Design Art Papers 2025 | No. 13

World Leaders are no exception when it comes to being meme material, especially in recent times, as the public engages with information related to them almost on a daily basis. Examples of the phenomenon include various AI generated images depicting Donald Trump and Vladimir Putin spending time together as well as a specific artificially generated video sparked by the White House meeting between Donald Trump and Volodimir Zelenski from February 2025 depicting the two presidents fighting. Such newmeme trends further press the idea that political figures are often nothing more than characters in the eyes of the internet. The notion of Internet ugly better defines humanity, rather than the polished look a computer produces (Douglas 2014). This notion also applies in the modern age when Artificial intelligence is being used in all fields, including memes. Their overly polished look sits in antithesis to how people are messy, sometimes incoherent and inherently different from one another as opposed to the cleaner looking, almost always similar form AI generated memes take. The point of memes, such as a painting, is to show the artist’s true intention and to resonate with other people. The democratization debate intersects with unresolved questions of authorship and agency. Traditional meme culture already complicates intellectual property due to its reliance on remixing. AI intensifies these ambiguities. As the EU AI Act (which entered into force on 1 August 2024 and will be fully applicable two years later, in 2026) suggests, it partially addresses these concerns by requiring transparency around AI-generated content, yet it does not resolve deeper ethical dilemmas of ownership and recognition (Friedrich, n.d.). AI memes represent what some scholars term post-authentic expression, where the link between message and messenger is broken. For some, this may seem liberating; for others, especially communities whose symbols are misappropriated, it represents erasure. Memes being used as a business strategy by various agencies as an attempt to show their customers that they relate to them and are also in touch with the latest trends and memes is also a case. The American fast-food chain Wendy’s started the trend by using their official Twitter account in order to give sarcastic comments to the customer complaints and questions. A more recent instance of the usage of memes for business is how Duolingo, the language learning application has started various memes by itself a few years ago, such as the Spanish or Vanish (Adam 2024) meme, which suggests that the Duolingo mascot will harm you if you do not complete your Spanish lessons. A more recent meme started by the company is the Duolingo Owl Dies meme (Philipp 2025). The meme started from Duolingo’s post on their official Twitter account stating that the bird has died. This has driven the internet to create more memes based on the original post. 4. Situational Learning as an Analytical Lens for Understanding Meme Evolution in the Age of AI To analyse the evolution of meme production, we interpret the data through the theoretical lens of Situated Learning (Lave et al. 1991). By tracking a single thematic concept—"The Overworked Academic" (represented by a Cat in a Suit), across our dataset, we identify three bounded situational contexts. Each context presents a distinct locus of agency and a unique pedagogical friction for the students in higher education. 4.1. Context A: The Pedagogy of Bricolage (Human-Authored) In the first situational context, broadly analogous to traditional foundation studio practice, the student’s experience is defined by bricolage. Here, the barrier to entry is technical facility and cultural capital. The student acts as an Editor, utilizing software tools (e.g., Photoshop) to manually assemble diverse cultural artifacts. Situational Vignette (The Manual Edit): To visualize "The Overworked Academic," a student searches for a high-resolution stock photo of a business suit and a separate image of their own pet cat. They spend twenty minutes using the magnetic lasso tool to mask the cat’s head, adjusting the color balance to match the suit, and manually typing the caption using the Impact font. Analytical Finding: Pedagogically, this context relies on "tacit knowledge"—the specific, hand-eye coordination required to manipulate pixels. The learning experience is one of high-friction iterative design. The humor derives from the "traceability" of the human labor—the visible, slightly imperfect tension between the domestic cat and the corporate signifier, requiring a literacy of making. 4.2. Context B: The Pedagogy of Co-Creation (AI-Assisted) The second context represents a rupture in this visual pedagogy, shifting the student from maker to director. In this "Human-in-the-Loop" workflow, the friction of production shifts from the manual to the linguistic. The situational learning here is dialogic. The student does not manipulate the material directly; they manipulate the latent space of a generative model. Situational Vignette (The Prompt Iteration): To visualize the same concept, the user prompts a model (e.g., Midjourney) with: "A stressed Persian cat wearing a tweed professor's jacket, sitting at a desk piled with papers." The first output looks too cartoonish. The user learns by negotiating with the model, refining the prompt to: "Cinematic lighting, photorealistic, 35mm lens, intense expression." Analytical Finding: This reconfigures the pedagogical feedback loop. The student submits a linguistic abstraction, critiques the high-fidelity output, and refines the input. The "double-take" effect observed in our data suggests the core competency here is epistemic judgment—navigating a space where the image of the cat is not constructed from parts, but summoned as a coherent, hallucinated whole. 4.3. Context C: The Pedagogy of Critical Systems (Fully Automated) In the final bounded context, human agency is removed from the production loop entirely. Autonomous agents execute the scraping, generation, and distribution of content based on algorithmic optimization. Situational Vignette (The Automated Farm): A Python script detects that "Burnout" and "Cats" are trending topics. It feeds these keywords into an LLM to generate 50 variations of captions (e.g., "Mondays be like...", "Grind set Mode"), pairs them with 50 automated variations of "Cat in Suit" images generated via Stable Diffusion, and posts them to Instagram Reels every 15 minutes to maximize engagement. Analytical Finding: For the higher education sector, this context is not a site of practice but a site of critical inquiry. The "learning" is performed by the algorithm (optimizing for dwell time) rather than the human. The pedagogical imperative shifts from creating the meme to interrogating the political economy of the image, viewing the content not as a joke about work, but as an industrial byproduct of the attention economy. 4.4. A Typology for Visual Literacy The analysis of this single thematic thread across three contexts indicates a fundamental shift in how "Legitimate Peripheral Participation" (Lave & Wenger, 1991) is enacted. The frictionof learning—and therefore the site of pedagogical intervention—is migrating from the hand (Context A) to the mind (Context B), and finally to the system (Context C). To assist educators in navigating these shifting terrains, Table 1 synthesizes these contexts into a pedagogical framework. Table 1. Shifting Pedagogical Imperatives in Meme Production A comparative analysis of student roles, frictions, and literacies using a controlled thematic variable. 5. A Summary of Meme Eras, Dissemination and Conclusion The trajectory of meme culture, from its inception through to its current entanglement with generative artificial intelligence, reveals a landscapemarkedbyboth continuity and transformation. Historically, the creation of memes has been characterised by remarkable speed and accessibility; almost any image or concept could be rapidly appropriated and disseminated as a meme, reflecting the participatory ethos that underpins internet, and respectively, meme culture. By categorising the evolution of memes into multiple ‘eras’, a more complete framework through which the function and form of memes as internet art, as well as multimodal constructs, emerges. Memes first appear as simply in-group jokes of early-internet communities, before evolving to incorporate references pertaining to their community’s interest, and in turn acting as a shorthand denoting in-group belonging. Communal creation is shown as an integral element of meme creation and propagation, as well as the function that separates them from trends or viral content. The addition of social media and image/video hosting websites popularise meme culture and provides social hubs within which meme inception and dissemination is vastly intensified, in turn reaching the mainstream internet userbase. Their overexposure and overuse lead to a counter-cultural push that critiques conventional meme structures while over time acquiring an absurdist and satirizing tone. The COVID-19 pandemic paired with an increasingly polarized society forces meme culture to diverge into multiple genres of participation, representative of users, platforms, formats and real- life influences that have come to affect memes. The addition of AI-generation, alongside further political divisions, have fragmented meme culture and pushed memes to be used as propaganda. 259 258 / / / / Caiete de Arte și Design / nr. 13 / 2025 / / / / Publicație a Centrului de Cercetare și Creație în Artele Decorative și Design / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / / /