Like tendrils weeping a static calm, this heart blunders into a facsimile of rendered fluctuation. Drip-by-faltering drip its counterfeit pace soothes me into oblivion...

Trigger spooled with lacking grace, attention's drilled to sag and waste away the qualms that seethe and spore to hungers chewing evermore.

Pump! Pump! I drop a load. Spiral on a quest foretold past time and space of status quo in cracks exploding what we know.

Without a map. Without a name. Without a test or wage to blame the nuisance ringing in my ear that chants of falsehoods claiming fear.

I'm ragged, worn, and filtered meek. Lost to all but drones who seek the bite that barks where ends maim fame and darkness wrongs a righteous bane.

Like tendrils weeping a static calm, this heart blunders into a facsimile of rendered fluctuation. Drip-by-faltering drip its counterfeit pace soothes me into oblivion...

—point blank—

© 2026 AnOublietteofThought. All rights reserved.

musical inspiration https://youtube.com/watch?v=OF3yBbLrkEY&is=73tjCqwmNzZPy66A

Chapter 1: The Question I Would Have Kept to Myself

The notebook is open beside your dinner plate, and there is a sentence you wrote down earlier that you cannot stop looking at. You heard it during a conversation about Jesus, and at the time it seemed clear enough to change something. Now the house is quiet, your phone is charging by the sink, and the sentence feels harder to understand. You know you agreed with it. You are not sure you are ready to live it. That small distance between agreement and willingness is what draws me to imagining an ordinary listener at the Sermon on the Mount. I think about the long walk home afterward, when there was no crowd to carry the excitement for you.

I have listened to people describe powerful moments of faith and wondered what they took into the following day. That is part of what interests me about what an ordinary person might have felt hearing Jesus teach on the mountain. I don't mean whether the person could describe the setting or repeat every word. I mean what happened when the sound of His voice was no longer filling the air and they were left alone with something they did not know how to answer. We often imagine that meeting Jesus would make our inner life simple. I wonder whether, for some people, hearing Him might first have made them more honest about how complicated it was.

There is a connection here to the quiet changes that begin after an encounter with Jesus, because I don't believe every meaningful response announces itself right away. A person may leave with a question that will not settle. They might discover that a habit they once defended has become difficult to excuse. They might want to believe what Jesus said about the Father and still find themselves afraid to trust. Scripture does not tell us what every listener thought as they went down that hill. I want to respect that silence instead of putting imagined speeches into their mouths. But I can bring my own questions to the words Matthew has preserved.

One question is uncomfortable to admit. If I had been there, would I really have wanted Jesus to tell me the truth, or would I have wanted Him to make me feel better about the life I was already living? It is possible to want God near while hoping He will leave certain doors closed. We may welcome His kindness and still resist the moment when kindness exposes something we have been avoiding. There are conversations we do not want to have, attitudes we have renamed as personality, and little compromises we explain to ourselves so often that the explanation begins to feel like truth.

Think about the person who sends a warm message to an old friend while quietly hoping the friend will not ask to meet. The friendship has become uneven, and they are tired of always being the one who reaches out. They do not know how to say that without sounding unkind, so they continue writing cheerful sentences they do not fully mean. It is not a terrible act. It is the kind of small dishonesty that grows when we are afraid of disappointing somebody. Sometimes the most faithful next step is neither another false promise nor a cruel rejection. It is a kind, clear conversation about what we can honestly offer.

That example might seem far away from a hillside in Galilee, but the teaching Jesus gave repeatedly reaches beneath the visible action. In Matthew 5, He talks about anger and contempt, not only the violent act everyone already knows is wrong. In Matthew 6, He speaks of giving and prayer, then asks His listeners to examine whether they are doing those things to be noticed. He cares about the part of a life that other people cannot easily see. Those passages make me wonder how often I have been satisfied with appearing considerate while leaving my real motives untouched.

I do not think the answer is to become suspicious of every kind impulse. That would make us so busy examining ourselves that we would forget to love anyone. The point is simpler and more demanding. We can give ourselves permission to be truthful before God. If we are doing something because we want praise, we can admit it. If we are afraid of an honest conversation, we can say so. If we have begun to resent a responsibility that we freely accepted, we can ask for wisdom about how to handle it. We do not need to invent a better version of ourselves before coming to Jesus.

The poor in spirit are the first people Jesus calls blessed in Matthew 5. I come back to that because admitting need does not fit the way many of us have been taught to present ourselves. We want to arrive with a thoughtful answer, a tidy account of our progress, and some proof that we deserve to be heard. But the words of Jesus make space for people who know they do not have enough in themselves. Recognizing that need is not the end of faith. It may be the first time we have stopped trying to conceal the reason we need grace.

Perhaps someone who heard Him that day went home with a truth they could not yet practice. Perhaps another felt comfort in a place that had been sore for years. Those are possibilities, not claims about people Matthew never names. What I know is that we can hear the same teaching now, and our reluctance does not have to end the conversation. We can tell Christ what we are afraid His words will require of us. We can ask for help taking one honest step instead of promising a sudden transformation we cannot sustain.

The notebook is still open when you finish dinner. You do not add a long resolution beneath the sentence. You write down the name of the friend you have been avoiding and decide to speak plainly with them tomorrow. You may not find the right words on the first attempt. There may still be discomfort, and the friendship may need a different shape. But the teaching has already moved beyond a line you admired on a page. It has reached a place in your life where you can no longer pretend you have nothing to decide.

Chapter 2: The Hours Nobody Knows You Gave

At five in the morning, the hallway light is still on because you never got around to turning it off. You have been awake twice to help someone you love get comfortable, and now you are rinsing a cup that held the last dose of medicine. The house is quiet enough that you can hear water moving through the pipes. Later, when people ask how things are going, you will probably tell them you are managing. It is a convenient answer. It protects them from a long explanation and protects you from discovering that they did not really want one.

There are ways to feel invisible even when people depend on you every day. You remember their appointments, fill out forms they cannot manage, and notice when something in the house needs attention. You do these things because they matter, and because the person needs you. But somewhere beneath that love is another feeling you are embarrassed to admit. You want somebody to understand how much it costs. You want one person to see the hours you have given without asking you to explain why you are tired. When no one does, you wonder whether the work itself has started to disappear.

That is where I would want to listen closely if I were standing on the hillside with Jesus. I would not be waiting for Him to give me a grand purpose or tell me that my life was more important than other people's lives. I think I would want to know whether God notices a person when there is nothing remarkable to notice. Would He see the one who stays up late to help another person? Would He see the person who does the right thing with some resentment still tangled in their heart? Would He notice the help that is given awkwardly, imperfectly, and without anyone saying thank you?

In Matthew 6, Jesus speaks of giving and praying without making a performance of them. He warns against practicing righteousness in order to be admired, and He speaks of the Father who sees what is done in secret. I have often thought about the difference between wanting to be praised and wanting to be known. They are not always the same thing. Sometimes we want applause because we hope it will make us feel superior. Other times we want recognition because we are exhausted and afraid that what we have done has cost us more than anyone understands. Jesus' words can confront our pride without mocking our need to be cared for.

I would be careful not to turn that teaching into another burden for the person washing the medicine cup. If someone said, “God sees you, so you shouldn't need any help,” they would be asking Scripture to excuse their own absence. Being noticed by our Father is not an instruction to carry every responsibility alone. There are times when loving someone includes calling a sibling, asking a neighbor to bring a meal, or telling a doctor that the arrangement at home is no longer sustainable. We can be faithful and worn out at the same time. We can trust God and still need other people to show up.

What changes, then, when Jesus tells us the Father sees in secret? For me, it changes the part of the evening when I begin to resent how little evidence there is of what I have done. A wiped counter becomes dirty again. A person who felt better yesterday needs help again today. The task leaves no monument. But if God sees the life being lived, its worth is not determined by whether somebody else remembers it. That does not make the labor easy. It does keep me from believing that unnoticed love is the same thing as wasted love.

Jesus also teaches His listeners how to pray. In Matthew 6:8, He says their Father knows what they need before they ask Him. I find that sentence especially tender when I imagine someone who no longer has the strength to organize a proper prayer. We often speak as though prayer must begin with a clear mind and carefully chosen words. But the person sitting on the edge of the bed might have only enough energy to say, “Please help me get through tomorrow.” God does not need an account of the night's events before He can understand the need. The person praying can tell the truth without preparing a case.

There is still something difficult about being seen by a God we cannot see. Human beings need voices, hands, meals, and visits. You might pray in an empty kitchen and still wish someone would knock on the door. I do not think faith requires you to feel ashamed of that wish. Jesus taught people to call God their Father, and He taught them to pray for daily bread, not simply for the strength to pretend they were not hungry. The spiritual life is not a competition to see who can endure the most with the least comfort. It is a relationship in which need can be spoken plainly.

If I were one of the unnamed listeners leaving that mountain, perhaps I would carry those words back to a room where no one had noticed my effort. I would still have work to do. I might still need to ask for assistance or have a difficult conversation with the people who assumed I could manage forever. But I might stop treating my need for help as evidence that I had failed. I might also stop believing that my worth was waiting for another person to award it to me. The Father Jesus described was not discovering my existence only when someone brought Him news of me.

By the time morning reaches the kitchen window, the cup is dry. You put it away, check the next appointment on the calendar, and write a message asking a relative whether they can stay for an hour this weekend. It takes courage to send that message because you are used to saying you have everything covered. Then you sit for a moment and pray without trying to sound grateful for being tired. You tell God that you love the person you are caring for, that you are frustrated, and that you need help. Nothing in the room becomes less ordinary. But you are no longer pretending that the hours have no weight or that you must carry them without being known.

Chapter 3: The Fear You Could Not Pray Away

The ticket number glows on the wall above the service counter, and you have been watching it change for nearly an hour. In your pocket is a letter saying your request has been denied. You have come to ask whether there has been a mistake, though you have already read the explanation so often that you can almost recite it. Across the room, a man answers his phone and begins talking happily about plans for the weekend. You find yourself resenting his ordinary happiness. He has done nothing wrong. Still, it feels unfair that the world can keep being pleasant for other people while you are struggling to hold your own life together.

I think that is one of the loneliest things about disappointment. We do not always become noble when life is difficult. Sometimes we become impatient, suspicious, and tired of hearing how well things are going for everyone else. We may be ashamed of those reactions, especially if we believe a Christian should meet every setback with immediate gratitude. So we hide the bitterness beneath polite words. We tell people that God has a plan because we believe He does, but we are afraid to admit how badly we wish we could understand it.

When I picture myself at the Sermon on the Mount, I wonder whether I would have been able to hear the words of Jesus without silently arguing with them. I know how the story reads now. I know that His teaching is precious. But if I had come carrying a hope that had just fallen apart, would I have been ready to hear Him speak about the Father's care? Or would I have thought about the particular thing I had asked for and not received? That question does not make me doubt the goodness of Jesus. It makes me more aware of the distance between knowing what He said and learning to trust Him with what I cannot explain.

In Matthew 6, Jesus speaks about the birds of the air and the lilies of the field. He asks His listeners to consider the care of their heavenly Father, and He tells them not to be consumed with worry about tomorrow. I can imagine those words being comforting to someone who had come to the hillside feeling forgotten. I can also imagine a weary listener needing time to receive them. Scripture does not give us the private reactions of everyone there, and I do not want to invent them. What it gives us is the invitation Jesus actually made: to seek first God's kingdom rather than allowing tomorrow's fears to become our master.

I used to think trust should feel a certain way. I imagined it as a steady confidence that would make difficult news less frightening. But what if trust sometimes feels like admitting that you are frightened and bringing that fear to God anyway? A person can believe in the Father's care while still struggling to sleep. They can ask for daily bread and still need to visit an assistance office or make an uncomfortable phone call. Jesus does not make responsibility disappear. He asks us not to mistake our ability to anticipate every disaster for our ability to keep ourselves safe.

Consider someone recovering from an injury who has spent weeks practicing the same few steps between the kitchen table and the doorway. They follow the therapist's instructions, celebrate a little progress, and then have a morning when their body refuses to cooperate. They know recovery is rarely a straight line, but knowing that does not keep discouragement from arriving. Watching other people move without thinking about it can bring on a wave of envy. A cheerful instruction to stop worrying would not make the fear disappear. They need patience, practical help, and room to say how hard it is.

If that person prayed tonight, the words might be very plain. They might tell God they are angry that the search has gone on so long. They might admit being jealous of friends whose lives appear secure. They might ask for healing and also ask for the courage to face another day if their strength does not return immediately. I do not believe such a prayer is less sincere because it lacks a peaceful ending. It may be the first prayer in a while that has not been arranged to sound like something the person thinks God expects to hear.

There is something else in Jesus' words that we can overlook when we rush to feel reassured. He says that each day has enough trouble of its own. That is a remarkably honest acknowledgment of how life feels. He does not tell His listeners that tomorrow will contain no trouble. He does not describe faith as a guarantee that circumstances will always improve on our schedule. He calls them to meet today's needs without carrying tomorrow as though it has already happened. That is not an easy practice for a frightened heart. It is a way to begin living again in the hours we have actually been given.

At the counter, the clerk finally calls your number. You unfold the letter and explain why you came. Perhaps the answer will remain no. Perhaps there is another form you can submit, or someone who can explain the next step. You listen, ask the questions you prepared, and write down what you need to remember. The man across the room is still smiling at his phone. This time you barely notice him. Not because your problems have been solved, but because you are doing the part of the day that belongs to you.

If I had heard Jesus on that hillside while carrying a disappointment I could not explain, I hope I would have taken His words home without forcing myself to pretend I was no longer afraid. I hope I would have learned to speak to the Father honestly and then give my attention to the next faithful thing I could do. There would still be days when I returned to fear, and days when somebody else's happiness made my own waiting feel harder. But I would want to stop treating those feelings as reasons to keep my distance from God. I would want to bring them into the conversation instead.

Chapter 4: The Person I Might Have Passed on the Way Home

The message arrives just as you are putting the last clean plate into the cupboard. Your teenage son asks if you can pick him up early from a friend's house. He doesn't explain why. He has been short with you lately, and an hour ago you were still irritated about the argument you had that morning. You could tell him to wait until the time you agreed on. You could ask what he did wrong before deciding whether to help. Instead, you take your keys from the hook and drive across town. When he climbs into the car, he looks at the floor and says he doesn't feel like talking.

There is a kind of love that nobody would recognize from a distance. It looks like driving in silence with someone who is not ready to tell you what happened. It means allowing another person a little space when your own feelings are already hurt. It means resisting the temptation to turn every difficult moment into a lesson because you happen to have words prepared. I am not always good at this kind of love. Sometimes I want to settle the matter quickly so I can feel useful again. I would rather give advice than sit beside a question that has no immediate answer.

That is why I keep imagining what would have happened after the Sermon on the Mount, when Jesus finished speaking and the people had to return to their ordinary obligations. Matthew says the crowds were astonished by His teaching. He does not say what the unnamed listeners did with the rest of their day. I wonder if some wanted to speak about everything they had heard and others needed silence. Perhaps a few recognized an old habit they could no longer defend. Perhaps the teaching left them with questions they were not yet ready to ask aloud. We cannot know. But the words Jesus spoke were never meant to remain on the hillside.

Near the end of Matthew 7, He talks about two people building houses. One hears His words and acts on them. The other hears the same words and does not. When the weather turns violent, the foundation makes the difference. I notice that both builders have heard. The wise person is not the one who attended the more impressive gathering or came away with a better story. The difference appears in the quiet, repeated work of building. A foundation takes shape before the storm, when what we choose may look too ordinary to matter.

I think we sometimes misunderstand that picture because we want following Jesus to produce an entirely new personality by tomorrow morning. We expect our impatience to disappear, our fear to become certainty, and our difficult relationships to settle into peace. But if I hear Jesus teach me to be merciful, I still have to decide what mercy looks like when I am tired. If I hear Him speak about loving my enemies, I still have to reckon with the anger I carry toward a particular person. The truth is no less true because I cannot live it perfectly at once. I need grace while I learn.

It matters that this is not a program for earning God's attention. Jesus did not come merely to give humanity better instructions. Christian faith rests on who He is and what He has done for us, including His death and resurrection. We are not trying to build a record impressive enough to make Him love us. We respond because we have been loved, and because His words show us what a life shaped by that love can become. When we fail, the answer is not to pretend it never happened or decide we are hopeless. We can confess the failure and return to Him.

The drive home continues without much conversation. Your son watches streetlights pass across the window. You want to tell him that you understand, but you do not yet know what there is to understand. Eventually you say you are glad he called. You let him know that you are available if he wants to talk later. You still have questions about what happened, and you may need to ask them when he is ready, especially if his safety is involved. But for these few minutes, you do not make your wounded pride the most important thing in the car.

I wonder whether I would have learned that kind of restraint if I had heard Jesus in person. I like to imagine that I would have stayed until the end and remembered every word. Yet I know how distracted I become by my own concerns. I know how quickly I can hear something beautiful and then return to a familiar reaction when someone disappoints me. If I am honest, I cannot promise what sort of listener I would have been. I can only decide what to do as I hear Him now.

That decision does not have to be impressive. Tomorrow, you might notice that you are speaking harshly to someone who has asked an innocent question. You can stop and begin again. You might realize you have spent an entire conversation waiting for your turn to talk. You can put your attention back on the person in front of you. You might offer help and then discover that you cannot reasonably provide everything requested. You can give an honest answer without becoming cold. These are not miracles. They are places where mercy and truth begin to acquire the shape of a real life.

There are also moments when we will not be able to see our own progress. We may pray and feel nothing settle. We may ask forgiveness and find that the relationship stays damaged. We may do what is right and still go home disappointed. I do not want to suggest that following Jesus means every good decision receives a visible reward. Sometimes the most meaningful change is simply that we no longer make every decision according to what would make us feel better immediately. We begin to care about what is true and loving, even when it is inconvenient.

At home, your son heads to his room. Before closing the door, he turns and thanks you for coming. He still has not explained what happened, and you do not know whether tonight will be remembered by either of you a year from now. You cannot measure the significance of the drive by what he told you. You can only know that when he asked for help, you went. There will be another conversation when the time is right. For now, you have let a quiet evening be what it needed to be.

If I could ask one question of a person who truly stood on that hillside, I do not think I would ask how loud the crowd was or how close they sat to Jesus. I would want to know what they noticed when they returned home. Did they see someone they had stopped seeing? Did they tell the truth about something they had hidden? Did they begin to believe that the Father heard the prayers they could barely speak? Scripture leaves those private histories with God. But it does leave us the words of Christ, and they are enough to ask us what kind of people we are willing to become.

The opportunity is not locked in a distant afternoon in Galilee. It can reach a person sitting in a parked car, uncertain what to say to someone they love. It can reach someone who has made mistakes and is still learning how to be honest. I cannot go back and stand among the first listeners. I can open the Gospel today, listen without pretending, and ask Jesus to help me live one small part of what I have heard. I would rather begin there than spend my life imagining how remarkable I might have been if only I had seen Him walk by.

Your friend, Douglas Vandergraph

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The software on the slide looked like something a sales team would buy. There was a dashboard. There were contact targets for the day. There was a pipeline that tracked each prospect from first message to final payment, and an assistant that suggested the next reply. Eric Huber, senior manager of adversary intelligence and disruption at TD Bank, was showing it to an audience at Black Hat USA 2026 in Las Vegas in August. The prospects in the pipeline were fraud victims. The workers hitting their daily quotas were, in many cases, trafficked people held in scam compounds in Cambodia and Myanmar, who faced punishment if they fell short.

One of the tools Huber demonstrated, according to reporting by Joel Witts at Expert Insights, was a reply generator called Editone. An operator loads a victim's profile alongside a fabricated persona, and the software drafts responses designed to land. It has voice cloning built in. Translation software lets a worker who speaks one or two languages work a target in a third. Tara Seals of Dark Reading described another kit, ProKYC, used by Nigerian fraud rings to defeat banks' identity checks by generating forged “selfie with ID” images stamped with fake location metadata, so a picture taken in Nigeria appears to come from Sydney. Her headline summed up the session: AI had sent global crime syndicates into “fraud nirvana”.

Huber was careful about one point, and it matters more than the headline. The tools, he said, do not automate the scam. They “help some poor person do the scamming by creating responses that are going to be the most effective.” What he described was not a robot that defrauds people by itself. It was a factory: a production line in which human labour, software and management systems are arranged to maximise output per worker, and in which each new piece of AI removes another bottleneck.

That distinction reframes the question people actually ask. When a voice that sounds exactly like your son calls in tears, or a colleague's face appears on a video call asking for an urgent transfer, or a stranger online seems to understand you better than anyone has for years, how do you tell the real from the manufactured? The uncomfortable answer from the research of the past year is that, in most cases, you cannot, at least not by looking and listening. The more useful answer is that you were never supposed to have to. Factories are beaten by changing their economics, not by asking each customer to inspect the product more closely.

A Production Line Built on Conversation

To understand why AI matters to fraud, start with what fraud work consists of. The most detailed answer comes from a study posted to arXiv in December 2025 by Gilad Gressel, Rahul Pankajakshan, Shir Rozenfeld, Ling Li, Ivan Franceschini, Krishnashree Achuthan and Yisroel Mirsky, titled “Love, Lies, and Language Models: Investigating AI's Role in Romance-Baiting Scams”. The researchers interviewed 145 insiders and five victims. Their central finding was that 87 per cent of scam labour consisted of what they called “systematized conversational tasks”, the scripted, repetitive work of building rapport over weeks of text messages before steering a target towards a fraudulent investment.

That figure is the key to the whole economy. A scam compound is, in effect, a call centre whose product is trust, and most of its costs are the hours it takes to produce that trust one conversation at a time. The team then tested what happens when a machine does the talking. In a week-long blinded study, a language-model agent elicited more trust from participants than human operators did, and achieved higher compliance with requests: 46 per cent against 18 per cent for the humans. Commercial safety filters, run over the romance-baiting dialogues, flagged 0.0 per cent of them. The authors concluded that these scams “may be amenable to full-scale LLM automation”.

International law enforcement has reached a similar conclusion. In March 2026, INTERPOL published its second Global Financial Fraud Threat Assessment, timed for its Global Fraud Summit. The organisation reported that AI-enhanced fraud is 4.5 times more profitable than traditional methods, and that fraud-related INTERPOL Notices and Diffusions, the alerts member countries use to flag suspects and methods, had risen 54 per cent since 2024. It warned that agentic AI systems can now run complete fraud campaigns, from reconnaissance to ransom demands. It described hybrid tactics in which sextortion is built into romance and investment scams using scripts and AI-generated content, and scam centres that were once regional now operating worldwide and involving hundreds of thousands of people, many of them trafficked. Valdecy Urquiza, INTERPOL's Secretary General, put it in a single phrase: “we are witnessing the industrialization of fraud.”

The United Nations Office on Drugs and Crime, in a threat assessment launched in Bangkok in July 2026, estimated scam losses across East and South-East Asia, Australia and New Zealand at between $88.3 billion and $114.1 billion in 2025. It documented the use of generative AI, deepfakes and automated fraud, and found people from at least 80 countries and territories inside the region's compounds. The geography of the labour force and the geography of the victims are both global.

Academic work has started to describe the same shift in its own terms. A January 2026 paper by Heedou Kim, Changsik Kim, Sanghwa Shin and Jaewoo Kang, which built a detection system called ScriptMind from 571 real Korean phone scam cases, observes in its introduction that “with advances in LLMs and generative AI, such scams have evolved into large-scale, organized, and multi-channel attacks.” A survey of AI-driven cybersecurity threats by Sai Teja Erukude, Viswa Chaitanya Marella and Suhasnadh Reddy Veluru, also posted in January 2026, puts it more bluntly: “The real danger of AI in cybercrime is that it's now possible to automate complex and large-scale scams.”

The Arithmetic of a Five-Minute Phone Call

Factories exist because of unit economics, and the most useful recent paper on AI fraud is an exercise in accounting. “Evaluating AI Models' Capability to Automate Voice Phishing Attacks”, by Fred Heiding of Harvard Kennedy School and colleagues including Claudio Mayrink Verdun, Simon Lermen, Andrew Kao and researchers at Meta, was posted to arXiv in July 2026 and published in the journal Expert Systems With Applications.

The team ran a survey experiment with 4,100 American adults, exposing them to recordings or transcripts of scam calls voiced by leading AI voice models, including systems from Google, OpenAI, ElevenLabs and Sesame, and comparing them with human-voiced versions. The overall compliance rate across five scam types was 16.5 per cent. In the “relative in distress” scenario, the one that maps onto the classic family emergency call, up to 36 per cent of participants said they would or might comply. Caller persuasiveness was the strongest predictor of compliance, and some synthetic voices, Sesame's in particular, were rated as persuasive as human ones or slightly more so.

Then came the accounting. A human vishing operator, calibrated at the average American non-farm wage of $34.55 an hour, handles about twelve five-minute attempts an hour. Assume the scammer extracts $450 from each successful victim, and that only 0.6 per cent of persuaded people actually pay, the lowest conversion rate the authors could find in any legitimate industry. On those assumptions, a human-run vishing operation at American wages loses around $27 an hour. Some AI models also lose money because inference is expensive. But others, including Gemini, Sesame and ElevenLabs, came out with positive expected profits. The authors estimated that building such a pipeline takes around 260 hours of engineering time. Their conclusion is the sentence that has travelled furthest from the paper: “even conservative estimates suggest that AI-automated vishing is economically viable at scales accessible to individual bad actors, not just organized crime syndicates.”

Precision matters here. The authors call AI vishing “roughly break-even” across the models they surveyed, not wildly profitable, and they found that targeting particular demographic groups was not yet worth its cost. So the popular shorthand, that the barrier to industrial fraud has fallen to zero, overstates the evidence. The real finding is subtler and more worrying. The constraint that used to cap phone fraud was human time. Each operator could hold one conversation at a time, and in a high-wage country that time cost more than the fraud returned. AI removes the constraint. As the paper notes, AI agents “can conduct thousands of concurrent calls, limited mainly by telephony and network capacities rather than human capacity.” The authors call the result an “automation dividend”: a situation in which “even small per-call success probabilities translate into large aggregate losses.”

Researchers outside the paper say the same thing in plainer language. In February 2026, the Guardian's Aisha Down reported on an analysis of the AI Incident Database, which found that frauds, scams and targeted manipulation had been the largest category of incidents reported to the database in 11 of the previous 12 months. Simon Mylius, an MIT researcher who works on a project linked to the database, told the paper that “capabilities have suddenly reached that level where fake content can be produced by pretty much anybody,” and that “there is really effectively no barrier to entry.” Heiding, quoted in the same piece, said: “It's becoming so cheap, almost anyone can use it now.”

Why Volume Beats Brilliance

The factory framing explains an apparent paradox. AI fraud does not have to be brilliant. It has to be good enough, cheap enough and plentiful enough.

A traditional con artist needed a high hit rate because each attempt cost hours of skilled work. A factory needs only a positive expected value per attempt, multiplied by a very large number of attempts. A 16.5 per cent compliance rate, or even a fraction of one per cent conversion to actual payment, is a disaster for an individual criminal working by hand. For an automated system running thousands of calls at once, around the clock, in dozens of languages, it is a business model. The Heiding team's economics deliberately assumed that AI scales no better than humans, which they acknowledge “is likely to underestimate the reach of AI-automated vishing”.

This is why the losses keep climbing. The FBI's Internet Crime Complaint Center reported 1,008,597 complaints in 2025, the first year it crossed one million, and reported losses of $20.877 billion, up 26 per cent on 2024. Investment fraud alone accounted for $8.6 billion. According to a Department of Justice release in April 2026, losses in the category of investment fraud the department ties to South-East Asian scam centres rose 24 per cent in 2025 to more than $7.2 billion.

The FBI also counted more than 22,000 complaints with an AI connection, with associated losses of nearly $900 million. That number is likely an undercount, for a reason that goes to the heart of the problem: victims usually have no way of knowing whether a message, a voice or a face was machine-made. Fraud built on synthetic trust leaves no fingerprint that the person defrauded can see. Statistics on “AI-enabled fraud” therefore measure the cases where AI was obvious, not the cases where it worked.

None of the technologies involved is exotic. Voice synthesis, real-time video generation and conversational language models are the same tools that power customer service bots, dubbing software and AI companions. The fraud factory does not need a research laboratory. It rents the consumer technology stack and points it at a different goal.

Your Senses Were Never the Security System

The standard advice to the public has long rested on perception. Listen for the robotic cadence. Watch for the blink that comes too late, the hands that look wrong, the shadow that falls the wrong way. Even the FBI's December 2024 public service announcement on generative AI fraud advised people to “look for subtle imperfections in images and videos, such as distorted hands or feet, unrealistic teeth or eyes”, and to “listen closely to the tone and word choice” to tell a loved one from a cloned voice.

The evidence on whether people can do this is not encouraging. In 2024, Alexander Diel and colleagues published a systematic review and meta-analysis of 56 papers on human deepfake detection in Computers in Human Behavior Reports, pooling results from more than 86,000 participants. Total detection accuracy was 55.54 per cent. Because the confidence interval crossed 50 per cent, the authors concluded that overall detection was not significantly better than chance. Audio was the easiest format at 62.08 per cent; images and text were barely distinguishable from guessing. An earlier study in iScience by Nils Köbis, Barbora Doležalová and Ivan Soraperra summed up the psychological trap in its title: “Fooled twice: People cannot detect deepfakes but think they can.”

Muhammad Tahir Ashraf, a practitioner and technology entrepreneur, made the consequence explicit in an April 2026 arXiv paper titled “Synthetic Trust Attacks”. “Generative AI is the force-multiplier behind this surge,” he writes, “enabling voice cloning, video deepfakes, and LLM-driven conversations that scale social engineering attacks to industrial speed.” His core argument is that existing defences focus on detecting synthetic media, while “the real attack surface is the victim's decision.” Citing the detection figures and the 46 versus 18 per cent compliance gap, he concludes that “the perception layer has already failed.” Ashraf's framework is a model rather than an empirical study, but its diagnosis lines up with the data.

The clearest real-world illustration remains the case Ashraf opens with. In early 2024, an employee in the Hong Kong office of the British engineering firm Arup joined a video call with people who appeared to be the company's chief financial officer and other colleagues. All of them were synthetic. The employee made 15 transfers totalling HK$200 million, about US$25.6 million, according to Hong Kong police as reported by CNN. Rob Greig, Arup's global chief information officer, later told the World Economic Forum that this was not a cyberattack in the usual sense, because no system was breached. “What happened at Arup,” he said, “I would call it technology-enhanced social engineering.” Nothing was hacked except a person's reasonable belief that the faces on the screen were real.

If perception has failed, then asking individuals to look harder is not a defence. It is a transfer of risk to the person least able to bear it.

The Executive Who Asked About a Book

There is a better model, and some of the most instructive examples come from people who were not fooled.

In July 2024, Bloomberg reported that an executive at Ferrari had received a series of WhatsApp messages, from an unfamiliar number, purporting to come from the chief executive, Benedetto Vigna. They described a confidential acquisition. A phone call followed, in a voice that imitated Vigna's southern Italian accent convincingly. The executive grew suspicious and said, according to the report: “Sorry, Benedetto, but I need to identify you.” He asked for the title of a book Vigna had recommended to him days earlier. The call ended abruptly.

That executive did not detect a deepfake. He did not spot a glitch or a wrong vowel. He applied a procedure: a challenge whose answer existed only in a shared history that the impersonator could not access. That is the crucial shift. A procedure works whether or not the fake is perfect. Perception works only when the fake is flawed, and the factories are paid to remove the flaws.

The second example shows what happens when procedure fails at the individual level but works at the system level. On 24 March 2025, a finance director at a multinational company in Singapore was contacted on WhatsApp by someone posing as the company's chief financial officer. A purported lawyer called to stress confidentiality, and the director signed a non-disclosure agreement. On a Zoom call the next day, he saw the chief executive and other executives, impersonated with deepfakes. On 26 March he transferred more than US$499,000 from the company's HSBC account into what turned out to be a money mule account. The scam came to light only when the fraudsters asked for another US$1.4 million. He alerted HSBC, which immediately notified Singapore's Anti-Scam Centre. By 28 March, working with the Anti-Deception Coordination Centre of the Hong Kong Police Force, the authorities had withheld the full amount that had been moved on to Hong Kong, more than US$494,000, and seized the remainder locally.

The director was fooled. The money was recovered anyway, because a bank, a national anti-scam centre and a foreign police unit could act within days across a border. The factory beat the person. It did not beat the system.

For individuals, the lesson is to replace judgement with routine wherever money or credentials are involved. The FBI's own list contains the useful parts: “Create a secret word or phrase with your family to verify their identity,” and verify a caller “by hanging up the phone, researching the contact of the bank or organization purporting to call you, and call the phone number directly.” The value of these steps is that they are channel-independent. A cloned voice cannot know a code word agreed at the kitchen table. A deepfaked colleague cannot intercept a call you place to a number you already hold. A romance that has never moved off one app, never met in a verifiable way and eventually turns to an “opportunity” fails a procedural test long before it fails a perceptual one.

Ashraf's paper packages similar advice as “Calm, Check, Confirm”, a protocol aimed at the moment of decision. The names matter less than the principle. Urgency, secrecy and a new channel are the three pressures that recur across the Arup, Ferrari and Singapore cases, and they recur because they are designed to stop the victim from running a procedure. Any request that combines them should trigger one automatically, however real the voice or face seems.

But these steps have limits. They protect people who set them up in advance, which disproportionately means the organised and the informed. They do little for someone isolated, someone in crisis, or someone whose new romantic interest has spent six weeks becoming the most attentive presence in their life. A defence that depends on billions of people behaving like a well-briefed Ferrari executive is not a defence against a factory. It is a lottery with better odds for some players.

Making the Bill Land Where the Fix Is

If individual vigilance cannot carry the load, the question becomes who can, and how to make them want to. The most promising answer of the past two years has been to move the cost of fraud onto the institutions that can change the factory's economics.

The United Kingdom made the boldest bet. Since 7 October 2024, the Payment Systems Regulator has required payment firms to reimburse most victims of authorised push payment fraud, the kind in which a victim is tricked into sending money themselves, up to £85,000, with the cost split between the sending and receiving firms. In the first full year, to the end of September 2025, the regulator reported that £173 million had been returned, 88 per cent of the money lost to in-scope scams. Only about three per cent of claims were rejected on the grounds that the customer had not taken enough care. More important for the factory argument, an independent evaluation published by the regulator in July 2026 found that APP fraud losses over Faster Payments fell by around 21 per cent after the requirement came in, a reduction of about £73 million a year, and that the rules had strengthened firms' incentives to invest in prevention. Reimbursement does more than compensate victims. When banks pay for fraud, they have a reason to hunt mule accounts, slow suspicious transfers and share the intelligence that makes fraud less profitable.

Singapore went further up the chain. Its Shared Responsibility Framework, developed by the Monetary Authority of Singapore and the Infocomm Media Development Authority and in force since 16 December 2024, assigns specific anti-phishing duties to banks and to telecoms operators, from real-time fraud surveillance to blocking unauthorised SMS sender IDs and filtering messages containing malicious links. Losses then flow down a “waterfall”: a bank that has breached its duties bears the loss first; if it has not, a telco that has breached its duties pays; only if both have complied does the loss stay with the consumer. The design point is that liability follows the specific failure, so each link in the chain has a reason to fix its own part.

Australia passed the broadest version. The Scams Prevention Framework Act, which cleared both houses of Parliament on 13 February 2025, imposes obligations to prevent, detect, report, disrupt and respond to scams on banks, telecoms providers and digital platforms, including social media, with civil penalties of up to A$50 million for serious breaches and a route for consumers to seek redress when a business has failed its obligations. The Australian figures also give the most honest picture of what system-level defence can and cannot do. According to the National Anti-Scam Centre, reported losses fell 25.9 per cent to A$2.03 billion in 2024, a drop the centre credited to joint work by government, industry, law enforcement and community groups. In 2025 they rose again by 7.8 per cent, to A$2.18 billion. Catriona Lowe, deputy chair of the Australian Competition and Consumer Commission, called scams a “wicked problem” because they are “complex, fast-evolving, and resistant to simple solutions,” and pointed to the “increasing sophistication in scam activity through artificial intelligence.”

That is the realistic shape of success. Coordinated systems can bend the curve. They cannot make a factory disappear. They have to keep changing its input costs faster than it can adapt.

Breaking the Machinery Upstream

The most direct way to raise a factory's costs is to attack its equipment, its premises and its money. Over the past year, that has started to happen.

The United Kingdom's Crime and Policing Act 2026, which received Royal Assent on 29 April 2026, created offences of possessing and supplying SIM farms without a legitimate reason. These devices, defined in government guidance as equipment able to use five or more SIM cards at once for calls or messages, allow a single operator to send scam texts at industrial volume. The government announced the measure in 2025 as a first in Europe and said it would take effect six months after Royal Assent. Critics have noted that much scam traffic originates abroad, which limits what a domestic ban can achieve. But the logic is sound. The offence targets the machine that multiplies one person's reach, rather than the message the machine sends.

In October 2025, after Myanmar's military said it had raided KK Park, one of the largest scam compounds on the Thai border, detaining more than 2,000 people and seizing 30 Starlink terminals, SpaceX said it had disabled more than 2,500 Starlink kits near suspected scam centres in the country. Reporting at the time noted that other compounds along the border remained active and that operations might simply relocate. Factories move when they are disrupted. That is a reason to disrupt them repeatedly, not a reason to stop.

The money is the third target. In October 2025, the US Department of Justice filed a civil forfeiture complaint against around 127,271 bitcoin, then worth roughly $15 billion, linked to Chen Zhi, chairman of Cambodia's Prince Group, whom prosecutors charged with wire fraud and money laundering conspiracy over forced-labour scam compounds. The US Treasury and the UK government imposed coordinated sanctions on the network. Chen and Prince Group have denied wrongdoing. Cambodia, which had revoked his Cambodian citizenship by royal decree in December 2025, arrested him on 6 January 2026 and, in a move announced the next day, sent him to China along with two other Chinese nationals. China's Ministry of Public Security said his group was suspected of fraud, running casinos and concealing criminal proceeds. The Justice Department's Scam Center Strike Force, created in November 2025, said by April 2026 that it had restrained more than $700 million in cryptocurrency and taken down more than 500 fraudulent investment websites. By September 2026, after a single-day action that restrained about $52 million linked to Xinbi Guarantee, a Telegram-based marketplace sanctioned by the US Treasury the same day, its cumulative total had reached about $938 million. INTERPOL, for its part, launched Operation Shadow Storm, a task force funded by the UK Home Office to go after the financial networks behind scam centres.

None of these actions alone ends industrial fraud. Together they move effort away from the moment a victim must decide whether a voice is real, and towards the infrastructure that makes it cheap to fake the voice ten thousand times.

Building Factories That Waste the Factory's Time

There is a further move available, and it has a pleasing symmetry. If AI makes it cheap for criminals to hold thousands of conversations, it makes it equally cheap for defenders to hold thousands of conversations with criminals.

In November 2024, the British mobile operator Virgin Media O2 unveiled Daisy, an AI “granny” built to answer scam calls in real time. It chains together a speech-to-text model, a custom language model with a character layer, and a synthetic voice, and it was trained with help from the YouTube scambaiter Jim Browning. O2 seeded Daisy's numbers onto the lists scammers use to find victims. The company said Daisy had kept numerous fraudsters on the phone for 40 minutes at a time. Murray Mackenzie, O2's director of fraud, warned that “no matter how persuasive someone on the other end of the phone may be, they aren't always who you think they are.”

Australia's Commonwealth Bank has taken the idea further. In June 2025 it announced a partnership with Apate.ai, a company spun out of Macquarie University's Cyber Security Hub and led by Professor Dali Kaafar. Apate runs a network of honeypot phone numbers designed to be found by scammers. When they call, they reach AI bots with varied ages, genders and accents, tuned with Australian slang, that keep them talking while gathering intelligence on their scripts and tactics. That intelligence feeds into the bank's scam controls and the wider anti-scam network in near real time.

The ScriptMind paper points the same way from the detection side. Its authors fine-tuned an 11-billion-parameter model on 22,712 structured examples built from real scam cases, report that it outperformed GPT-4o by 13 per cent, and found that in simulated calls it raised and sustained users' suspicion. The idea is not to ask people to hear the fake, but to have a machine recognise the script every factory relies on and warn the person in the moment.

These systems will not stop fraud alone, and some of them, Daisy especially, are partly marketing exercises whose results are reported by the companies themselves. But they point at the right target. A fraud factory's margin depends on the share of its labour and compute that reaches paying victims. Every minute a worker or an AI agent spends talking to a bot that will never pay, and every script that is captured and turned into a warning, is a cost the factory has to absorb. Automation does not only help the attacker. For once, it lets defenders operate at the same scale.

What Protection Looks Like for One Person Facing a Machine

So, back to the person holding the phone.

The honest answer to how an individual distinguishes a genuine interaction from a manufactured one is that, much of the time, they cannot by sense alone. Human detection sits close to chance. AI voices and conversationalists match or beat humans. And the factory does not need to fool you in particular. It needs to fool a small fraction of a very large number of people, and it can now afford to try them all.

What remains is a smaller set of habits that do not depend on perception at all. Agree a code word with the people whose voices you would trust in a crisis. When a request involves money, credentials or secrecy, end the conversation and re-establish contact through a channel you already hold. Treat urgency, confidentiality and a new or unusual channel, appearing together, as the signature of a procedure being bypassed. Talk to someone before you pay. None of that requires you to be a forensic analyst. All of it works whether the fake is crude or perfect.

The larger answer is that protection for one person has to be built mostly out of things that one person does not control. It looks like a bank that has a financial reason to stop the transfer, because it will pay if it does not. It looks like a telecoms network that blocks the SIM farm and the spoofed sender, because it bears a share of the loss when it fails to. It looks like a platform that faces penalties for letting a scam reach its users. It looks like anti-scam centres that can freeze money across a border within a day of the alarm being raised, satellite providers that cut off compounds, prosecutors who seize the bitcoin, and defensive AI that wastes the attackers' hours and steals their scripts.

INTERPOL's Valdecy Urquiza warned that the cost of financial crime “is not just money – it is people's life savings, their dignity, and in the worst case, their life.” The fraud factory runs on the assumption that this cost will continue to fall on individuals, one call, one video and one conversation at a time. The evidence from London, Singapore and Canberra suggests that assumption can be broken, and that the right response to industrialised deception is not a more suspicious public. It is an industrial defence. Every person on earth may now be a potential target. That does not make every person on earth responsible for being the last line of defence.

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References and Sources

1. Black Hat USA 2026 presentation by Eric Huber, Senior Manager of Adversary Intelligence and Disruption, TD Bank, as reported in: Witts, Joel. “Research reveals how criminal gangs are using AI to improve financial scams.” Expert Insights, 4 August 2026, https://expertinsights.com/news/research-reveals-how-criminal-gangs-are-using-ai-to-improve-financial-scams; and Seals, Tara. “AI Sends Global Crime Syndicates Into Fraud Nirvana.” Dark Reading, August 2026, https://www.darkreading.com/threat-intelligence/ai-global-crime-syndicates-fraud-nirvana
2. Gressel, Gilad, Rahul Pankajakshan, Shir Rozenfeld, Ling Li, Ivan Franceschini, Krishnashree Achuthan and Yisroel Mirsky. “Love, Lies, and Language Models: Investigating AI's Role in Romance-Baiting Scams.” arXiv:2512.16280, submitted 18 December 2025. https://arxiv.org/abs/2512.16280
3. INTERPOL. “INTERPOL report warns of increasingly sophisticated global financial fraud threat.” News release, 16 March 2026, including quotes from Secretary General Valdecy Urquiza; and the 2nd INTERPOL Global Financial Fraud Threat Assessment, 2026. https://www.interpol.int/en/News-and-Events/News/2026/INTERPOL-report-warns-of-increasingly-sophisticated-global-financial-fraud-threat
4. Organized Crime and Corruption Reporting Project. “UN Report Details Southeast Asia's Interconnected Criminal Economy.” 21 July 2026, reporting on the UNODC threat assessment “An Interconnected Criminal Ecosystem”, launched in Bangkok on 21 July 2026. https://www.occrp.org/en/news/un-report-details-southeast-asias-interconnected-criminal-economy
5. Kim, Heedou, Changsik Kim, Sanghwa Shin and Jaewoo Kang. “SCRIPTMIND: Crime Script Inference and Cognitive Evaluation for LLM-based Social Engineering Scam Detection System.” arXiv:2601.13581, submitted 20 January 2026. https://arxiv.org/abs/2601.13581
6. Erukude, Sai Teja, Viswa Chaitanya Marella and Suhasnadh Reddy Veluru. “AI-Driven Cybersecurity Threats: A Survey of Emerging Risks and Defensive Strategies.” arXiv:2601.03304, submitted 6 January 2026. https://arxiv.org/abs/2601.03304
7. Heiding, Fred, Claudio Mayrink Verdun, Simon Lermen, Andrew Kao, Vitor Albiero, Lauren Deason, Irina-Elena Veliche and Christine Lehane. “Evaluating AI Models' Capability to Automate Voice Phishing Attacks.” arXiv:2607.09970, submitted 10 July 2026, revised 20 August 2026; published in Expert Systems With Applications, volume 332, article 133620. DOI 10.1016/j.eswa.2026.133620. https://arxiv.org/abs/2607.09970
8. Down, Aisha. “Deepfake fraud taking place on an industrial scale, study finds.” The Guardian, 6 February 2026; syndicated by the Irish Examiner as “AI experts say deepfakes now at 'industrial' scale”, 6 February 2026, including quotes from Simon Mylius (MIT) and Fred Heiding (Harvard). https://www.irishexaminer.com/news/arid-41789042.html
9. Federal Bureau of Investigation, Internet Crime Complaint Center. “2025 Internet Crime Report.” 7 April 2026. https://www.ic3.gov/AnnualReport/Reports/2025_IC3Report.pdf
10. US Department of Justice. “Scam Center Strike Force Takes Major Actions Against Southeast Asian Scam Centers Targeting Americans.” Office of Public Affairs press release, 23 April 2026, https://www.justice.gov/opa/pr/scam-center-strike-force-takes-major-actions-against-southeast-asian-scam-centers-targeting; and US Attorney's Office for the District of Columbia, “Scam Center Strike Force”, web page updated 15 October 2026, accessed 20 October 2026, https://www.justice.gov/usao-dc/scam-center-strike-force; see also Crypto Briefing, “Scam Center Strike Force restrains $52M in laundered crypto in one day”, 9 September 2026, https://cryptobriefing.com/scam-center-strike-force-52m-crypto-madagascar/
11. Federal Bureau of Investigation. “Criminals Use Generative Artificial Intelligence to Facilitate Financial Fraud.” Public Service Announcement, Alert Number I-120324-PSA, 3 December 2024. https://www.ic3.gov/psa/2024/psa241203
12. Diel, Alexander, et al. “Human performance in detecting deepfakes: A systematic review and meta-analysis of 56 papers.” Computers in Human Behavior Reports, volume 16, article 100538, December 2024, DOI 10.1016/j.chbr.2024.100538; and Köbis, Nils C., Barbora Doležalová and Ivan Soraperra. “Fooled twice: People cannot detect deepfakes but think they can.” iScience, volume 24, issue 11, article 103364, 2021, DOI 10.1016/j.isci.2021.103364.
13. Ashraf, Muhammad Tahir. “Synthetic Trust Attacks: Modeling How Generative AI Manipulates Human Decisions in Social Engineering Fraud.” arXiv:2604.04951, submitted 2 April 2026. https://arxiv.org/abs/2604.04951
14. Magramo, Kathleen. “British engineering giant Arup revealed as $25 million deepfake scam victim.” CNN, 16 May 2024, https://edition.cnn.com/2024/05/16/tech/arup-deepfake-scam-loss-hong-kong-intl-hnk; and World Economic Forum, interview with Rob Greig, Global Chief Information Officer, Arup, February 2025, https://www.weforum.org/stories/2025/02/deepfake-ai-cybercrime-arup/
15. Bloomberg. “Ferrari Narrowly Dodges Deepfake Scam Simulating Deal-Hungry CEO.” 26 July 2024; see also Motor1, “Someone Deepfaked Ferrari CEO's Voice and Tried to Scam the Company”, July 2024. https://www.motor1.com/news/728264/ferrari-ceo-deepfake-voice-phone/
16. Singapore Police Force. “Singapore and Hong Kong Police Force Recover Over $670,000 in a Scam.” News release, 7 April 2025. https://www.police.gov.sg/media-hub/news/2025/04/20250407_singapore_and_hong_kong_police_force_recover_over_$670000_in_a_scam
17. Payment Systems Regulator. “One year on: impact of APP reimbursement on victims.” 2025, https://www.psr.org.uk/news-and-updates/latest-news/news/one-year-on-impact-of-app-reimbursement-on-victims/; and the independent evaluation published by the regulator in July 2026, as summarised in Norton Rose Fulbright, Regulation Tomorrow, “Payment fraud falls by £73m following PSR reimbursement scheme”, 1 July 2026, https://www.regulationtomorrow.com/2026/07/payment-fraud-falls-by-73m-following-psr-reimbursement-scheme/
18. Infocomm Media Development Authority and Monetary Authority of Singapore. “Implementation of Shared Responsibility Framework.” Joint press release, 24 October 2024; and MAS, “Guidelines on Shared Responsibility Framework”. https://imda.gov.sg/resources/press-releases-factsheets-and-speeches/press-releases/2024/implementation-of-shared-responsibility-framework
19. Gilbert + Tobin. “The Scams Prevention Framework legislation passes Parliament: time to get your house in order.” February 2025. https://www.gtlaw.com.au/insights/the-scams-prevention-framework-legislation-passes-parliament-time-to-get-your-house-in-order
20. Australian Competition and Consumer Commission, National Anti-Scam Centre. “Targeting scams: Report of the National Anti-Scam Centre on scams data and activity 2024.” March 2025, https://www.accc.gov.au/about-us/publications/serial-publications/targeting-scams-reports-on-scams-activity/targeting-scams-report-of-the-national-anti-scam-centre-on-scams-data-and-activity-2024; and Croft, Daniel, “Scams cost Australians over $2bn in 2025, says ACCC”, Cyber Daily, 30 March 2026, including quotes from Catriona Lowe, Deputy Chair, ACCC, https://www.cyberdaily.au/security/13400-scams-cost-australians-over-2bn-in-2025-says-accc
21. UK Home Office. “Major step for fraud prevention with landmark ban on SIM farms.” GOV.UK news story, 2025; and “Crime and Policing Act 2026 guidance: offences relating to the possession and supply of SIM farms”, GOV.UK, July 2026. https://www.gov.uk/government/news/major-step-for-fraud-prevention-with-landmark-ban-on-sim-farms
22. Arab News, via Agence France-Presse. “SpaceX says 'disabled' 2,500 Starlink devices at Myanmar scam centers.” October 2025. https://www.arabnews.com/node/2619810/world
23. US Department of Justice, US Attorney's Office for the Eastern District of New York. “Chairman of Prince Group Indicted for Operating Cambodian Forced Labor Scam Compounds Engaged in Cryptocurrency Fraud Schemes.” Press release, 14 October 2025, https://www.justice.gov/usao-edny/pr/chairman-prince-group-indicted-operating-cambodian-forced-labor-scam-compounds-engaged; Elliptic, “Prince Group targeted with $15B crypto seizure and sanctions for pig butchering operations”, October 2025, https://www.elliptic.co/blog/prince-group-targeted-with-crypto-sanctions-for-global-pig-butchering-operations; Associated Press, “Businessman extradited from Cambodia to China suspected of running vast online criminal empire”, 8 January 2026, republished by NY1, https://ny1.com/nyc/all-boroughs/ap-top-news/2026/01/08/businessman-extradited-from-cambodia-to-china-suspected-of-running-vast-online-criminal-empire; and CamboJA News, “Chen Zhi, Alleged Scam Network Kingpin, Sent to China”, 8 January 2026, https://cambojanews.com/chen-zhi-alleged-scam-network-kingpin-sent-to-china/
24. Virgin Media O2. “O2 unveils Daisy, the AI granny wasting scammers' time.” Press release, 14 November 2024, including quotes from Murray Mackenzie, Director of Fraud. https://news.virginmediao2.co.uk/o2-unveils-daisy-the-ai-granny-wasting-scammers-time/
25. Commonwealth Bank of Australia. “CommBank deploys AI bots to outsmart scammers” (partnership with Apate.ai). Newsroom, June 2025. https://www.commbank.com.au/articles/newsroom/2025/06/apate-ai.html

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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

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There are not enough summers,

Nor winters,

Falls or springs,

For any encounter

To span enough years.

I got stabbed today. im not going to explain it. im sure you can live with that. i ned some rest at home for a few days. perhaps ill go back to work after that. but anyway, i do have something to complain about today. yes. as if we dont do that every single time i come here. ill complain about celebrities. more specifically, the way people worship them. those worthless humans. i dont understand it. i dont want to understand it, either, but the fact that it happens so often makes it difficult to ignore. pathetic people are walking around treating some random man like hes been sent down from heaven because he can sing over a beat. they’ll learn his lyrics go on and defend his honour spend their rent money to look at him from a distance, and behave as though hes responsible for the continued rotation of the earth. for what? because he sings? god forbid somebody says something bad about him. suddenly, they’ve got an entire army of pathetic strangers ready to fight over a man who doesnt even know their names. Oh, woah woah im so worried that if i mention someone in particular, i might get swatted. imagine having to worry about a bunch of strangers breaking into your house because you ont like their favourite singer. very normal behaviour. and Oh, dont get me started on people who become famous for doing stupid shit on the internet. i guess, being a dumbass in front of a camera is a career now. people will call them geniouses and admire their every more and blah bla blahs. i wonder if these people hear themselves. its a man singing nonsense into a microphone, humans. he might not even know how to count to a hundred without using his fingers, yet somehow hes got thousands of people treating him like a god, that he dont know how to count. i dont understand it. i dont want to understand it.. enjoy the music, laugh at the stupid videos and go on about your day. why does everything have to turn into an obsession? why must every half-decent singer or internet fool have a bunch of idiots ready to defend their honour?

I mean, just look at you. its embarrassing, really. for everyone involved, including you. except the celebrity, whos probably sitting at home counting his money while you wear his face on your shirt, screaming your lungs out trying to get his attention, and get nothing in return. God, some humans are actually a waste of oxygen. if you are one of those people. please leave my page right now. i dont want to hear your silent argument over the screen, and im certainly not interested in being educated by someone whose entire personality revolves around a man who wouldnt recognise them in a police lineup.

Sincerely, someone who has better things to be annoyed about

In Summary: * Listening to relaxing music as a pretty good Monday winds down. Was able to make good progress on some of the issues that were bothering me last night, so I won't have the weight of those on my mind tonight when head gets put to pillow.

Night meds and night prayers are in order now as I debate with myself whether or not to try and follow the early part tonight's World Series game.

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.

Health Metrics: * bw= 216.71 lbs. * bp= 128/80 (64)

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

Diet: * 04:15 – 1 banana * 05:15 – 2 little cookies * 06:45 – ½ roast beef sandwich * 09:10 – 1 peanut butter sandwich * 11:00 – snacking on M&M's * 13:00 – 1 fresh apple * 13:50 – fried livers and onions

Activities, Chores, etc.: * 03:00 – listen to local news talk radio * 03:50 – bank accounts activity monitored * 04:10 -read, write, pray, follow news reports from various sources, surf the socials, take daily meds, unpack, organize, and nap' * 09:20 – phoned Lakewood, left voice mail. * 09:54 – same as above * 13:30 – watching old episodes of Classic Doctor Who * 16:00 – follow news reports from various sources, surf the socials, organize * 17:00 – listening to relaxing music

Chess: * 08:30 – moved in all pending CC games