www-noemamag-com-zt2clg.txt (42139B)
1 [1]Skip to the content 2 3 [2][noema-logo] 4 [3]Subscribe 5 6 [4] Published 7 by the 8 Berggruen 9 Institute 10 11 Topics 12 13 • [5]Technology & the Human 14 • [6]Future of Capitalism 15 • [7]Philosophy & Culture 16 • [8]Climate Crisis 17 18 • [9]Geopolitics & Deglobalization 19 • [10]Future of Democracy 20 • [11]Digital Society 21 • [12]Read Noema In Print 22 23 Search 24 25 [13][ ] 26 Go 27 The Last Days Of Social Media 28 29 Social media promised connection, but it has delivered exhaustion. 30 31 Illustration by Daniel Barreto. Illustration by Daniel Barreto. 32 Daniel Barreto 33 [15]Essay[16]Digital Society 34 By [17]James O'Sullivan September 2, 2025 35 [18][19][20][21][22] 36 Credits 37 38 James O’Sullivan lectures in the School of English and Digital Humanities at 39 University College Cork, where his work explores the intersection of technology 40 and culture. 41 42 At first glance, the feed looks familiar, a seamless carousel of “For You” 43 updates gliding beneath your thumb. But déjà‑vu sets in as 10 posts from 10 44 different accounts carry the same stock portrait and the same breathless 45 promise — “click here for free pics” or “here is the one productivity hack you 46 need in 2025.” Swipe again and three near‑identical replies appear, each from a 47 pout‑filtered avatar directing you to “free pics.” Between them sits an ad for 48 a cash‑back crypto card. 49 50 Scroll further and recycled TikTok clips with “original audio” bleed into Reels 51 on Facebook and Instagram; AI‑stitched football highlights showcase players’ 52 limbs bending like marionettes. Refresh once more, and the woman who enjoys 53 your snaps of sushi rolls has seemingly spawned five clones. 54 55 Whatever remains of genuine, human content is increasingly sidelined by 56 algorithmic prioritization, receiving fewer interactions than the engineered 57 content and AI slop optimized solely for clicks. 58 59 These are the last days of social media as we know it. 60 61 Drowning The Real 62 63 Social media was built on the romance of authenticity. Early platforms sold 64 themselves as conduits for genuine connection: stuff you wanted to see, like 65 your friend’s wedding and your cousin’s dog. 66 67 Even influencer culture, for all its artifice, promised that behind the 68 ring‑light stood an actual person. But the attention economy, and more 69 recently, the generative AI-fueled late attention economy, have broken whatever 70 social contract underpinned that illusion. The feed no longer feels crowded 71 with people but crowded with content. At this point, it has far less to do with 72 people than with consumers and consumption. 73 74 In recent years, Facebook and other platforms that facilitate billions of daily 75 interactions have slowly morphed into the internet’s largest repositories of 76 [23]AI‑generated spam. Research has found what users plainly see: tens of 77 thousands of machine‑written posts [24]now flood public groups — pushing scams, 78 chasing clicks — with [25]clickbait headlines, half‑coherent listicles and hazy 79 lifestyle images stitched together in AI tools like Midjourney. 80 81 It’s all just vapid, empty shit produced for engagement’s sake. Facebook is 82 “sloshing” in low-effort AI-generated posts, as Arwa Mahdawi [26]notes in The 83 Guardian; some even bolstered by algorithmic boosts, like “[27]Shrimp Jesus.” 84 85 The difference between human and synthetic content is becoming increasingly 86 indistinguishable, and platforms seem unable, or uninterested, in trying to 87 police it. Earlier this year, CEO Steve Huffman pledged to “[28]keep Reddit 88 human,” a tacit admission that floodwaters were already lapping at the last 89 high ground. TikTok, meanwhile, [29]swarms with AI narrators presenting 90 concocted news reports and [30]“what‑if” histories. A few creators do append 91 labels disclaiming that their videos depict “no real events,” but many creators 92 don’t bother, and many consumers don’t seem to care. 93 94 The problem is not just the rise of fake material, but the collapse of context 95 and the acceptance that truth no longer matters as long as our cravings for 96 colors and noise are satisfied. Contemporary social media content is more often 97 rootless, detached from cultural memory, interpersonal exchange or shared 98 conversation. It arrives fully formed, optimized for attention rather than 99 meaning, producing a kind of semantic sludge, posts that look like language yet 100 say almost nothing. 101 102 We’re drowning in this nothingness. 103 104 The Bot-Girl Economy 105 106 If spam (AI or otherwise) is the white noise of the modern timeline, its 107 dominant melody is a different form of automation: the hyper‑optimized, 108 sex‑adjacent human avatar. She appears everywhere, replying to trending tweets 109 with selfies, promising “funny memes in bio” and linking, inevitably, to 110 OnlyFans or one of its proxies. Sometimes she is real. Sometimes she is not. 111 Sometimes she is a he, sitting in a [31]compound in Myanmar. Increasingly, it 112 makes no difference. 113 114 This convergence of bots, scammers, brand-funnels and soft‑core marketing 115 underpins what might be called the bot-girl economy, a parasocial marketplace 116 [32]fueled in a large part by economic precarity. At its core is a 117 transactional logic: Attention is scarce, intimacy is monetizable and platforms 118 generally won’t intervene so long as engagement [33]stays high. As more women 119 now turn to online sex work, lots of men are eager to pay them for their 120 services. And as these workers try to cope with the precarity imposed by 121 platform metrics and competition, some can spiral, forever downward, into a 122 transactional attention-to-intimacy logic that eventually turns them into more 123 bot than human. To hold attention, some creators increasingly opt to behave 124 like algorithms themselves, [34]automating replies, optimizing content for 125 engagement, or mimicking affection at scale. The distinction between 126 performance and intention must surely erode as real people perform as synthetic 127 avatars and synthetic avatars mimic real women. 128 129 There is loneliness, desperation and predation everywhere. 130 131 “Genuine, human content is increasingly sidelined by algorithmic 132 prioritization, receiving fewer interactions than the engineered content 133 and AI slop optimized solely for clicks.” 134 135 The bot-girl is more than just a symptom; she is a proof of concept for how 136 social media bends even aesthetics to the logic of engagement. Once, profile 137 pictures (both real and synthetic) aspired to hyper-glamor, unreachable beauty 138 filtered through fantasy. But that fantasy began to underperform as average men 139 sensed the ruse, recognizing that supermodels typically don’t send them DMs. 140 And so, the system adapted, surfacing profiles that felt more plausible, more 141 emotionally available. Today’s avatars project a curated accessibility: They’re 142 attractive but not flawless, styled to suggest they might genuinely be 143 interested in you. It’s a calibrated effect, just human enough to convey 144 plausibility, just artificial enough to scale. She has to look more human to 145 stay afloat, but act more bot to keep up. Nearly everything is socially 146 engineered for maximum interaction: the like, the comment, the click, the 147 private message. 148 149 Once seen as the fringe economy of cam sites, OnlyFans has become the dominant 150 digital marketplace for sex workers. In 2023, the then-seven-year-old platform 151 [35]generated $6.63 billion in gross payments from fans, with $658 million in 152 profit before tax. Its success has bled across the social web; platforms like X 153 (formerly Twitter) now serve as de facto marketing layers for OnlyFans 154 creators, with thousands of accounts running fan-funnel operations, [36]baiting 155 users into paid subscriptions. 156 157 The tools of seduction are also changing. One 2024 study [37]estimated that 158 thousands of X accounts use AI to generate fake profile photos. Many content 159 creators have also [38]begun using AI for talking-head videos, [39]synthetic 160 voices or endlessly varied selfies. Content is likely A/B tested for 161 click-through rates. Bios are written with conversion in mind. DMs are 162 automated or [40]outsourced to AI impersonators. For users, the effect is a 163 strange hybrid of influencer, chatbot and parasitic marketing loop. One minute 164 you’re arguing politics, the next, you’re being pitched a girlfriend experience 165 by a bot. 166 167 Engagement In Freefall 168 169 While content proliferates, engagement is evaporating. Average interaction 170 rates across major platforms are declining fast: Facebook and X posts now 171 scrape an average 0.15% engagement, while Instagram has dropped 24% 172 year-on-year. Even TikTok has [41]begun to plateau. People aren’t connecting or 173 conversing on social media like they used to; they’re just wading through slop, 174 that is, low-effort, low-quality content produced at scale, often with AI, for 175 engagement. 176 177 And much of it is slop: Less than half of American adults [42]now rate the 178 information they see on social media as “mostly reliable”— down from roughly 179 two-thirds in the mid-2010s. Young adults register the steepest collapse, 180 which is unsurprising; as digital natives, they better understand that the 181 content they scroll upon wasn’t necessarily produced by humans. And yet, they 182 continue to scroll. 183 184 The timeline is no longer a source of information or social presence, but more 185 of a mood-regulation device, endlessly replenishing itself with just enough 186 novelty to suppress the anxiety of stopping. Scrolling has become a form of 187 ambient dissociation, half-conscious, half-compulsive, closer to scratching an 188 itch than seeking anything in particular. People know the feed is fake, they 189 just don’t care. 190 191 Platforms have little incentive to stem the tide. Synthetic accounts are cheap, 192 tireless and lucrative because they never demand wages or unionize. Systems 193 designed to surface peer-to-peer engagement are now systematically filtering 194 out such activity, because what counts as engagement has changed. Engagement is 195 now about raw user attention – time spent, impressions, scroll velocity – and 196 the net effect is an online world in which you are constantly being addressed 197 but never truly spoken to. 198 199 The Great Unbundling 200 201 Social media’s death rattle will not be a bang but a shrug. 202 203 These networks once promised a single interface for the whole of online life: 204 Facebook as social hub, Twitter as news‑wire, YouTube as broadcaster, Instagram 205 as photo album, TikTok as distraction engine. Growth appeared inexorable. But 206 now, the model is splintering, and users are drifting toward smaller, slower, 207 more private spaces, like group chats, Discord servers and [43]federated 208 microblogs — a billion little gardens. 209 210 Since Elon Musk’s takeover, X has [44]shed at least 15% of its global user 211 base. Meta’s Threads, launched with great fanfare in 2023, saw its number of 212 daily active users collapse within a month, [45]falling from around 50 million 213 active Android users at launch in July to only 10 million active users the 214 following August. Twitch [46]recorded its lowest monthly watch-time in over 215 four years in December 2024, just 1.58 billion hours, 11% lower than the 216 December average from 2020-23. 217 218 “While content proliferates, engagement is evaporating.” 219 220 Even the giants that still command vast audiences are no longer growing 221 exponentially. Many platforms have already died (Vine, Google+, Yik Yak), are 222 functionally dead or zombified (Tumblr, Ello), or have been revived and died 223 again (MySpace, Bebo). Some notable exceptions aside, like Reddit and BlueSky 224 (though it’s still early days for the latter), growth has plateaued across the 225 board. While social media adoption continues to rise overall, it’s no longer 226 explosive. [47]As of early 2025, around 5.3 billion user identities — roughly 227 65% of the global population — are on social platforms, but annual growth has 228 decelerated to just 4-5%, a steep drop from the double-digit surges seen 229 earlier in the 2010s. 230 231 Intentional, opt-in micro‑communities are rising in their place — like Patreon 232 collectives and Substack newsletters — where creators chase depth over scale, 233 retention over virality. A writer with 10,000 devoted subscribers can 234 potentially earn more and burn out less than one with a million passive 235 followers on Instagram. 236 237 But the old practices are still evident: Substack is full of personal brands 238 announcing their journeys, Discord servers host influencers disguised as 239 community leaders and Patreon bios promise exclusive access that is often just 240 recycled content. Still, something has shifted. These are not mass arenas; they 241 are clubs — opt-in spaces with boundaries, where people remember who you are. 242 And they are often paywalled, or at least heavily moderated, which at the very 243 least keeps the bots out. What’s being sold is less a product than a sense of 244 proximity, and while the economics may be similar, the affective atmosphere is 245 different, smaller, slower, more reciprocal. In these spaces, creators don’t 246 chase virality; they cultivate trust. 247 248 Even the big platforms sense the turning tide. Instagram has begun emphasizing 249 DMs, X is pushing subscriber‑only circles and TikTok is experimenting with 250 private communities. Behind these developments is an implicit acknowledgement 251 that the infinite scroll, stuffed with bots and synthetic sludge, is 252 approaching the limit of what humans will tolerate. A lot of people [48]seem to 253 be fine with slop, but as more start to crave authenticity, the platforms will 254 be forced to take note. 255 256 From Attention To Exhaustion 257 258 The social internet was built on attention, not only the promise to capture 259 yours but the chance for you to capture a slice of everyone else’s. After two 260 decades, the mechanism has inverted, replacing connection with exhaustion. 261 “Dopamine detox” and “digital Sabbath” have entered the mainstream. In the 262 U.S., [49]a significant proportion of 18‑ to 34‑year‑olds took deliberate 263 breaks from social media in 2024, citing mental health as the motivation, 264 according to an American Psychiatric Association poll. And yet, time spent on 265 the platforms remains high — people scroll not because they enjoy it, but 266 because they don’t know how to stop. Self-help influencers now recommend weekly 267 “no-screen Sundays” (yes, the irony). The mark of the hipster is no longer an 268 ill-fitting beanie but an old-school Nokia dumbphone. 269 270 [50]Some creators are quitting, too. Competing with synthetic performers who 271 never sleep, they find the visibility race not merely tiring but absurd. Why 272 post a selfie when an AI can generate a prettier one? Why craft a thought when 273 ChatGPT can produce one faster? 274 275 These are the last days of social media, not because we lack content, but 276 because the attention economy has neared its outer limit — we have exhausted 277 the capacity to care. There is more to watch, read, click and react to than 278 ever before — an endless buffet of stimulation. But novelty has become 279 indistinguishable from noise. Every scroll brings more, and each addition 280 subtracts meaning. We are indeed drowning. In this saturation, even the most 281 outrageous or emotive content struggles to provoke more than a blink. 282 283 Outrage fatigues. Irony flattens. Virality cannibalizes itself. The feed no 284 longer surprises but sedates, and in that sedation, something quietly breaks, 285 and social media no longer feels like a place to be; it is a surface to skim. 286 287 No one is forcing anyone to go on TikTok or to consume the clickbait in their 288 feeds. The content served to us by algorithms is, in effect, a warped mirror, 289 reflecting and distorting our worst impulses. For younger users in particular, 290 their scrolling of social media can [51]become compulsive, rewarding [52]their 291 developing brains with unpredictable hits of dopamine that keep them glued to 292 their screens. 293 [53]Read Noema in print. 294 295 Social media platforms have also achieved something more elegant than coercion: 296 They’ve made non-participation a form of self-exile, a luxury available only to 297 those who can afford its costs. 298 299 “Why post a selfie when an AI can generate a prettier one? Why craft a 300 thought when ChatGPT can produce one faster?” 301 302 Our offline reality is irrevocably shaped by our online world: Consider the 303 worker who deletes or was never on LinkedIn, excluding themselves from 304 professional networks that increasingly exist nowhere else; or the small 305 business owner who abandons Instagram, watching customers drift toward 306 competitors who maintain their social media presence. The teenager who refuses 307 TikTok may find herself unable to parse references, memes and microcultures 308 that soon constitute her peers’ vernacular. 309 310 These platforms haven’t just captured attention, they’ve enclosed the commons 311 where social, economic and cultural capital are exchanged. But enclosure breeds 312 resistance, and as exhaustion sets in, alternatives begin to emerge. 313 314 Architectures Of Intention 315 316 The successor to mass social media is, as already noted, emerging not as a 317 single platform, but as a scattering of alleyways, salons, encrypted lounges 318 and federated town squares — those little gardens. 319 320 Maybe today’s major social media platforms will find new ways to hold the gaze 321 of the masses, or maybe they will continue to decline in relevance, lingering 322 like derelict shopping centers or a dying online game, haunted by bots and the 323 echo of once‑human chatter. Occasionally we may wander back, out of habit or 324 nostalgia, or to converse once more as a crowd, among the ruins. But as social 325 media collapses on itself, the future points to a quieter, more fractured, more 326 human web, something that no longer promises to be everything, everywhere, for 327 everyone. 328 329 This is a good thing. Group chats and invite‑only circles are where context and 330 connection survive. These are spaces defined less by scale than by shared 331 understanding, where people no longer perform for an algorithmic audience but 332 speak in the presence of chosen others. Messaging apps like Signal are quietly 333 [54]becoming dominant infrastructures for digital social life, not because they 334 promise discovery, but because they don’t. In these spaces, a message often 335 carries more meaning because it is usually directed, not broadcast. 336 337 Social media’s current logic is designed to reduce friction, to give users 338 infinite content for instant gratification, or at the very least, the 339 anticipation of such. The antidote to this compulsive, numbing overload will be 340 found in deliberative friction, design patterns that introduce pause and 341 reflection into digital interaction, or platforms and algorithms that create 342 space for intention. 343 344 This isn’t about making platforms needlessly cumbersome but about 345 distinguishing between helpful constraints and extractive ones. Consider [55] 346 Are.na, a non-profit, ad-free creative platform founded in 2014 for collecting 347 and connecting ideas that feels like the anti-Pinterest: There’s no algorithmic 348 feed or engagement metrics, no trending tab to fall into and no infinite 349 scroll. The pace is glacial by social media standards. Connections between 350 ideas must be made manually, and thus, thoughtfully — there are no algorithmic 351 suggestions or ranked content. 352 353 To demand intention over passive, mindless screen time, X could require a 354 90-second delay before posting replies, not to deter participation, but to curb 355 reactive broadcasting and engagement farming. Instagram could show how long 356 you’ve spent scrolling before allowing uploads of posts or stories, and 357 Facebook could display the carbon cost of its data centers, reminding users 358 that digital actions have material consequences, with each refresh. These small 359 added moments of friction and purposeful interruptions — what UX designers 360 currently optimize away — are precisely what we need to break the cycle of 361 passive consumption and restore intention to digital interaction. 362 363 We can dream of a digital future where belonging is no longer measured by 364 follower counts or engagement rates, but rather by the development of trust and 365 the quality of conversation. We can dream of a digital future in which 366 communities form around shared interests and mutual care rather than 367 algorithmic prediction. Our public squares — the big algorithmic platforms — 368 will never be cordoned off entirely, but they might sit alongside countless 369 semi‑public parlors where people choose their company and set their own rules, 370 spaces that prioritize continuity over reach and coherence over chaos. People 371 will show up not to go viral, but to be seen in context. None of this is about 372 escaping the social internet, but about reclaiming its scale, pace, and 373 purpose. 374 375 Governance Scaffolding 376 377 The most radical redesign of social media might be the most familiar: What if 378 we treated these platforms as [56]public utilities rather than private casinos? 379 380 A public-service model wouldn’t require state control; rather, it could be 381 governed through civic charters, much like public broadcasters operate under 382 mandates that balance independence and accountability. This vision stands in 383 stark contrast to the current direction of most major platforms, which are 384 becoming increasingly opaque. 385 386 “Non-participation [is] a form of self-exile, a luxury available only to 387 those who can afford its costs.” 388 389 In recent years, Reddit and X, among other platforms, have either restricted or 390 removed API access, dismantling open-data pathways. The very infrastructures 391 that shape public discourse are retreating from public access and oversight. 392 Imagine social media platforms with transparent algorithms subject to public 393 audit, user representation on governance boards, revenue models based on public 394 funding or member dues rather than surveillance advertising, mandates to serve 395 democratic discourse rather than maximize engagement, and regular impact 396 assessments that measure not just usage but societal effects. 397 398 Some initiatives gesture in this direction. Meta’s Oversight Board, for 399 example, frames itself as an independent body for content moderation appeals, 400 though its remit is narrow and its influence ultimately limited by Meta’s 401 discretion. X’s Community Notes, meanwhile, allows user-generated fact-checks 402 but relies on opaque scoring mechanisms and lacks formal accountability. Both 403 are add-ons to existing platform logic rather than systemic redesigns. A true 404 public-service model would bake accountability into the platform’s 405 infrastructure, not just bolt it on after the fact. 406 407 The European Union has begun exploring this territory through its Digital 408 Markets Act and Digital Services Act, but these laws, enacted in 2022, largely 409 focus on regulating existing platforms rather than imagining new ones. In the 410 United States, efforts are more fragmented. Proposals such as the Platform 411 Accountability and Transparency Act (PATA) and state-level laws in California 412 and New York aim to increase oversight of algorithmic systems, particularly 413 where they impact youth and mental health. Still, most of these measures seek 414 to retrofit accountability onto current platforms. What we need are spaces 415 built from the ground up on different principles, where incentives align with 416 human interest rather than extractive, for-profit ends. 417 418 This could take multiple forms, like municipal platforms for local civic 419 engagement, professionally focused networks run by trade associations, and 420 educational spaces managed by public library systems. The key is diversity, 421 delivering an ecosystem of civic digital spaces that each serve specific 422 communities with transparent governance. 423 424 Of course, publicly governed platforms aren’t immune to their own risks. State 425 involvement can bring with it the threat of politicization, censorship or 426 propaganda, and this is why the governance question must be treated as 427 infrastructural, rather than simply institutional. Just as public broadcasters 428 in many democracies operate under charters that insulate them from partisan 429 interference, civic digital spaces would require independent oversight, clear 430 ethical mandates, and democratically accountable governance boards, not 431 centralized state control. The goal is not to build a digital ministry of 432 truth, but to create pluralistic public utilities: platforms built for 433 communities, governed by communities and held to standards of transparency, 434 rights protection and civic purpose. 435 436 The technical architecture of the next social web is already emerging through 437 federated and distributed protocols like ActivityPub (used by Mastodon and 438 Threads) and Bluesky’s [57]Authenticated Transfer (AT) Protocol, or atproto, (a 439 decentralised framework that allows users to move between platforms while 440 keeping their identity and social graph) as well as various blockchain-based 441 experiments, [58]like Lens and [59]Farcaster. 442 443 But protocols alone won’t save us. The email protocol is decentralized, yet 444 most email flows through a handful of corporate providers. We need to “[60] 445 rewild the internet,” as Maria Farrell and Robin Berjon mentioned in a Noema 446 essay. We need governance scaffolding, shared institutions that make 447 decentralization viable at scale. Think credit unions for the social web that 448 function as member-owned entities providing the infrastructure that individual 449 users can’t maintain alone. These could offer shared moderation services that 450 smaller instances can subscribe to, universally portable identity systems that 451 let users move between platforms without losing their history, collective 452 bargaining power for algorithm transparency and data rights, user data 453 dividends for all, not just influencers (if platforms profit from our data, we 454 should share in those profits), and algorithm choice interfaces that let users 455 select from different recommender systems. 456 457 Bluesky’s AT Protocol explicitly allows users to port identity and social 458 graphs, but it’s very early days and cross-protocol and platform portability 459 remains extremely limited, if not effectively non-existent. Bluesky also allows 460 users to choose among multiple content algorithms, an important step toward 461 user control. But these models remain largely tied to individual platforms and 462 developer communities. What’s still missing is a civic architecture that makes 463 algorithmic choice universal, portable, auditable and grounded in 464 public-interest governance rather than market dynamics alone. 465 466 Imagine being able to toggle between different ranking logics: a chronological 467 feed, where posts appear in real time; a mutuals-first algorithm that 468 privileges content from people who follow you back; a local context filter that 469 surfaces posts from your geographic region or language group; a serendipity 470 engine designed to introduce you to unfamiliar but diverse content; or even a 471 human-curated layer, like playlists or editorials built by trusted institutions 472 or communities. Many of these recommender models do exist, but they are rarely 473 user-selectable, and almost never transparent or accountable. Algorithm choice 474 shouldn’t require a hack or browser extension; it should be built into the 475 architecture as a civic right, not a hidden setting. 476 477 “What if we treated these platforms as public utilities rather than private 478 casinos?” 479 480 Algorithmic choice can also develop new hierarchies. If feeds can be curated 481 like playlists, the next influencer may not be the one creating content, but 482 editing it. Institutions, celebrities and brands will be best positioned to 483 build and promote their own recommendation systems. For individuals, the 484 incentive to do this curatorial work will likely depend on reputation, 485 relational capital or ideological investment. Unless we design these systems 486 with care, we risk reproducing old dynamics of platform power, just in a new 487 form. 488 489 Federated platforms like Mastodon and Bluesky face [61]real tensions between 490 autonomy and safety: Without centralized moderation, harmful content can 491 proliferate, while over-reliance on volunteer admins creates sustainability 492 problems at scale. These networks also risk reinforcing ideological silos, as 493 communities block or mute one another, fragmenting the very idea of a shared 494 public square. Decentralization gives users more control, but it also raises 495 difficult questions about governance, cohesion and collective responsibility — 496 questions that any humane digital future will have to answer. 497 498 But there is a possible future where a user, upon opening an app, is asked how 499 they would like to see the world on a given day. They might choose the 500 serendipity engine for unexpected connections, the focus filter for deep reads 501 or the local lens for community news. This is technically very achievable — the 502 data would be the same; the algorithms would just need to be slightly tweaked — 503 but it would require a design philosophy that treats users as citizens of a 504 shared digital system rather than cattle. While this is possible, it can feel 505 like a pipe dream. 506 507 To make algorithmic choice more than a thought experiment, we need to change 508 the incentives that govern platform design. Regulation can help, but real 509 change will come when platforms are rewarded for serving the public interest. 510 This could mean tying tax breaks or public procurement eligibility to the 511 implementation of transparent, user-controllable algorithms. It could mean 512 funding research into alternative recommender systems and making those tools 513 open-source and interoperable. Most radically, it could involve certifying 514 platforms based on civic impact, rewarding those that prioritize user autonomy 515 and trust over sheer engagement. 516 517 Digital Literacy As Public Health 518 519 Perhaps most crucially, we need to reframe digital literacy not as an 520 individual responsibility but as a collective capacity. This means moving 521 beyond spot-the-fake-news workshops to more fundamental efforts to understand 522 how algorithms shape perception and how design patterns exploit our cognitive 523 processes. 524 525 Some education systems are [62]beginning to respond, embedding digital and 526 media literacy across curricula. Researchers and educators argue that this work 527 needs to begin in early childhood and continue through secondary education as a 528 core competency. The goal is to equip students to critically examine the 529 digital environments they inhabit daily, to [63]become active participants in 530 shaping the future of digital culture rather than passive consumers. This 531 includes what some call algorithmic literacy, the ability to understand how 532 recommender systems work, how content is ranked and surfaced, and how personal 533 data is used to shape what you see — and what you don’t. 534 535 Teaching this at scale would mean treating digital literacy as public 536 infrastructure, not just a skill set for individuals, but a form of shared 537 civic defense. This would involve long-term investments in teacher training, 538 curriculum design and support for public institutions, such as libraries and 539 schools, to serve as digital literacy hubs. When we build collective capacity, 540 we begin to lay the foundations for a digital culture grounded in 541 understanding, context and care. 542 543 We also need behavioral safeguards like default privacy settings that protect 544 rather than expose, mandatory cooling-off periods for viral content 545 (deliberately slowing the spread of posts that suddenly attract high 546 engagement), algorithmic impact assessments before major platform changes and 547 public dashboards that show platform manipulation, that is, coordinated or 548 deceptive behaviors that distort how content is amplified or suppressed, in 549 real-time. If platforms are forced to disclose their engagement tactics, these 550 tactics lose power. The ambition is to make visible hugely influential systems 551 that currently operate in obscurity. 552 553 We need to build new digital spaces grounded in different principles, but this 554 isn’t an either-or proposition. We also must reckon with the scale and 555 entrenchment of existing platforms that still structure much of public life. 556 Reforming them matters too. Systemic safeguards may not address the core 557 incentives that inform platform design, but they can mitigate harm in the short 558 term. The work, then, is to constrain the damage of the current system while 559 constructing better ones in parallel, to contain what we have, even as we 560 create what we need. 561 562 The choice isn’t between technological determinism and Luddite retreat; it’s 563 about constructing alternatives that learn from what made major platforms 564 usable and compelling while rejecting the extractive mechanics that turned 565 those features into tools for exploitation. This won’t happen through 566 individual choice, though choice helps; it also won’t happen through 567 regulation, though regulation can really help. It will require our collective 568 imagination to envision and build systems focused on serving human flourishing 569 rather than harvesting human attention. 570 571 Social media as we know it is dying, but we’re not condemned to its ruins. We 572 are capable of building better — smaller, slower, more intentional, more 573 accountable — spaces for digital interaction, spaces where the metrics that 574 matter aren’t engagement and growth but understanding and connection, where 575 algorithms serve the community rather than strip-mining it. 576 577 The last days of social media might be the first days of something more human: 578 a web that remembers why we came online in the first place — not to be 579 harvested but to be heard, not to go viral but to find our people, not to 580 scroll but to connect. We built these systems, and we can certainly build 581 better ones. The question is whether we will do this or whether we will 582 continue to drown. 583 584 [64]Enjoy the read? 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