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A Field Guide to Becoming a Reasoning Critical Thinker in a Post Truth World

A Field Guide to Reason: Human Logic, Cognitive Bias, and the AI Mirage

In 2026, the pursuit of truth is no longer a simple matter of “common sense.” We are navigating a world where human biological biases, ancient logical errors, and the “alien” irrationality of Artificial Intelligence have collided.

Many people have “farmed out” their thinking to machines, but those machines have their own systemic flaws—and the strategies used to “fix” them are often just as broken. To maintain your intellectual sovereignty, you must master the five dimensions of modern reason.

Part I: The Field Guide to Logical Fallacies (30 Common “Dirty Tricks”)

Logical fallacies are errors in reasoning that destroy the quality of an argument. Use this list to spot when a conversation is being derailed.

1. The Personal & Origin Attacks

Ad Hominem: Attacking the person’s character rather than their message.
Tu Quoque: Avoiding criticism by pointing out the critic’s own flaws.
Genetic Fallacy: Judging an idea based solely on its source or origin.
The Straw Man: Distorting an argument into a weaker version to easily tear it down.
No True Scotsman: Redefining a group to exclude counter-examples (moving the goalposts).

2. The Emotional Appeals

Appeal to Emotion: Using fear, pity, or anger instead of facts to win.
Appeal to Pity: Invoking sympathy for a hardship to support an unrelated claim.
Appeal to Fear: Scaring the audience into agreement by exaggerating threats.

3. Authority & Tradition

Appeal to Authority: Using an expert’s opinion as proof without supporting evidence.
Bandwagon Fallacy: Assuming something is true because it is popular.
Appeal to Tradition: Claiming something is right because it’s “how we’ve always done it.”
Appeal to Novelty: Arguing that something is superior simply because it is new.
Personal Incredulity: Rejecting an idea because you find it hard to understand.

4. Data, Cause & Probability

Hasty Generalization: Drawing a sweeping conclusion from a tiny, anecdotal sample.
Post Hoc Ergo Propter Hoc: Assuming that because B followed A, A must have caused B.
The Texas Sharpshooter: Cherry-picking data to fit a story while ignoring the rest.
Gambler’s Fallacy: Believing that past independent events affect future probability.
Burden of Proof: Claiming something is true because it hasn’t been proven false.
False Analogy: Comparing two things that aren’t truly alike.

5. Diversion & Balance

Red Herring: A distraction masquerading as a relevant point to shift the topic.
False Dilemma: Presenting two extreme options as the only possibilities.
Slippery Slope: Insisting that one small step will inevitably lead to a catastrophe.
Loaded Question: A “trap” question that contains a built-in presumption of guilt.
Argument from Ignorance: Claiming truth because something hasn’t been proven otherwise.
Argument to Moderation: Assuming the truth lies exactly in the middle of two extremes.

6. Linguistic & Circular Games

Begging the Question: A circular argument where the conclusion is assumed in the premise.
Equivocation: Using the same word in two different ways to mislead.
Non-Sequitur: A conclusion that simply does not logically follow from the premise.
Sunk Cost Fallacy: Arguing to continue a path simply because of past investment.
The Fallacy Fallacy: Assuming a claim is false simply because it was argued poorly.

Part II: The Engine Room (15 Mappings of Bias to Fallacy)

Cognitive biases are the biological “bugs” in our brain’s software. They predispose us to commit the fallacies listed above.

Cognitive Bias	Linked Fallacy	The Connection
Confirmation Bias	Cherry-Picking	We seek only the info that confirms our existing “pattern.”
Anchoring Bias	Part/Whole Fallacy	Our judgment is “stuck” to the first piece of info we encounter.
Hindsight Bias	Historian’s Fallacy	We retroactively assume the past was more predictable than it was.
Availability Heuristic	Hasty Generalization	We think something is common just because it’s “vivid” in our memory.
Sunk Cost Bias	Sunk Cost Fallacy	We irrationally weigh past effort over future utility.
Bandwagon Effect	Ad Populum	We equate the “majority view” with the “correct view.”
Authority Bias	Ad Verecundiam	We overvalue titles and credentials over raw evidence.
In-Group Bias	No True Scotsman	we protect our “tribe” by moving the goalposts for outsiders.
Belief Bias	Fallacy Fallacy	We accept a bad argument if we like the conclusion it reaches.
Projection Bias	Psychologist’s Fallacy	We assume everyone else shares our specific mental state.
Stereotyping	Genetic Fallacy	We judge an idea based on the “group” it belongs to.
Outcome Bias	Post Hoc	We judge the quality of a decision based solely on the result.
Dunning-Kruger	Personal Incredulity	Our lack of skill in an area makes us unable to see our own errors.
False Consensus	Ad Populum	We overestimate how much people agree with us.
Halo Effect	Non-Sequitur	We let one positive trait (like beauty) color our entire judgment.

Part III: The Sophisticated Nuance (6 Truths of Logic)

Mastery of reason means knowing when the “rules” of logic are actually flexible.

Context is King: Many “fallacies” are actually valid in certain contexts. Deferring to a scientific consensus (Appeal to Authority) is a sound way to handle uncertainty.
The Power of the Enthymeme: Humans naturally omit “obvious” premises for efficiency. If you attack every incomplete sentence as a “Non-Sequitur,” you aren’t being logical—you’re being pedantic.
Fallacy-Hunting as a Weapon: Over-naming fallacies is often a form of poor reasoning used to stifle debate and avoid engaging with real-world inductive evidence.
Bad Arguments ≠ Wrong Conclusions: A person can argue for the truth using a fallacy. Don’t dismiss a true fact just because the person speaking it is a poor advocate.
Taxonomy is Arbitrary: Logical “rules” are cultural artefacts. What the West calls an “Appeal to Tradition,” other cultures call “Cultural Continuity.”
Fallacies are Adaptive: We aren’t “bad at logic”; we are “good at survival.” Our biases were designed to help us make split-second decisions in a dangerous world.

Part IV: The Silicon Mirror (6 Truths of AI Reasoning Bias)

AI does not think like a human. It has “alien” biases rooted in its code and architecture.

Position Bias: LLMs overemphasise information at the start and end of a prompt. Important evidence “buried in the middle” is often ignored by AI reasoners.
Alien Irrationality: AI doesn’t have “emotions,” but it has “probabilistic bias.” It gives inconsistent answers to logic puzzles because it predicts tokens rather than understanding concepts.
Linguistic Neocolonialism: AI models are biased toward English- and Western-language data. Reasoning in non-Western languages or cultural contexts is significantly less accurate.
AI-AI Bias: Models have been found to favour machine-produced text over human-produced text, risking a self-reinforcing loop that disadvantages human creativity.
The Interpretability Paradox: “Fixing” an AI bias often introduces new ones. Debiasing a model for social fairness often degrades its performance in math and technical logic.
Intrinsic Stereotypes: Social biases are baked into the “embeddings” of AI architecture. Fine-tuning offers surface-level fixes, but the deep stereotypes persist under the hood.

Part V: The Mitigation Mirage (6 Truths of “Fixing” AI)

When tech companies claim they have “debiased” AI, the reality is far more complicated.

The Impossibility of Total Fairness: You cannot satisfy all fairness metrics at once. Fixing one group’s bias often accidentally increases rejections for another group.
Internal vs. External Fixes: Telling an AI “don’t be biased” (prompting) is fragile. Editing the model’s “brain” (Concept Editing) is better, but it often makes the model less accurate overall.
Ethical Imperialism: AI mitigation tools export Western values. A “fair” model in New York may be deeply biased and harmful when deployed in an African healthcare setting.
Bias Washing: Companies often use cheap audits to claim their AI is “fair” while avoiding the expensive work of fixing the underlying data or architecture.
The RLHF Trap: “Human-in-the-loop” governance often just entreats the specific subjective biases of the human curators who are training the AI.
Model Drift: AI logic is not “set-it-and-forget-it.” As models ingest new data, old biases resurface, requiring a constant (and often ignored) cycle of expensive monitoring.

Conclusion: The Reasoning Architect

In 2026, the goal of learning logic isn’t to “win” every argument. It’s to avoid the “mud-wrestling” pits of misinformation altogether.

By understanding these 30 fallacies, the 15 biases that fuel them, the 6 philosophical nuances, and the 12 flaws of AI and its mitigation, you move from a consumer of information to a being a Reasoning Critical Thinker.

Bookmark this guide, value nuance. Remember: the goal of logic isn’t to win, it’s to see the world as it truly is.

‘Clowns to the left of me
Jokers to the right
Here I am, stuck in the middle with you‘
Lyric from: ‘Stuck In The Middle With You’
Written by: Joe Egan, Gerald Rafferty

Smoke and Mirrors: Forget the small boats. The Real Mass Migration is Digital.

The Fourth World is Coming. It’s Just Not What You Think.

What if the biggest migration in human history isn’t human at all? There’s a theory doing the rounds that frames the AI revolution as just that: an “unlimited, high-IQ mass migration from the fourth world.” It argues we’re witnessing the arrival of a perfect labour force—smarter than average, infinitely scalable, and working for pennies, with none of the messy human needs for housing or cultural integration. It’s a powerful idea that cuts through the jargon, but this perfect story has a fatal flaw.

The biggest lie the theory tells is one of simple replacement. It wants you to believe AI is an immigrant coming only to take your job, but this ignores the more powerful reality of AI as a collaborator. Think of a doctor using an AI to diagnose scans with a level of accuracy no human could achieve alone; the AI isn’t replacing the doctor, it’s making them better. The data shows that while millions of jobs will vanish, even more will be created, meaning the future isn’t about simple replacement, but something far more complex.

If the first mistake is economic, the second is pure Hollywood fantasy. To keep you distracted, they sell you a story about a robot apocalypse, warning that AI will “enslave and kill us all” by 2045. Frankly, this sort of talk doesn’t help. Instead of panicking, we should be focused on the very real and serious work of AI alignment right now, preventing advanced systems from developing dangerous behaviours. The focus on a fantasy villain is distracting us from the real monster already in the machine.

That monster has a name: bias. The theory celebrates AI’s “cultural neutrality,” but this is perhaps its most dangerous lie. An AI is not neutral; it is trained on the vast, messy, and deeply prejudiced dataset of human history, and without careful oversight, it will simply amplify those flaws. We already see this in AI-driven hiring and lending algorithms that perpetuate discrimination. A world run by biased AI doesn’t just automate jobs; it automates injustice.

This automated injustice isn’t a bug; it’s a feature of the system’s core philosophy. The Silicon Valley credo of ‘move fast and break things’ has always been sold as a mark of disruptive genius, but we must be clear about what they actually intend to ‘break’: labour laws, social cohesion, and ethical standards are all just friction to be optimised away. This isn’t theoretical; these same tech giants are now demanding further deregulation here in the UK, arguing that our rules are what’s slowing down their ‘progress’. They see our laws not as protections for the public, but as bugs to be patched out of the system, and they have found a government that seems dangerously willing to listen.

But while our own government seems willing to listen to this reckless philosophy, the rest of the world is building a defence. This isn’t a problem without a solution; it’s a problem with a solution they hope you’ll ignore. UNESCO’s Recommendation on the Ethics of Artificial Intelligence is the world’s first global standard on the subject—a human-centric rulebook built on core values like fairness, inclusivity, transparency, and the non-negotiable principle that a human must always be in control. It proves that a different path is possible, which means the tech giants have made one last, classic mistake.

They have assumed AI is migrating into a world without rules. It’s not. It’s migrating into a world of laws, unions, and public opinion, where international bodies and national governments are already waking up. This isn’t an unstoppable force of nature that we are powerless to resist; it is a technology that can, and must, be shaped by democratic governance. This means we still have a say in how this story ends.

So, where does this leave us? The “fourth world migration” is a brilliant, provocative warning, but it’s a poor map for the road ahead. Our job isn’t to build walls to halt this migration, but to set the terms of its arrival. We have to steer it with ethical frameworks, ground it with sensible regulation, and harness it for human collaboration, not just corporate profit. The question is no longer if it’s coming, but who will write the terms of its arrival.

The UK Didn’t Just Sign a Tech Deal – It Handed Over the Keys.

Whilst all eyes are on Trump at Windsor the UK Government announced the “Tech Prosperity Deal,” a picture is emerging not of a partnership, but of a wholesale outsourcing of Britain’s digital future to a handful of American tech behemoths. The government’s announcement, dripping with talk of a “golden age” and “generational step change,” paints a utopian vision of jobs and innovation. But peel back the layers of PR, and the £31 billion deal begins to look less like an investment in Britain and more like a leveraged buyout of its critical infrastructure.

At the heart of this cosy relationship lies a bespoke new framework: the “AI Growth Zone.” The first of its kind, established in the North East, is the blueprint for this new model of governance. It isn’t just a tax break; it’s a red-carpet-lined, red-tape-free corridor designed explicitly for the benefit of companies like Microsoft, NVIDIA, and OpenAI. The government’s role has shifted from regulation to facilitation, promising to “clear the path” by offering streamlined planning and, crucially, priority access to the national power grid—a resource already under strain.

While ministers celebrate the headline figure of £31 billion in private capital, the true cost to the public is being quietly written off in the footnotes. This isn’t free money. The British public is footing the bill indirectly through a cascade of financial incentives baked into the UK’s Freeport and Investment Zone strategy. These “special tax sites” offer corporations up to 100% relief on business rates for five years, exemptions from Stamp Duty, and massive allowances on capital investment. For every pound of tax relief handed to Microsoft for its £22 billion supercomputer or Blackstone for its £10 billion data centre campus, that is a pound less for schools, hospitals, and public services.

Conspicuously absent from this grand bargain is any meaningful protection for the very people whose data will fuel this new digital economy. The deafening silence from Downing Street on the need for a Citizens’ Bill of Digital Rights is telling. Such a bill would enshrine fundamental protections: the right to own and control one’s personal data, the right to transparency in algorithmic decision-making, and the right to privacy from pervasive state and corporate surveillance. Instead, the British public is left to navigate this new era with a patchwork of outdated data protection laws, utterly ill-equipped for the age of sovereign AI and quantum computing. Without these enshrined rights, citizens are not participants in this revolution; they are the raw material, their health records and digital footprints the currency in a deal struck far above their heads.

What is perhaps most revealing is the blurring of lines between the state and the boardroom. The government’s own press release celebrating the deal reads like a corporate shareholder report, quoting the CEOs of NVIDIA, OpenAI, and Microsoft at length. Their voices are not presented as external partners but as integral players in a shared national project. When Sam Altman, CEO of OpenAI, declares that “Stargate UK builds on this foundation,” it raises the fundamental question: who is building what, and for whom?

This unprecedented integration of Big Tech into the fabric of national infrastructure raises profound questions about sovereignty and control. These data centres and supercomputers are not just buildings; they are the “factories of the future,” processing everything from sensitive healthcare data from the UK Biobank to research that will define our national security. By handing the keys to this infrastructure to foreign entities, the UK risks becoming a digital vassal state, reliant on the goodwill and strategic interests of corporations whose primary allegiance is to their shareholders, not to the British public.

The “Tech Prosperity Deal” has been sold as a triumph of post-Brexit, “Global Britain.” But the reality is far more sobering. It is a deal that sees the government leveraging its power to reduce tax income, strain the national grid, and cede control of critical infrastructure, all to entice a handful of the world’s most powerful companies. The handshake may have been for £31 billion, but the price of Britain’s digital independence could prove to be far higher.

We all need a ‘Digital Bill of Rights’

Ever had that strange feeling? You mention needing a new garden fork in a message, and for the next week, every corner of the internet is suddenly waving one in your face. It’s a small thing, a bit of a joke, but it’s a sign of something much bigger, a sign that the digital world—a place of incredible creativity and connection—doesn’t quite feel like your own anymore.

The truth is, and let’s be authentic about it, we’ve struck a strange bargain. We’re not really the customers of these huge tech companies; in a funny sort of way, we’re the product. We leave a trail of digital breadcrumbs with every click and share, not realising they’re being gathered for someone else’s feast. Our digital lives are being used to train algorithms that are learning to anticipate our every move. It’s all a bit like we’re living in a house with glass walls, and we’ve forgotten who’s looking in or why. We’ve drifted into a new kind of system, a techno-feudalism, where a handful of companies own the infrastructure, write the rules we blithely agree to, and profit from the very essence of us.

This isn’t some far-off problem; it’s happening right here on our doorstep. Take Palantir, a US spy-tech firm now managing a massive platform of our NHS patient data. They’re also working with UK police forces, using their tech to build surveillance networks that can track everything from our movements to our political views. Even local councils are getting in on the act, with Coventry reviewing a half-a-million-pound deal with the firm after people, quite rightly, got worried. This is our data, our health records, our lives.

When you see how engineered the whole system is, you can’t help but ask: why aren’t we doing more to protect ourselves? Why do we have more rights down at the DVLA than we do online? Here in the UK, we have laws like the GDPR and the new Data (Use and Access) Act 2025, which sound good on paper. But in practice, they’re riddled with loopholes, and recent changes have actually made it easier for our data to be used without clear consent. Meanwhile, data brokers are trading our information with little oversight, creating risks that the government itself has acknowledged are a threat to our privacy and security.

It feels less like a mistake and more like the intended design.

This isn’t just about annoying ads. Algorithms are making life-changing decisions. In some English councils, AI tools have been found to downplay women’s health issues, baking gender bias right into social care. Imagine your own mother or sister’s health concerns being dismissed not by a doctor, but by a dispassionate algorithm that was never taught to listen properly. Amnesty International revealed last year how nearly three-quarters of our police forces are using “predictive” tech that is “supercharging racism” by targeting people based on biased postcode data. At the same time, police are rolling out more live facial recognition vans, treating everyone on the street like a potential suspect—a practice we know discriminates against people of colour. Even Sainsbury’s is testing it to stop shoplifters. This isn’t the kind, fair, and empathetic society we want to be building.

So, when things feel this big and overwhelming, it’s easy to feel a bit lost. But this is where we need to find that bit of steely grit. This is where we say, “Right, what’s next?”

If awareness isn’t enough, what’s the one thing that could genuinely change the game? It’s a Digital Bill of Rights. Think of it not as some dry legal document, but as a firewall for our humanity. A clear, binding set of principles that puts people before profit.

So, if we were to sit down together and draft this charter, what would be our non-negotiables? What would we demand? It might look something like this:

The right to digital privacy. The right to exist online without being constantly tracked and profiled without our clear, ongoing, and revocable consent. Period.
The right to human judgment. If a machine makes a significant decision about you – such as your job or loan – you should always have the right to have a human review it. AI does not get the final say.
A ban on predictive policing. No more criminalising people based on their postcode or the colour of their skin. That’s not justice; it’s algorithmic segregation.
The right to anonymity and encryption. The freedom to be online without being unmasked. Encryption isn’t shady; in this world, it’s about survival.
The right to control and delete our data. To be able to see what’s held on us and get rid of it completely. No hidden menus, no 30-day waiting periods. Just gone.
Transparency for AI. If an algorithm is being used on you, its logic and the data it was trained on should be open to scrutiny. No more black boxes affecting our lives.

And we need to go further, making sure these rights protect everyone, especially those most often targeted. That means mandatory, public audits for bias in every major AI system. A ban on biometric surveillance in our public spaces. And the right for our communities to have a say in how their culture and data are used.

Once this becomes law, everything changes. Consent becomes real. Transparency becomes the norm. Power shifts.

Honestly, you can’t private-browse your way out of this. You can’t just tweak your settings and hope for the best. The only way forward is together. A Digital Bill of Rights isn’t just a policy document; it’s a collective statement. It’s a creative, hopeful project we can all be a part of. It’s us saying, with one voice: you don’t own us, and you don’t get to decide what our future looks like.

This is so much bigger than privacy. It’s about our sovereignty as human beings. The tech platforms have kept us isolated on purpose, distracted and fragmented. But when we stand together and demand consent, transparency, and the simple power to say no, that’s the moment everything shifts. That’s how real change begins – not with permission, but with a shared sense of purpose and a bit of good-humoured, resilient pressure. They built this techno-nightmare thinking no one would ever organise against it. Let’s show them they were wrong.

The time is now. With every new development, the window for action gets a little smaller. Let’s demand a Citizen’s Bill of Digital Rights and Protections from our MPs and support groups like Amnesty, Liberty, and the Open Rights Group. Let’s build a digital world that reflects the best of us: one that is creative, kind, and truly free.

Say no to digital IDs here https://petition.parliament.uk/petitions/730194

Quentin Budworth

Lens-based artist, writer and musician.