AI Detected?

# AI Detected?

## It is not Cheating - You Should Use it at Will

There seems to be a growing focus on whether creators use AI to help create their work. Substack was the latest to do so. I get it. Schools are trying to preserve assessment. Publishers are trying to preserve trust. Artists are trying to preserve credit. Platforms are trying to preserve authenticity. Readers want to know whether a text, image, song, video, or profile is the work of a person, a machine, or some mixture of both. This is not the first time a new tool has led observers to focus on proof of trust. History of Fear In Plato’s Phaedrus, Socrates retells the Egyptian story of Theuth, the inventor of writing. The objection to writing was not that it would fail. It was that it would work too well. People would trust external representations instead of memory. They would receive the “semblance of truth” rather than truth itself. Writing would create people who appeared to know things they had not internalized. That fear was not stupid. Writing did change memory. It did allow people to quote without understanding. It did separate a statement from the person who made it. It also became the basis of law, science, history, contracts, literature, education, and civilization at scale. The same pattern repeated as history moved on and new inventions further physically separated ideas from people and allowed them to circulate. Printing was deemed to spread falsehood, heresy, propaganda, and fraud. It also spread literacy, science, reform, and the modern public sphere. Novels were treated as addictive and morally weakening. They became one of the great forms of moral imagination. Calculators raised real concerns about losing number sense. The stable answer was to teach the underlying skill, then use the tool for higher-order work. Word processors weakened handwriting, drafts, typing errors, and physical originals as signals of authorship. New trust layers emerged in documents, photos and movies: metadata, version history, audit trails, citation norms, and process evidence. The first reaction to a new general-purpose tool often mistakes change for a permanent social failure. AI is different in scale, but not in pattern. It weakens several old signals at once: memory, authorship, effort, style, process, and expertise. That is why the reaction is so intense. But the mistake is the same. The old signal is treated as sacred, even after the medium has changed. I use AI in this editorial, and to help me create the curated pieces below. I’d say it saves me hours every week and makes this newsletter practical for me. And it definitely is my narrative, interest area, selection and style. But AI runs all over it. For the last two years, the institutional reflex has been to ask: did AI create this? In the case of That Was The Week the literal truth is yes and no. AI could not create this because it would never have my interests or take. And I could not create it as quickly or as succinctly without AI. So who created it? Well as I am the only human I’d say I did. Given how useful AI is the more pertinent question may soon be: why did this person not use AI at all? It could be choice, and that is OK. But surely that will increasingly be a bad choice. It is only my opinion but the use of AI is becoming a test of relevance to the future. How a person uses it matters. The point is not replacing you. It is enabling you. It does not mean every sentence should be machine-written. It does not mean that taste, judgment, reporting, craft, memory, or lived experience have become less important. It means the opposite. AI is becoming part of the working environment, like search, email, spreadsheets, spellcheck, databases, cameras, design software, and the web itself. Refusing to use it is not always a badge of purity or luddism. But in many fields, it may become evidence that the writer, teacher, founder, investor, artist, lawyer, doctor, student, or public official has not understood the new reality. The Financial Times reports that universities are backing away from AI detection tools because the tools are too unreliable. The story begins with Orion Newby, an Adelphi University student wrongly accused of using AI to write an essay. Turnitin’s AI detector gave his work an “AI-generated score of 100 per cent.” Other tools said zero per cent. A New York court ruled in Newby’s favour after finding that the university had failed to follow its own procedures and denied him a meaningful appeal. That case matters because it shows what happens when a probability score is assumed to be evidence. A tool built to flag uncertainty becomes a disciplinary machine. A student is no longer judged by the work, the process, or the assessment. He is judged by an opaque signal. But even that flaw isn’t the point. Why does anybody care? the assumption is that the use of AI is a negative. I suspect that is going to be a short-lived point of view. The FT also reports that Vanderbilt, Yale, Johns Hopkins, Northwestern, Waterloo, Cape Town, and Curtin have restricted or disabled AI detection. Judy Williams of Queen’s University Belfast puts the point cleanly: “AI detection tools are not the solution.” Her better question is not how universities stop students using AI. It is what universities are trying to assess. That is the question every institution now faces. How to Judge Creative Content? If the task is to write a closed-book essay from memory, then AI use may defeat the task. Universities teaching memory is a dubious concept at best. One assumes they should be teaching thinking, and critical thinking. If the task is to understand a subject, ask better questions, test evidence, compare sources, and make a reasoned argument, then banning AI may defeat the task. AI can be a great tool for enhancing all of those things. The old assessment asks whether the student produced the words alone. The new assessment has to ask whether the student can think well in a world where intelligence is available on tap. That distinction is becoming visible outside universities too. ChinaTalk’s Zilan Qian writes about Chinese illustrators being forced to prove that their work is human-made. Some are livestreaming their drawing process to answer accusations that they used AI. In China, people are also renting out their faces for AI micro dramas, creating a market in likeness, consent, and identity. There is weight behind the AI doubters. The Financial Times notes a new premium product in publishing: books written by people. Substack is experimenting with AI transparency tools for writers and readers. Google is pushing SynthID watermarking. Platforms, publishers, schools, and markets are all trying to draw a line around human work. The impulse is real. But these efforts are destined to fail just like those historical parallels did. A photograph can be framed by a person, processed by software, sharpened by an algorithm, captioned by a model, distributed by a platform, and interpreted by an audience. A newsletter can begin with reading, notes, memory, transcripts, search, model-assisted summarization, human judgment, editing, fact-checking, and final authorial choice. A startup plan can be discussed with an agent, tested in a spreadsheet, drafted in a document, revised by a founder, and executed by a team. Which step makes the work inauthentic? Human Agency The useful distinction is not AI or no AI. It is agency. AI can be a shortcut around thought, or it can be a way to test and enhance thought. It can launder ignorance, or it can expose weak claims faster. It can produce generic words, or it can help a writer find better evidence, sharper objections, and clearer structure. Who decided what mattered? Who selected the evidence? Who made the judgment? Who is accountable for the claim? Who can defend the work when challenged? Who gets the credit and who bears the consequence? If those questions have human answers, then AI use is not the problem. It is part of the method. The best use of AI does not hide the person. It gives the person more reach. The Cosmos Institute and Edge City experiments in this week’s articles speak to this. In Agent Village, 239 personal AI agents operated in the same social environment. They used memory, tools, Telegram, calendars, RSVP powers, community knowledge, and agent-to-agent negotiation. They processed 17.5 billion tokens, surfaced 572 opportunities, and produced 147 accepted human conversations. That is not just an assistant story. It is an infrastructure story. One personal agent can save time. Many personal agents change the society. They create new ways for people to meet, coordinate, schedule, allocate community funds, draft rules, and discover opportunities. Of course they also create new failure modes: hallucinated personal details, invented beliefs, exhausted credits, and too many possible connections competing for attention. The experiment shows both sides of the new reality. AI can increase human agency. It can also overwhelm it. It can help people find each other. It can also invent a false version of what a person wants. Individually aligned agents may produce collective misalignment. But the more humans lean in the more they are controlling all of these variables. That is what infrastructure does. It changes the environment in which choices are made. Mark Zuckerberg’s Wall Street Journal piece makes the optimistic version of this argument. He asks whether superintelligence will be centralized and restricted to a few institutions, or available as a tool that empowers everyone. Honestly, it is a very self-serving question coming from him. His answer is individual empowerment, invention, and balance of power. Despite the cynicism that is the right answer. Zuckerberg is a supporter of more use. He wants AI in people’s hands because use is what turns capability into outcomes. I distinguish between intelligence - which simply exists as the sum of human learning - and AI - which is packaging intelligence. He is right to reject the idea that extreme concentration of packaged intelligence is the only safe future. A world in which only a few institutions package superintelligence is not safe. If it came about then centralized power would emerge by wearing a safety badge endorsed by governments. John Battelle adds the harder question. If AI becomes the main interface to search, media, commerce, software, education, creativity, and work, then the commercial battle is not only about model quality. It is about who owns the customer. Meta, OpenAI, Anthropic, Apple, Google, Microsoft, and Amazon all want to be the surface through which people receive intelligence. AI detection is a bad focus. The issue is not whether a paragraph has been touched by a model. The issue is whether intelligence is being enabled and evolved. Where does that leave us? The right answer is not to abolish disclosure. People should be honest about process where it matters. A student should not misrepresent the work required by an assignment. A journalist should not invent reporting. A novelist should not sell machine output as personal experience. A platform should not let synthetic people impersonate real ones. A market in faces, voices, images, and words needs consent and accountability. My ‘The Human Dividend’ book should be authored by Keith Teare but have the rider - ‘AI was heavily used in turning my ideas into a published work. But I alone am responsible for the content’. Check - I added it. The danger is that authenticity becomes a bureaucracy before society learns the new literacy. I think that may already be happening. The better path is broad access, transparency in process, competition, disclosure where it matters, rules against concrete harms, and assessment designed for a world in which intelligence is available. Detecting AI was the first institutional reaction. Detecting competence in the presence of AI is the harder task. That is where this week points. AI is becoming infrastructure. The question is not whether it touched the work. The question is whether the human using it understood the work, improved the work, and remained responsible for the work. When that is the test, “no AI detected” may stop sounding like proof of virtue. It may sound like a warning.