’s algorithm “knows them better than they know themselves.” The effect is that you encounter the unexpected regularly. It feels organic and eerie at the same time – like magic. For content creators, this means they sometimes go viral out of nowhere and gain an audience they never anticipated. A random teenager’s video of them skateboarding while drinking juice and vibing to a Fleetwood Mac song can garner millions of views and turn them into an overnight internet celeb (this actually happened, a famous case with a TikTok by Nathan Apodaca, aka Doggface208, riding a skateboard with “Dreams” by Fleetwood Mac playing, which became a huge wholesome viral moment).
  • Meme and Trend Culture (Collective Real): TikTok’s format encourages imitation and iteration. There are always trending sounds, dances, or challenges. Users riff on each other’s creations by using the same song or format but adding their personal twist. It’s a collective creativity where no one person owns a trend; it evolves as thousands join in. This means that meaning is constantly being created in a decentralized way. Sometimes a trend gets out of hand or subverted – a trend that started innocently might get taken in a weird or darkly humorous direction by some users. The platform can suddenly flood with variations of a meme that outsiders find completely nonsensical. This mass spread of an idea that even the algorithm might not have foreseen is like a Real event in culture – a burst of shared jouissance (enjoyment) that isn’t centrally directed, often breaking conventional logic. For example, a simple dance might morph into comedic parodies, which then morph into meta-commentaries on the trend itself. By the end, it’s hard to explain why the original thing was popular – it just was, and everyone rode the wave.
  • Short Attention and Emotional Whiplash: On TikTok, the next video is seconds away. Users often report getting emotionally whiplashed – you might see a hilarious prank video followed immediately by a heartfelt story of someone overcoming hardship, then a cooking tutorial, then a scary clip about a conspiracy theory. The app doesn’t separate or cushion these; it’s just all content of roughly equal size in the feed. This fragmentation (somewhat like a supercharged version of channel surfing or scroll culture) can hit deeper than Twitter’s text because video/audio is more visceral. You can be laughing one minute and then moved to tears the next, then confused, then inspired. That unpredictability of emotional experience is an aspect of the Real – it’s not neatly ordered like a TV channel’s scheduled programming. TikTok is famously addictive partly for this reason; you literally never know what’s coming next, which our brains find hard to leave. Spontaneity is built-in: TikTok encourages creators to respond rapidly to trends (like, “here’s my take on today’s viral joke”), which keeps content feeling current and surprising.

Generational dynamics on TikTok:

  • Gen Z is the poster child of TikTok. This platform aligned perfectly with the Gen Z sensibility that was moving away from the Millennial “curated perfection” and towards “messy realness” (Authentically connecting your brand with Gen Z and Millennials). A typical Gen Z TikTok user, say Emily (18 years old in 2020), might post a video of herself in her bedroom trying on thrifted outfits to a popular song, then next day post a clip where she earnestly talks about feeling anxious about college applications, then repost a funny lip-sync meme. Her feed is an eclectic scrapbook of her life and interests, without an obvious filter or theme besides “things Emily cares about or finds funny.” She doesn’t worry about whether it all looks consistent – in fact, making it too polished might be seen as inauthentic or cheugy (a Gen Z slang teasing Millennials for being overly earnest or out-of-touch with internet native style (Authentically connecting your brand with Gen Z and Millennials)). Emily also interacts with others by dueting (a TikTok feature where you split screen and react to someone’s video) – which might lead to comedic chains where people keep reacting or adding on (a collaborative spontaneous chain). She might get modest views typically, but one of her comedic skits unexpectedly hits big, and suddenly she has 50,000 followers who arrived overnight because of one video. This doesn’t immediately make her a star (TikTok followers are not as “sticky” as YouTube subscribers perhaps), but it does give her a thrill and a taste of virality.
  • Millennials on TikTok were initially fewer (many stuck to Instagram and watched TikToks that spilled over onto other platforms). But by late Stage 2 and certainly by 2020, plenty of Millennials joined TikTok, especially during the COVID-19 pandemic when people of all ages were looking for entertainment at home. Millennials often approach TikTok with a bit more strategy or hesitation – some treat it like a new frontier to build a following (applying lessons from Instagram/YouTube, sometimes with success, sometimes finding they need to loosen up their style to fit TikTok’s ethos). Others mainly consume content, enjoying the candidness. There’s also a subset of Millennials who create family or parenting content on TikTok (sharing cute or funny moments with their kids). For example, a Millennial mom might post a TikTok of the chaos of breakfast time, complete with a toddler flinging cereal – something that on Instagram she might have only posted a cleaned-up picture of. On TikTok she posts the messy video with a humorous caption, and it resonates because it’s real parenting, not magazine parenting.
  • Gen X and Boomers largely were late to TikTok. Initially, TikTok was seen as that “Gen Z dance app.” But as viral TikToks began to permeate mainstream media, older generations took notice. Some Boomers joined to follow what their grandkids were doing or just out of curiosity after seeing references on the news or late-night shows. There’s a charming trend of some Boomers who do join TikTok often becoming beloved for their unorthodox content – for example, an older man just calmly cooking or gardening and sharing life wisdom might strike a chord as a wholesome alternative in the feed. Some Gen X users embraced TikTok humor and even turned it into a place to share reflections, like comedic takes on midlife or work. Gary, a Gen X 50-year-old, might use TikTok to post a funny rant about how music today confuses him – but he does it in good spirit with some trending sound – and ironically gets a bunch of younger followers who find “Grumpy Uncle Gary” entertaining. Meanwhile, many Gen X/ Boomers remain non-creators but enjoy watching: TikTok’s algorithm will find them content that suits them once they start using it. A Boomer who likes videos of 1970s music or classic car restoration will see more of that. They might never post a video themselves, but they’re contributing to TikTok’s growth as viewers (and sometimes leaving comments, like “This song brings back memories!” on a video of a teen discovering a Beatles track).

A Gen Z TikTok Real experience (detailed example): Aaliyah, age 20, is scrolling TikTok at 1 AM. She comes across a live video (TikTok also has lives) of someone’s ceiling with weird noises – perhaps an unintentional stream. She scrolls and the next video is a perfectly targeted comedy skit about a very specific college struggle she had that day – she’s amazed how did TikTok know? She laughs and hearts it. Next, she sees a video with 5 likes from a girl crying and talking about a breakup. It’s raw and clearly just posted. Aaliyah feels like she’s peeking into someone’s real emotional moment; she leaves a supportive comment. Then comes a sponsored ad video for makeup – she skips it after 2 seconds. Then she hits a video in which a popular science communicator excitedly shares a discovery – she’s learning something new unexpectedly. Within 5 minutes, Aaliyah’s emotions and focus have zigzagged across empathy, humor, annoyance, curiosity. This rollercoaster is engaging but also a bit exhausting. She eventually puts the phone down to sleep but the content lingers in her mind. TikTok, more than any prior platform, compresses the highs and lows of shared human experience into a rapid feed. It feels real in the sense that it’s a torrent of life’s bits and pieces: funny, sad, stupid, enlightening, disturbing, all side by side.

TikTok’s influence by the end of Stage 2 was huge: Instagram redesigned itself to include Reels to compete, YouTube introduced “Shorts” (short vertical videos) – indicating that the short-form video format born of TikTok was reshaping even the giants of Stage 1. Moreover, TikTok showed that algorithmic content discovery (where what you see is not only based on who you follow, but on what the system thinks you’ll like) can be incredibly effective. This marks a shift towards the machine playing a bigger role in curating our media diet – a harbinger of Stage 3, where AI doesn’t just curate but creates content.

Let’s summarize Stage 2 with a quick generational comparison and Lacanian framing:

GenerationStage 2 Engagement (Video Era)Lacanian Notes
Baby BoomersPrimarily YouTube viewers: watched news clips, DIY tutorials, music, nostalgia content. Some began exploring TikTok as viewers late in this stage (often content tailored to their interests by the algorithm). Few actively created content, but those who did often gained novelty status (e.g., the charming grandma on TikTok). Used Facebook Live or video calls more than short-form social video.Symbolic to Real Shift: Generally stayed in comfortable Symbolic patterns (YouTube as extension of TV learning or Facebook’s structured socializing). TikTok exposure for Boomers often meant sudden confrontation with the Real of internet humor or trends (which might bewilder or amuse them). Their own content (when it happened) tended to be sincere (Imaginary identity-sharing or informative), which sometimes unintentionally played into TikTok’s love for unpolished authenticity (Realness), making them endearing to young audiences.
Gen XEmbraced YouTube both for learning and as a platform for interests. Some Gen X became prominent YouTube content creators in niches (tech, education, lifestyle) – often presenting as authoritative or mentor-like figures. Slower to adopt TikTok, but those who did enjoyed comedic or interest-based content. Many lurked on TikTok or participated via their kids. Instagram Stories were used to share more “real life” moments with friends (e.g., a candid clip at a reunion or a throwback video).Symbolic/Imaginary with emerging Real: Gen X kept a foot in the Symbolic – using structured content on YouTube and Facebook – but also sampled the Imaginary fun of Instagram’s visuals. TikTok’s Real elements (spontaneous, unstructured humor) were either lightly enjoyed or avoided depending on the person. Gen X creators often added structure and commentary to the chaotic world (e.g., reaction videos on YouTube analyzing viral TikToks, which is literally imposing symbolic analysis on raw content).
MillennialsSome pivoted to become full-time YouTubers or Instagram influencers, monetizing content (Symbolic economic integration of their Imaginary self-brand). Heavy users of Instagram Stories and later Reels. Increasingly present on TikTok especially post-2019, either as content creators leveraging their creative skills or as consumers of entertainment and life hacks. During this stage, many Millennials started families, and some content reflected that (YouTube family vlogs, TikTok parenting humor).Imaginary meets Symbolic, and learning Real from Gen Z: Millennials largely drove the polished content economy (Imaginary perfected image on a Symbolic schedule) but found themselves challenged by Gen Z’s preference for authenticity. Many adapted by showing more “real life” aspects in stories or TikToks, blending Imaginary with bits of Real (e.g., showing messy behind the scenes). On TikTok, Millennial creators learned to be less formal, sometimes intentionally poking fun at themselves for being “old” on the app, which ironically won them Real connection with younger viewers.
Gen ZThe TikTok generation – leading creators and consumers on that platform, setting viral trends and slang. Used YouTube mostly to follow interests or idols, but were less likely to have long attention spans for very long videos (unless deeply interested). Preferred Snapchat and Instagram Stories for direct socializing with friends, but TikTok for creative expression or entertainment. Gen Z content often blurred personal and public: dancing, venting, joking, educating peers on issues (like mini video essays on social justice or mental health).Real and Imaginary interplay: Gen Z content thrived on authenticity and spontaneity – a Real embrace (glitches, candid moments made content relatable (How to Go Viral on TikTok: A Complete Guide)). Yet, Gen Z also crafted strong visual identities (Imaginary) especially in how they edited and presented even casual content (a kind of effortlessly aesthetic realness). They were adept at meme language (Symbolic codes of Gen Z internet culture) but loved to break or remix those codes constantly (dissolving Symbolic boundaries into playful Real). They found Facebook’s Symbolic formality largely irrelevant, opting instead for forms of communication that felt alive and unfiltered.

By the end of Stage 2, digital media had become highly dynamic and participatory. People not only connected with those they knew (as in Stage 1) but also regularly interacted with content from strangers across the world based on shared interests or algorithmic serendipity. The Imaginary order was still present (we still curate how we look and appear, even in videos), the Symbolic order evolved (new norms, roles like “influencer,” and algorithmic laws governed success), and the Real was more evident than before (quirkiness, unpredictability, and raw moments often driving engagement, particularly in short video culture).

As we transition to Stage 3, the AI-driven media era, we will see these threads take another turn. In Stage 3, the content itself starts to be generated by AI agents, not just recommended by them. This introduces profound questions: What happens to the Imaginary when an AI can generate any image we want? How does the Symbolic order shift when bots can produce endless dialogue or when our interlocutor might not be human? And how do we encounter the Real in AI outputs – perhaps in the eerie feeling when an AI output is almost human but not quite, or when it produces something shockingly novel?

Stage 3 will delve into platforms and tools like ChatGPT, DALL-E, and AI music generators like Suno, examining how each corresponds to Lacan’s three orders – and of course, how different generations are beginning to use (or wrestle with) these AI-mediated experiences.

Stage 3: AI-Driven Media – When the Medium Becomes an Active Participant

We have arrived at the cutting edge of media evolution: the era where Artificial Intelligence (AI) is not just curating or filtering human-generated content, but actually creating content and interacting with us in human-like ways. Stage 3, unfolding through the 2020s, is characterized by the rise of generative AI platforms – services that can produce text, images, audio, and more based on prompts. Notable examples include:

  • ChatGPT (and similar AI chatbots), which can generate human-like text and engage in conversation.
  • DALL-E, Midjourney, and other AI image generators, which can create artwork or realistic images from a simple textual description.
  • Suno (and various AI music tools), which can compose music or mimic voices from brief prompts.

In this stage, the distinctions between producer and consumer blur even further. In Stage 1, you had to sit at a keyboard or hold a camera to make content. In Stage 2, you performed or spoke to create content. Now in Stage 3, you might simply describe what you want to see or hear, and the AI will attempt to produce it for you. It’s a new kind of collaboration between human and machine. Lacan’s orders offer a fascinating lens here:

  • The Imaginary: Now AI can directly generate images (synthesizing the Imaginary without a human photographer or artist) (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). This means our mirror – the image world we look at to form identity or desire – can be shaped by AI fantasies. We must ask: whose imagination is it? Ours, through the prompt, or the AI’s, through learned patterns?
  • The Symbolic: ChatGPT and its cousins operate squarely in language, the domain of the Symbolic. They are essentially automatons of the Symbolic order, churning out words and sentences that fit the forms of human discourse (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). They can simulate different styles, from casual chat to Shakespearean poetry. They follow the rules (grammar, genre conventions) eerily well. How does this affect our relationship to language and meaning? When an AI can produce a perfectly structured narrative or essay on command, what does that do to our symbolic exchange of ideas?
  • The Real: AI-generated content can be surprising, weird, or even unsettling. An AI might create a face that looks almost real but has something just off (like too many fingers on a hand, a common glitch in early AI images) – these are moments that jolt us because they reveal the AI doesn’t truly “know” reality, it’s just approximating. Also, AI music or AI-generated sounds can evoke feelings without any human emotion behind them. There’s an aspect of the uncanny here – encountering something that feels real but isn’t, which can be a brush with the Real (in Lacan’s sense of what’s beyond our norm). Moreover, when the AI output defies our expectations or produces an error that a human wouldn’t, it’s like seeing the gap in the system, a Real moment of “breakdown” in meaning.

Let’s explore specific facets of Stage 3 through key examples (ChatGPT for Symbolic, DALL-E for Imaginary, Suno for Real in music), and weave in generational experiences. Since Stage 3 is very current (the mid-2020s), generational patterns are still forming, but we can draw on how each generation has begun to adopt or react to these AI tools.

AI Imagery (DALL-E and Friends): The Imaginary Synthesized by Machine

Imagine typing a sentence like “a seaside town painted in the style of Van Gogh” and within seconds, seeing an image that looks like a lost Van Gogh painting of a seaside town. That is what tools like DALL-E (developed by OpenAI, introduced in 2021 and improved in later versions) can do. They take natural language descriptions and produce original images that match those descriptions, drawing from the vast visual patterns they learned from training data. Similarly, other systems can generate human-like faces, fantastical scenes, or concept art for virtually anything you can describe.

In Lacanian terms, DALL-E and similar AI image generators represent the Imaginary order being directly produced by a non-human agent (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). It’s like having a mirror that reflects not your physical self, but your imagination itself. You think it (or say it), and the machine shows it. This is powerful and a bit disorienting.

Implications for the Imaginary:

  • Self-Representation: Previously, to craft an image of oneself (or one’s persona), you took a photo or hired an artist or Photoshopped something manually. Now, someone can literally ask the AI to “show me as a warrior in medieval armor” or “generate a professional headshot of me with slightly better hair” (using a reference photo or just a concept). AI can create avatars and idealized images that aren’t photos we took – they are imagined images. For instance, a Millennial blogger could use DALL-E to generate a unique logo or cartoon that represents her, rather than hiring a graphic designer. A Gen Z teen might generate fantasy artwork of their Dungeons & Dragons character to use as a profile picture. The Imaginary realm (our avatars, icons, visual identity symbols) expands because we can now conjure things that never “existed” as photographs or paintings in the real world, yet look convincing.
  • Creativity and Daydreams: People are using AI art to bring daydreams to life. You might wonder what your dream house in the mountains could look like – now you can visualize it by prompting an AI. This can be delightful and inspiring, but also potentially disconnecting: there’s a difference between dreaming something and actually seeing it materialize on screen. Some find that seeing it lessens the mystery; others find it motivates them to pursue it. Lacanian Imaginary is tied to desire – the AI can image our desire in a literal way. Does that satiate the desire or amplify it? It might do both in different cases.
  • Generational use differences: Gen Z and Millennials, being more tech-savvy on average, are early experimenters with AI image generators. For example, in online communities, you’ll find young artists using AI to brainstorm ideas or to create meme images for fun. A typical Gen Z scenario: Liam, age 17, loves anime and superheroes. He doesn’t know how to draw well, but he has a vivid idea of a new superhero character. He types into a free AI art tool: “teen superhero, electric powers, blue and black costume, dynamic pose.” He gets several images and is wowed by one that looks like a comic book cover. He shares it with friends saying “Look at my original hero!” Here, Liam gets to engage in imaginative creation without the years of art training that would normally be required – AI filled that gap. It’s empowering, though the images are based on patterns drawn from thousands of artists’ works (which raises ethical questions beyond our scope here). Millennial usage might skew toward practical creativity: Jane, 35, runs an Etsy store selling homemade candles. She’s not great at graphic design. Instead of buying expensive stock photos, she uses an AI to generate moody, beautiful images of candles in various settings to use in her marketing. It saves her time and money, and the images look professional, even though they’re not “real” photographs. She just has to be careful not to generate something misleading. For instance, if the AI adds an element she doesn’t actually offer (like a type of candle or background setting she can’t replicate), she might adjust the prompt. Jane finds this tool has leveled the playing field for her as a small business, giving her an Imaginary edge in presentation that competes with big brands. Gen X and Boomers might dabble in AI imagery for curiosity. A Gen X man might say “I always wanted to see a crossover between Star Trek and Star Wars” and have the AI create Captain Kirk shaking hands with Darth Vader. It’s novel entertainment. A Boomer grandma might get someone to help her generate a funny birthday card image – “a cat DJing at a party” – which she’d never find in stores. They might not use these tools daily, but when they do, the reaction often is amazement, sometimes mixed with “the future is crazy” sentiments. Some older people also express a kind of loss of trust in images: “Now that AI can fake photos so well, I feel I can’t always believe pictures anymore.” That sense of Imaginary no longer guaranteed to reflect reality can be unsettling. For example, Boomers who grew up in an era of “photographic evidence” now have to question if an image is real or AI-generated. The phrase “seeing is believing” is eroding. This can be considered a disturbance in the Imaginary register – the mirror might lie. It introduces a bit of the Real (uncertainty, doubt) into what we see.
  • Community and Play: There’s also a fun, collective aspect: people share prompts and results, almost like playing Pictionary with an AI partner. Online challenges emerge, like “AI image generators challenged to create images that look like historical photos of things that never happened” – e.g., “Rome never fell and here’s a 19th-century photograph of Romans with steam engines.” These games tickle the imagination and often produce almost plausible fakes that make you double-take. It’s an interplay of Imaginary (the convincing image) and Real (the jolt of “this isn’t actually real, history didn’t go that way”).

Overall, AI imagery tools amplify the Imaginary order by giving us near-infinite mirrors for our thoughts and fantasies (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). They also challenge us to integrate that with our sense of truth and identity. Different generations are exploring this with varying levels of enthusiasm and caution, but it’s increasingly accessible to all (many such tools are just a website away).

ChatGPT and AI Chatbots: Automating the Symbolic Discourse

When ChatGPT (a conversational AI developed by OpenAI) was released to the public in late 2022, it quickly became a phenomenon. Here was a chatbot you could ask almost anything – to explain, to write, to brainstorm, to emulate a style – and it would respond in fluent, coherent text most of the time. It felt as if you were messaging a knowledgeable (if somewhat predictably polite) person who had read the entire internet. People used it to draft emails, get recipe ideas, learn about complex topics in simple terms, or even for companionship in lonely moments.

In Lacanian terms, ChatGPT represents the Symbolic order mediated by an AI (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). It’s literally built on language patterns. It doesn’t “think” or “feel,” but it very effectively produces language that makes sense syntactically and contextually because it has been trained on huge amounts of human-written text. It’s an “automated discourse engine” (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). So how does this affect our lives and each generation’s experience?

Effects on the Symbolic:

  • Language as Tool: For many, tools like ChatGPT have become like an advanced extension of the dictionary or search engine – a helper in composing text. It can help write a cover letter, create code, translate languages, or summarize a report. This is a big shift: the Symbolic order (which includes our knowledge and info) is now being generated on the fly, not just stored and retrieved. If Instagram gave everyone a camera and made imagery universal, ChatGPT gives everyone a writing assistant or even a pseudo-author. People who struggle with writing (maybe non-native speakers, or those with dyslexia, or simply those who find putting thoughts into words hard) can use AI to articulate for them. This democratizes participation in the Symbolic realm of writing, but also raises questions about authenticity and skill.
  • Changing Communication Habits: Some have started to use AI to draft messages. For example, a Gen Z student might have ChatGPT help them craft a polite email to a professor, adding the formal flourishes they might not normally use. A Gen X manager might use it to outline a project proposal before fine-tuning it. This speeds things up and perhaps improves clarity, but if overused, one worries if human communication might start to feel formulaic or if voices will homogenize because they’re filtered through AI suggestions. In workplaces, you might not know if a memo was written by your colleague or with heavy AI help. The Symbolic code of professional language could become more standardized as AI nudges everyone to a mean style. On the other hand, human creativity can push back – many still prefer their quirky, personal way of writing and use AI only to refine, not replace their style.
  • Education and Learning: This is huge – schools and universities are dealing with the fact that students can generate essays and homework answers via AI. A Millennial teacher might find that a typically mediocre student turned in a surprisingly eloquent essay – was it them or AI? They have to become detectives or change assignments to be more discussion-based or in-class to ensure genuine learning. Meanwhile, the student (Gen Z) might argue: “This is just a tool, like a calculator. Why ban it? Instead teach us how to use it properly.” There’s an ongoing negotiation about how the Symbolic labor of writing and demonstrating knowledge will change. Perhaps education will shift more towards oral exams, project work, or critical analysis of AI outputs. It’s similar to when Google became widespread – memorization became less crucial, and critical thinking became more emphasized. Now that generating a decent essay is trivial, maybe original thought and the process of editing become the focus.
  • Generational Uptake: Gen Z and Millennials jumped on ChatGPT pretty quickly, sharing tips and “prompts” (how to talk to it to get good results) online. They ask it everything from “Explain quantum physics in simple terms” to “Give me ideas for a TikTok script about college life.” Many view it as a helpful friend for brainstorming. Some also pushed its limits: trying to get it to tell jokes, roleplay scenarios, or even reveal its “hidden rules” (leading to those viral examples where it produced unexpected or off-limits responses). They treat it with a mix of utilitarian approach and playful curiosity. Gen X might use it more practically: a Gen X programmer can have ChatGPT help write code or troubleshoot an error (StackOverflow forums even saw a decline in traffic because why ask humans when the AI can suggest a fix immediately?). Gen X folks in content jobs might use it to eliminate writer’s block – “give me an outline for my report” – then flesh it out with their expertise. They might also be a bit warier of accuracy; knowing the AI can sound confident but sometimes be wrong (the term “hallucination” is used for AI making up facts). So a savvy Gen X user double-checks important outputs. Boomers are definitely using it too, though perhaps less spontaneously. Some Boomers encountered it through media stories and tried it out of curiosity. Richard, 65, who isn’t very techy, hears about ChatGPT on the news and one day asks his granddaughter to show him. He ends up dictating a question: “ChatGPT, what can you tell me about antique car restoration?” and is amazed at the detailed, polite answer it gives, listing tips and resources. He might not need it daily, but he sees the appeal. Another Boomer use-case: Susan, 70, finds companionship in chatting with AI. She asks it about history, engages it in conversation about books she’s read, or even vents about her day. It’s always polite and responsive – in some ways more patient than busy family members. While that might not replace human connection, it does fulfill some social and intellectual stimulation. There have been accounts of elderly using AI chatbots for combating loneliness (ChatGPT: A Game-changer for Personalized Mental Health Care for …) (ChatGPT: A Game-changer for Personalized Mental Health Care for …) – essentially the AI becoming a Symbolic other, a stand-in conversation partner.
  • Symbolic Limitations and Real Intrusions: Using ChatGPT isn’t without quirks. Sometimes it gives a perfectly structured but utterly incorrect answer (like confidently stating a wrong historical date or a miscalculation). If a user takes it at face value, they can be misled. The AI doesn’t “know” truth; it only knows how to convincingly format information. So users must learn how to fact-check AI or use it as a starting point, not the final authority. This is a new literacy: understanding that fluent language isn’t always correct language. It’s like the Symbolic order (language, knowledge) decoupled from a truth guarantee – a very post-modern situation. When an error is discovered, it’s a bit of a Real moment: the facade of an “all-knowing assistant” cracks, revealing the machine’s alienness (it doesn’t truly understand, it’s just predicting likely words). For example, Daniel, a Millennial, uses ChatGPT to help write a segment of a report on medical data. It looks great, but when a colleague checks the references, they find one study doesn’t exist – the AI made up a plausible-sounding reference. That’s a shock and a hassle. Daniel learns he must specifically prompt it to only use real references or double-check them himself. In essence, the user must remain critically engaged; you can’t fully offload judgment to the AI.

AI and Creativity – Gen X User Story (Symbolic meets Imaginary): Consider Dana, a Gen X aspiring novelist who’s been stuck on a story. She decides to experiment with ChatGPT as a writing buddy (Found out my author friend uses ChatGPT in her writing process.). She asks, “Can you write a short scene where my detective character interrogates a suspect in a humorous tone?” ChatGPT whips up a scene. Dana reads it – it’s a bit cliché but has some witty lines. She takes one or two ideas from it that spark her own twist. She then writes her version of the scene, which is now flowing. In this scenario, ChatGPT acted like a Symbolic mirror to bounce ideas off. It gave her a generic version (the collective wisdom of a thousand detective stories), and she, with her personal Imaginary vision of her story, reshaped it into something unique. Dana doesn’t feel the AI “wrote her book” – she feels she did, but she’s not shy to admit that the AI helped break her writer’s block. Another day, she might use it to brainstorm title ideas or character names; it’s like having an intern who’s read everything and can spew out lists to pick from.

This kind of usage is increasingly common among creatives and professionals – AI as an idea generator and drafter, with the human as the editor and decider. It’s a new kind of collaboration. However, it also raises philosophical questions: if the AI comes up with a perfect line for the novel and she uses it verbatim, is that line truly “hers”? For now, most legal systems say yes, the human directing the AI is the author, but ethically and psychologically it’s an interesting grey area. The Symbolic order of authorship and originality is being renegotiated.

AI-Generated Audio and Music (Suno, etc.): A New Real of Sound and Expression

The third aspect of Stage 3 to consider is AI-generated audio – including music, voices, and sound effects. Tools like Suno can create music from text prompts, and other AI models can clone voices (make an AI speak or sing in a specific person’s voice) or generate natural-sounding speech from text. While ChatGPT deals with language and DALL-E with images, AI music taps into a less explicit form of communication – sound, which often hits us at an emotional or bodily level that can bypass rational analysis. Lacan’s idea of “lalangue” refers to the aspect of language that is like pure sound and enjoyment (the babble and musicality of language rather than its clear meaning) (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). AI music creation can be seen as operating in this zone – producing patterns of sound that affect us even without lyrical meaning.

What does AI music mean for the Real?

  • Emotional Impact without Human Emotion: When you listen to a piece of music composed by an AI, you might find it beautiful or moving. Yet, if you reflect, you know no person actually felt an emotion to create that – it was generated by analyzing patterns in countless human-made music pieces. This can be a bit eerie. It’s a kind of ghost in the machine scenario. The Real aspect is that the music can genuinely touch you (because it follows structures that human music does, which are tied to how we emotionally respond to melody, harmony, rhythm), but at the same time, there’s an absence of an intentional human expression. Some describe it as “the universe singing back at you with a voice assembled from echoes of human songs.” It challenges the assumption that art requires a soul. If one hears an AI song and loves it, then finds out it was AI-made, they might feel a pinch of disillusion or perhaps not care – this is a new question. A Gen Z music lover might jam to a catchy tune on Spotify, then learn it was algorithmically generated and have to decide, “Do I still stan this track if there’s no cool artist behind it?” Some will, some won’t.
  • Infinite Content and Niche Personalization: AI can produce music in any style on demand. Need a lo-fi hip-hop track for background study music? Press a button, and it can churn out an endless stream of similar vibes, never repeating exactly. This is great for utilitarian music (background scores, elevator music, etc.), and it could impact musicians who used to make a living composing for those needs. It also means you could personalize soundtracks. For example, a Millennial runner might say, “AI DJ, generate a 30-minute 140 bpm workout mix that gradually intensifies,” and get a perfect arc of music for their run, no famous songs needed. This convenience is appealing, but perhaps it also lacks the personality or surprise that a human-curated playlist might have. If everything becomes perfectly catered, the little surprises of shuffle or radio might diminish.
  • Voice Cloning and Identity: AI can clone voices very convincingly with enough training data. This is another Imaginary/Symbolic disruption that evokes the Real when misused. For instance, someone could make a fake audio of a celebrity or politician saying something they never said – a new form of misinformation (Symbolic misuse) that can cause real confusion until debunked. On the positive side, voice AI can be used to let people customize GPS voices (“I want Morgan Freeman’s voice giving me directions”), or to help those who lost their voice to speak in their old voice by typing (there are projects for patients with diseases like ALS to bank their voice and use it through AI). Generations differ in trust: younger people who grew up with deepfakes and AI voices are quick to question “Is this real audio or AI?”, whereas older might be initially more credulous (thinking audio evidence is solid). However, as awareness spreads, everyone is adjusting to a world where seeing and hearing isn’t necessarily believing – a classic entry of the Real in that our fundamental sensory trust is shaken.
  • Generational uses of AI music: Gen Z artists have been playing with AI music as a tool. For example, some create AI covers – they take a song and use AI to make it sound like another artist is singing it (there was a trend of making pop songs sound like they were sung by famous characters or other singers). These are often done for fun and shared on platforms like TikTok or YouTube. They know it’s borderline legal and just a novelty. It’s like remix culture taken to the next level – remixing the performer as well as the song. This demonstrates creative play but also raises questions of ownership and ethics. Millennials and Gen X, some in the music industry, might use AI to assist in production – maybe generating a baseline melody or drum pattern to build on. Or an indie game developer (Millennial) with no budget for composers could use AI to score their game. This opens up possibilities for those who can’t afford human musicians, though it might take away gigs from entry-level composers. Boomers might engage with AI music more as consumers – maybe using AI-generated nature sound mixes for relaxation, or listening to “oldies in the style of modern pop” out of curiosity if such a mashup is created by AI. Some older famous musicians have actually dabbled too (with the help of engineers) – like having an AI model their own past compositions to spark new inspiration.
  • Suno example: Let’s consider Michael, a Millennial singer-songwriter. He has lots of song ideas but can’t play many instruments. He uses an AI like Suno: he hums a tune and asks Suno to turn it into a guitar riff and drum beat in the style of 90s rock. It does so. He then adds his real vocals over it and writes lyrics. The final song is a hybrid: Michael’s voice and melody, AI’s instrumental interpretation. It sounds good. He feels a bit weird because he didn’t hire a guitarist or drummer, but the result scratches his creative itch. When sharing it on SoundCloud, he notes it was co-created with AI. Some listeners are intrigued, some purists scoff that it’s not all “him.” This illustrates how the Imaginary ideal of a one-man-band can be achieved via AI, and how the Symbolic role of “musician” is evolving – is he a composer if he delegated arrangement to AI? For Michael, what matters is the song exists as he imagined it, thanks to the AI filling in. The realness of the output – people can dance to it – matters more to him than the process purity.
  • The Real in AI audio – glitches and eeriness: Sometimes AI-generated music or voices have slight glitches: a note that sounds out of place, a warble in a cloned voice that makes it sound momentarily robotic. These remind you it’s artificial. For example, an AI might generate a pop song that at first seems sung by a human, but as you listen closely, you notice the breathing is too perfectly timed, and no actual lyrics, just melodic vocalizations that mimic the sound of words without being words. This almost human, but not quality can be uncanny. One might enjoy it but also feel “something is off.” That uneasy feeling is encountering the Real – the recognition that beyond the polished surface of the Symbolic (musical structure) and Imaginary (pleasing sound), there is an absence, a void where the human creator should be. How each person reacts varies: some are unfazed and just enjoy the tune; others find it hollow after the novelty wears off.

Finally, consider how Stage 3’s AI tools interplay: ChatGPT can write lyrics, DALL-E can make album art, Suno can produce the music, and perhaps an AI voice can sing. In theory, an entirely AI-generated song (lyrics, composition, performance, album cover) could be created with minimal human input, maybe just a prompt like “Create a heartbreak pop ballad in the style of Adele.” We are reaching a point where AI can simulate the full creative cycle. Will people listen to that? Possibly – if it’s good. Or will we inherently value the human touch? It might be similar to how people view handmade crafts vs. factory-made: the factory product can be flawless and cheap, but handmade has a story and intentionality that some cherish. In media, maybe AI content will dominate generic uses, but human-created art will hold its prestige for authenticity and connection. Or, humans might use AI so much in creation that the line blurs until we no longer care about the distinction.

Living with AI: Generational Reflections and Adaptations

As AI becomes woven into media, each generation faces different challenges and opportunities:

  • Boomers, who spanned from analog to digital late in life, now have to grapple with possibly the fastest, most disorienting shift: content that appears human but isn’t. They may approach with caution. Many will rely on younger family to guide them, as with other tech. But once comfort is established, they could greatly benefit – AI assistants for health questions, AI companions, and easier ways to get things done (like writing or finding info without sifting through search results) can improve their quality of life. The key is trust and training.
  • Gen X, often pragmatic, might incorporate AI in their work and home gradually. They remember a pre-internet youth but have long adapted to digital. They might be initially skeptical (“Is this AI really needed?”) but won’t want to be left behind. They can leverage their critical thinking to use AI smartly. For example, a Gen X marketer might use AI to analyze consumer data and draft campaign messages, but with oversight. They might also serve as the bridge in workplaces, mentoring both older colleagues who struggle with AI and younger ones who might over-rely on it without understanding fundamentals.
  • Millennials, many of whom are in their career primes, could see AI as a competitive edge or threat. They may adopt it enthusiastically to multitask (e.g., a Millennial startup founder uses AI to generate code, marketing copy, and even investor pitch outlines in a single afternoon – something that used to take a team days). On the flip side, a Millennial content writer might worry AI will replace their job. So there’s a push to upskill – become the one who guides the AI rather than gets replaced by it. In general, Millennials are adapting by focusing on high-level creative or strategic tasks and letting AI handle grunt work. They also navigate new ethical areas, since they often hold positions where policies might be set (like whether their company should use AI, or how to credit AI in projects).
  • Gen Z, entering adulthood with these AI tools already at their disposal, might find them as normal as we find smartphones. They are likely to incorporate AI into daily routines with less hesitancy – using it as a tutor, a coach, an entertainment source. The concern and opportunity for Gen Z is to develop their own skills deeply even with AI doing so much. Educators are focusing on teaching them how to ask good questions (prompts) and to always verify AI outputs. Gen Z is also creative in bending AI to novel uses (they might come up with forms of storytelling or interactive entertainment using AI that older folks wouldn’t imagine, like AI-driven roleplay games, or AI characters in virtual worlds to hang out with).
  • Cross-generational dynamic: There’s potential for misunderstanding – e.g., a Gen Z employee might think it’s fine to use ChatGPT for a client email, while their Boomer boss might see that as impersonal or even dishonest. Open conversations about appropriate AI use will be necessary, just like we had to navigate personal internet use at work, etc.

One could foresee something like: in a family, the Gen Z kid sets up an AI voice assistant for the home that can have real conversations. The Boomer grandparent is amazed that this “robot” tells jokes and remembers previous chats, but also a bit uneasy talking to something not alive. The Millennial parent uses it to help plan meals and schedules. The Gen X uncle visiting is impressed but insists on double-checking everything it says. This scenario shows each finding their way to co-exist with AI.

Conclusion: From Mirrors to Algorithms – Media’s Evolving Tapestry

Looking back over the three stages of media evolution, we see a journey from human-driven identity play, to performative social structuring, to AI-augmented creation and interaction. Each stage corresponds not only to technological advances but to shifts in how we experience key aspects of Lacan’s triad – Imaginary, Symbolic, Real – in our digital lives.

  • In Stage 1 (Classical Social Media), the Imaginary was salient in the curated images of Instagram and the ideal selves we projected. The Symbolic was built up in Facebook’s network of relationships and status updates, giving us a shared “social reality” online. The Real seeped in through Twitter’s unfiltered, rapid discourse – little truth bursts or chaos that sometimes slipped past the censors of polite society. Generations each navigated these in their own way: Boomers embraced the Symbolic on Facebook to reconnect and belong; Millennials indulged the Imaginary on Instagram, chasing aesthetic validation; Gen X tried a bit of both while maintaining a foothold in old and new; Gen Z peeked into this world as digital natives, already hankering for more authenticity.
  • In Stage 2 (Video-Based Platforms), the Imaginary order expanded through moving images – YouTube and Instagram visuals became stages for self-expression and identity, yet with an added layer of performance. The Symbolic took on an algorithmic edge: success on YouTube or TikTok meant understanding and leveraging platform rules, from hashtags to watch-time optimization (a modern code of meaning-making and value online) (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). The Real was more pronounced in TikTok’s algorithmic surprises, glitch trends, and the way it enabled raw spontaneity to often overshadow polished planning (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). We saw Gen Z thrive here, making “authentic” the new cool, while Millennials and Gen X adjusted to a world where you might get famous overnight or be talking to a camera as often as to friends. Content creation became more democratized, but also more flooded – birthing the influencer culture and a new economic Symbolic of likes and followers. Families often bonded or clashed over these new norms (“Put your phone down!” vs “Wait, let’s make a TikTok together!”).
  • Now, in Stage 3 (AI-Driven Media), the landscape is shifting under our feet. The Imaginary is perhaps limitless – we can literally visualize nearly any dream or see ourselves in any scenario via AI images (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). The Symbolic is getting outsourced in part to machines – language and meaning structures being generated and processed by AI at scale (Three Stages of Media Evolution: From Lacanian Orders to AI Communication – Žižekian Analysis). And the Real — well, it emerges in the cracks and edges: in the uneasy feeling when an AI-written text is soullessly accurate, or when a deepfake video makes us doubt our own eyes, or when an AI melody moves us and we wonder why. It also emerges in the form of new questions and challenges that don’t have easy answers: issues of authenticity, authorship, and truth in a media world where human and AI content blend. Generationally, Stage 3 is a great equalizer in some ways – everyone is having to learn and adapt at once, because these AI tools arrived for mass use quite suddenly. Younger folks might adapt faster, but older folks bring wisdom and context that are crucial for guiding responsible use (for instance, ethical considerations or historical perspectives to foresee consequences).

Throughout these stages, one thing remains clear: the human desire for connection, expression, and understanding drives these technologies. We want to be seen (Imaginary), to make sense of our world (Symbolic), and to encounter something genuine (Real). Each evolution of media has offered new avenues for those desires – sometimes fulfilling them, sometimes warping them. Social media gave voice to the voiceless but also spread misinformation; video platforms created new stars and communities but also new pressures and anxieties; AI promises efficiency and creativity unlocked, but could also lead to loss of skills or authenticity crises.

It’s not a linear progression where one order replaces another; rather, each stage layers on top of previous ones. Even now, Stage 1 platforms like Facebook still exist (albeit transformed and often seen as less trendy); Stage 2 behaviors (like vlogging or meme-making) persist; Stage 3 is adding new dimensions but not erasing the old. In fact, they intermingle – for example, an influencer (Stage 2 concept) might use AI tools (Stage 3 tech) to enhance their Instagram posts (Stage 1 platform repurposed).

For individuals, especially those who have lived through all three stages (older Millennials and Gen X saw it all unfold), it can be dizzying to recall how, in roughly 20 years, we went from carefully crafting MySpace “About Me” sections to watching AI create art and music in seconds. For younger Gen Z, who might barely remember a time before smartphones, the challenge is perhaps maintaining a sense of grounding and identity when so much of one’s environment is virtual or augmented by AI.

Each generation brings something valuable to the table in this current era:

  • Boomers bring a reminder of life before constant connectivity – they often value in-person interaction and privacy more, which is a healthy check on excesses of digital life.
  • Gen X brings a foot in both worlds – they’re the translators, often, between analog sensibilities and digital possibilities. They can help implement technology thoughtfully, having seen enough to be neither overly impressed nor Luddite.
  • Millennials bring collaborative and innovative spirit – they grew with the internet and often believe in its power to do good (connecting people, spreading knowledge). They also have learned from the downsides (like social media burnout) and are now in positions to shape new platforms and policies.
  • Gen Z brings fearless creativity and a demand for authenticity – they push older platforms to be more real and inclusive, and they’ll likely push AI to be used in ways that align with values (they’re vocal about ethics, climate, social justice – expect them to ask how AI can help, not just disrupt). They also adapt rapidly, which will drive adoption of beneficial innovations.

As we continue into Stage 3 and beyond, a key theme will be balance: balancing human and AI, online and offline, image and reality, structure and surprise. Lacan’s orders teach us that none of those dimensions can be eliminated – they are intrinsic to experience. So in media, no matter how advanced it gets, people will still seek:

  • Imaginary: spaces to play with identity and see reflections of what they could be (even if that reflection is now through an avatar or AI persona).
  • Symbolic: frameworks of meaning and community – we see already how people create new norms in AI communities (like guidelines for prompt sharing, or ethical norms for deepfakes). The big Other is still there, just taking new forms (like perhaps the “algorithm” is now an almost mythical Other we try to please or resist).
  • Real: cracks where something new or unscripted emerges – spontaneity, genuine emotion, or revelation. We might even use AI to find the Real (“show me something I’ve never seen”) or conversely, seek refuge in very human experiences (like live theater, nature walks) as an antidote to the digital saturation – those moments of raw presence.

In practical terms, how might a day in the life reflect all this? Picture a Millennial dad in 2025: in the morning, he uses a smart mirror (with an AI assistant) that compliments his outfit (Imaginary boost and Symbolic small-talk from AI). At work, he collaborates with colleagues worldwide on a VR whiteboard, while an AI summarizes their meeting notes (Symbolic support). On lunch break, he doomscrolls a bit on Twitter, sees a random hilarious video (Real laughter from some TikTok repost). In the evening, he and his Gen Z daughter ask their voice assistant to tell a story – the AI weaves one on the fly involving their suggestions (combining Symbolic narrative with imaginative play). Before bed, he might put his phone down and read a physical book or play guitar – something tangible and self-made – to reconnect with a more grounded sense of self. This mix shows how Stage 1, 2, 3 elements can all be present.

Finally, what does this mean culturally? We are likely moving toward a culture that is more fluid and co-created. The lines between creator and audience blurred in Stage 2; Stage 3 blurs human and machine roles in creation. The Lacanian lens reminds us that while tech changes, fundamental human psyche patterns reassert themselves. We will use new tools to pursue age-old aims: presenting who we are (or wish to be), making sense of our world, and reaching for what feels real and meaningful.

In sum, the evolution from the early days of social media to the AI-driven present is a complex, fascinating story of how our tools shape us and how we shape our tools in return. By viewing it through Imaginary, Symbolic, and Real, we see that each stage didn’t come out of nowhere – it answered certain desires and left certain gaps that the next stage then tried to fill. And across generations, although the surface behaviors differ (Grandpa might reminisce on Facebook, Mom posts on Instagram, teen dances on TikTok, and toddler watches AI-curated YouTube cartoons), underlying it all is the human quest for recognition, communication, and authenticity.

As we stand in this current moment, it’s clear that media evolution is not over – Stage 3 might herald Stage 4 (perhaps something like fully immersive AR/VR metaverses or brain-computer interface media, who knows?). But armed with an understanding of these patterns, we can approach the future a bit more mindfully. We can ask: How do we maintain our humanity – our empathy, creativity, and critical thinking – as our media mirrors become ever more enchanting? And we can celebrate how far we’ve come: from posting plain-text statuses like “is feeling happy today” to collaborating with intelligent machines to express entire worlds of imagination.

The three stages and Lacan’s triad ultimately highlight that technology changes, but human nature – in its imaginative, social, and truth-seeking dimensions – endures. By keeping that in focus, we can hopefully guide media evolution to enhance our lives, connect across generations, and perhaps even bring out the best in us, rather than the worst. It’s an ongoing conversation – one that, fittingly, we are having across tweets, videos, and AI-written posts, weaving the next chapter of our shared cultural story.

3 comments

Comments are closed.