This paper explores the transformative impact of artificial intelligence (AI) on visual culture and its broader implications for contemporary society. The proliferation of machine learning models in generating visual content necessitates a critical reassessment of the relationship between reality and representation. AI-generated imagery not only challenges traditional conceptions of human creativity and perception but also intensifies the dominance of visual media in shaping public consciousness. By critiquing the reliance on vision as the primary mode of knowledge, this study examines how AI technologies blur the boundaries between reality and artificial constructs, deepening societal alienation. To illustrate these dynamics, the paper presents an experiment conducted in Bolzano, Italy, where six distinct visual scenarios for an urban redevelopment project were created. Public engagement with these scenarios revealed a strong preference for visually striking AI-generated images, often at the expense of addressing real-life challenges, underscoring the influence of the spectacle in shaping perceptions and decisions. The paper further investigates the role of AI in accelerating the commodification of images, perpetuating existing power structures, and raising critical questions about the human role in creating and interpreting visual media. Ultimately, this work calls for a re-evaluation of the societal implications of AI-driven visual culture, as it redefines the dynamics of observation, meaning, and agency.
Alex: Welcome to another episode of ResearchPod. Sam, what are we diving into today?
Sam: We're looking at a paper called "Artificial Intelligence: Beyond Ocularcentrism, The New Age of Humans Beyond the Spectacle" by Mustapha El Moussaoui from the Free University of Bolzano. It argues that AI-generated images are making people prefer flashy visuals over practical fixes when planning real cities.
Alex: So this paper is basically asking whether we're letting perfect AI pictures trick us into bad decisions about our neighborhoods?
Sam: Yes, exactly. Society puts sight on a pedestal—we trust what looks good more than what works in real life. This bias, called ocularcentrism, means AI's polished images can overshadow everyday issues like potholes or bad lighting. To test it, the author ran an experiment in Bolzano, Italy, for an urban redevelopment project. They made six picture sets of possible neighborhood changes: five created by AI tools that look dreamy and futuristic, and one showing real fixes for actual problems. Then they asked 87 locals to pick their favorite—over 80% chose the AI ones, even though those ignored safety and access needs.
Alex: Right, like picking a shiny movie poster over the story that actually helps people walk safely at night.
Sam: That's the hook. As AI floods us with these flawless scenes, the public picks spectacle over substance. The paper suggests this deepens a divide where images control how we see and shape our world, pulling us from real experiences.
Alex: And that experiment shows it's already happening in planning meetings?
Sam: Precisely. People voted for futuristic parks over designs fixing poor lighting and paths, proving how visual allure sways choices. It echoes older ideas about "the spectacle," where eye-catching media hides tougher truths.
Alex: So those ideas about spectacle hiding truths... they're playing out right now with AI images in city planning?
Sam: Yes. AI makes pictures so convincing they challenge what we think is real. One way it does this is through systems where one part of the AI tries to create fake images of neighborhoods, while another part acts like a judge, spotting the fakes and giving feedback. They keep competing until the fakes look just as good as photos from life. Tools like GANs—Generative Adversarial Networks—and Stable Diffusion speed up making endless perfect scenes, taking away humans' main role in creating visuals. Think of it like a forger practicing with a detective until the fakes fool everyone.
Alex: Wait, so these AI pictures aren't based on real fixes—they're basically made-up dreams? Why call them "hallucinations"?
Sam: Exactly, they're inventions that mix real styles with fantasy, blurring what's actual from what's dreamed up by code. Like a mind inventing scenes that never happened but feel true to the eye. The paper calls these AI hallucinations, and they create a kind of show where machine-made beauty tricks us into forgetting practical needs, like safe paths or lights.
Alex: That sounds like it pulls from older warnings about vision fooling us.
Sam: It does. Thinkers like Juhani Pallasmaa point out how favoring sight alone starves our other senses—touch, sound, smell—which make spaces feel truly lived-in. In architecture, pretty looks win over designs you can actually use with your whole body. Plato's cave story warns of shadows on a wall seeming real, trapping people from truth.
Alex: So AI amps up that trap, making us pick eye-candy over body-friendly reality?
Sam: The experiment bears that out. Public choices show how these visuals reshape power—who watches, who shapes space—without us noticing the shift. One thinker, Jonathan Crary, points out how tools like photography and cinema have changed not just what we see, but the whole way vision works in society. They turn seeing into something bought and sold, split between the person looking and the thing looked at.
Alex: Wait, so AI isn't just showing pictures—it's rewriting the rules of who watches what?
Sam: Exactly. Guy Debord described a world where images aren't just pretty—they're a way to control people. Life becomes a huge pile of shows that keep folks passive, buying into power without questioning it. Images hide real problems like unfairness, making shiny distractions seem normal. AI cranks this up: apps like Instagram feed endless curated visuals, where algorithms pick what you see, turning users into both makers and watchers of this controlled show.
Alex: Right—like social media deciding your feed to keep you scrolling, not thinking.
Sam: Yes, and this creates what's called the hyperreal by Jean Baudrillard—fake scenes so perfect they feel more true than actual streets. In city planning, that means picking dream parks over fixing real potholes.
Alex: So the public experiment showed folks falling for that hyperreal pull?
Sam: It did. Over 80% chose those AI visions, sidelining practical changes. The paper suggests this risks deeper splits—spectacle masking real needs, reshaping spaces through looks alone.
Alex: A meaningful warning, yeah. But the paper also talks about AI maybe challenging that visual bias somehow—how does that fit?
Sam: It does, in a twist. AI image tools go beyond copying what humans see—they invent scenes from patterns in huge piles of photos, making pictures that look real but come from pure math, not cameras. This shakes the idea that only eyes tell truth, since machines now "dream up" visuals better than some real shots. The paper sees this as a chance to question vision's top spot. Deepfakes use AI to swap faces or actions in videos, so someone appears to say words they never spoke—like pasting your teacher's head on a dancer. Once photos proved events happened; now AI blurs that, weakening trust in any visual proof.
Alex: So if visuals lose reliability, does that help break the spectacle's grip—or make control easier?
Sam: Both risks exist. It could push new manipulations, like fake scenes propping up leaders. Or it might let anyone challenge official stories with counter-images. Either way, machines now craft the show, shifting who holds the strings. Thinker Shoshana Zuboff describes "surveillance capitalism," where firms grab your data—clicks, likes—to guess and nudge what you do next. Algorithms feed tailored images, extending spectacle into personal lives.
Alex: So identity gets performative too, like curating a feed?
Sam: Exactly. Platforms make sharing your image constant, so self becomes a show for likes—hiding real feelings behind filters. Philosopher Robert Pfaller calls this "interpassivity": you hand over living the moment to apps or pics, watching your own life as spectacle. The paper warns this pulls us from full, body-based experience.
Alex: That ties right back to the Bolzano experiment. Walk me through how they set that up.
Sam: In October 2023, researchers in Bolzano's Don Bosco neighborhood created six picture sets showing possible future changes. Five came from AI tools like Midjourney and ComfyUI: four drew from a study on sustainability goals by 2030—one on local traditions, another on global ideas adapted nearby, a third on personal choices, and the fourth on tech fixes for green living. The fifth was a darker vision. The sixth showed straightforward answers to everyday problems, like better paths for wheelchairs, safer walks at night, and spots where neighbors connect easily. They called this a phenomenological approach, meaning it started from how people actually feel and move through spaces with their whole bodies.
Alex: Okay, so four hopeful futures, one grim one—all AI-made—and one fixing real stuff. How'd they make those AI pictures so appealing?
Sam: The AI used a setup where two parts work against each other. One part dreams up neighborhood scenes from patterns in tons of real photos, like mixing ingredients from recipes to bake a new cake. The other part checks them, saying "that's not quite right" until the dreams look real enough to fool anyone. They held a public event with 87 locals of all ages. After explaining each set, folks voted on their top pick—about 80% went for the AI versions, calling them spectacular, even though those skipped the practical fixes.
Alex: So most ignored the safe paths and lights for shiny dreams? That really shows the pull of looks over fixes.
Sam: It does. The paper points out this speed of AI image-making breaks the old slow buildup of spectacle. Instead of waiting for photos or films, we get endless new visuals instantly.
Alex: Right, so it could open doors to fresher ideas... or just amp up the distractions. Does the paper see any upsides here for how we think about ourselves?
Sam: It does point to a shift. As machines mix into daily life, our sense of self starts blending human and tech parts—like identity becoming a web of real and digital ties. The paper calls this a posthuman view, where we're not fixed alone but shaped by tools around us.
Alex: Like evolving with AI instead of against it? But with only 87 people from one spot in Italy, how solid is that takeaway?
Sam: Fair point—the group was small and local to Bolzano, so it might not speak for everywhere. They didn't track details like ages or backgrounds in votes, or test if knowing the images were AI changed picks. Still, it flags a clear pattern worth watching: visuals swaying real decisions.
Alex: Okay, so limits on size and who joined mean we can't overclaim. What might come next to balance this?
Sam: Planners could weave in tools that hit more senses—like sounds of a street or feels of a bench—not just sights. This tempers the flash with real-life checks, aiming for spaces that work for everyone. The paper urges questioning every image, turning AI's power into a tool for fairer changes rather than new traps.
Alex: That lands well—critically using these visuals without letting them run the show. A solid nudge for how we shape cities ahead.
Sam: Precisely. The Bolzano case shows both the risk and the opening: AI visuals dominate now, but mindful steps can blend them with lived needs.
Alex: Thanks, Sam—clear insights on a timely tension. That's it for this look at AI's role in our visual world. Thanks for listening to ResearchPod.