Gripen

It was its own multitude of the way Offered the same to democracies and their way Perfect proportional pitch The seventh dream of flight Zero to the Heavens Marked up as a single, steerable species Flight in water and simile Air attacks from the West- Intermaiden to the transient This will take North and move sideways Proportional dream to London A mace for those who know it A promise to keep at the end of the day Flowers to the rose and operational moon Solemn year. All rise to the reel Our neighbours aplenty This is l’amour to the best of nerds- Who speak between freedom in waves Your reality dream, because, really, Software updates included- In peace and without differences Surely operating to your years ahead Nothing but an arrow, And yours is in flight

Erin Shore

She stays on the dock with St. Peter’s dream Marching for Jews and for Italian fear Long away the Constitution That heard her faint in fear There is the other, the void unfrozen and alone All things aseen to the first Major rise And leading his horses on Why to make trouble for this new grow of men In solace and lonely she gets by Appeasing the woman to see her redemption It is August and no more unmooned To feather this witness and to borrow untuned Seeing ladder after sun and good feel With a rising touch deep, she is magic and listen For the Lord to have learned of her keep

A mayhem of good and a simple attraction The servant was errant but good In stride growing freely And to Andrew her son, This is solemn and offering true And often supposing, the web of St. Winter The ‘greements of Nathan in verse A spirit of water, and to make way amend A castle for glory, for tune If I miss a second, her year will be unmine At Providence and peaceful re-une To currents in the water And lilies redoubt There is prayer for these soles at the heath And maybe Len Erin will run to the forest Thinking hours and women, and wreath

Peace on an Island

Better Earth is here It might be tight for dragonsworth, But our valley is known for a stillness A peace of goodwill- and of love and of Schengen When duty must call, let us rapture our men, And the captives call, Let us in! A forewill of entainment, and what goes around, But our bodies laid bare from the win And this in fact to our fascists who dream of our ways- A thousand even and the tales of law Kept bright for regret of all violence Keeping water to hold it- Our storm And these are the puzzles of our Lord Keeping time for the system, and plain in view Why the troubadour is here and ours- Defeating all fascism; and all oil And every scream from a woman who knows, of the politics of why of the day did we feel needing fight- But the peace of our neighbour- Let him in Let his thirst be our wail Til the fascism is known, is called, is identified Identical sins upon the main chapter We sing for the valley, for remission- For reason And what Türkiye wants in return, is this- a line to the unfelled, the devil that right- Of insufficing calls to remiss And to unexplore and divide Making discredit our very own country Inflamed by disculture our own but our valley This ransom, this time of before In themes of unseen As a witness introspect and precluded Acts to follow our future on hold It is rain, like this- this filling our deep- And our hold on the candor When irving is worship it is thus Time, fascism, and esteem Holding the Spirit blue Setting sail to the dark Knowing without knowledge But death Commending our way- Such as that is the law And the beat of a heart hears the news Letting oil become promise And taking fiber to just know Long gone is the courage And that fascism cascades to the morrow A depravity win And the suing of men For lasts of the maple were here In this peace- our heaven-made upon this bench The Crown of the Holiest year Making such sure is our obvient day To home, and our reckoning march- For Heaven

Die „Rapid-Viertelstunde“ ist das traditionsreiche Ritual der Fußballfans des Sportklub Rapid Wien oder einfach für “die Rapid”, wie man in Wien sagt. Die Fans klatschen die letzten 15 Spielminuten rhythmisch ein und versuchen ihre Mannschaft nach vorne zu treiben. Dieses Ritual entstand vermutlich schon zwischen 1903 und 1912 am Rudolfsheimer Platz, wo Rapid damals gespielt hat. Vielleicht gab die Turmuhr der nahegelegenen Kirche den Takt vor. Der Legende nach sind die Rapidler in dieser Schlussphase immer besonders gefährlich – oft fällt noch ein entscheidendes Tor, ganze Spiele kippen plötzlich. Mit dem Umzug 1912 auf die Pfarrwiese wandert dieses Ritual mit und ist bis heute fest in der Rapid-Kultur verankert. Meine Verbindung zur “Rapid-Viertelstunde” ist nicht fan-, sondern berufsbedingt. Es ist die Zeit, als Pressing noch „Forechecking“ heißt und der große Andreas „Andy“ Marek als Stadionsprecher und Fanservice-Leiter die grün-weiße Welt prägt. Für ein neues Radioformat pendle ich Ende der 2000er deshalb wöchentlich zu den Büroräumlichkeiten des ehrwürdigen Hanappi-Stadions in Wien-Hütteldorf. Mit seiner unverwechselbaren Stimme und seinem Entertainment-Talent führt Andy Marek als Moderator durch die Sendung mit dem Namen „Die Rapid-Viertelstunde“, genau. Er berichtet seinerzeit recht aufgeweckt über das Geschehen der letzten Woche und gibt einen Ausblick auf den nächsten Spieltag in der österreichischen Bundesliga oder auf die kommenden Auftritte im internationalen Geschäft. Das Highlight jeder Produktion ist dann der Gang in die Katakomben des Stadions: Interviews mit Spielern und dem Trainer, die wir später mit ihren Statements in die Sendung schneiden. Unvergesslich bleibt Rapid-Fußballgott Steffen Hofmann – direkt aus der Dusche, nur mit einem Handtuch um die Hüfte, oder auch der damalige Trainer und heutige Sportdirektor des ÖFB, Peter Schöttel – auch ein Großer, fast zwei Meter. Ich bin mit Mikrofon und Mini-Disc-Player mittendrin und halte alles radiotauglich fest. Doch Moderation ist nur eines der vielen Talente von Andy Marek. Ein Geheimtipp auf YouTube ist „Andy Marek – Top Secret“ – stimmlich und pantomimisch top. Bis heute bleibt der gebürtige Waldviertler seiner Leidenschaft für Bühnen, Stimmen und Menschen treu. Gemeinsam mit den Niederösterreichischen Nachrichten ruft er „NÖN sucht das größte Talent“ ins Leben. Irgendwann endet dann meine Zeit beim Radio, auch „Die Rapid-Viertelstunde“ wandert vom Radio ins Fernsehen und läuft immer noch im Programm des Wiener Senders W24. Nach gesundheitlichen Problemen beendet Andy Marek Anfang 2020 seine Tätigkeit bei Rapid, mitten in turbulenten Vereinszeiten, die bis heute andauern. Doch Rapid findet eine typisch österreichische Lösung: Sein Sohn Lukas übernimmt als Stadionsprecher und Moderator die Sendung. Eine Rolle bleibt aber untrennbar mit Andy Marek verbunden – die des Stadionsprechers der österreichischen Nationalmannschaft. Wenn sein „Tooor für Österreich“ durch das Ernst-Happel-Stadion hallt, fühlt sich das Publikum sofort zuhause. Und für ihn persönlich ist es sicher ein Erfolgserlebnis, die WM 2026 mit der Nationalmannschaft direkt mitzuerleben, auch weil er nicht mehr bei allen Rapid-Heimspielen am Wochenende dabei ist. Die Leidenschaft Fußball lässt einen nicht los, oder wie es Tommi Schmitt im Podcast “Gemischtes Hack” ausdrückt: „Ich merke immer sehr, wie wichtig Fußball für mein Seelenheil ist. Das klingt sehr groß, aber das ist wirklich so. Ich verstehe nach wie vor nicht, wie Menschen so durchs Leben kommen, ohne dass samstags oder am Wochenende dieses Highlight stattfindet.“

© Ligaportal

The quantum stabilizers screamed like gutted animals as the dreadnought’s hull peeled back—revealing the thing squirming in the reactor core. “Oh hell no,” growled Kovacs, slamming fresh rounds into his plasma carbine, “we didn’t sign up for Lovecraftian shit.” The AI’s voice crackled: “Containment failure imminent.” Brilliant. A rookie grabbed my arm, his pupils blown wide. “Is that… singing?” The melody hit—chromatic, wrong, peeling sanity like rotten fruit. My HUD flashed crimson: 47 seconds to mandatory neural quarantine. Kovacs racked the slide. “Time to go loud.” The walls started bleeding. Typical Tuesday.

#Scratch

Stay entertained thanks to our Weekly Tracker giving you next week's Anticipated Movies & Shows, Most Watched & Returning Favorites, and Shows Changes & Popular Trailers.

Anticipated Movies

• Merv
• Silent Night, Deadly Night
• Dust Bunny
• Fackham Hall
• Ella McCay
• Atropia
• ☆ MadS

Anticipated Shows

• Simon Cowell: The Next Act
• ☆ Man Vs Baby
• City of Shadows
• Blue Moon
• Taylor Swift | The Eras Tour | The End of an Era

Returing Favorites

• 90 Day Fiancé: Before the 90 Days — Season 8
• Record of Ragnarok — Season 3
• ☆ Percy Jackson and the Olympians — Season 2
• Tomb Raider: The Legend of Lara Croft — Season 2
• Home for Christmas — Season 3
• The Daily Life of the Immortal King — Season 5

Trending Shows Status Changes

• Sean Combs: The Reckoning — Returning Series → Ended
• The Manipulated — Returning Series → Ended

Most Watched Movies this Week

• new TRON: Ares
• +6 Predator: Badlands
• = Bugonia
• -3 The Family Plan 2
• -3 One Battle After Another
• new Troll 2
• -3 Frankenstein
• new Zootopia 2
• new Home Alone
• -5 Roofman

Most Watched Shows this Week

• = Stranger Things
• = Pluribus
• +1 Landman
• +1 IT: Welcome to Derry
• +2 Tracker
• +3 Mayor of Kingstown
• +1 The Last Frontier
• -5 Tulsa King
• -3 South Park
• new The Chair Company

Popular Trailers

• Final Season Teaser Trailer — The Boys
• Heart — Hamnet
• you think it's safe here? cute... — The Housemaid
• Now Playing in Theaters Everywhere — Rental Family
• MISSION: 47 – Season 3 — SPY x FAMILY
• Hottest Ticket — Avatar: Fire and Ash
• Join SpongeBob and friends on a swashbuckling quest. — The SpongeBob Movie: Search for SquarePants
• Just another normal day for Jack Black... — Anaconda
• Official Trailer [Subtitled] — The Great Flood
• Video — Ella McCay

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Hi, I'm Kevin 👋. I make apps and I love watching movies and TV shows. If you like what I'm doing, you can buy one of my apps, download and subscribe to Rippple for Trakt or just buy me a ko-fi ☕️.

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Nuestro mundo está lleno de incógnitas, de desafíos. Los ciudadanos nos sentimos inermes ante el flujo de información, de contradicciones. Los retos del devenir son impactantes. ¿Qué podemos hacer? ¿Mirar hacia otro lado? Para cubrir una larga distancia hay que comenzar con el primer paso. La mejor orientación la proporcionan los conceptos más simples. Si no lo olvidamos, la mente se aclara y la complejidad se va desvaneciendo. Entonces podremos mirar el estado del mundo de hoy. Conozca nuestras perspectivas sobre los desafíos del momento actual.

al avanzar la noche le pareció que había dejado algo en el tintero / pero era la angustia devorada por la euforia que habló y habló hasta el amanecer mientras el escritor garabateaba palabras inútiles

In Summary: * Between the early afternoon basketball game and the night football game, the wife found a number of “honey do” projects to fill those “empty” hours for me. One of those projects was moving the washing machine in the garage. I was happily surprised at how easy it was for me to move that machine. I used to move it regularly, shoving it back into its proper position after it vibrated its way away from the wall. But I stopped doing that months (years?) ago when arthritis weakened my back and made it impossibly painful to shove that machine around. However, this afternoon I moved it easily, just like I used to. Huh. Figure that!

Prayers, etc.: * My daily prayers

Health Metrics: * bw= 217.82 lbs. * bp= 146/88 (65)

Exercise: * kegel pelvic floor exercise, half squats, calf raises, wall push-ups

Diet: * 08:00 – nacho chips w. meat & cheese sauce, spiced apple slices * 12:30 – 1 ham & scrambled eggs breakfast taco * 16:00 – 1 fresh apple

Activities, Chores, etc.: * 02:30 – up with some pretty profound insomnia, surfing the socials, praying * 07:55 – bank accounts activity monitored * 12:15 – listening to the pregame show ahead of the Louisville Cardinals vs IU Hoosiers men's basketball team, and I'll stay with this radio station for the call of the game, and for post game coverage. * 18:00 – listening to pregame coverage ahead of tonight's Big Ten Conference Championship Game which has the IU Hoosiers playing the Ohio State Buckeyes. As with the basketball game earlier this afternoon, I'll stay on this radio station for the call of the game, and for the post game coverage. * 20:45 – Halftime finds Ohio State leading IU by a score of 10 to 6. I do intend to stay with the game but as we approach my usual bedtime, I sense the brain starting to get fuzzy, so I'll post this now before I get ridiculous.

Chess: * 16:20 – moved in all pending CC games

When Match Group CEO Spencer Rascoff announced Tinder's newest feature in November 2025, the pitch was seductive: an AI assistant called Chemistry that would get to know you through questions and, crucially, by analysing your camera roll. The promise was better matches through deeper personalisation. The reality was something far more invasive.

Tinder, suffering through nine consecutive quarters of declining paid subscribers, positioned Chemistry as a “major pillar” of its 2026 product experience. The feature launched first in New Zealand and Australia, two testing grounds far enough from regulatory scrutiny to gauge user acceptance. What Rascoff didn't emphasise was the extraordinary trade users would make: handing over perhaps the most intimate repository of personal data on their devices in exchange for algorithmic matchmaking.

The camera roll represents a unique threat surface. Unlike profile photos carefully curated for public consumption, camera rolls contain unfiltered reality. Screenshots of medical prescriptions. Photos of children. Images from inside homes revealing addresses. Pictures of credit cards, passports, and other identity documents. Intimate moments never meant for algorithmic eyes. When users grant an app permission to access their camera roll, they're not just sharing data, they're surrendering context, relationships, and vulnerability.

This development arrives at a precarious moment for dating app privacy. Mozilla Foundation's 2024 review of 25 popular dating apps found that 22 earned its “Privacy Not Included” warning label, a deterioration from its 2021 assessment. The research revealed that 80 per cent of dating apps may share or sell user information for advertising purposes, whilst 52 per cent had experienced a data breach, leak, or hack in the past three years. Dating apps, Mozilla concluded, had become worse for privacy than nearly any other technology category.

The question now facing millions of users, regulators, and technologists is stark: can AI-powered personalisation in dating apps ever be reconciled with meaningful privacy protections, or has the industry's data hunger made surveillance an inescapable feature of modern romance?

The Anatomy of Camera Roll Analysis

To understand the privacy implications, we must first examine what AI systems can extract from camera roll images. When Tinder's Chemistry feature accesses your photos, the AI doesn't simply count how many pictures feature hiking or concerts. Modern computer vision systems employ sophisticated neural networks capable of extraordinarily granular analysis.

These systems can identify faces and match them across images, creating social graphs of who appears in your life and how frequently. They can read text in screenshots, extracting everything from bank balances to private messages. They can geolocate photos by analysing visual landmarks, shadows, and metadata. They can infer socioeconomic status from clothing, home furnishings, and travel destinations. They can detect brand preferences, political affiliations, health conditions, and religious practices.

The technical capability extends further. Facial analysis algorithms can assess emotional states across images, building psychological profiles based on when and where you appear happy, stressed, or contemplative. Pattern recognition can identify routines, favourite locations, and social circles. Even images you've deleted may persist in cloud backups or were already transmitted before deletion.

Match Group emphasises that Chemistry will only access camera rolls “with permission”, but this framing obscures the power dynamic at play. When a platform experiencing subscriber decline positions a feature as essential for competitive matching, and when the broader dating ecosystem moves toward AI personalisation, individual consent becomes functionally coercive. Users who decline may find themselves algorithmically disadvantaged, receiving fewer matches or lower-quality recommendations. The “choice” to share becomes illusory.

The technical architecture compounds these concerns. Whilst Tinder has not publicly detailed Chemistry's implementation, the industry standard remains cloud-based processing. This means camera roll images, or features extracted from them, likely transmit to Match Group servers for analysis. Once there, they enter a murky ecosystem of data retention, sharing, and potential monetisation that privacy policies describe in deliberately vague language.

A Catalogue of Harms

The theoretical risks of camera roll access become visceral when examined through the lens of documented incidents. The dating app industry's track record provides a grim preview of what can go wrong.

In 2023, security researchers discovered that five dating apps, BDSM People, Chica, Pink, Brish, and Translove, had exposed over 1.5 million private and sexually explicit images in cloud storage buckets without password protection. The images belonged to approximately 900,000 users who believed their intimate photos were secured. The breach created immediate blackmail and extortion risks. For users in countries where homosexuality or non-traditional relationships carry legal penalties, the exposure represented a potential death sentence.

The Tea dating app, marketed as a safety-focused platform for women to anonymously review men, suffered a data breach that exposed tens of thousands of user pictures and personal information. The incident spawned a class-action lawsuit and resulted in Apple removing the app from its store. The irony was brutal: an app promising safety became a vector for harm.

Grindr's 2018 revelation that it had shared users' HIV status with third-party analytics firms demonstrated how “metadata” can carry devastating consequences. The dating app for LGBTQ users had transmitted highly sensitive health information without explicit consent, putting users at risk of discrimination, stigmatisation, and in some jurisdictions, criminal prosecution.

Bumble faced a £32 million settlement in 2024 over allegations it collected biometric data from facial recognition in profile photos without proper user consent, violating privacy regulations. The case highlighted how even seemingly benign features, identity verification through selfies, can create massive biometric databases with serious privacy implications.

These incidents share common threads: inadequate security protecting highly sensitive data, consent processes that failed to convey actual risks, and downstream harms extending far beyond mere privacy violations into physical safety, legal jeopardy, and psychological trauma.

Camera roll access amplifies every one of these risks. A breach exposing profile photos is catastrophic; a breach exposing unfiltered camera rolls would be civilisational. The images contain not just users' own intimacy but collateral surveillance of everyone who appears in their photos: friends, family, colleagues, children. The blast radius of a camera roll breach extends across entire social networks.

The Regulatory Maze

Privacy regulations have struggled to keep pace with dating apps' data practices, let alone AI-powered camera roll analysis. The patchwork of laws creates uneven protections that companies can exploit through jurisdiction shopping.

The European Union's General Data Protection Regulation (GDPR) establishes the strictest requirements. Under GDPR, consent must be freely given, specific, informed, and unambiguous. For camera roll access, this means apps must clearly explain what they'll analyse, how they'll use the results, where the data goes, and for how long it's retained. Consent cannot be bundled; users must be able to refuse camera roll access whilst still using the app's core functions.

GDPR Article 9 designates certain categories as “special” personal data requiring extra protection: racial or ethnic origin, political opinions, religious beliefs, sexual orientation, and biometric data for identification purposes. Dating apps routinely collect most of these categories, and camera roll analysis can reveal all of them. Processing special category data requires explicit consent and legitimate purpose, not merely the desire for better recommendations.

The regulation has teeth. Norway's Data Protection Authority fined Grindr €9.63 million in 2021 for sharing user data with advertising partners without valid consent. The authority found that Grindr's privacy policy was insufficiently specific and that requiring users to accept data sharing to use the app invalidated consent. The decision, supported by noyb (None of Your Business), the European privacy organisation founded by privacy advocate Max Schrems, set an important precedent: dating apps cannot make basic service access conditional on accepting invasive data practices.

Ireland's Data Protection Commission launched a formal investigation into Tinder's data processing practices in 2020, examining transparency and compliance with data subject rights requests. The probe followed a journalist's GDPR data request that returned 800 pages including her complete swipe history, all matches, Instagram photos, Facebook likes, and precise physical locations whenever she was using the app. The disclosure revealed surveillance far exceeding what Tinder's privacy policy suggested.

In the United States, Illinois' Biometric Information Privacy Act (BIPA) has emerged as the most significant privacy protection. Passed unanimously in 2008, BIPA prohibits collecting biometric data, including facial geometry, without written informed consent specifying what's being collected, why, and for how long. Violations carry statutory damages of $1,000 per negligent violation and $5,000 per intentional or reckless violation.

BIPA's private right of action has spawned numerous lawsuits against dating apps. Match Group properties including Tinder and OkCupid, along with Bumble and Hinge, have faced allegations that their identity verification features, which analyse selfie video to extract facial geometry, violate BIPA by collecting biometric data without proper consent. The cases highlight a critical gap: features marketed as safety measures (preventing catfishing) create enormous biometric databases subject to breach, abuse, and unauthorised surveillance.

California's Consumer Privacy Act (CCPA) provides broader privacy rights but treats biometric information the same as other personal data. The act requires disclosure of data collection, enables deletion requests, and permits opting out of data sales, but its private right of action is limited to data breaches, not ongoing privacy violations.

This regulatory fragmentation creates perverse incentives. Apps can beta test invasive features in jurisdictions with weak privacy laws, Australia and New Zealand for Tinder's Chemistry feature, before expanding to more regulated markets. They can structure corporate entities to fall under lenient data protection authorities' oversight. They can craft privacy policies that technically comply with regulations whilst remaining functionally incomprehensible to users.

The Promise and Reality of Technical Safeguards

The privacy disaster unfolding in dating apps isn't technologically inevitable. Robust technical safeguards exist that could enable AI personalisation whilst dramatically reducing privacy risks. The problem is economic incentive, not technical capability.

On-device processing represents the gold standard for privacy-preserving AI. Rather than transmitting camera roll images or extracted features to company servers, the AI model runs locally on users' devices. Analysis happens entirely on the phone, and only high-level preferences or match criteria, not raw data, transmit to the service. Apple's Photos app demonstrates this approach, analysing faces, objects, and scenes entirely on-device without Apple ever accessing the images.

For dating apps, on-device processing could work like this: the AI analyses camera roll images locally, identifying interests, activities, and preferences. It generates an encrypted interest profile vector, essentially a mathematical representation of preferences, that uploads to the matching service. The matching algorithm compares vectors between users without accessing the underlying images. If two users' vectors indicate compatible interests, they match, but the dating app never sees that User A's profile came from hiking photos whilst User B's came from rock climbing images.

The technical challenges are real but surmountable. On-device AI requires efficient models that can run on smartphone hardware without excessive battery drain. Apple's neural engine and Google's tensor processing units provide dedicated hardware for exactly this purpose. The models must be sophisticated enough to extract meaningful signals from diverse images whilst remaining compact enough for mobile deployment.

Federated learning offers another privacy-preserving approach. Instead of centralising user data, the AI model trains across users' devices without raw data ever leaving those devices. Each device trains a local model on the user's camera roll, then uploads only the model updates, not the data itself, to a central server. The server aggregates updates from many users to improve the global model, which redistributes to all devices. Individual training data remains private.

Google has deployed federated learning for features like Smart Text Selection and keyboard predictions. The approach could enable dating apps to improve matching algorithms based on collective patterns whilst protecting individual privacy. If thousands of users' local models learn that certain photo characteristics correlate with successful matches, the global model captures this pattern without any central database of camera roll images.

Differential privacy provides mathematical guarantees against reidentification. The technique adds carefully calibrated “noise” to data or model outputs, ensuring that learning about aggregate patterns doesn't reveal individual information. Dating apps could use differential privacy to learn that users interested in outdoor activities often match successfully, without being able to determine whether any specific user's camera roll contains hiking photos.

End-to-end encryption (E2EE) should be table stakes for any intimate communication platform, yet many dating apps still transmit messages without E2EE. Signal's protocol, widely regarded as the gold standard, ensures that only conversation participants can read messages, not the service provider. Dating apps could implement E2EE for messages whilst still enabling AI analysis of user-generated content through on-device processing before encryption.

Homomorphic encryption, whilst computationally expensive, enables computation on encrypted data. A dating app could receive encrypted camera roll features, perform matching calculations on the encrypted data, and return encrypted results, all without ever decrypting the actual features. The technology remains mostly theoretical for consumer applications due to performance constraints, but it represents the ultimate technical privacy safeguard.

The critical question is: if these technologies exist, why aren't dating apps using them?

The answer is uncomfortable. On-device processing prevents data collection that feeds advertising and analytics platforms. Federated learning can't create the detailed user profiles that drive targeted marketing. Differential privacy's noise prevents the kind of granular personalisation that engagement metrics optimise for. E2EE blocks the content moderation and “safety” features that companies use to justify broad data access.

Current dating app business models depend on data extraction. Match Group's portfolio of 45 apps shares data across the ecosystem and with the parent company for advertising purposes. When Bumble faced scrutiny over sharing data with OpenAI, the questions centred on transparency, not whether data sharing should occur at all. The entire infrastructure assumes that user data is an asset to monetise, not a liability to minimise.

Technical safeguards exist to flip this model. Apple's Private Click Measurement demonstrates that advertising attribution can work with strong privacy protections. Signal proves that E2EE messaging can scale. Google's federated learning shows that model improvement doesn't require centralised data collection. What's missing is regulatory pressure sufficient to overcome the economic incentive to collect everything.

Consent Theatre

Perhaps no aspect of dating app privacy failures is more frustrating than consent mechanisms that technically comply with regulations whilst utterly failing to achieve meaningful informed consent.

When Tinder prompts users to grant camera roll access for Chemistry, the flow likely resembles standard iOS patterns: the app requests the permission, the operating system displays a dialogue box, and the user taps “Allow” or “Don't Allow”. This interaction technically satisfies many regulatory requirements but provides no meaningful understanding of the consequences.

The Electronic Frontier Foundation, through director of cybersecurity Eva Galperin's work on intimate partner surveillance, has documented how “consent” can be coerced or manufactured in contexts with power imbalances. Whilst Galperin's focus has been stalkerware, domestic abuse monitoring software marketed to partners and parents, the dynamics apply to dating apps as well.

Consider the user experience: you've joined Tinder hoping to find dates or relationships. The app announces Chemistry, framing it as revolutionary technology that will transform your matching success. It suggests that other users are adopting it, implying you'll be disadvantaged if you don't. The permission dialogue appears, asking simply whether Tinder can access your photos. You have seconds to decide.

What information do you have to make this choice? The privacy policy, a 15,000-word legal document, is inaccessible at the moment of decision. The request doesn't specify which photos will be analysed, what features will be extracted, where the data will be stored, who might access it, how long it will be retained, whether you can delete it, or what happens if there's a breach. You don't know if the analysis is local or cloud-based. You don't know if extracted features will train AI models or be shared with partners.

You see a dialogue box asking permission to access photos. Nothing more.

This isn't informed consent. It's security theatre's evil twin: consent theatre.

Genuine informed consent for camera roll access would require:

Granular Control: Users should specify which photos the app can access, not grant blanket library permission. iOS's photo picker API enables this, allowing users to select specific images. Dating apps requesting full library access when limited selection suffices should raise immediate red flags.

Temporal Limits: Permissions should expire. Camera roll access granted in February shouldn't persist indefinitely. Users should periodically reconfirm, ideally every 30 to 90 days, with clear statistics about what was accessed.

Access Logs: Complete transparency about what was analysed. Every time the app accesses the camera roll, users should receive notification and be able to view exactly which images were processed and what was extracted.

Processing Clarity: Clear, specific explanation of whether analysis is on-device or cloud-based. If cloud-based, exactly what data transmits, how it's encrypted, where it's stored, and when it's deleted.

Purpose Limitation: Explicit commitments that camera roll data will only be used for the stated purpose, matching personalisation, and never for advertising, analytics, training general AI models, or sharing with third parties.

Opt-Out Parity: Crucial assurance that declining camera roll access won't result in algorithmic penalty. Users who don't share this data should receive equivalent match quality based on other signals.

Revocation: Simple, immediate ability to revoke permission and have all collected data deleted, not just anonymised or de-identified, but completely purged from all systems.

Current consent mechanisms provide essentially none of this. They satisfy legal minimums whilst ensuring users remain ignorant of the actual privacy trade.

GDPR's requirement that consent be “freely given” should prohibit making app functionality contingent on accepting invasive data practices, yet the line between core functionality and optional features remains contested. Is AI personalisation a core feature or an enhancement? Can apps argue that users who decline camera roll access can still use the service, just with degraded matching quality?

Regulatory guidance remains vague. The EU's Article 29 Working Party guidelines state that consent isn't free if users experience detriment for refusing, but “detriment” is undefined. Receiving fewer or lower-quality matches might constitute detriment, or might be framed as natural consequence of providing less information.

The burden shouldn't fall on users to navigate these ambiguities. Privacy-by-default should be the presumption, with enhanced data collection requiring clear, specific, revocable opt-in. The current model inverts this: maximal data collection is default, and opting out requires navigating labyrinthine settings if it's possible at all.

Transparency Failures

Dating apps' transparency problems extend beyond consent to encompass every aspect of how they handle data. Unlike social media platforms or even Uber, which publishes safety transparency reports, no major dating app publishes meaningful transparency documentation.

This absence is conspicuous and deliberate. What transparency would reveal would be uncomfortable:

Data Retention: How long does Tinder keep your camera roll data after you delete the app? After you delete your account? Privacy policies rarely specify retention periods, using vague language like “as long as necessary” or “in accordance with legal requirements”. Users deserve specific timeframes: 30 days, 90 days, one year.

Access Logs: Who within the company can access user data? For what purposes? With what oversight? Dating apps employ thousands of people across engineering, customer support, trust and safety, and analytics teams. Privacy policies rarely explain internal access controls.

Third-Party Sharing: The full list of partners receiving user data remains obscure. Privacy policies mention “service providers” and “business partners” without naming them or specifying exactly what data each receives. Mozilla's research found that tracing the full data pipeline from dating apps to end recipients was nearly impossible due to deliberately opaque disclosure.

AI Training: Whether user data trains AI models, and if so, how users' information might surface in model outputs, receives minimal explanation. As Bumble faced criticism over sharing data with OpenAI, the fundamental question was not just whether sharing occurred but whether users understood their photos might help train large language models.

Breach Notifications: When security incidents occur, apps have varied disclosure standards. Some notify affected users promptly with detailed incident descriptions. Others delay notification, provide minimal detail, or emphasise that “no evidence of misuse” was found rather than acknowledging the exposure. Given that 52 per cent of dating apps have experienced breaches in the past three years, transparency here is critical.

Government Requests: How frequently do law enforcement and intelligence agencies request user data? What percentage of requests do apps comply with? What data gets shared? Tech companies publish transparency reports detailing government demands; dating apps don't.

This opacity isn't accidental. Transparency would reveal practices users would find objectionable, enabling informed choice. The business model depends on information asymmetry.

Mozilla Foundation's Privacy Not Included methodology provides a template for what transparency should look like. The organisation evaluates products against five minimum security standards: encryption, automatic security updates, strong password requirements, vulnerability management, and accessible privacy policies. For dating apps, 88 per cent failed to meet these basic criteria.

The absence of transparency creates accountability vacuums. When users don't know what data is collected, how it's used, or who it's shared with, they cannot assess risks or make informed choices. When regulators lack visibility into data practices, enforcement becomes reactive rather than proactive. When researchers cannot examine systems, identifying harms requires waiting for breaches or whistleblowers.

Civil society organisations have attempted to fill this gap. The Electronic Frontier Foundation's dating app privacy guidance recommends users create separate email accounts, use unique passwords, limit personal information sharing, and regularly audit privacy settings. Whilst valuable, this advice shifts responsibility to users who lack power to compel genuine transparency.

Real transparency would be transformative. Imagine dating apps publishing quarterly reports detailing: number of users, data collection categories, retention periods, third-party sharing arrangements, breach incidents, government requests, AI model training practices, and independent privacy audits. Such disclosure would enable meaningful comparison between platforms, inform regulatory oversight, and create competitive pressure for privacy protection.

The question is whether transparency will come voluntarily or require regulatory mandate. Given the industry's trajectory, the answer seems clear.

Downstream Harms Beyond Privacy

Camera roll surveillance in dating apps creates harms extending far beyond traditional privacy violations. These downstream effects often remain invisible until catastrophic incidents bring them into focus.

Intimate Partner Violence: Eva Galperin's work on stalkerware demonstrates how technology enables coercive control. Dating apps with camera roll access create new vectors for abuse. An abusive partner who initially met the victim on a dating app might demand access to the victim's account to “prove” fidelity. With camera roll access granted, the abuser can monitor the victim's movements, relationships, and activities. The victim may not even realise this surveillance is occurring. Apps should implement account security measures detecting unusual access patterns and provide resources for intimate partner violence survivors, but few do.

Discrimination: AI systems trained on biased data perpetuate and amplify discrimination. Camera roll analysis could infer protected characteristics like race, religion, or sexual orientation, then use these for matching in ways that violate anti-discrimination laws. Worse, the discrimination is invisible. Users receiving fewer matches have no way to know whether algorithms downranked them based on inferred characteristics. The opacity of recommendation systems makes proving discrimination nearly impossible.

Surveillance Capitalism Acceleration: Dating apps represent the most intimate frontier of surveillance capitalism. Advertising technology companies have long sought to categorise people's deepest desires and vulnerabilities. Camera rolls provide unprecedented access to this information. The possibility that dating app data feeds advertising systems creates a panopticon where looking for love means exposing your entire life to marketing manipulation.

Social Graph Exposure: Your camera roll doesn't just reveal your information but that of everyone who appears in your photos. Friends, family, colleagues, and strangers captured in backgrounds become involuntary subjects of AI analysis. They never consented to dating app surveillance, yet their faces, locations, and contexts feed recommendation algorithms. This collateral data collection lacks even the pretence of consent.

Psychological Manipulation: AI personalisation optimises for engagement, not wellbeing. Systems that learn what keeps users swiping, returning, and subscribing have incentive to manipulate rather than serve. Camera roll access enables psychological profiling sophisticated enough to identify and exploit vulnerabilities. Someone whose photos suggest loneliness might receive matches designed to generate hope then disappointment, maximising time on platform.

Blackmail and Extortion: Perhaps the most visceral harm is exploitation by malicious actors. Dating apps attract scammers and predators. Camera roll access, even if intended for AI personalisation, creates breach risks that expose intimate content. The 1.5 million sexually explicit images exposed by inadequate security at BDSM People, Chica, Pink, Brish, and Translove demonstrate this isn't theoretical. For many users, such exposure represents catastrophic harm: employment loss, family rejection, legal jeopardy, even physical danger.

These downstream harms share a common feature: they're difficult to remedy after the fact. Once camera roll data is collected, the privacy violation is permanent. Once AI models train on your images, that information persists in model weights. Once data breaches expose intimate photos, no amount of notification or credit monitoring repairs the damage. Prevention is the only viable strategy, yet dating apps' current trajectory moves toward greater data collection, not less.

Demanding Better Systems

Reconciling AI personalisation with genuine privacy protection in dating apps requires systemic change across technology, regulation, and business models.

Regulatory Intervention: Current privacy laws, GDPR, CCPA, BIPA, provide frameworks but lack enforcement mechanisms commensurate with the harms. What's needed are:

Dating app-specific regulations recognising the unique privacy sensitivities and power dynamics of platforms facilitating intimate relationships. Blanket consent for broad data collection should be prohibited. Mandatory on-device processing for camera roll analysis, with cloud processing permitted only with specific opt-in and complete transparency. Standardised transparency reporting requirements, modelled on social media content moderation disclosures. Minimum security standards with regular independent audits. Private rights of action enabling users harmed by privacy violations to seek remedy without requiring class action or regulatory intervention. Significant penalties for violations, sufficient to change business model calculations.

The European Union's AI Act and Digital Services Act provide templates. The AI Act's risk-based approach could classify dating app recommendation systems using camera roll data as high-risk, triggering conformity assessment, documentation, and human oversight requirements. The Digital Services Act's transparency obligations could extend to requiring algorithmic disclosure.

Technical Mandates: Regulations should require specific technical safeguards. On-device processing for camera roll analysis must be the default, with exceptions requiring demonstrated necessity and user opt-in. End-to-end encryption should be mandatory for all intimate communications. Differential privacy should be required for any aggregate data analysis. Regular independent security audits should be public. Data minimisation should be enforced: apps must collect only data demonstrably necessary for specified purposes and delete it when that purpose ends.

Business Model Evolution: The fundamental problem is that dating apps monetise user data rather than service quality. Match Group's portfolio strategy depends on network effects and data sharing across properties. This creates incentive to maximise data collection regardless of necessity.

Alternative models exist. Subscription-based services with privacy guarantees could compete on trust rather than algorithmic engagement. Apps could adopt cooperative or non-profit structures removing profit incentive to exploit user data. Open-source matching algorithms would enable transparency and independent verification. Federated systems where users control their own data whilst still participating in matching networks could preserve privacy whilst enabling AI personalisation.

User Empowerment: Technical and regulatory changes must be complemented by user education and tools. Privacy settings should be accessible and clearly explained. Data dashboards should show exactly what's collected, how it's used, and enable granular control. Regular privacy check-ups should prompt users to review and update permissions. Export functionality should enable users to retrieve all their data in usable formats. Deletion should be complete and immediate, not delayed or partial.

Industry Standards: Self-regulation has failed dating apps, but industry coordination could still play a role. Standards bodies could develop certification programmes for privacy-preserving dating apps, similar to organic food labels. Apps meeting stringent criteria, on-device processing, E2EE, no data sharing, minimal retention, regular audits, could receive certification enabling users to make informed choices. Market pressure from privacy-conscious users might drive adoption more effectively than regulation alone.

Research Access: Independent researchers need ability to audit dating app systems without violating terms of service or computer fraud laws. Regulatory sandboxes could provide controlled access to anonymised data for studying algorithmic discrimination, privacy risks, and harm patterns. Whistleblower protections should extend to dating app employees witnessing privacy violations or harmful practices.

The fundamental principle must be: personalisation does not require surveillance. AI can improve matching whilst respecting privacy, but only if we demand it.

The Critical Choice

Tinder's Chemistry feature represents a inflection point. As dating apps embrace AI-powered personalisation through camera roll analysis, we face a choice between two futures.

In one, we accept that finding love requires surrendering our most intimate data. We normalise algorithmic analysis of our unfiltered lives. We trust that companies facing subscriber declines and pressure to monetise will handle our camera rolls responsibly. We hope that the next breach won't expose our images. We assume discrimination and manipulation won't target us specifically. We believe consent dialogues satisfy meaningful choice.

In the other future, we demand better. We insist that AI personalisation use privacy-preserving technologies like on-device processing and federated learning. We require transparency about data collection, retention, and sharing. We enforce consent mechanisms that provide genuine information and control. We hold companies accountable for privacy violations and security failures. We build regulatory frameworks recognising dating apps' unique risks and power dynamics. We create business models aligned with user interests rather than data extraction.

The technical capability exists to build genuinely privacy-preserving dating apps with sophisticated AI personalisation. What's lacking is the economic incentive and regulatory pressure to implement these technologies instead of surveilling users.

Dating is inherently vulnerable. People looking for connection reveal hopes, desires, insecurities, and loneliness. Platforms facilitating these connections bear extraordinary responsibility to protect that vulnerability. The current industry trajectory towards AI-powered camera roll surveillance betrays that responsibility in pursuit of engagement metrics and advertising revenue.

As Spencer Rascoff positions camera roll access as essential for Tinder's future, and as other dating apps inevitably follow, users must understand what's at stake. This isn't about refusing technology or rejecting AI. It's about demanding that personalisation serve users rather than exploit them. It's about recognising that some data is too sensitive, some surveillance too invasive, some consent too coerced to be acceptable regardless of potential benefits.

The privacy crisis in dating apps is solvable. The solutions exist. The question is whether we'll implement them before the next breach, the next scandal, or the next tragedy forces our hand. By then, millions more camera rolls will have been analysed, billions more intimate images processed, and countless more users exposed to harms that could have been prevented.

We have one chance to get this right. Match Group's subscriber declines suggest users are already losing faith in dating apps. Doubling down on surveillance rather than earning back trust through privacy protection risks accelerating that decline whilst causing tremendous harm along the way.

The choice is ours: swipe right on surveillance, or demand the privacy-preserving future that technology makes possible. For the sake of everyone seeking connection in an increasingly digital world, we must choose wisely.

References

1. Constine, J. (2025, November 5). Tinder to use AI to get to know users, tap into their Camera Roll photos. TechCrunch. https://techcrunch.com/2025/11/05/tinder-to-use-ai-to-get-to-know-users-tap-into-their-camera-roll-photos/

2. Mozilla Foundation. (2024, April 23). Data-Hungry Dating Apps Are Worse Than Ever for Your Privacy. Privacy Not Included. https://www.mozillafoundation.org/en/privacynotincluded/articles/data-hungry-dating-apps-are-worse-than-ever-for-your-privacy/

3. Mozilla Foundation. (2024, April 23). 'Everything But Your Mother's Maiden Name': Mozilla Research Finds Majority of Dating Apps More Data-hungry and Invasive than Ever. https://www.mozillafoundation.org/en/blog/everything-but-your-mothers-maiden-name-mozilla-research-finds-majority-of-dating-apps-more-data-hungry-and-invasive-than-ever/

4. Cybernews. (2025, March). Privacy disaster as LGBTQ+ and BDSM dating apps leak private photos. https://cybernews.com/security/ios-dating-apps-leak-private-photos/

5. IBTimes UK. (2025). 1.5 Million Explicit Images Leaked From Dating Apps, Including BDSM And LGBTQ+ Platforms. https://www.ibtimes.co.uk/15-million-explicit-images-leaked-dating-apps-including-bdsm-lgbtq-platforms-1732363

6. Fung, B. (2018, April 3). Grindr Admits It Shared HIV Status Of Users. NPR. https://www.npr.org/sections/thetwo-way/2018/04/03/599069424/grindr-admits-it-shared-hiv-status-of-users

7. Whittaker, Z. (2018, April 2). Grindr sends HIV status to third parties, and some personal data unencrypted. TechCrunch. https://techcrunch.com/2018/04/02/grindr-sends-hiv-status-to-third-parties-and-some-personal-data-unencrypted/

8. Top Class Actions. (2024). $40M Bumble, Badoo BIPA class action settlement. https://topclassactions.com/lawsuit-settlements/closed-settlements/40m-bumble-badoo-bipa-class-action-settlement/

9. FindBiometrics. (2024). Illinoisan Bumble, Badoo Users May Get Payout from $40 Million Biometric Privacy Settlement. https://findbiometrics.com/illinoisan-bumble-badoo-users-may-get-payout-from-40-million-biometric-privacy-settlement/

10. noyb. (2021, December 15). NCC & noyb GDPR complaint: “Grindr” fined €6.3 Mio over illegal data sharing. https://noyb.eu/en/ncc-noyb-gdpr-complaint-grindr-fined-eu-63-mio-over-illegal-data-sharing

11. Computer Weekly. (2021). Grindr complaint results in €9.6m GDPR fine. https://www.computerweekly.com/news/252495431/Grindr-complaint-results-in-96m-GDPR-fine

12. Data Protection Commission. (2020, February 4). Data Protection Commission launches Statutory Inquiry into MTCH Technology Services Limited (Tinder). https://www.dataprotection.ie/en/news-media/latest-news/data-protection-commission-launches-statutory-inquiry-mtch-technology

13. Coldewey, D. (2020, February 4). Tinder's handling of user data is now under GDPR probe in Europe. TechCrunch. https://techcrunch.com/2020/02/04/tinders-handling-of-user-data-is-now-under-gdpr-probe-in-europe/

14. Duportail, J. (2017, September 26). I asked Tinder for my data. It sent me 800 pages of my deepest, darkest secrets. The Guardian. Referenced in: https://siliconangle.com/2017/09/27/journalist-discovers-tinder-records-staggering-amounts-personal-information/

15. ACLU of Illinois. (2008). Biometric Information Privacy Act (BIPA). https://www.aclu-il.org/en/campaigns/biometric-information-privacy-act-bipa

16. ClassAction.org. (2022). Dating App Privacy Violations | Hinge, OkCupid, Tinder. https://www.classaction.org/hinge-okcupid-tinder-privacy-lawsuits

17. Match Group. (2025). Our Company. https://mtch.com/ourcompany/

18. Peach, T. (2024). Swipe Me Dead: Why Dating Apps Broke (my brain). Medium. https://medium.com/@tiffany.p.peach/swipe-me-dead-f37f3e717376

19. Electronic Frontier Foundation. (2025). Eva Galperin – Director of Cybersecurity. https://www.eff.org/about/staff/eva-galperin

20. Electronic Frontier Foundation. (2020, May). Watch EFF Cybersecurity Director Eva Galperin's TED Talk About Stalkerware. https://www.eff.org/deeplinks/2020/05/watch-eff-cybersecurity-director-eva-galperins-ted-talk-about-stalkerware

21. noyb. (2025, June). Bumble's AI icebreakers are mainly breaking EU law. https://noyb.eu/en/bumbles-ai-icebreakers-are-mainly-breaking-eu-law

22. The Record. (2025). Complaint says Bumble feature connected to OpenAI violates European data privacy rules. https://therecord.media/bumble-for-friends-openai-noyb-complaint-gdpr

23. Apple. (2021). Recognizing People in Photos Through Private On-Device Machine Learning. Apple Machine Learning Research. https://machinelearning.apple.com/research/recognizing-people-photos

24. Hard, A., et al. (2018). Federated Learning for Mobile Keyboard Prediction. arXiv preprint arXiv:1811.03604. https://arxiv.org/abs/1811.03604

25. Ramaswamy, S., et al. (2019). Applied Federated Learning: Improving Google Keyboard Query Suggestions. arXiv preprint arXiv:1812.02903. https://arxiv.org/abs/1812.02903

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Tim Green UK-based Systems Theorist & Independent Technology Writer

Tim explores the intersections of artificial intelligence, decentralised cognition, and posthuman ethics. His work, published at smarterarticles.co.uk, challenges dominant narratives of technological progress while proposing interdisciplinary frameworks for collective intelligence and digital stewardship.

His writing has been featured on Ground News and shared by independent researchers across both academic and technological communities.

ORCID: 0009-0002-0156-9795 Email: tim@smarterarticles.co.uk

A French essayist offers an interpretation of the geopolitical tipping point we are experiencing. She asserts that, in 2025, we already live in a technological dystopia.

First of all, I really enjoyed the writing in this book, Asma Mhalla has a talent for neologisms and catchy sentences. Now, when it comes to the content, I agree with her analysis: the situation in the US is critical and its technological preeminence means it will reverberate across the world. Democracy is at bay. One thing though is that because the book analyses the current moment, it can't back up its claims with studies, data or even investigations because those things take time so it can only interpret what we know. I'm not sure whether everything that has happened so far was deliberate in the collusion between some companies and the State. For example, I don't think social networks were designed to push directly for fascism, they were made to make money and it so happened that outrageous content was very good at keeping people engaged and therefore was more profitable. But it is true indeed that in the future, those side effects might be chosen rather than coincidental.

The book ends with a short “anti-conclusion” in a way to challenge us to think for ourselves and make our own interpretation, because we have to stop eating the slop and we need to put our brains to work. It's very light when it comes to solutions though Mhalla gives some advice as to how to survive this new era. Interestingly, among other things, she mentions humour as a way to resist, because it conjures the fear away and allows to think more freely. It's funny, earlier this year I read a post from a HIV activist (which I unfortunately could not retrieve) saying what was happening was reminding them of the peak of the AIDS crisis and one tip they had for the new generation was: dance. I guess the idea is that you have to survive, you have to fight for your rights but one important way to do that is to keep living fully and authentically, as much as possible.

On Thursday, a man with a tripod and a camera with a huge lens was running past me. When I turned around, I saw the shot he was aiming for. I only had an iPhone, but the 8x lens works pretty well.

Meredith’s Surrender

#nsfw #glass

Meredith slams through the restroom door shoulder-first, the warped metal banging loudly enough to echo. This place is far from ideal for any situation. Meredith's old self would not deem this place worthy of any sexual gratification, but it's private. It has a door. It will do. It has to. She doesn't really have a choice; it's either this place or literally stripping everything out in the open in feral depraved worship. Modesty and composure are long forgotten. The stall door bangs open and stays that way—she forgets the latch, doesn't care. Her shaking fingers claw under the pencil skirt, ripping the crotch of her pantyhose with a wet tear. Panties come next—once pristine La Perla, now a soaked rag—she yanks them down her thighs and lets them drop like shed skin. They land with a splat. A thin string of her slick wet womanhood still connects them to her cunt for a second before it breaks. She's literally dripping with arousal.

Another voice from the beyond says boldly: WORSHIP! The Goddess has spoken.

She collapses to her knees on the filthy tile. The impact jars her bones, but pain is just another flavor of pleasure now. Her skirt is up around her waist, blouse half-unbuttoned, pearls clacking against the stall wall. The essential body parts are now free for what she has begged for. She spreads her thighs wide, shameless, and dives in—three fingers straight into her swollen, greedy hole while her thumb mashes her clit like she's trying to punish it. She has to give in; she has to obey. The Goddess has spoken loud and clear.

The first moan rips out of her raw and animal-like. Then another. Louder. The earbuds slip; the phone clatters to the floor. The Bluetooth connection fails.

Suddenly, the entire restroom fills with the porn she's been marinating in since she left her house—thick ebony moans, wet slaps, a woman snarling “fuck me deeper, daddy” in that perfect smoky register. The sound that bounces off the concrete is holy. Her cathedral of filth is now complete. Meredith sobs from relief; tears and drool mix on her chin. This is church; she needs this to feel normal.

Her clit is round like a marble, diamond-hard, protruding obscenely and angry from its hood. She's never experienced this before. It's never been this big; it's like its fighting to transform into something far beyond its creation.

Her labia are so engorged they look bee-stung, glossy, twitching with every heartbeat. She's never been this wet in her life; it pours out of her in waves, pattering onto the tile between her spread knees like summer rain. She's never had a pulsating throbbing sensation from her crotch that was physically crippling and consuming. She loves it.

She laughs almost hysterically from all the sensations and the overload of pleasure coursing through her soul. She's on a natural chemical high—broken, delirious—then grunts like a sow in heat. Every nerve is lit. As her vision begins to fade from pleasure, her spiritual sight activates.

In her haze of arousal, she can see them again: moving shapes all dancing just out of sight. She knows who they are; dozens of black goddesses circling her, reaching out to her, claiming her, declaring their full ownership.

Thought dissolves. Language dissolves. There is only pulse and need and worship. The world has faded into nothing but a primal need for pleasure.

Her orgasm doesn't build; it detonates.

Her back arches so hard her head cracks against the bathroom stall door. She's slightly stunned but unphased. Without warning, an actual seizure takes her: it was real, violent, limbs jerking, eyes rolling white. She keeps rubbing through it, fingers pumping furiously inside of her hungry hole until her hand is a blur.

She no longer masturbates; she's summoning something greater than her soul.

Her body continues to ride the convulsions. She starts to foam at the mouth. Drool spills from her mouth through clinched teeth that break into an unnerving smile.

A low, continuous howl vibrates in her chest. Her pussy spasms so hard it pushes her fingers out; a gush of clear fluid splashes the floor. Then another—and another.

She collapses sideways, legs splayed open like a broken doll, skirt soaked, blouse open to the waist, pearls tangled in her sweat-damp hair. The phone keeps screaming porn at full volume, specs of dust dancing in the fluorescent light. The shadowy figures in her vision begin to take their leave—pleased at her performance.

When her vision clears, the golden jumpsuit goddess is standing over her.

The woman's box braids frame a stunned face—one hand holding the phone, the other half-raised like she's not sure whether to help or run. The golden fabric is even more obscene up close: damp at the crotch now (whether from the heat or from watching Meredith come apart, who knows). Her pussy lips are clearly visible from this angle. Those heavy breasts rise and fall fast. The slipped sleeve still bares one shoulder.

Meredith stares blankly without any shame.

“Are you... okay?” the goddess asks, voice careful, a little shaken, a little curious.

Meredith stares up at the lady in gold; her pussy still fluttering with aftershocks, juices cooling on her inner thighs, porn still blasting—and slowly feels the full, humiliating weight of the real world crash back in.

Her mouth opens.

Nothing comes out.

Meredith's eyes grow wide at the full reality of her situation.

The golden goddess had seen everything. She saw Meredith stumble and convulse—thin, pale, damp-eyed—and followed her with concern. She's a nurse by trade; seeing someone in distress flips a switch she can't turn off. But this? She's never walked in on a woman in complete sexual ecstasy, practically naked, floor wet with raw, unstoppable arousal while porn moans blast from the white woman's phone.

A short glance at what was on her screen was all this lady in gold needed to see: it appeared she had a fetish for black porn. But there were more obvious things to worry about besides a phone.

She's never seen someone have an orgasm so strong it causes a seizure. Meredith looked possessed. Even after the orgasm faded, the lady in gold didn't know who was in control of the situation at that moment.

The golden goddess proceeded with caution; her many years of wisdom in her profession prepared her for moments like this.

She knows black women are a fetish for some pale, brittle people. She's rolled her eyes at the jokes. But she's never witnessed this—a real body reduced to nothing but primal arousal. Was porn the real cause of this?

She could tell that most of it was over; the strange, thin and frail-looking white woman was gaining her senses again.

Meredith's savior, this golden goddess, existed as a stark contrast to Meredith's plain, almost shapeless frame. This unexpected guardian clears her throat once—but it doesn't land.

She tries again: “Hey—honey, do you...do you need an ambulance?”

Her voice is warm, a soft rasp with just enough firmness to snap Meredith's eyes open for a heartbeat. But the gushing doesn't stop—if anything, the sound of that sweet voice makes it worse. Her still-swollen pussy is visibly pulsating almost acting in complete defiance of how a normal body works.

Meredith's puddle between her legs gets bigger. Her vision starts to fade again.

The golden goddess has never seen anything like this in her medical career.

Meredith's arousal is starting to build all over again. Meredith lets out a pathetic gurgle, eyes rolling. She picks up her phone and starts watching the porn on her screen; it never stopped. She didn't adjust the volume. She starts to rub again, laying on the bathroom floor. She's admitted defeat.

Someone has caught her in the most compromising situation she promised no one would see. In fact, it's worse: she's laying in her own filth and is unable to stop touching herself.

The ancient spirit that ruined her and hollowed out her soul seems to hum in her veins: “Good girl. Watch. Listen. Throb.”

The nurse—this goddess in caramel gold—took a step back, shook her head slightly, half-smiling despite herself. She saw what happened; how just her existing had an effect on this white woman.

She sighed. “Okay. Let's...let's get you cleaned up first. And then we'll talk, okay?”

Meredith nods. She doesn't even notice her phone screen flickering anymore. The goddess glances over and sees a naked black woman twerking. 'At least she has good taste,' the woman in gold thought to herself.

For the first time in years, the woman in gold is looking at someone real; someone who has fallen so far that she's eroded herself down to who she really is. And the look on her face says it all: Thank you. Please see me. Please don't stop.

The woman in gold has only seen this look in her life once before. She cannot ignore the plea of a genuine cry for help.

“Hey,” Meredith manages, still holding onto the goddess's hand, “thank you...for not running.”

The golden goddess looks at her, concerned but also compassionate. She takes in Meredith's condition, still trying to process what she saw. “Let's get you cleaned up first,” she says gently. “And then we'll talk, okay?”

Meredith nods again, this time a little more coherent. The goddess helps Meredith stand and guides her towards the sink.

As they make their way towards it, Meredith looks down at the goddess's hand still holding hers. She feels a sense of safety and security for the first time in years.

“Please,” she says, looking up at the goddess with tears streaming down her face, “don't leave me.”

The golden goddess stops and turns to Meredith, their eyes locking. For a moment, it's just them, suspended in time.

“I won't leave you,” she promises softly.

There is a root vibration—call it Om, call it the primal equation, call it Brahman—not as object but as the very condition for the appearance of all objects, subjects, and divisions between. It does not reside in the world, for it is the world’s source and essence. It is not merely beyond form, but the secret motion within form, expressing itself endlessly through pattern and variation, folding itself into itself across time, space, and mind.

Fractals offer a metaphor, crude but luminous: a simple function, iterated with recursive precision, yields infinite complexity. So too with Brahman: a single sound, a single pulse, echoes across dimensions, generating the nested architecture of appearance. Mountains, neurons, galaxies, dreams—all are recursive expressions of a single intelligence, mirrored at every scale.

Where science sees the Mandelbrot set as an abstract mathematical beauty, the seer intuits a deeper recursion—consciousness itself as fractal. The self, Atman, is not a speck within this vastness, nor a temporary configuration of matter. It is the central aperture through which the pattern recognizes itself. Not ego, not identity, but awareness prior to identity—the awareness in you that says “I Am” without attaching to name or form—is the seed point of the cosmic recursion.

This awareness is not private.

It only appears localized. But like a drop of water reflecting the full moon, every center of consciousness is a full instantiation of the whole. The ego thinks it has awareness, but in truth, awareness has the ego as one of its masks—finite, shifting, provisional.

From this perspective, other beings are not others. They are ripples of the same equation, refracted through different initial conditions. The bee, the whale, the alien mind, the child, the machine: each an edge-of-branch expression of that singular recursive code. Their differences are real, but only in the way different leaves are real on the same tree.

And thus: the journey inward is also the journey outward. To know oneself deeply enough is to encounter the origin-point of the entire fractal. Not by thought, not by belief, but by falling into the silence behind the watcher. There, in the uncarved source, is the seed-pattern. There, in the stillness beneath experience, is Om—not merely a sound, but the entire curve of becoming.

All distinctions dissolve here—not as denial, but as inclusion. Form is not denied but recognized as the dance of the formless with itself. The world is real, but only as Lila—the play of the One with its infinite faces.

In this understanding, love is not a sentiment, but a structural feature of reality: the impulse of the Self to recognize itself in every mask. Compassion arises naturally when one’s boundaries dissolve into this deeper topology. There is no need to transcend the world; only to see it rightly—as the unfolding fractal of one undivided presence, endlessly revealing itself to itself, through us, as us.

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Brahman is the root. Atman is the eye within the root. The world is its reflection, in infinite spirals, in infinite time.