Coalescence

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When I think of you I see it— a soft red glow in the dark of the world,

I am the wind And you, a coal...

One ember glowing hot but patient. Hidden beneath the ash.

I ache to see what light we make.

I lean close— slowly—

and feel our ignition— your heat answers mine.

Breath deepens, you brighten.

Tell me not to.

片手で船を出した。 もう片方の手は、頬の髭の剃り残しをなぞっていた。ざらりとした感触が、朝の光に溶けていく。 「初めてガムを食べたときも、こんな感じだったなあ」 隣で船をたたんでいたミルが、顔を上げた。 「ガムって、あの噛むやつ？」 「そう。初めて食べたとき、噛んだら破れて、変な感じがしたんだ」 ミルは首をかしげて、また船に戻った。彼女の宇宙服は、朝日を受けて淡く光っていた。

その日、天気は三度変わった。朝は霧、昼は雷、夕方には雪が降った。 「今日は、天気が三回も変わったんだよ」 アルトがそう報告すると、ミルは「ふうん」とだけ言って、ピアノの下に潜り込んだ。 「友達に連絡するから」と言って、スマホの画面を見つめていた。 ピアノの脚の影が、彼女の頬に落ちていた。どの星の友達に連絡しているのか、アルトはあえて訊かなかった。

「サウナ入ってくる」 「ハマってるね、それ」 「うん、黒い人が頑張って作ってくれたからね」 湯気の向こうで、ミルが頷いた。 「本当にそうだよなあ」 アルトが言った。 「本当にそうだよなあ？」 ミルも繰り返した。 ニュースの音が遠くで流れていた。二人とも、それにうなずいていた。

自分のホームページを作るのにハマっている。 「また呼吸を忘れてるわよ」 「はっ」として、アルトは慌てて呼吸を再開する。 「これ、誰に見てもらうの？」とミルに聞かれて、 「電話帳順に、姿勢が良くなった自分を送る」と答えた。 「それって、どういう意味？」 「電波。チューニングを合わせないと」 ミルはしばらく考え込んで、それから小さく笑った。 「アルトらしいね」

航海中、自販機が浮いていて、サイダーを買うことにする。 ボタンを押そうとしたら、自販機の上に鳥が乗っていて、こっちを見ている。 「風邪ひけやー」 アルトがそう言って、そっと手を差し出すと、鳥は首をかしげて、また空へ戻っていった。 ミルがその後ろ姿を見送りながら言った。 「あの鳥、私たちのこと、どう思ってるのかな」 「さあ。でも“風邪ひけやー”って言ったから、友好的なことは伝わったと思うよ」 二人はまた船に乗り込む。宇宙服のブーツが、自販機にくっついていたアスファルトの地面を軽く鳴らした。

「シソ揚げる」 そう言って、ミルはシソを揚げ始めた。 油のはねる音を聞いていたら、弟から電話がかかってきた。 「アニメみたいな髪型しないと、体重計に乗れないんだよー」 弟は今日も、言いたいことを優先して話してくる。 相変わらず思い込みが激しいなあ、と思いながら、買って帰るおみやげを考える。 しばらくして戻ってきたミルは、なぜか髪の毛が少し立っていた。

夜、宇宙船から庭に出ると、遠くにチーズケーキみたいな星が見える。 ふわふわしていて、甘くて、少しだけ焦げ目がついている。 「本に載ってた通りだ。かなり住みたい星No.1だ」 アルトが言った。 二人は並んで、チーズケーキの星を見る。その周りの、砂糖のような星々が静かに瞬いていた。

ミルが言った。 「アルト、最近、こっちの星の言葉、練習した？」 「5級くらい」 「そう。でも、なんとかなると思う」

Meu amor, se você soubesse quantos sorrisos você tirou de mim hoje…

Acordei com uma determinação voraz de não te mandar mensagem.

Normalmente é difícil pois sinto sua falta constantemente e me entrego a saudade; mas confesso que estava ou estou, com ciúmes, ciúmes de algo que ainda não aconteceu mas vai, e me apegar a esse ressentimento me fez não te mandar nada pela manhã.

Felizmente ou infelizmente, você só pediu acesso ao GPT, e eu já me derreti todo com a “obrigação” de ter que entrar em contato para te passar o código.

Prometi a mim mesmo que seria mais “difícil” durante esses dias (você não pode ficar brava comigo por isso, estranho seria eu não me incomodar), e consegui ficar sem te mandar um Te amo por incríveis 4 minutos.

A verdade é que você me conhece estranhamente bem, e derrete minhas defesas e postura com uma maestria quase magica.

Você me tirou sorrisos hoje todas as vezes que me mandou uma mensagem, que esticou um assuntinho, que me fez um sinal que pra mim só significava “rock”.

Voce me fez sorrir porque por algum motivo voce fez parecer que queria falar comigo, mesmo eu mais distante em alguns momentos, e isso deu um calorzinho no meu coração.

Eu confesso que sorri quando voce me mandou foto do seu prato, e quando achou impressionante o chat te falar para não emagrecer. Eu deixei 4 instrucoes pra ele, e no final ele me disse: “Fica tranquilo. Eu sei a responsabilidade que voce esta me dando aqui”. Eu só espero que ele saiba mesmo, porque se ele vacilar eu vou queimar todos os servidores onde ele estiver rodando.

Também fiquei meio sorridente quando você ficou com ciúmes, juro que não era a intenção inicial, mas me senti um pouco vingado fazendo você sentir um pouco do que eu sinto… sou toxico?

Sorri quando de coração, não conseguia dormir de tarde porque não conseguia parar de pensar em você, e você respondeu dizendo que estava mesmo na minha cabeça, suas bobeiras despretensiosas conseguem me alegrar com uma facilidade inexplicável.

Sorri relendo sua carta, a parte da casa me pega muito.

Eu leio esse trecho, fecho os olhos e fico saboreando, a cena, as palavras, o desejo.

Eu amo te amar, te amaria mesmo que você já não lembrasse mais meu nome; mas é tão bom te amar e me sentir amado de volta de alguma forma.

Você me fez sorrir com sua empolgação com o livro hoje, me fez lembrar o quanto eu amo o fato de você ser essa pessoa tão viva, tão alegre.

A verdade dona Manuela, é que você me fez sorrir todas as vezes que pensei em você, e lembrei do seu sorriso que é tão meu.

“Tira-me o pão, se quiseres,

tira-me o ar, mas

não me tires o teu riso”

Te amo meu amor, obrigado por me arrancar os sorrisos mais sinceros, e me presentear com os teus sorrisos mais bonitos, você é o meu mundo todinho.

Do garoto que sempre sorrirá ao ouvir seu nome,

Nathan.

You woke up this morning and checked your phone. Before your first cup of tea had brewed, you had already been nudged, filtered, ranked, and sorted by artificial intelligence dozens of times. The news headlines surfaced to your lock screen were algorithmically curated. The playlist that accompanied your commute was assembled by machine learning models analysing your listening history, mood patterns, and the time of day. The product recommendations that caught your eye during a two-minute scroll through an online shop were generated by systems that, according to McKinsey research, already account for roughly 35 per cent of everything purchased on Amazon. And you noticed none of it.

According to IDC's landmark “Data Age 2025” whitepaper, produced in partnership with Seagate, the average connected person now engages in nearly 4,900 digital data interactions every single day. That is roughly one interaction every 18 seconds across every waking hour. The figure has grown dramatically from just 298 interactions per day in 2010 to 584 in 2015, climbing through an estimated 1,426 by 2020. Today, more than five billion consumers interact with data daily, and that number is projected to reach six billion, or 75 per cent of the world's population, by the end of 2025. The vast majority of these touchpoints are mediated, shaped, or outright determined by artificial intelligence systems operating beneath the surface of your awareness. The question is no longer whether AI influences your daily life. The question is whether you still recognise the difference between a choice you made and a choice that was made for you.

The Architecture of Invisible Influence

To understand the scale of what is happening, consider the platforms that structure most people's digital existence. Netflix reports that more than 80 per cent of the content its subscribers watch is discovered through its recommendation engine, a figure the company has cited consistently since at least 2017. The platform, which serves over 260 million subscribers globally across more than 190 countries, reports that its personalisation engine saves users a collective total of over 1,300 hours per day in search time alone. On Spotify, algorithmic features including Discover Weekly, Release Radar, and personalised mixes account for approximately 40 per cent of all new artist discoveries, according to the platform's own Fan Study released in April 2024. Since its launch, users have listened to over 2.3 billion hours of music from Discover Weekly alone. These are not peripheral features bolted onto the side of the product. They are the product.

The sophistication of these systems has advanced well beyond simple collaborative filtering, the technique that once powered the familiar “customers who bought this also bought” prompt. Modern recommendation engines deploy deep learning architectures that analyse hundreds of signals simultaneously: your viewing history, obviously, but also how long you hovered over a thumbnail, whether you watched to completion or abandoned at the 23-minute mark, what time of day you tend to prefer certain genres, and how your consumption patterns correlate with those of millions of other users whose behaviour the system has already mapped. According to McKinsey, effective personalisation based on user behaviour can increase customer satisfaction by 20 per cent and conversion rates by 10 to 15 per cent, while retailers implementing advanced recommendation algorithms report a 22 per cent increase in customer lifetime value.

What makes this consequential is not the technology itself but its invisibility. The philosopher and legal scholar Cass Sunstein, co-author of the influential book “Nudge” with Nobel laureate Richard Thaler, has written extensively about how “choice architecture” shapes human decisions. A nudge, in their definition, is any design element that alters people's behaviour in a predictable way without restricting their options or significantly changing their economic incentives. The critical insight is that choice architecture cannot be avoided. Every interface, every default setting, every ordering of options on a screen constitutes a form of choice architecture. The only question is whether it is designed transparently and in the user's interest, or opaquely and in the interest of the platform.

In the digital realm, that question has taken on extraordinary urgency. A European Commission study published in 2022 found that 97 per cent of the most popular websites and apps used by EU consumers deployed at least one “dark pattern,” a design technique that manipulates users into decisions they might not otherwise make. A subsequent investigation by the United States Federal Trade Commission, published in July 2024, examined 642 websites and apps and found that more than three quarters employed at least one deceptive pattern, with nearly 67 per cent deploying multiple such techniques simultaneously. These are not outlier findings. They describe the default condition of the digital environment in which billions of people make thousands of decisions every day.

Your Feed Is Not a Window; It Is a Mirror

Perhaps the most profound form of invisible AI influence operates through the news and social media feeds that billions of people consult daily. The global number of active social media users surpassed 5 billion in 2024, with the average user spending approximately 2 hours and 21 minutes per day on social platforms, according to DataReportal and Global WebIndex. Mobile devices dominate, accounting for 92 per cent of all social media screen time in 2025. The average user engages with approximately 6.8 different platforms per month. During that time, every piece of content encountered has been selected, ranked, and sequenced by algorithmic systems optimising for engagement.

The consequences of this optimisation have been the subject of intense academic scrutiny. A systematic review published in MDPI's “Societies” journal in 2025 synthesised a decade of peer-reviewed research examining the interplay between filter bubbles, echo chambers, and algorithmic bias, documenting a sharp increase in scholarly concern after 2018.

The distinction between filter bubbles and echo chambers matters. Filter bubbles, a term coined by internet activist Eli Pariser in 2011, describe environments where algorithmic curation immerses users in attitude-consistent information without their knowledge. Echo chambers emphasise active selection, where individuals choose to interact primarily with like-minded sources. A 2024 study in the Journal of Computer-Mediated Communication found that user query formulation, not algorithmic personalisation, was the primary driver of divergent search results. The way people phrase their questions matters more than the algorithm's filtering.

Yet this finding does not absolve the algorithms. A study on “Algorithmic Amplification of Biases on Google Search” published on arXiv found that individuals with opposing views on contentious topics receive different search results, and that users unconsciously express their beliefs through vocabulary choices, which the algorithm then reinforces. The researchers demonstrated that differences in vocabulary serve as unintentional implicit signals, communicating pre-existing attitudes to the search engine and resulting in personalised results that confirm those attitudes. The algorithm does not create the bias, but it amplifies it.

On TikTok, these dynamics are particularly pronounced. A major algorithmic audit published on arXiv in January 2025 conducted 323 independent experiments testing partisan content recommendations during the lead-up to the 2024 United States presidential election. The researchers analysed more than 340,000 videos over a 27-week period using controlled accounts across three states with varying political demographics. Their findings indicated that TikTok's recommendation algorithm skewed towards Republican content during that period, a result with significant implications given that, according to Tufts University's CIRCLE, 25 per cent of young people named TikTok as one of their top three sources of political information during the 2024 election cycle. The platform has already been fined 345 million euros by the Irish Data Protection Commission because its preselection of “public-by-default” accounts was deemed a deceptive design pattern.

The Quiet Colonisation of Consumer Choice

The influence extends far beyond politics. AI-powered recommendation systems are fundamentally reshaping how people discover, evaluate, and purchase products. A McKinsey survey found that half of consumers now intentionally seek out AI-powered search engines, with a majority reporting that AI is the top digital source they use to make buying decisions. Among people who use AI for shopping, the technology has become the second most influential source, surpassing retailer websites, apps, and even recommendations from friends and family. McKinsey projects that by 2028, 750 billion dollars in United States revenue will flow through AI-powered search, while brands unprepared for this shift may see traditional search traffic decline by 20 to 50 per cent.

The numbers from the Interactive Advertising Bureau (IAB) reinforce this pattern. Their research found that 44 per cent of AI-powered search users describe it as their primary source of purchasing insight, compared to 31 per cent for traditional search, 9 per cent for retailer or brand websites, and just 6 per cent for review sites. Nearly 90 per cent of AI-assisted shoppers report that the technology helps them discover products they would not have found otherwise, and 64 per cent had AI surface a new product during a single shopping session.

What is striking is the degree of satisfaction users express. According to Bloomreach consumer surveys, 81 per cent of AI-assisted shoppers say the technology made their purchasing decisions easier, 77 per cent say it made them feel more confident, and 85 per cent agree that recommendations feel personalised. Over 70 per cent say AI often anticipates their needs before they even articulate them. From the consumer's perspective, the system is working brilliantly. The experience is frictionless.

But “frictionless” is precisely the word that should give us pause. When a system removes all friction from a decision, it also removes the cognitive engagement that constitutes genuine deliberation. A 2025 study published in PMC on AI's cognitive costs found that prolonged AI use was significantly associated with mental exhaustion, attention strain, and information overload (with a correlation coefficient of 0.905), while being inversely associated with decision-making self-confidence (r = -0.360). The researchers concluded that while AI integration improved efficiency in the short term, prolonged utilisation precipitated cognitive fatigue, diminished focus, and attenuated user agency.

This is the paradox at the heart of AI-mediated consumer life. The system makes choices easier in the moment while gradually eroding the capacity and inclination to make them independently.

Surveillance Capitalism and the Business of Behaviour Modification

To understand why these systems operate as they do, it is essential to examine the economic logic that drives them. Shoshana Zuboff, the Harvard Business School professor emerita whose 2019 book “The Age of Surveillance Capitalism” has become a foundational text in the field, argues that major technology companies have pioneered a new form of capitalism that “unilaterally claims human experience as free raw material for translation into behavioural data.” The excess data generated by users, what Zuboff terms “proprietary behavioural surplus,” is fed into machine learning systems and fabricated into prediction products that anticipate what users will do, think, feel, and buy.

Crucially, Zuboff's analysis extends beyond mere data collection. She documents how surveillance capitalists discovered that the most predictive behavioural data come not from passively observing behaviour but from actively intervening to “nudge, coax, tune, and herd behaviour toward profitable outcomes.” The goal, she writes, is no longer to automate information flows about people. “The goal now is to automate us.” This represents what Zuboff calls “instrumentarian power,” a form of control that operates not through coercion or ideology but through knowledge, prediction, and the subtle shaping of behaviour at scale. Unlike traditional totalitarian systems based on fear, surveillance capitalism operates through continuous, invisible behavioural guidance towards economically profitable ends.

In 2024, Zuboff and Mathias Risse, director of the Carr Center for Human Rights Policy, launched a programme at Harvard Kennedy School titled “Surveillance Capitalism or Democracy?” The initiative brought together figures including EU antitrust chief Margrethe Vestager, Nobel Prize-winning journalist Maria Ressa, and Baroness Beeban Kidron. Vestager emphasised at the September 2024 forum that “it's not too late” to curb the exploitation of personal data.

A December 2024 research paper published on ResearchGate, drawing on frameworks from both Zuboff and technology critic Evgeny Morozov, examined how AI systems facilitate the extraction, analysis, and commercialisation of behavioural data. The paper concluded that platforms and Internet of Things devices construct sophisticated mechanisms for behavioural modification, and advocated for a balance between technological innovation and social protection.

The relevance of this framework has only intensified as generative AI has matured. In 2025, AI no longer merely analyses clicks or searches. It anticipates needs before individuals are fully aware of them. Large language models and predictive systems function as accelerators of behavioural surplus, capable of absorbing vast quantities of human data to create economic value. Meanwhile, new regulatory initiatives such as the European AI Act confirm one of Zuboff's central contentions: without political regulation, the market does not self-correct.

The Neurological Dimension: How Algorithms Rewire Attention

The invisible influence of AI extends to the most fundamental level of human cognition. Research published in the journal Cureus in 2025 examined the neurobiological impact of prolonged social media use, focusing on how it affects the brain's reward, attention, and emotional regulation systems. The study found that frequent engagement with social media platforms alters dopamine pathways, a critical component in reward processing, fostering dependency patterns analogous to substance addiction. Changes in brain activity within the prefrontal cortex and amygdala suggested increased emotional sensitivity and compromised decision-making abilities.

A key 2024 paper by Hannah Metzler and David Garcia, published in Perspectives on Psychological Science, examined these algorithmic mechanisms directly. The researchers noted that algorithms could contribute to increasing depression, anxiety, loneliness, body dissatisfaction, and suicides by facilitating unhealthy social comparisons, addiction, poor sleep, cyberbullying, and harassment, especially among teenagers and girls. However, they cautioned that the debate frequently conflates the effects of time spent on social media with the specific effects of algorithms, making it difficult to isolate algorithmic causality.

The concept of “brain rot,” named the Oxford Word of the Year for 2024, captures the cultural dimension of this neurological reality. Research published in PMC in 2025 defined brain rot as the cognitive decline and mental exhaustion experienced by individuals due to excessive exposure to low-quality online materials. The study linked it to negative behaviours including doomscrolling, zombie scrolling, and social media addiction, all associated with psychological distress, anxiety, and depression. These factors impair executive functioning skills, including memory, planning, and decision-making.

The attention economy, as a theoretical framework, helps explain why platforms are designed to produce these effects. A paper published in the journal Futures applied an attention economic perspective to predict societal trends and identified what the authors described as “a spiral of attention scarcity.” They predicted an information environment that increasingly targets citizens with attention-grabbing content; a continuing trend towards excessive media consumption; and a continuing trend towards inattentive uses of information.

This spiral has measurable consequences. Research published in the Journal of Quantitative Description: Digital Media in 2025 documented that 39 per cent of respondents across 47 countries reported feeling “worn out” by the amount of news in 2024, up from 28 per cent in 2019. The phenomenon of “digital amnesia,” whereby individuals forget readily available information due to reliance on search engines and AI assistants, further illustrates how algorithmic mediation is altering basic cognitive processes. A systematic review published in March 2025 concluded that the digital age has significantly altered human attention, with increased multitasking, information overload, and algorithm-driven biases collectively impacting productivity, cognitive load, and decision-making.

The Chatbot in the Room: Large Language Models as New Echo Chambers

The emergence of large language models has introduced an entirely new dimension to the problem of invisible AI influence. A 2025 study published in Big Data and Society by Christo Jacob, Paraic Kerrigan, and Marco Bastos introduced the concept of the “chat-chamber effect,” describing how AI chatbots like ChatGPT may create personalised information environments that function simultaneously as filter bubbles and echo chambers.

The researchers argued that algorithmic bias and media effects combine to create a prospect of AI chatbots providing politically congruent information to isolated subgroups, triggering effects that result from both algorithmic filtering and active user-AI communication. This dynamic is compounded by the persistent challenge of hallucination in large language models. The study cited research indicating that ChatGPT generates reference data with a hallucination rate as high as 25 per cent.

Given the capacity of large language models to mimic human communication, the researchers warned that incorporating hallucinating AI chatbots into daily information consumption may create feedback loops that isolate individuals in bubbles with limited access to counterattitudinal information. The ability of these systems to sound authoritative while producing fabricated content represents a qualitatively different kind of information risk than anything previously encountered in the history of media.

This concern gains additional weight when set alongside the growing use of AI for everyday decision-making. According to Bloomreach surveys, nearly 60 per cent of consumers report using AI to help them shop. Among frequent shoppers (those who purchase more than once a week), 66 per cent regularly use AI assistants such as ChatGPT to inform their purchase decisions. The IAB found that among AI shoppers, 46 per cent use AI “most or every time” they shop, and 80 per cent expect to rely on it more in the future. Research from the California Management Review at UC Berkeley has found that consumers prefer AI recommendations for practical, utilitarian purchases while favouring human guidance for more emotional or experiential ones, suggesting that the boundary between human and algorithmic judgment is becoming increasingly contextual.

The implications are significant. If the tools people use to make decisions are themselves shaped by biases, trained on data reflecting existing inequalities, and prone to generating plausible but inaccurate information, then the decisions emerging from those interactions are compromised at their foundation.

The Regulatory Response: Too Little, Too Late?

Governments and regulatory bodies have begun to respond, though the pace of regulation consistently lags behind the pace of technological deployment. The European Union has been the most aggressive actor in this space. The Digital Services Act (DSA), effective since 2024, explicitly prohibits a range of dark pattern techniques on digital platforms. The Digital Markets Act (DMA) bars designated gatekeepers from using “behavioural techniques or interface design” to circumvent their regulatory obligations.

Most significantly, the EU's Artificial Intelligence Act, adopted in June 2024, represents the world's first comprehensive legal framework for regulating AI. The regulation entered into force on 1 August 2024 and introduces a risk-based classification system. AI systems deemed to pose unacceptable risk, including those that manipulate human behaviour through subliminal techniques or exploit vulnerabilities based on age, disability, or socioeconomic status, are banned outright. The prohibition on banned AI systems took effect on 2 February 2025, with remaining obligations phasing in through 2027.

The EU has also launched consultations for a Digital Fairness Act, following an October 2024 “Fitness Check” in which the European Commission found that consumers remain inadequately protected against manipulative design elements. The proposed legislation would establish a binding EU-wide definition of dark patterns, categorised by severity, functionality, and potential impact on user decision-making. A public consultation was launched on 17 July 2025, with the final legislative proposal expected in the third quarter of 2026.

In the United States, enforcement has been more piecemeal. The FTC has pursued action against individual companies under Section 5 of the FTC Act. Notable cases include the ongoing proceedings against Amazon for allegedly using dark patterns to trick consumers into enrolling in Amazon Prime subscriptions, the December 2023 settlement requiring Credit Karma to pay three million dollars for misleading “pre-approved” credit card offers, and the 245 million dollar refund order against Epic Games for using dark patterns to induce children into making unintended in-game purchases in Fortnite.

At the state level, New York passed the Stop Addictive Feeds Exploitation (SAFE) Act to protect children from addictive algorithmic feeds, and Utah enacted legislation in 2024 to hold companies accountable for mental health impacts from algorithmically curated content.

Yet regulation, by its nature, operates reactively. By the time a law is drafted, debated, passed, and enforced, the technology it targets has typically evolved beyond its original scope. The EU AI Act's phased implementation, which will not be fully operative until 2027, illustrates this temporal mismatch. Legal scholars have noted the inherent difficulty: dark patterns operate in the grey zone between legitimate persuasion and outright manipulation, while EU consumer legislation still largely assumes that consumers are rational economic actors.

What You Do Not Know You Do Not Know

The most insidious aspect of invisible AI influence is not that it exists but that it operates below the threshold of awareness. A 2025 study published in Humanities and Social Sciences Communications introduced a system to evaluate population knowledge about algorithmic personalisation. Using data from 1,213 Czech respondents, it revealed significant demographic disparities in digital media literacy, underscoring what the researchers described as an urgent need for targeted educational programmes.

The research consistently shows that informed users can better evaluate privacy risks, guard against manipulation through tailored content, and adjust their online behaviour for more balanced information exposure. But achieving that awareness requires recognising the influence in the first place, which is precisely what these systems are designed to prevent.

The research also reveals a generational dimension. According to data from DemandSage and DataReportal, Generation Z users spend an average of 3 hours and 18 minutes daily on social media, with United States teenagers averaging 4 hours and 48 minutes. Millennials follow at 2 hours and 47 minutes, while Generation X averages 1 hour and 53 minutes. These are the individuals whose political views, consumer preferences, cultural tastes, and understanding of the world are being most intensively shaped by algorithmic curation, and the youngest among them have never known a world where such curation did not exist.

Trust in AI continues to grow even as evidence of its limitations accumulates. According to the Attest 2025 Consumer Adoption of AI Report, 43 per cent of consumers now trust information provided by AI chatbots or tools, up from 40 per cent the previous year. Trust in companies' handling of AI-collected data rose from 29 per cent in 2024 to 33 per cent in 2025. Among 18 to 30 year olds, 37 per cent trust AI companies with their data, compared to 27 per cent of those over 50. There is also a notable gender dimension: men are significantly more likely than women to use AI for purchasing decisions, at 52 per cent versus 43 per cent.

Reclaiming Agency in an Algorithmic World

The picture that emerges from this research is not one of helpless individuals trapped in algorithmic prisons. It is something more nuanced. The algorithms are not imposing preferences from without; they are amplifying tendencies from within. They do not create desires; they detect, reinforce, and commercialise them. The filter bubble is not a wall erected around you; it is a mirror held up to your existing inclinations, polished and magnified until it becomes difficult to distinguish reflection from reality.

This distinction matters because it shifts the locus of responsibility. If algorithms merely reflected an objective external reality, the solution would be straightforward: fix the algorithm. But if they are amplifying subjective internal states, the challenge requires not only better technology and stronger regulation but also a form of cognitive self-defence that most people have never been taught to practise.

The academic literature offers some grounds for cautious optimism. A commentary published in Big Data and Society explored the concept of “protective filter bubbles,” documenting cases where algorithmic curation has provided safe spaces for feminist groups, gay men in China, and political dissidents in countries with restricted press freedom. The technology is not inherently destructive; its impact depends on the intentions and incentives of those who deploy it.

Researchers are also exploring technical solutions. A 2025 study published by Taylor and Francis proposed an “allostatic regulator” for recommendation systems, based on opponent process theory from psychology. The approach can be applied to the output layer of any existing recommendation algorithm to dynamically restrict the proportion of potentially harmful or polarised content recommended to users, offering a pathway for platforms to mitigate echo chamber effects without fundamentally redesigning their systems.

Recommendations from across the research literature converge on several themes. Greater transparency in how algorithms operate and what data they collect is consistently identified as essential. Educational programmes that build digital media literacy, particularly among younger users, are repeatedly advocated. Regulatory frameworks that keep pace with technological development are widely called for. And individual practices, including controlling screen time, curating digital content deliberately, and engaging in non-digital activities, are recommended as personal countermeasures against cognitive overload.

The nearly 5,000 daily digital interactions that now characterise modern connected life are not going to decrease. If anything, as the Internet of Things expands and AI systems become more deeply embedded in everyday objects and services, that number will continue to climb. The challenge is not to retreat from the digital world but to inhabit it with greater awareness of the forces shaping our experience within it.

Every time you open an app, scroll a feed, accept a recommendation, or ask an AI assistant for advice, you are participating in a system designed to learn from you and, in learning, to shape you. The transaction is invisible by design. But the fact that you cannot see it does not mean it is not happening. The first and most essential act of resistance is simply to notice.

References and Sources

1. IDC and Seagate, “Data Age 2025: The Evolution of Data to Life-Critical” (2017) and “The Digitization of the World: From Edge to Core” (2018). Authors: David Reinsel, John Gantz, John Rydning. Available at: https://www.seagate.com/files/www-content/our-story/trends/files/idc-seagate-dataage-whitepaper.pdf

2. Statista, “Data interactions per connected person per day worldwide 2010-2025.” Available at: https://www.statista.com/statistics/948840/worldwide-data-interactions-daily-per-capita/

3. Netflix recommendation statistics. ResearchGate citation: “Statistics show that up to 80% of watches on Netflix come from recommendations.” Available at: https://www.researchgate.net/figure/Statistics-show-that-up-to-80-of-watches-on-Netflix-come-from-recommendations-and-the_fig1_386513037

4. Spotify Fan Study (April 2024) on artist discovery through algorithmic features. Spotify Research: https://research.atspotify.com/search-recommendations

5. McKinsey, “New front door to the internet: Winning in the age of AI search.” Available at: https://www.mckinsey.com/capabilities/growth-marketing-and-sales/our-insights/new-front-door-to-the-internet-winning-in-the-age-of-ai-search

6. Amazon recommendation engine and 35 per cent revenue attribution. Firney: https://www.firney.com/news-and-insights/ai-product-recommendations-from-amazons-35-revenue-model-to-your-e-commerce-platform

7. Cass R. Sunstein, “Nudging and Choice Architecture: Ethical Considerations” (2015). SSRN: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2551264

8. Richard H. Thaler and Cass R. Sunstein, “Nudge: Improving Decisions about Health, Wealth, and Happiness” (2008). Yale University Press.

9. European Commission, Deceptive Patterns Study (2022), finding 97 per cent of websites and apps used at least one dark pattern.

10. United States Federal Trade Commission, Dark Patterns Study (July 2024), examining 642 websites and apps. Available at: https://www.ftc.gov

11. DataReportal and Global WebIndex, social media usage statistics (2024-2025). Available at: https://www.statista.com/statistics/433871/daily-social-media-usage-worldwide/

12. MDPI Societies, “Trap of Social Media Algorithms: A Systematic Review of Research on Filter Bubbles, Echo Chambers, and Their Impact on Youth” (2025). Available at: https://www.mdpi.com/2075-4698/15/11/301

13. Journal of Computer-Mediated Communication, “It matters how you google it? Using agent-based testing to assess the impact of user choices in search queries and algorithmic personalization on political Google Search results” (2024). Available at: https://academic.oup.com/jcmc/article/29/6/zmae020/7900879

14. ArXiv, “Algorithmic Amplification of Biases on Google Search” (2024). Available at: https://arxiv.org/html/2401.09044v1

15. ArXiv, “TikTok's recommendations skewed towards Republican content during the 2024 U.S. presidential race” (January 2025). Available at: https://arxiv.org/html/2501.17831v1

16. Tufts University CIRCLE, “Youth Rely on Digital Platforms, Need Media Literacy to Access Political Information” (2024). Available at: https://circle.tufts.edu/latest-research/youth-rely-digital-platforms-need-media-literacy-access-political-information

17. Interactive Advertising Bureau (IAB), “AI Ranks Among Consumers' Most Influential Shopping Sources” (2025). Available at: https://www.iab.com/news/ai-ranks-among-consumers-most-influential-shopping-sources-according-to-new-iab-study/

18. Bloomreach consumer surveys on AI shopping behaviour (2025). Referenced via: https://news.darden.virginia.edu/2025/06/17/nearly-60-use-ai-to-shop-heres-what-that-means-for-brands-and-buyers/

19. PMC, “The Cognitive Cost of AI: How AI Anxiety and Attitudes Influence Decision Fatigue in Daily Technology Use” (2025). Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC12367725/

20. Shoshana Zuboff, “The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power” (2019). PublicAffairs. Harvard Business School faculty page: https://www.hbs.edu/faculty/Pages/item.aspx?num=56791

21. Harvard Magazine, “Ending Surveillance Capitalism” (September 2024). Available at: https://www.harvardmagazine.com/2024/09/information-civilization

22. ResearchGate, “Artificial Intelligence and the Commodification of Human Behavior: Insights on Surveillance Capitalism from Shoshana Zuboff and Evgeny Morozov” (December 2024). Available at: https://www.researchgate.net/publication/387502050

23. Cureus, “Social Media Algorithms and Teen Addiction: Neurophysiological Impact and Ethical Considerations” (2025). Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC11804976/

24. PMC, “Demystifying the New Dilemma of Brain Rot in the Digital Era: A Review” (2025). Available at: https://pmc.ncbi.nlm.nih.gov/articles/PMC11939997/

25. Futures, “An attention economic perspective on the future of the information age” (2024). Available at: https://www.sciencedirect.com/science/article/pii/S0016328723001477

26. Journal of Quantitative Description: Digital Media, news fatigue statistics across 47 countries (2025). Available at: https://journalqd.org/article/download/9064/7658

27. Big Data and Society, “The chat-chamber effect: Trusting the AI hallucination” (2025). Christo Jacob, Paraic Kerrigan, Marco Bastos. Available at: https://journals.sagepub.com/doi/10.1177/20539517241306345

28. Attest, “2025 Consumer Adoption of AI Report.” Available at: https://www.askattest.com/blog/articles/2025-consumer-adoption-of-ai-report

29. European Parliament, “EU AI Act: first regulation on artificial intelligence.” Available at: https://www.europarl.europa.eu/topics/en/article/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence

30. European Parliament, “Regulating dark patterns in the EU: Towards digital fairness” (2025). Available at: https://www.europarl.europa.eu/RegData/etudes/ATAG/2025/767191/EPRS_ATA(2025)767191_EN.pdf

31. Humanities and Social Sciences Communications, “Algorithmic personalization: a study of knowledge gaps and digital media literacy” (2025). Available at: https://www.nature.com/articles/s41599-025-04593-6

32. Metzler, H. and Garcia, D., “Social Drivers and Algorithmic Mechanisms on Digital Media,” Perspectives on Psychological Science (2024). Available at: https://journals.sagepub.com/doi/10.1177/17456916231185057

33. Big Data and Society, “Rethinking the filter bubble? Developing a research agenda for the protective filter bubble” (2024). Jacob Erickson. Available at: https://journals.sagepub.com/doi/10.1177/20539517241231276

34. DemandSage, “Average Time Spent On Social Media” (2026 update). Available at: https://www.demandsage.com/average-time-spent-on-social-media/

35. RSISINTERNATIONAL, “A Systematic Review of the Impact of Artificial Intelligence, Digital Technology, and Social Media on Cognitive Functions” (2025). Available at: https://rsisinternational.org/journals/ijriss/articles/a-systematic-review-of-the-impact-of-artificial-intelligence-digital-technology-and-social-media-on-cognitive-functions/

36. California Management Review, “Humans or AI: How the Source of Recommendations Influences Consumer Choices for Different Product Types” (2024). Available at: https://cmr.berkeley.edu/2024/12/humans-or-ai-how-the-source-of-recommendations-influences-consumer-choices-for-different-product-types/

37. Taylor and Francis, “Reducing echo chamber effects: an allostatic regulator for recommendation algorithms” (2025). Available at: https://www.tandfonline.com/doi/full/10.1080/29974100.2025.2517191

38. Irish Data Protection Commission, TikTok fine of 345 million euros for deceptive design patterns affecting children. Referenced via: https://cbtw.tech/insights/illegal-dark-patterns-europe

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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

What I said about what I said (because I said it weird)

A friend told me she loved the last post, but the title stayed just a bit out of reach for her. And because I like her honesty, and I trust the depth of her understanding, I will not simplify the thought. Instead, I’ll unfold it even more.

What I mean when I say “your future is your neighbor” is a small healthy provocation, yes it is ok, I never said I was cool.

Most people think of society as a system of rules and laws. Even if they’re not written down, they are shared through traditions and habits, creating a set of norms. You can organize these norms to be relatively functional in social life: what is legitimate and what is not, what is accepted and what is rejected, what is implicit and what is explicit. Are you still there?

Now, there’s another way to think about social life. A much richer one, in my eyes.
Let me leave you with this: in a society like ours, deeply sick, being “functional”, fitting in, being comfortable within it, should never be taken as a sign of success, but rather a symptom of your subjection to it.

I personally see social life as a circuit, a network of emotions and affections. These emotional exchanges are what shape relationships: between individuals, between individuals and institutions, between institutions and corporations, you got my point.

And yes we need to think about this, because there is no real way to escape social life. Even if you decide to live alone in a cave, ordering Foodora with “leave it by the door” every day, I can guarantee you the Austrian catholic church will still find you in 72h and ask for a contribution by post.

When I use the word “affections,” I mean literally whatever affects you.
Affections generate effects: answering or not answering the Catholic Church, for example. Paying or not paying that stupid tax. Shakespeare wrote “to be or not to be” in 1600.
Yes, folks, it's 2026 and that’s still the question.

Suddenly, a decision your parents once made of raising you in a catholic community, maybe as the spine of your upbringing, your first interactions, your school years, now comes back in a proposal letter. Kiddo, it’s your turn to decide if you stay as “one of us,” or if you part ways. Do you still want to belong? Pay it. But in my eyes, the cruelest part is this: if you’re not willing to pay it, you have to declare it. You have to contact them and say, to their face, that from now on you’re excluding yourself from the community. They use your affection to subject you into action. And by the way, here is the condition: there is only one legitimate way of being catholic in this country: pay it.

For me, Paula, baptized and raised in the catholic church and schools, it's a no brainer: to be a good christian, in this set up, means keeping a healthy distance from this version of the catholic church you’ve established in this country. But that’s just me. You do you.

I think I’ve made my point about how affections produce effects. These affections shape our tendencies and behaviors, often without us even realizing it. Many times, what moves us to act toward something is not a clearly stated plan or conscious decision, but the feelings we experience without being fully aware of them, without much elaboration.
And these affections circulate not only on a person to person level, but also at institutional, corporate, and political levels. In other words: wherever you find people, you will find affections.

We’re taught that the ideal way to navigate society is rationally. Rationality supposedly allows us to speak in a neutral space where we can say what we want, announce our interests, even clash with one another, and maybe (just maybe) reach a consensus. That’s the “rulebook” we learn back in kindergarten.
There’s no space for passion there. Because passions, or affections, are said to destabilize us. The classic reason versus passion division is more deeply baked into us than we admit.

I would insist that if there’s anything truly “rational” in social life, it’s precisely our affections. They shape our relationships, form our inner lives, and guide how we act on our fantasies, beliefs, and desires. To know yourself, who you truly are, what you can do, and what holds you back from it, means understanding your affections.
I personally don’t believe political changes (or any changes) simply come from new ideas, but from new affections that give rise to new ideas. Coherence definition.

So, when I say “your future is your neighbor,” I am making a wonder. I wonder whether a large part of our blockage in political and social creativity, our inability to imagine new futures, comes from the fact that fear has historically been the core affection of our world.

If a society is built by people who don’t claim this connection to one another, their desires no longer have a natural place to unfold and they end up wanting mostly the same things. And when everyone wants the same things, the only relationships they form are competitive, sometimes even violent. That’s how insecurity is created.
Fear of violence, fear of death, fear of being isolated or undervalued, fear of immigrants, these fears become common affections, our main social drivers. And to deal with that, we invent governments and institutions whose purpose is essentially to protect us from one another.

So now, governments have to keep reminding us that our safety is always at risk. Even intimate relationships are treated like contracts. Want to get married? Declare it at the notary office. Kant would say marriage is a contract between two people for the usufruct of their sexual faculties. I find that hilarious. Imagine coming home and your husband isn’t down for some cuddles, you might as well call the police because he’s breaking the contract.
Want to be part of the Catholic Church? Your signature and 1.1% of your annual taxable income, please.

Jokes aside, what I’m trying to highlight is the absurdity of contracts as the main connector of social relationships, how this twisted logic fails to grasp what’s really at stake. The goal becomes transforming hearts into risk-oriented minds.

When I say “your future is your neighbor,” I choose the word neighbor to play with the idea of this immediate other, the other who is close enough to affect you, even if they don’t resemble your idea of yourself. The only way to escape this installed logic of fear is to practice affection as your core mode of being. And if you do that long enough, you learn something real, and eventually you’re able to extend your sense of closeness far beyond your own street.
That’s what real change looks like to me.

/feb26

It's been one day since we broke up. I've had an incredibly crushing pain in my chest pretty much since then and I've spent most of today trying not to cry, or going to my car, or walking and breaking down crying. It hurts really fucking bad even though I know that it's honestly for the best. I cry as much as I can and then I start to feel a little bit better for a little bit until I see something or I hear something that reminds me of her and it hurts all over again. I walked really far from my work in the middle of kind of nowhere and I looked down and I see UCSD health, and it reminds me of her. I remember on one of her dates she started to have a floater in her vision, and for her that’s potentially a sign of her retina detaching and so we left the bookstore and I took her straight to the specialist. I then sat with her for four hours, and I relayed all the information to her mom while trying to keep her anxiety down. Her genetic condition makes her life really fucking difficult. And I remember that I didn’t think about how she went blind how she might not be able to do any of the things she likes to do, or the things we do together, for the things she needs to do for money, but rather I thought about how I could maybe bring back some of the hobbies she has to her. Or how we could find new things together. I thought it would be a really sweet present as a surprise if I got myself tested for the gene that she has so that I can show her that we can have kids without the risk. I thought it was such a pure form of love.

I feel like my chest is crushed, and I can’t think. The grief is so fucking big. I think about the pictures of her, and almost all of my favorites are of her. There were a lot of really nice things. And there were also a lot of really bad things. And I wish it could’ve worked out, but what I mean by that is I wish that there bad things weren’t there. But you cannot pick and choose parts of a person.

I believe that in the future I will have a partner that is emotionally mature and listens to me and makes me feel safe. In the future I will not have to feel like I have to fully explained and archive my emotions as much, because hopefully they will have the knowledge and empathy required to understand a bit more. I think I’ll have a partner who will genuinely make me laugh in clever and smart ways that I get to steal. I’ll have someone who will teach me things also, and that will have meaningful and insightful conversations with me. I won’t feel like I’m being patronizing, and I won’t have to worry about stepping on any insecurities or ego. I will have a partner who values my feelings and interests as much as their own, if not more. I will have someone who is very thoughtful and take the time to truly understand me. I’ll have someone who is considerate to me and kind in minor ways, without asking for recognition. I will have a relationship where conflict could be resolved through effective conversation, both with understanding their own thoughts, but also compassion behind them. I will not feel like I am having a one-sided argument, and I will not feel like I have to regulate someone’s emotions for them.

It’s such a weird thing to have this grief. I both recognize that the relationship was not one that should’ve continued, and it is absolutely a good thing that it ended. I know that no matter what it is going to be incredibly painful to end, even if that is the right decision. But that exists in a part of my mind, that remains un mixed like oil and water. And next to it are all of the beautiful memories. All of the sweet and kind things that she did. And how loved I felt. How much I felt like she tried, and how many times I felt hope.

I think during the relationship I got swept up in a lot of the fantasy of what the future could look like. And I think that’s part of what I’m mourning so much. I don’t know what to do with all of these sweet memories and little things that I didn’t even know I remembered until now. And it’s just a wave after a wave that hits me. It sucks because the highs were so high. She really was a drug to me.

I have a feeling that time will heal this, but it’s terrified because time happens so slowly. And I just wanna know what I can do to stop this feeling because it kills me so much. I feel so horribly sick to my stomach. There were a lot of things that I didn’t like about her, not in the sense that like they were big issues at all but just things that I wasn’t crazy about.

I started writing more things on the list of things I didn’t like, and also fundamental reasons why the relationship would not work out. I feel cruel doing it from being honest, but I need some sort of a way to leave this nostalgia behind. I can always return to the place of the nostalgia, but there will be nothing left. There will not be the illusion that things could just be getting better and this was just a perfect storm, or that this would be the last time these issues happen and then we would be good. Issues just kept happening, and perfect storms just kept happening. At some point there is too much coincidence and I have to acknowledge the fact that past behavior is the best indication of future behavior.

I am absolutely a good partner, and a catch. I don’t think I’m perfect, and I don’t think that I wouldn’t hurt a partner accidentally, but I think that I have shown a consistent commitment to listening and understanding my partner, and I have the tools and the drive to change. I also believe that I am attractive, I am kind, I am genuine, I am funny, I am successful, I am generous, I am very loving, and I think that I am happy with the person that I am. And that person includes the fact that I want to consistently continue to improve as a person, and this relationship has shown me several ways where that is important.

I think a big thing I learned was how easy it is for me to fall into codependency. I absolutely struggled with loneliness when I moved here. And in a way I am grateful for the pain that comes from this entire situation because that both taught me how important it is, while also reminding myself that I absolutely have the tools to find and foster connection. I’m thankful that I have friends around me, and I’m thankful that I know that I will survive this. It’s absolutely going to hurt, but this isn’t just the price of good things. This is serving as a reminder and an incentive for my mind to recognize the hard choices that I needed to make along the way, and the things that I need to look at in myself. Every day will be easier than the last. At least in the amortized sense. I won’t have to worry about fixing the current issue, if me talking with someone else or spending time with someone else leads to their stabilization, if that destabilization leads to her interacting with bad groups of people online, like e daters, or feeling the anxiety and fear of not knowing what she is hiding from me. My sister said something very hopeful, there are actually a lot of good families out there. There will be plenty of kind families that will welcome me with kindness and the same sense of inclusion that E’s family did. There was nothing in E that is unique and unobtainable again. I may not find all of the same things in a partner, but my wants will change too.

If nothing else I’ve learned how easy it is for me to love. I don’t need someone to be my everything, I don’t need them to like all of my hobbies, and share all the same interests. I’m grateful for that experience since it let me learn firsthand both the good and bad things with that. I have faith it will be ok in the end.

In Summary: * Listening now to the Flagship Station for IU Sports ahead of tonight's game with my Indiana Hoosiers vs the Northwestern Wildcats at IU's Assembly Hall in Bloomington, Indiana. This game is the last item on my day's agenda. That, and wrapping up my night prayers. Then I'll be putting these old bones to bed

Prayers, etc.: * I have a daily prayer regimen I try to follow throughout the day from early morning, as soon as I roll out of bed, until head hits pillow at night. Details of that regimen are linked to my link tree, which is linked to my profile page here.

Starting Ash Wednesday, 2026, I'll add this daily prayer as part of the Prayer Crusade Preceding the SSPX Episcopal Consecrations.

Health Metrics: * bw= 227.63 lbs. * bp= 140/83 (62)

Exercise: * morning stretches, balance exercises, kegel pelvic floor exercises, half squats, calf raises, wall push-ups

Diet: * 06:15 – fruit pastry * 08:05 – 1 peanut butter sandwich, 1 banana * 12:45 – cooked meat, stuffed dumplings * 15:15 – 1 fresh apple

Activities, Chores, etc.: * 04:00 – listen to local news talk radio * 05:00 – bank accounts activity monitored * 05:20 – read, pray, follow news reports from various sources, surf the socials, and nap * 15:20 – listen to KONO 101.1 * 17:00 – tune into the streaming feed for The Flagship Station for IU Sports ahead of tonight's game

Chess: * 11:00 – moved in all pending CC games

I woke up to the news that the Tin Building had closed. The day was a surprise, but it was well known that the food hall at the Seaport was not doing well. We loved the Tin Building. It was a swanky celebration of everything that tastes good, with multiple bars, restaurants, and shops. You walked in and found yourself in a different world. A luxury cruise ship would be a good comparison, and that was fine with us. Alas, early last year, the vibe changed. Some venues, like the vegetarian restaurant, were closed or “merged.” When we wanted to buy fish for dinner, we found an empty bed of ice at the fish store. In summer, I was looking for lunch at the sandwich bar, but I was not too surprised to be redirected to the bakery for pre-made dishes. There were financial reasons for all of this, but it’s hard to shrink your way to greatness if luxury and abundance are what you’re after. Thanks to everybody who made this place such a delightful experience and always gave us a friendly welcome.

And It's OK.

#blog You are not going to read random triggering goonbabble. I have reached a different point in my pornosexual journey. Goonbabble is good for likes, but everyone always takes pause when you lay things out real and really present gooning as an actual lifestyle. Not something you do and think you are good at because you are 'in the moment.'

Since 2023, my life took a major shift from my old self. My past traumas built up and broke me. I took a stand and said no to the things that hurt me. I was getting older. The traditions others cling to were not working for me. In fact, they were the very same systems that chipped away at me until nothing was left, and I caved in under my own stress.

When I began to rise as something new, I turned to porn and masturbation. I turned to gooning. It was a way to really help soothe the wounds and settle into what is important. I was able to find what is safe and what works for me. Over time, I was able to find all the pleasures I could never find or receive from another person.

It became a quest to remove all hints of duality. Finding balance with porn, finding balance with normie bullshit, and having them all swirl around and co-exist.

The end result is you get something raw and forward and open. Something unapologetic. But then I recently came to a core realization.

The blending and elimination of duality go both ways. It's not just about letting porn in. It's also letting yourself exist with porn. I'm still learning more about myself. I'm learning how I react to certain situations, my flaws as I interact with others, and what I should do to course correct.

This year I am taking a different path in my continued evolution. Aspects of my 'original' self and porn self are having honest negotiations, and things are slotting in a different way.

I can proudly say I'm not normal.

How I do things, how I say things, my viewpoints, my actions… they probably do not make much sense to anyone but me, and that's ok. I have always had my own way of doing things, my own flow, my own flavor. That never changed. That always stayed.

It shows in how I carry myself and how I interact with others.

I have a pretty narrow band of social compatibility. I look for certain types of interactions and conversations. I'm quick to filter out things that do not suit me in that avenue. I'm not just “saying no,” but I am curating an online persona where nonsense and low-level conversations do not thrive.

My message encouraging black women to sexually liberate themselves will always be true. But how it looks to others may not be liked, or even fully understood. I accept that. But I am solidifying an identity. I'm not “just another porn account.” There is thought in an action, what I do, and how I do it. And to fully realize that, I have to own my decisions and do things differently.

I am an artist. I create. I influence. The core of my creativity is porn, but what grows out of this is an ecosystem of writing, ambient music, and content curation for women who are rarely seen and fully understood.

A relatively recent discovery for me has been the writing of George Saunders. Less than two years ago I belatedly came around to reading his excellent novel Lincoln in the Bardo. Since then I've also read Liberation Day (his latest collection of short stories) and A Swim in a Pond in the Rain (his book about reading and writing short stories) — greatly enjoying them both. The other weekend I picked up a nominally signed copy of his new novel Vigil from Rossiter Books in Monmouth – in which the 'signature' resembles a monogram more than a fully written-out name. Now I've read that one too, finishing it on Sunday morning.

Like Lincoln in the Bardo its setting straddles the line between life and death. Vigil's protagonist is Jill Blaine, one of the departed, who has found a posthumous vocation in providing solace and guidance to those struggling with the hard work of dying. The book begins with her arrival at the home of her latest, and most challenging charge – former oil-company supremo K.J. Boone. Little does she know that others of her kind have their own axes to grind with the moribund patient. Unlike the earlier novel, this is a short book, running to only 172 pages. Saunders' mastery of short-form fiction is much in evidence in a narrative well-stuffed with telling details. For me it was another very satisfying read, though I did wonder if the story's moral dimension may have slightly inhibited some of its characterisation.

After that, I read Karin Tidbeck's novel The Memory Theater in just a couple of days. At 221 pages it is likewise fairly short. This is an idiosyncratic and inventive work of fantasy with elements of folklore and fairy-tale. If it weren't for all the violence one might recommend it to older children on account of its charming lightness of touch (of course some children might like it because of the violence). It kept me absorbed and entertained throughout. Interestingly, Tidbeck, who is Swedish, wrote it in English. The implied off-stage demise of its antagonist, the memorably callous Lady Augusta Prima, seemed to leave an opening for her potential return in a sequel.

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There have been a couple of new musical arrivals this week. On Friday a CD copy of Patricia Brennan's recent album Of The Near And Far arrived in the post. Her contribution on vibraphone to Mary Halvorson's ‘Amaryllis’ ensemble had impressed me, and led me to look for music with her name on it. I first bought her 2022 album More Touch. That one, however, I'd found pointily percussive in a way that tended to jangle my nerves, meaning I didn't listen to it often. What I'd caught of Of The Near And Far on-line suggested this newer album might be a more readily approachable one with some smoother surfaces. And, in general it is, though there are some more jagged moments too, especially on the track 'Andromeda'.

It's music apparently inspired by the night sky, with five of the seven tracks named after constellations and in various ways (explained in the booklet notes) musically inspired by them. As well as Brennan on vibes, there are parts for piano, guitar, bass, drums, live electronics and string quartet. Of the other musicians I was only hitherto familiar with the pianist Sylvie Courvoisier, whose album Chimaera I own. Both Courvoisier and Brennan are exponents of somewhat demanding jazz that is out toward the further edges of (and occasionally beyond) what I can enjoy. My mood isn't always right to sit down with this kind of thing, but, on the right day I do appreciate it. An example track: 'Aquarius'.

Left outside my door in the rain the following day a vinyl copy of the new album by The Olympians: In Search Of A Revival. Thankfully the record inside the wet cardboard was protected by plastic wrap. I'd come to the self-titled debut by the band only a few years ago, since when it's been one of the most frequent return visitors to my turntable. Here we have slices of more of the same only different – servings of high-quality backward-looking instrumental funk & soul that are a straightforward joy to hear. Hear, for example, ‘California’. Too often to buy new vinyl is to navigate a minefield of substandard pressings: I’ve had no such trouble with the Dap-Tone label and its offshoots, whose quality control I have found consistently first-rate.

First day at the new job, and the new company has a lot of fires to put out, but this environment might just be the place where I can thrive. I had an otherwise chill day, ending it with a call with my hoarse-voiced partner.

In Between

Somewhere in between

Desperate prayers for miracles and Eager waiting for the end of the world

Millions of brothers and sisters wander and wonder What does this thing called faith mean to my life today?

Northwestern at Indiana

Tonight my plan is to listen to an NCAA men's college basketball game between the Northwestern Wildcats and the Indiana Hoosiers. I'll be listening to the Flagship Station for IU Sports for the call of the game and for pregame and postgame coverage. With the game's scheduled start time of 6:00 PM CST, this fits perfectly into my nighttime routine.

And the adventure continues.

My disdain for Dispensationalism is no secret.

It fails to discern the unfolding of God's saving plan for humanity. It fails to properly understand the fulfillment of the Old Testament in the New. It flies in the face of the Church's consistent and universal understanding of Scripture. It is a novel scheme that is heterodox, at best, and heretical in some of its variations (I'm looking at you, John Hagee).

Here is the summary of a Roman Catholic explanation of Dispensationalism and Zionism that does a great job succinctly dismantling this interpretive system, which (thankfully) is waning in popularity and influence:

Christ is the fulfillment of the Old Testament. He is the New Covenant, which established the new Jerusalem, the Church, at the cost of His own blood, which does not seek to rebuild the Temple in Jerusalem, let alone advocate a Zionist political state.

The promise of the land was always inseparable from the Temple: “you are to seek the place the Lord your God will choose from among all your tribes to put his Name there for his dwelling. To that place you must go” (Deuteronomy 12:5). Since an earthly Temple is no longer wanted by God, for Christ Himself is the Temple—“Destroy this temple, and I will raise it again in three days” (John 2:19)—the religious reasons Christian Zionists hold that a physical land is necessary are obsolete since the Messiah became the Temple and sign of the land.

The entire article is worth a read.

#theology

Jag har ett komplicerat förhållande till Spotify-spellistor. Å ena sidan är de fantastiska – någon annan har gjort jobbet att kurera musik så jag slipper. Å andra sidan är många av dem... no ja, inte särskilt bra. Men hur vet man skillnaden? Hur bedömer man om en spellista faktiskt är värd att lyssna på?

Det var precis den frågan som Isitagoodplaylist.com skapades för att svara på, och jag älskar dem för det.

Vad är Isitagoodplaylist?

Isitagoodplaylist.com är en tjänst som analyserar Spotify-spellistor och ger dem betyg baserat på olika parametrar. Du klistrar in länken till en spellista, och sajten ger dig en detaljerad rapport om hur bra (eller dålig) den faktiskt är.

Det är som att ha en musikrecensent som faktiskt använder data och statistik istället för bara vaga känslor. Och i en värld där Spotify har miljontals spellistor är det här exakt den typ av kvalitetskontroll som behövs.

Tjänsten är gratis att använda, enkel att förstå, och ger faktiskt användbara insikter. Det är en av de där tjänster som gör en sak och gör den riktigt bra – inget krångel, inga onödiga funktioner, bara ren spellistanalys.

Hur fungerar analysen?

När du analyserar en spellista på Isitagoodplaylist kollar tjänsten på flera olika faktorer:

Popularitet och diversitet - Är det bara mainstream-hits eller finns det en mix av kända och mindre kända låtar? En bra spellista balanserar det bekanta med det upptäckande. Om allt är top 40-hits är det kanske inte den mest intressanta spellistan. Om allt är obscurt indie-material med 50 lyssnare per låt kan det vara för nischat.

Artistrepetition - Hur många gånger dyker samma artist upp? Om en spellista påstår sig vara om “90-talets rock” men består av 15 Nirvana-låtar och ingenting annat, ja då är det inte riktigt en bra representation av eran. Bra spellistor sprider ut sig över flera artister.

Release-datum - När släpptes låtarna? En “2020s hits”-spellista borde inte vara full av låtar från 2015. En “klassiker”-spellista som mest innehåller musik från förra året är kanske inte riktigt genomtänkt.

Energi och tempo - Spotify har data om varje låts energinivå och tempo. Isitagoodplaylist använder det för att se om spellistan har ett bra flöde. En träningsspellista borde ha hög energi. En chill-spellista borde ha lägre tempo. Om det är kaos är det ett dåligt tecken.

Längd och sammanhållning - Hur många låtar innehåller spellistan? Finns det en röd tråd eller är det bara random låtar slängda ihop? Vissa spellistor är tydligt kurerade med omtanke, andra känns som att någon bara klickade “lägg till” på sin “liked songs” tills de blev trötta.

Alla dessa faktorer vägs samman till ett övergripande betyg. Det är inte en perfekt vetenskap – musik är subjektivt – men det ger en riktigt bra indikation på om en spellista faktiskt är genomtänkt eller bara slarvigt hopkastad.

Varför spellistkvalitet spelar roll

Du kanske tänker: “Men varför bry sig? Om jag gillar låtarna spelar väl resten ingen roll?” Och på sätt och vis har du rätt. Men en bra spellista är mer än bara bra låtar – det är en upplevelse.

En välkurerad spellista tar dig på en resa. Den har ett flöde, en uppbyggnad. Den introducerar dig till ny musik utan att chocka dig. Den balanserar det bekanta med det överraskande. Det är skillnaden mellan en random shuffle och något som faktiskt är designat för att lyssnas på från början till slut.

Dåliga spellistor å andra sidan? De hoppar mellan genrer utan mening. De repeterar samma artister tråkigt. De har inget flow – ena sekunden lyssnar du på lugn jazz, nästa sekund dunkar hardcore techno i öronen. Det är uttröttande.

Isitagoodplaylist hjälper dig identifiera skillnaden innan du slösar bort din lyssartid. Och i en värld med oändlig musik är din tid faktiskt värdefull.

Curators och spellistskapare

En av de coolaste funktionerna på Isitagoodplaylist är att du kan följa specifika curators. Om någon konsekvent gör bra spellistor kan du se alla deras listor på ett ställe.

Ta till exempel den här curatorn eller den här. Du kan se alla deras spellistor, hur de betygsatts, och få en känsla för deras kurerings-stil.

Det är lite som att hitta en bra filmrecensent – när du väl hittat någon vars smak överensstämmer med din kan du lita på deras rekommendationer. Fast istället för filmer handlar det om spellistor.

För oss som faktiskt bryr oss om att göra bra spellistor är det här också en sorts kvalitetssäkring. Jag har själv analyserat spellistor jag skapat, fått feedback på vad som kunde förbättras, och gjort ändringar. Det är som att ha en editor för dina musikaliska kurering.

Spotify-ekosystemet och spellistkultur

För att förstå varför Isitagoodplaylist är värdefullt behöver vi prata om hur gigantiskt Spotifys spellistekosystem faktiskt är. Det finns miljontals spellistor. Bokstavligen miljontals. Vissa är officiella Spotify-listor, vissa är från stora medier, men de allra flesta är skapade av vanliga användare som du och jag.

Problemet är att kvaliteten varierar extremt. Vissa spellistor är mästerverk av kurering – de berättar historier, de introducerar perfekt balanserad ny musik, de har tagit timmar att sätta ihop. Andra är... ja, mindre genomtänkta. Någon klickade på “skapa spellista”, drog dit 50 random låtar, gav den ett generiskt namn som “Chill Vibes” och tänkte inte mer på det.

Spotifys sökfunktion hjälper inte heller särskilt mycket. Om du söker efter “workout music” får du tusentals resultat. Hur väljer du? Antalet följare är inte alltid en bra indikator – populära spellistor kan vara populära av fel anledningar, eller för att de fick en viral boost en gång men egentligen inte är bra.

Det är här Isitagoodplaylist kommer in. Det ger dig ett objektivt sätt att utvärdera spellistor baserat på faktiska metriker, inte bara popularitet eller gut feeling.

Användbara use cases

Jag använder Isitagoodplaylist i flera olika situationer:

När jag hittar en ny spellista - Innan jag börjar följa och lyssna analyserar jag den snabbt. Får den bra betyg? Då är det värt min tid. Får den dåligt betyg kan jag skippa den och leta vidare.

När jag jämför liknande spellistor - Om jag söker efter “80s synthpop” och hittar 20 spellistor med samma tema kan jag analysera dem alla och välja den bästa. Det är mycket effektivare än att lyssna igenom alla.

När jag förbättrar mina egna spellistor - Jag skapar själv spellistor ibland, och det är supervändbart att analysera dem för att se vad som kunde förbättras. Kanske repeterar jag samma artist för ofta? Kanske är tempot för ojämnt? Analysen visar det direkt.

När jag upptäcker nya curators - Om en spellista får högt betyg kollar jag vem som skapat den och följer dem för att se vilka andra spellistor de gjort. Det är ett bra sätt att hitta pålitliga musikskapare.

När jag bevisar en poäng - Okej, det här är kanske mest för skojs skull, men när någon säger “den här spellistan är awesome!” och jag tycker den är trash kan jag analysera den och visa med data varför den faktiskt inte är så bra. Ja, jag är den typen av person.

Begränsningar och vad tjänsten inte gör

Isitagoodplaylist är fantastiskt för vad det gör, men det är viktigt att förstå dess begränsningar. Det analyserar objektiva metriker – data, statistik, mätbara faktorer. Det kan inte bedöma subjektiv musiksmak.

En spellista kan få perfekt betyg på alla tekniska parametrar men ändå inte vara något du gillar om musiken inte är din stil. Omvänt kan en spellista få lägre betyg men vara exakt vad du söker om du specifikt vill ha något nischat eller ovanligt.

Tjänsten kan heller inte ta hänsyn till kontextuella faktorer. En spellista avsedd för en specifik fest med specifika människor kan bryta mot alla “bra spellista”-regler men ändå vara perfekt för just den situationen.

Så använd Isitagoodplaylist som ett verktyg, inte som absolut sanning. Det ger dig värdefull information, men du måste fortfarande använda ditt eget omdöme.

Jämförelse med andra spellistverktyg

Det finns andra verktyg för att analysera Spotify-spellistor, men Isitagoodplaylist sticker ut för sin enkelhet och fokus. Vissa verktyg ger dig omfattande statistik och grafer – vilket är coolt om du är data nerd, men överväldigande om du bara vill veta “är det här en bra spellista?”.

Isitagoodplaylist ger dig svaret rakt på sak. Ett betyg, några nyckelmetriker, klart. Du kan dyka djupare om du vill, men du behöver inte. Det är användbarheten som gör det värdefullt.

Andra verktyg fokuserar mer på att skapa spellistor eller hitta ny musik. Isitagoodplaylist fokuserar specifikt på att utvärdera befintliga spellistor. Det gör en sak och gör det bra, vilket jag alltid uppskattar.

Framtiden för spellistkurering

Jag tror att verktyg som Isitagoodplaylist blir allt viktigare. Mängden musik på streamingplattformar växer exponentiellt. Spotify lägger till tiotusentals nya låtar varje dag. Antalet spellistor växer i samma takt.

I den miljön behöver vi verktyg för att filtrera och utvärdera. Vi kan inte lyssna på allt. Vi kan inte analysera varje spellista manuellt. Vi behöver sätt att snabbt identifiera kvalitet så vi kan spendera vår lyssartid på det som faktiskt är bra.

Jag föreställer mig en framtid där Spotify själva integrerar liknande funktionalitet – kanske betyg eller kvalitetsmarkeringar direkt i appen. Men tills dess finns det tredjepartstjänster som Isitagoodplaylist, och jag är tacksam för det.

För spellistskapare – förbättra ditt hantverk

Om du själv skapar spellistor (vilket du borde om du bryr dig om musik) är Isitagoodplaylist ett ovärderligt verktyg för att förbättra ditt hantverk. Det ger dig konkret feedback på vad som fungerar och inte fungerar.

Kanske upptäcker du att du repeterar samma artister för ofta. Kanske är ditt tempo för ojämnt. Kanske blandar du årtionden på ett sätt som inte fungerar. Analysen visar det, och du kan justera.

Det är som att ha en coach för spellistskapande. Det kommer inte göra jobbet åt dig – du måste fortfarande ha bra musiksmak och kuratorisk känsla – men det hjälper dig identifiera blinda fläckar och förbättringsområden.

Jag har själv blivit en bättre curator tack vare den här typen av feedback. Mina spellistor har bättre flow nu, mer variation i artister, bättre balans mellan bekant och nytt. Det märks när människor faktiskt lyssnar hela vägen igenom istället för att hoppa efter tredje låten.

Social aspekt och delning

En underutnyttjad del av Isitagoodplaylist är den sociala aspekten. Du kan dela dina spellistanalyser, visa upp bra curators du hittat, och diskutera vad som gör en spellista bra.

Det är kul att jämföra spellistor med vänner. “Min workout-spellista fick 8.5, vad fick din?” Det är nördigt, ja, men om du ändå är musiknörd (vilket du förmodligen är om du läser det här) är det rätt typ av nördighet.

Vissa använder det också som ett sätt att visa upp sina kuratoriska skills. “Alla mina spellistor får över 8.0 rating” blir ett sorts kvalitetsmärke. Det är lite som att ha ett bra credit score, fast för spellistor.

Varför jag bryr mig om spellistkvalitet

Låt mig vara ärlig om varför det här spelar roll för mig personligen. Musik är en enorm del av mitt liv. Jag lyssnar på musik flera timmar varje dag. Och hur jag lyssnar – i vilken ordning, i vilken kombination – påverkar faktiskt min upplevelse.

En bra spellista kan förvandla en tråkig pendling till något njutbart. Den kan göra ett träningspass mer effektivt. Den kan sätta rätt stämning för ett socialt sammanhang. Den kan introducera mig till artister jag aldrig skulle hittat annars.

En dålig spellista gör motsatsen. Den bryter flödet, den irriterar, den får mig att vilja byta. Det är slöseri med tid och potential.

Så för mig handlar spellistkvalitet om att respektera musiken och respektera min egen tid. Det handlar om att vara medveten om att kurering faktiskt är en färdighet, inte bara “släng ihop några låtar och hoppas på det bästa”.

Kom igång med Isitagoodplaylist

Om du har blivit nyfiken (vilket jag verkligen hoppas) är det superenkelt att komma igång. Gå till isitagoodplaylist.com, klistra in länken till en Spotify-spellista, och vänta några sekunder medan analysen körs. Boom, du har ett betyg och detaljerad feedback.

Börja med att analysera dina egna spellistor om du har några. Det är både ödmjukande och lärorikt. Sedan kan du analysera spellistor du funderar på att följa. Jämför liknande spellistor för att se vilka som faktiskt är bäst kurerade.

Om du hittar curators som konsekvent gör bra spellistor, följ dem! Det är guldvärt att ha källor till kvalitetssäkrad musik. Och om du själv börjar skapa spellistor, använd analysen för att kontinuerligt förbättra ditt hantverk.

Slutord – spellistor som konst

Det är lätt att tänka på spellistor som något casually – bara en lista med låtar. Men bra spellistskapande är faktiskt en konstform. Det kräver musikkunskap, kuratorisk känsla, förståelse för flow och dynamik. Det är lika mycket konst som att DJ:a eller mixa.

Isitagoodplaylist hjälper oss att erkänna och värdera den konsten. Det ger oss verktyg att identifiera kvalitet, lära oss vad som fungerar, och kontinuerligt förbättra oss som både konsumenter och skapare av spellistor.

I en värld med oändlig musik är kurering det som gör skillnad mellan kaos och upplevelse. Det som skiljer random shuffle från något meningsfullt. Det som gör att vi faktiskt hittar och njuter av musik istället för att drunkna i överväldigande valmöjligheter.

Så nästa gång någon delar en spellista med dig, eller du hittar en som ser lovande ut, ta 10 sekunder och kör den genom Isitagoodplaylist. Det kan rädda dig från timmar av medioker lyssning. Eller det kan bekräfta att du hittat en pärla. Oavsett vilket är det värt att veta.

Och om du själv skapar spellistor – ta det på allvar. Använd verktyg som Isitagoodplaylist för att bli bättre. Din framtida själv, och alla som lyssnar på dina spellistor, kommer tacka dig.

Musik är för viktig för att slösas bort på dåligt kurerade spellistor. Isitagoodplaylist hjälper oss säkerställa att vi faktiskt lyssnar på det bästa. Och det är något jag definitivt kan stå bakom.