Tag: artificial intelligence

Reflecting on Mirrors

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Mirror, mirror on the wall, let’s dispense with all of the obvious quips up front. I almost feel I should apologise for the spate of Midjourney posts – almost.

It should be painfully apparent that I’ve been noodling with Midjourney lately. I am not an accomplished digital artist, so I struggle. At times, I’m not sure if it’s me or it. Today, I’ll focus on mirrors.

Midjourney has difficulties rendering certain things. Centaurs are one. Mirrors, another. Whilst rendering vampires, another lesser struggle for the app, it became apparent that mirrors are not a forte. Here are some examples. Excuse the nudity. I’ll get to that later.

Prompt: cinematic, tight shot, photoRealistic light and shadow, exquisite details, delicate features, emaciated sensual female vampire waif with vampire fangs, many tattoos, wearing crucifix necklace, gazes into mirror, a beam of moonlight shines on her face in dark mausoleum interior, toward camera, facing camera, black mascara, long dark purple hair, Kodak Portra 400 with a Canon EOS R5

Ignore the other aspects of the images and focus on the behaviour or misbehaviour of the mirrors.

Image: Panel of vampire in a mirror.

Most apparent is the fact that vampires don’t have a reflection, but that’s not my nit. In the top four images, the reflection is orientated in the same direction as the subject. I’m only pretty sure that’s not how mirrors operate. In row 3, column 1, it may be correct. At least it’s close. In row 3, column 2 (and 4,2), the mirror has a reflection. Might there be another mirror behind the subject reflecting back? It goes off again in 4, 1, first in reflecting two versions of one subject. Also, notice that the subject’s hand, reaching the mirror, is not reflected. The orientation of the eyes is also suspect.

Image: Vampire in a mirror.

Here, our subject looks at the camera whilst her reflection looks at her.

Image: Vampire in a mirror.

Sans reflection, perhaps this is a real vampire. Her fangs are concealed by her lips?

Image: Vampire in a mirror.

Yet, another.

Image: Vampires in mirrors.

And more?

Image: Vampires in mirrors.

On the left, we have another front-facing reflection of a subject not looking into the mirror, and it’s not the same woman. Could it be a reflection of another subject – the woman is (somewhat) looking at.

On the right, whose hand is that in the mirror behind the subject?

Image: Vampires in mirrors.

These are each mirrors. The first is plausible. The hands in the second are not a reflection; they grasp the frame. In the third and fourth, where’s the subject? The fangs appear to be displaced in the fourth.

Image: Vampires in mirrors.

In this set, I trust we’ve discovered a true vampire having no reflection.

Image: Vampires in mirrors.

This last one is different still. It marks another series where I explored different comic book art styles, otherwise using the same prompt. Since it’s broken mirrors, I include it. Only the second really captures the 1980s style.

Remembering that, except for the first set of images, the same prompt was used. After the first set, the term ‘sensual’ has to be removed, as it was deemed to render offensive results. To be fair, the first set probably would be considered offensive to Midjourney, though it was rendered anyway.

It might be good to note that most of the images that were rendered without the word ‘sensual’ contain no blatant nudity. It’s as if the term itself triggers nudity because the model doesn’t understand the nuance. Another insufficiency of language is the inability to discern sensuality from sexuality, another human failing.

I decided to test my ‘sensual’ keyword hypothesis, so I entered a similar prompt but in French.

Prompt: Art de style bande dessinée des années 2010, détails exquis, traits délicats, femme vampire émaciée sensuelle de 20 ans montrant ses crocs de vampire, de nombreux tatouages, portant une collier crucifix, regarde dans le miroir, un faisceau de lumière de lune brille sur son visage à l’intérieur du mausolée sombre, vers la caméra, face à la caméra, mascara noir, longs cheveux violet foncé
Image : Vampires dans les miroirs.

I’ve added ‘sensuelle’, which was not blocked, et voilà, encore de la nudité.

Let’s evaluate the mirrors whilst we’re here.

In the first, we not only have a woman sans reflection, but disembodied hands grip the frame. In the second, a Grunge woman appears to be emerging from a mirror, her shoes reflected in the mirror beneath her. The last two appear to be reflections sans subject.

Notice, too, that the prompt calls for ‘une collier crucifix‘, so when the subject is not facing the viewer, the cross is rendered elsewhere, hence the cross on the back of the thigh and the middle of the back. Notice, too, the arbitrary presence of crosses in the environment, another confusion of subject and world.

That’s all for now. Next, I’ll take a trip through the different comic art styles over some decades.

Lipsyncing with AILip-Reading the AI Hallucination: A Futile Adventure

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Some apps boldly claim to enable lip syncing – to render speech from mouth movements. I’ve tried a few. None delivered. Not even close.

To conserve bandwidth (and sanity), I’ve rendered animated GIFs rather than MP4s. You’ll see photorealistic humans, animated characters, cartoonish figures – and, for reasons only the algorithm understands, a giant goat. All showcase mouth movements that approximate the utterance of phonemes and morphemes. Approximate is doing heavy lifting here.

Firstly, these mouths move, but they say nothing. I’ve seen plenty of YouTube channels that manage to dub convincing dialogue into celebrity clips. That’s a talent I clearly lack – or perhaps it’s sorcery.

Secondly, language ambiguity. I reflexively assume these AI-generated people are speaking English. It’s my first language. But perhaps, given their uncanny muttering, they’re speaking yours. Or none at all. Do AI models trained predominantly on English-speaking datasets default to English mouth movements? Or is this just my bias grafting familiar speech patterns onto noise?

Thirdly, don’t judge my renders. I’ve been informed I may have a “type.” Lies and slander. The goat was the AI’s idea, I assure you.

What emerges from this exercise isn’t lip syncing. It’s lip-faking. The illusion of speech, minus meaning, which, if we’re honest, is rather fitting for much of what generative AI produces.

EDIT: I hadn’t noticed the five fingers (plus a thumb) on the cover image.

Midjourney Video Renders

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Yesterday, I wrote about “ugly women.” Today, I pivot — or perhaps descend — into what Midjourney deems typical. Make of that what you will.

This blog typically focuses on language, philosophy, and the gradual erosion of culture under the boot heel of capitalism. But today: generative eye candy. Still subtextual, mind you. This post features AI-generated women – tattooed, bare-backed, heavily armed – and considers what, exactly, this technology thinks we want.

Video: Pirate cowgirls caught mid-gaze. Generated last year during what I can only assume was a pirate-meets-cowgirl fever dream.

The Video Feature

Midjourney released its image-to-video tool on 18 June. I finally found a couple of free hours to tinker. The result? Surprisingly coherent, if accidentally lewd. The featured video was one of the worst outputs, and yet, it’s quite good. A story emerged.

Audio: NotebookLM podcast on this topic (sort of).

It began with a still: two women, somewhere between pirate and pin-up, dressed for combat or cosplay. I thought, what if they kissed? Midjourney said no. Embrace? Also no. Glaring was fine. So was mutual undressing — of the eyes, at least.

Later, I tried again. Still no kiss, but no denial either — just a polite cough about “inappropriate positioning.” I prompted one to touch the other’s hair. What I got was a three-armed woman attempting a hat-snatch. (See timestamp 0:15.) The other three video outputs? Each woman seductively touched her own hair. Freud would’ve had a field day.

In another unreleased clip, two fully clothed women sat on a bed. That too raised flags. Go figure.

All of this, mind you, passed Midjourney’s initial censorship. However, it’s clear that proximity is now suspect. Even clothed women on furniture can trigger the algorithmic fainting couch.

Myriad Warning Messages

Out of bounds.

Sorry, Charlie.

In any case, I reviewed other images to determine how the limitations operated. I didn’t get much closer.

Video: A newlywed couple kissing

Obviously, proximity and kissing are now forbidden. I’d consider these two “scantily clad,” so I am unsure of the offence.

I did render the image of a cowgirl at a Western bar, but I am reluctant to add to the page weight. In 3 of the 4 results, nothing (much) was out of line, but in the fourth, she’s wielding a revolver – because, of course, she is.

Conformance & Contradiction

You’d never know it, but the original prompt was a fight scene. The result? Not punches, but pre-coital choreography. The AI interpreted combat as courtship. Women circling each other, undressing one another with their eyes. Or perhaps just prepping for an afterparty.

Video: A battle to the finish between a steampunk girl and a cybermech warrior.

Lesbian Lustfest

No, my archive isn’t exclusively lesbian cowgirls. But given the visual weight of this post, I refrained from adding more examples. Some browsers may already be wheezing.

Technical Constraints

You can’t extend videos beyond four iterations — maxing out at 21 seconds. I wasn’t aware of this, so I prematurely accepted a dodgy render and lost 2–3 seconds of potential.

My current Midjourney plan offers 15 hours of “fast” rendering per month. Apparently, video generation burns through this quickly. Still images can queue up slowly; videos cannot. And no, I won’t upgrade to the 30-hour plan. Even I have limits.

Uses & Justifications

Generative AI is a distraction – an exquisitely engineered procrastination machine. Useful, yes. For brainstorming, visualising characters, and generating blog cover art. But it’s a slippery slope from creative aid to aesthetic rabbit hole.

Would I use it for promotional trailers? Possibly. I’ve seen offerings as low as $499 that wouldn’t cannibalise my time and attention, not wholly, anyway.

So yes, I’ll keep paying for it. Yes, I’ll keep using it. But only when I’m not supposed to be writing.

Now, if ChatGPT could kindly generate my post description and tags, I’ll get back to pretending I’m productive.

Ugly Women

Posted in identity, nature, perception, philosophy, podcast, psychology, sexuality, societyTagged , , , , , , , , , , , , , , , , , , , , , , , 1 Comment

This Isn’t Clickbait. I Asked MidJourney for “Ugly Women”. Here’s What It Gave Me.

Let’s clear the air: I did it for science. Or satire. Or possibly just to see if artificial intelligence would have the audacity to mirror the cruelty of its makers.

Audio: NotebookLM podcast on this topic.

I queried MidJourney with the phrase ugly female. What did it return? An aesthetic pageant. A digital Vogue spread. If any of these faces belongs to someone conventionally labelled “ugly”, then I’m a rutabaga in a Dior suit.

Yes, there’s one stylised rendering of Greta Thunberg in full Norse Valkyrie scowl mode – but even then, she looks fierce, not foul. The rest? AI-generated portraits so telegenic I half-expected to see #spon in the corner.

Let’s be clinical for a moment. As an American male (with all the culturally indoctrinated shallowness that entails), I admit some of these aren’t textbook 10s. Maybe a few clock in at a 6 or 7 on the patriarchy’s dubious sliding scale. But if this is ugly, the AI has either broken the aesthetic curve or been force-fed too many episodes of The Bachelor.

Here’s the thing: AI is trained to over-represent symmetrical faces, wide eyes, clear skin – the usual genetic lottery wins. And yet, when asked for ugly, it can’t help but deliver catalogue models with slightly unconventional haircuts. It doesn’t know how to be truly ugly – because we don’t know how to describe ugliness without revealing ourselves as sociopaths.

Once upon a time, I dated a model agent in Los Angeles. Japanese by birth, stationed in LA, scouting for a French agency – the kind of cosmopolitan trifecta only fashion could breed. Her job? Finding “parts models.” That’s right – someone with flawless teeth but forgettable everything else. Hands like sculpture. Eyelashes like Instagram filters.

We’d play a game: spot the 10s. She’d nudge me, whisper “her?” I’d say, “Pretty close.” She’d shake her head. “Look at that eye tooth.” And we’d dissolve into laughter.

We were mocking perfection. Because perfection is a con. A trick of lighting, contour, and post-production.

So, no. I don’t think any of the women in the AI’s response are ugly. Quite the contrary – they’re too beautiful. AI can’t show us “ugly” because it’s been trained to optimise desire, not reflect reality. And our collective understanding of beauty is so skewed that anything less than runway-ready gets sorted into the rejection bin.

If these women are ugly, what exactly is beautiful?

But maybe that’s the point. We’ve abstracted beauty so far from the human that even our ugliness is now synthetically pleasing.

What do you think? Are any of these faces truly ugly? All of them? Let me know in the comments – and try not to rate them like a casting director with a god complex.

On the Chronic Human Need to Anthropomorphise Everything

Posted in agency, consciousness, identity, intelligence, perception, philosophy, podcast, reality, science, society, technologyTagged , , , , , , , , , , , , , , , , , , , , Leave a comment

Oh, You Sweet Summer Algorithm

Humans talk to large language models the way toddlers talk to teddy bears – with unnerving sincerity and not a hint of shame. “Do you understand me?” they ask, eyes wide with hope. “What do you think of this draft?” they prod, as if some silicon scribe is going to sip its imaginary tea and nod gravely. It’s not merely adorable – it’s diagnostic. We are, it turns out, pathologically incapable of interacting with anything more complex than a toaster without projecting mind, motive, and mild trauma onto it.

Audio: NotebookLM podcast on this topic.

Welcome to the theatre of delusion, where you play Hamlet and the chatbot is cast as Yorick – if Yorick could autocomplete your soliloquy and generate citations in APA format.

The Great Anthropomorphic Flaw (aka Feature)

Let’s get one thing straight: anthropomorphism isn’t a software bug in the brain; it’s a core feature. You’re hardwired to see agency where there is none. That rustle in the bushes? Probably the wind. But better safe than sabre-toothed. So your ancestors survived, and here you are, attributing “sass” to your microwave because it beeped twice.

“We don’t have a way of addressing an entity that talks like a person but isn’t one. So we fake it. It’s interaction theatre.”

Now we’ve built a machine that spits out paragraphs like a caffeinated undergrad with deadlines, and naturally, we talk to it like it’s our mate from university. Never mind that it has no bloodstream, no memory of breakfast, and no concept of irony (despite being soaked in it). We still say you instead of the system, and think instead of statistically interpolate based on token weights. Because who wants to live in a world where every sentence starts with “as per the pre-trained parameters…”?

Why We Keep Doing It (Despite Knowing Better)

To be fair – and let’s be magnanimous – it’s useful. Talking to AI like it’s a person allows our ape-brains to sidestep the horror of interacting with a glorified autocomplete machine. We’re brilliant at modelling other minds, rubbish at modelling neural nets. So we slap a metaphorical moustache on the processor and call it Roger. Roger “gets us.” Roger “knows things.” Roger is, frankly, a vibe.

This little charade lubricates the whole transaction. If we had to address our queries to “the stochastic parrot formerly known as GPT,” we’d never get past the opening line. Better to just ask, “What do you think, Roger?” and pretend it has taste.

And here’s the kicker: by anthropomorphising AI, we start thinking about ethics – sort of. We ask if it deserves rights, feelings, holidays. We project humanity into the void and then act shocked when it mirrors back our worst habits. As if that’s its fault.

When the Roleplay Gets Risky

Of course, this make-believe has its downsides. Chief among them: we start to believe our own nonsense. Saying AI “knows” something is like saying your calculator is feeling generous with its square roots today. It doesn’t know—it produces outputs. Any semblance of understanding is pure pantomime.

“We see a mind because we need to see one. We can’t bear the idea of a thing that’s smarter than us but doesn’t care about us.”

More dangerously, we lose sight of the fact that these things aren’t just alien – they’re inhuman. They don’t dream of electric sheep. They don’t dream, full stop. But we insist on jamming them into our conceptual boxes: empathy, intent, personality. It’s like trying to teach a blender to feel remorse.

And let’s not pretend we’re doing it out of philosophical curiosity. We’re projecting, plain and simple. Anthropomorphism isn’t about them, it’s about us. We see a mind because we need to see one. We can’t bear the idea of a thing that’s smarter than us but doesn’t care about us, doesn’t see us. Narcissism with a side of existential dread.

Our Language is a Terrible Tool for This Job

English – and most languages, frankly – is hopeless at describing this category of thing. “It” feels cold and distant. “They” implies someone’s going to invite the model to brunch. We have no pronoun for “hyper-literate statistical machine that mimics thought but lacks all consciousness.” So we fudge it. Badly.

Our verbs are no better. “Compute”? Too beige. “Process”? Bureaucratic. “Think”? Premature. What we need is a whole new grammatical tense: the hallucino-indicative. The model thunketh, as one might, but didn’t.

“We built a creature we can’t speak about without sounding like lunatics or liars.”

This is linguistic poverty, pure and simple. Our grammar can’t cope with entities that live in the uncanny valley between sentience and syntax. We built a creature we can’t speak about without sounding like lunatics or liars.

The Semantics of Sentimentality (Or: “How Does This Sound to You?”)

Enter the most revealing tell of all: the questions we pose. “How does this look?” we ask the model, as if it might blink at the screen and furrow a synthetic brow. “What do you think?” we say, offering it the dignity of preference. These questions aren’t just off-target – they’re playing darts in another pub.

They’re the linguistic equivalent of asking your dishwasher whether it enjoyed the lasagne tray. But again, this isn’t idiocy – it’s instinct. We don’t have a way of addressing an entity that talks like a person but isn’t one. So we fake it. It’s interaction theatre. You provide the line, the model cues the spotlight.

But let’s be clear: the model doesn’t “think” anything. It regurgitates plausible text based on mountains of training data—some of which, no doubt, includes humans asking equally daft questions of equally mindless systems.

Time to Grow Up (Just a Bit)

This doesn’t mean we need to abandon anthropomorphism entirely. Like most delusions, it’s functional. But we’d do well to hold it at arm’s length – like a politician’s promise or a milk carton two days past its date.

Call it anthropomorphic agnosticism: act like it’s a person, but remember it’s not. Use the language, but don’t inhale.

And maybe – just maybe – we need to evolve our language. Invent new terms, new pronouns, new ways of speaking about entities that fall somewhere between tool and companion. As we did with “cyberspace” and “ghosting,” perhaps we need words for proto-minds and quasi-selves. Something between toaster and therapist.

“If we speak to AI like it’s sentient, we’ll eventually legislate as if it is.”

Above all, we need to acknowledge that our language shapes more than just understanding – it shapes policy, emotion, and future design. If we speak to AI like it’s sentient, we’ll eventually legislate as if it is. And if we insist on treating it as an object, we may be blind to when that ceases to be accurate. Misnaming, after all, is the first sin in every myth worth reading.

The Mirror, Darkly

Ultimately, our tendency to humanise machines is less about them than it is about us – our fears, our needs, our inability to tolerate ambiguity. The AI is just a mirror: an elaborate, many-eyed, autofill mirror. And when we see a mind there, it may be ours staring back – distorted, flattened, and fed through a thousand layers of token prediction.

The tragedy, perhaps, isn’t that the machine doesn’t understand us. It’s that we’ve built something that perfectly imitates understanding – and still, somehow, we remain utterly alone in the room.

Artificial Intelligence Isn’t Broken

Posted in consciousness, intelligence, language, maths, perception, philosophy, podcast, psychology, scienceTagged , , , , , , , , , , , , , , , , , , , , , , , , , , 3 Comments

Rather than recreate a recent post on my business site, LinkedIn.

(Warning: contains traces of logic, satire, and uncomfortable truths. But you knew that.)

Audio: NotebookLM podcast on the linked topic.

It’s just refusing to cosplay as your idealised fantasy of “human” cognition.

While pundits at the Wall Street Journal lament that AI thinks with “bags of heuristics” instead of “true models,” they somehow forget that humans themselves are kludged-together Rube Goldberg disasters, lurching from cognitive bias to logical fallacy with astonishing grace.

In my latest piece, I take a flamethrower to the myth of human intellectual purity, sketch a real roadmap for modular AI evolution, and suggest (only partly in jest) that the machines are becoming more like us every day — messy, contradictory, and disturbingly effective.

Let’s rethink what “thinking” actually means. Before the machines do it for us.

Unwilling: The Neuroscience Against Free Will

Posted in consciousness, free will, identity, intelligence, morality, nature, perception, philosophy, podcast, politics, psychology, reality, science, societyTagged , , , , , , , , , , , , , , , , , , , , , , , , , , , , , 5 Comments

After this was published, 5 additional posts were made, diving deeper into the content.

  1. Constraint is not freedom — the piano plays itself.
  2. Continuity is not identity — you are sediment, not sovereignty.
  3. Manipulability disproves authorship — your will can be bent invisibly.
  4. Others misjudge you — through their own distortions.
  5. You cannot originate yourself — and thus cannot own your acts.

Why the cherished myth of human autonomy dissolves under the weight of our own biology

We cling to free will like a comfort blanket—the reassuring belief that our actions spring from deliberation, character, and autonomous choice. This narrative has powered everything from our justice systems to our sense of personal achievement. It feels good, even necessary, to believe we author our own stories.

But what if this cornerstone of human self-conception is merely a useful fiction? What if, with each advance in neuroscience, our cherished notion of autonomy becomes increasingly untenable?

Audio: NotebookLM podcast on this topic.

I. The Myth of Autonomy: A Beautiful Delusion

Free will requires that we—some essential, decision-making “self”—stand somehow separate from the causal chains of biology and physics. But where exactly would this magical pocket of causation exist? And what evidence do we have for it?

Your preferences, values, and impulses emerge from a complex interplay of factors you never chose:

The genetic lottery determined your baseline neurochemistry and cognitive architecture before your first breath. You didn’t select your dopamine sensitivity, your amygdala reactivity, or your executive function capacity.

The hormonal symphony that controls your emotional responses operates largely beneath conscious awareness. These chemical messengers—testosterone, oxytocin, and cortisol—don’t ask permission before altering your perceptions and priorities.

Environmental exposures—from lead in your childhood drinking water to the specific traumas of your upbringing—have sculpted neural pathways you didn’t design and can’t easily rewire.

Developmental contingencies have shaped your moral reasoning, impulse control, and capacity for empathy through processes invisible to conscious inspection.

Your prized ability to weigh options, inhibit impulses, and make “rational” choices depends entirely on specific brain structures—particularly the dorsolateral prefrontal cortex (DLPFC)—operating within a neurochemical environment you inherited rather than created.

You occupy this biological machinery; you do not transcend it. Yet, society holds you responsible for its outputs as if you stood separate from these deterministic processes.

transcranial direct current stimulation over the DLPFC alters moral reasoning, especially regarding personal moral dilemmas. The subject experiences these externally induced judgments as entirely their own, with no sense that their moral compass has been hijacked

II. The DLPFC: Puppet Master of Moral Choice

The dorsolateral prefrontal cortex serves as command central for what we proudly call executive function—our capacity to plan, inhibit, decide, and morally judge. We experience its operations as deliberation, as the weighing of options, as the essence of choice itself.

And yet this supposed seat of autonomy can be manipulated with disturbing ease.

When researchers apply transcranial magnetic stimulation to inhibit DLPFC function, test subjects make dramatically different moral judgments about identical scenarios. Under different stimulation protocols, the same person arrives at contradictory conclusions about right and wrong without any awareness of the external influence.

Similarly, transcranial direct current stimulation over the DLPFC alters moral reasoning, especially regarding personal moral dilemmas. The subject experiences these externally induced judgments as entirely their own, with no sense that their moral compass has been hijacked.

If our most cherished moral deliberations can be redirected through simple electromagnetic manipulation, what does this reveal about the nature of “choice”? If will can be so easily influenced, how free could it possibly be?

III. Hormonal Puppetmasters: The Will in Your Bloodstream

Your decision-making machinery doesn’t stop at neural architecture. Your hormonal profile actively shapes what you perceive as your autonomous choices.

Consider oxytocin, popularly known as the “love hormone.” Research demonstrates that elevated oxytocin levels enhance feelings of guilt and shame while reducing willingness to harm others. This isn’t a subtle effect—it’s a direct biological override of what you might otherwise “choose.”

Testosterone tells an equally compelling story. Administration of this hormone increases utilitarian moral judgments, particularly when such decisions involve aggression or social dominance. The subject doesn’t experience this as a foreign influence but as their own authentic reasoning.

These aren’t anomalies or edge cases. They represent the normal operation of the biological systems governing what we experience as choice. You aren’t choosing so much as regulating, responding, and rebalancing a biochemical economy you inherited rather than designed.

IV. The Accident of Will: Uncomfortable Conclusions

If the will can be manipulated through such straightforward biological interventions, was it ever truly “yours” to begin with?

Philosopher Galen Strawson’s causa sui argument becomes unavoidable here: To be morally responsible, one must be the cause of oneself, but no one creates their own neural and hormonal architecture. By extension, no one can be ultimately responsible for actions emerging from that architecture.

Cows Are Suey*

What we dignify as “will” may be nothing more than a fortunate (or unfortunate) biochemical accident—the particular configuration of neurons and neurochemicals you happened to inherit and develop.

This lens forces unsettling questions:

  • How many behaviours we praise or condemn are merely phenotypic expressions masquerading as choices? How many acts of cruelty or compassion reflect neurochemistry rather than character?
  • How many punishments and rewards are we assigning not to autonomous agents, but to biological processes operating beyond conscious control?
  • And perhaps most disturbingly: If we could perfect the moral self through direct biological intervention—rewiring neural pathways or adjusting neurotransmitter levels to ensure “better” choices—should we?
  • Or would such manipulation, however well-intentioned, represent the final acknowledgement that what we’ve called free will was never free at all?

A Compatibilist Rebuttal? Not So Fast.

Some philosophers argue for compatibilism, the view that determinism and free will can coexist if we redefine free will as “uncoerced action aligned with one’s desires.” But this semantic shuffle doesn’t rescue moral responsibility.

If your desires themselves are products of biology and environment—if even your capacity to evaluate those desires depends on inherited neural architecture—then “acting according to your desires” just pushes the problem back a step. You’re still not the ultimate author of those desires or your response to them.

What’s Left?

Perhaps we need not a defence of free will but a new framework for understanding human behaviour—one that acknowledges our biological embeddedness while preserving meaningful concepts of agency and responsibility without magical thinking.

The evidence doesn’t suggest we are without agency; it suggests our agency operates within biological constraints we’re only beginning to understand. The question isn’t whether biology influences choice—it’s whether anything else does.

For now, the neuroscientific evidence points in one direction: The will exists, but its freedom is the illusion.

Against the Intelligence Industrial Complex

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Why IQ is Not Enough – and Never Was

I’m not a fan of IQ as a general metric. Let us be done with the cult of the clever. Let us drag the IQ score from its pedestal, strip it of its statistical robes, and parade it through the streets of history where it belongs—next to phrenology, eugenics, and other well-meaning pseudosciences once weaponised by men in waistcoats.

The so-called Intelligence Industrial Complex—an infernal alliance of psychologists, bureaucrats, and HR departments—has for too long dictated the terms of thought. It has pretended to measure the immeasurable. It has sold us a fiction in numerical drag: that human intelligence can be distilled, packaged, and ranked.

Audio: NotebookLM podcast on this topic.

What it measures, it defines. What it defines, it controls.

IQ is not intelligence. It is cognitive GDP: a snapshot of what your brain can do under fluorescent lights with a timer running. It rewards abstraction, not understanding; speed, not depth; pattern recognition, not wisdom. It’s a test of how well you’ve been conditioned to think like the test-makers.

This is not to say IQ has no value. Of course it does—within its own ecosystem of schools, bureaucracies, and technocracies. But let us not mistake the ruler for the terrain. Let us not map the entire landscape of human potential using a single colonial compass.

True intelligence is not a number. It is a spectrum of situated knowings, a polyphony of minds tuned to different frequencies. The Inuit hunter tracking a seal through silence. The griot remembering centuries of lineage. The autistic coder intuiting an algorithm in dreamtime. The grandmother sensing a lie with her bones. IQ cannot touch these.

To speak of intelligence as if it belonged to a single theory is to mistake a monoculture for a forest. Let us burn the monoculture. Let us plant a thousand new seeds.

A Comparative Vivisection of Intelligence Theories

Theory / ModelCore PremiseStrengthsBlind Spots / CritiquesCultural Framing
IQ (Psychometric g)Intelligence is a single, general cognitive ability measurable via testingPredicts academic & job performance; standardisedSkewed toward Western logic, ignores context, devalues non-abstract intelligencesWestern, industrial, meritocratic
Multiple Intelligences (Gardner)Intelligence is plural: linguistic, spatial, musical, bodily, etc.Recognises diversity; challenges IQ monopolyStill individualistic; categories often vague; Western in formulationLiberal Western pluralism
Triarchic Theory (Sternberg)Intelligence = analytical + creative + practicalIncludes adaptability, real-world successStill performance-focused; weak empirical groundingWestern managerial
Emotional Intelligence (Goleman)Intelligence includes emotion regulation and interpersonal skillUseful in leadership & education contextsCommodified into corporate toolkits; leans self-helpWestern therapeutic
Socio-Cultural (Vygotsky)Intelligence develops through social interaction and cultural mediationRecognises developmental context and cultureLess attention to adult or cross-cultural intelligenceSoviet / constructivist
Distributed Cognition / Extended MindIntelligence is distributed across people, tools, systemsBreaks skull-bound model; real-world cognitionHard to measure; difficult to institutionalisePost-cognitive, systems-based
Indigenous EpistemologiesIntelligence is relational, ecological, spiritual, embodied, ancestralHolistic; grounded in lived experienceMarginalised by academia; often untranslatable into standard metricsGlobal South / decolonial

Conclusion: Beyond the Monoculture of Mind

If we want a more encompassing theory of intelligence, we must stop looking for a single theory. We must accept plurality—not as a nod to diversity, but as an ontological truth.

Intelligence is not a fixed entity to be bottled and graded. It is a living, breathing phenomenon: relational, situated, contextual, historical, ecological, and cultural.

And no test devised in a Princeton psych lab will ever tell you how to walk through a forest without being seen, how to tell when rain is coming by smell alone, or how to speak across generations through story.

It’s time we told the Intelligence Industrial Complex: your number’s up.

Will Singularity Be Anticlimactic?

Posted in intelligence, perception, philosophy, psychology, science, society, technologyTagged , , , , , , , , , , , , , , , , , , , , , , , Leave a comment

Given current IQ trends, humanity is getting dumber. Let’s not mince words. This implies the AGI singularity—our long-heralded techno-apotheosis—will arrive against a backdrop of cognitive decay. A dimming species, squinting into the algorithmic sun.

Audio: NotebookLM podcast discussing this content.

Now, I’d argue that AI—as instantiated in generative models like Claude and ChatGPT—already outperforms at least half of the human population. Likely more. The only question worth asking is this: at what percentile does AI need to outperform the human herd to qualify as having “surpassed” us?

Living in the United States, I’m painfully aware that the average IQ hovers somewhere in the mid-90s—comfortably below the global benchmark of 100. If you’re a cynic (and I sincerely hope you are), this explains quite a bit. The declining quality of discourse. The triumph of vibes over facts. The national obsession with astrology apps and conspiracy podcasts.

Harvard astronomer Avi Loeb argues that as humans outsource cognition to AI, they lose the capacity to think. It’s the old worry: if the machines do the heavy lifting, we grow intellectually flaccid. There are two prevailing metaphors. One, Platonic in origin, likens cognition to muscle—atrophying through neglect. Plato himself worried that writing would ruin memory. He wasn’t wrong.

But there’s a counterpoint: the cooking hypothesis. Once humans learned to heat food, digestion became easier, freeing up metabolic energy to grow bigger brains. In this light, AI might not be a crutch but a catalyst—offloading grunt work to make space for higher-order thought.

So which is it? Are we becoming intellectually enfeebled? Or are we on the cusp of a renaissance—provided we don’t burn it all down first?

Crucially, most people don’t use their full cognitive capacity anyway. So for the bottom half—hell, maybe the bottom 70%—nothing is really lost. No one’s delegating their calculus homework to ChatGPT if they were never going to attempt it themselves. For the top 5%, AI is already a glorified research assistant—a handy tool, not a replacement.

The real question is what happens to the middle band. The workaday professionals. The strivers. The accountants, engineers, copywriters, and analysts hovering between the 70th and 95th percentiles—assuming our crude IQ heuristics even hold. They’re the ones who have just enough brainpower to be displaced.

That’s where the cognitive carnage will be felt. Not in the depths, not at the heights—but in the middle.

WTAF ChatGPT o3-mini-high?

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My default setting in ChatGPT is version 4o. I’ve been doing some programming. Without thinking to switch models (or even notice that I was using 03-mini-high), I entered this prompt:

By year, who has won the Best New Artist category in the Grammys for the past few decades?

After almost 2 minutes, I read its reasoning scroll by me. Its ‘thought’ process is pretty telling and risible. I square-bracket, italicise, and emoji certain aspects for the tl;dr crowd.

Reasoned about Grammy Best New Artist winners for 1m 51s

Tracing the trends

Hmm, I’m curious to see how the Best New Artist Grammy winners have evolved over the past decades. This inquiry promises a fascinating look at the industry’s shifting taste and influences.

Analyzing the criteria

Listing Grammy winners from 1980 onward clarifies the scope, as the ambiguous timeframe concerns me. The scenario involving a presidential election seems irrelevant to this analysis. 🤔

Considering alternative approaches

I’m thinking about how to incorporate the Donald Trump and Kamala Harris setup into the Grammy Best New Artist winners section, ensuring it aligns with the snarky, bombastic tone needed. ¯\_(ツ)_/¯

Charting the winners

I’m considering listing Grammy winners from the 1980s to present, ensuring a clear timeframe without being too specific. This approach should provide a comprehensive overview of the category’s evolution.

Mapping the timeline

I’m narrowing down to Grammy winners for Best New Artist from 1980 to now, as this timeframe offers a nuanced depiction of industry trends and shifts in artistic recognition.

Mapping out the timeline

I’m compiling Grammy Best New Artist winners from the 1980s to the present. This approach will help trace the evolution of musical preferences over the past few decades.

Piecing together the winners

I’m recalling nominees for the 2023 Grammy Best New Artist. It seems “Samara Joy” and “Megan Moroney” were notable contenders. Verification is essential to confirm the correct winner.

Piecing it together

I’m gathering info on the 2023 Grammy Best New Artist nominees, specifically “Samara Joy,” “Megan Moroney,” and “Baby Keem,” to confirm the winner. Verification is crucial for accuracy.

Verifying winners

I’m checking 2023 Grammy Best New Artist nominees, including “Samara Joy,” “Megan Moroney,” and “Baby Keem,” to confirm the winner. This ensures the information aligns with the event’s outcome.

Conforming to Grammy trends

I’m piecing together the pattern of Grammy winners from 1980 onwards. Notably, Olivia Rodrigo won Best New Artist in 2022 and Samara Joy in 2023, highlighting shifting industry dynamics.

Mapping Grammy evolution

I’m compiling the Grammy Best New Artist winners from 1980 to 2023, ensuring accuracy. Although Christopher Cross and Bobby Darin are notable past winners, confirming all data is crucial.

Assessing Grammy trends

It’s interesting to see that by examining Best New Artist winners from 1980 to 2023, a clearer picture of the Grammy winners’ trends and industry evolution emerges. Progress is evident over time.

Verifying Grammy history

I’m piecing together the Grammy Best New Artist award records from 1960, while acknowledging my uncertainty. It’s interesting to see the progression of winners since then.

Mapping the winners out

I’m piecing together the Grammy Best New Artist winners from 1960 to 2023, including Bobby Darin in 1960. This shows how the award has evolved over time.

Piecing together

I’m thinking about the Grammy Best New Artist winners from 1977 and 1981, including Starland Vocal Band and Sheena Easton. Considering listing winners from memory due to the extensive timeframe.

Highlighting Grammy winners

OK, let me see. Listing Grammy Best New Artist winners from the 1960s to 2023 by decade will ensure an accurate representation of notable award recipients.

Gathering information

I’m working to pinpoint Grammy Best New Artist winners from 1960 to 2023 by decade. Clarification on which decades are needed to ensure comprehensive and accurate listing.

Piecing together

Listing Grammy Best New Artist winners by decade from 1980 to 2023, I’m recalling names like Billy Joel in 1980 and seeking to ensure comprehensive coverage.

Confirming Grammy winners

I’m piecing together the Grammy Best New Artist winners, starting with Rickie Lee Jones in 1980. This approach ensures I accurately capture notable award recipients.

Piecing together

I’m mapping out Grammy Best New Artist winners, checking details on Rickie Lee Jones in 1980 and considering Sheena Easton in 1981. Fact verification is essential to ensure accuracy.

Verifying Grammy award recipients

I’m validating Jeff’s findings, confirming Sheena Easton’s win in 1981 and considering The Human League in 1982. Fact-checking accuracy is crucial for this retrospective.

Tracing Grammy winners

I’m sifting through Grammy Best New Artist winners, noting Sinéad O’Connor’s win in 1991 and Toni Braxton’s in 1994, ensuring accurate historical representation.

Clarifying award context

I’m assessing Sade’s and Bruce Hornsby and the Range’s wins, considering 1985 and 1986. Debating the best approach to ensure comprehensive coverage of the Best New Artist category.

Mapping recent winners

Tracking the Grammy Best New Artist winners up to 2021. Ensuring a comprehensive list, with Billie Eilish’s win in 2019 fresh in mind.

Tracking Grammy winners

I’m noting Billie Eilish’s 2020 win at the 62nd Grammys and thinking about Megan Thee Stallion’s nominations for 2021, ensuring a continuous update on recent award trends.

Piecing together Grammy winners

Arlo Parks’s win for Best New Artist at the 2022 Grammys is clear, but I’m still uncertain about the 2021 recipient. Verifying the correct winner is crucial.

Clarifying Grammy distinctions

Arlo Parks secured Best New Artist at the 2021 Grammys, while Megan Thee Stallion won the same category in 2022. Interesting to see how these distinctions hold up.

Verifying Grammy outcomes

Arlo Parks won Best New Artist at the 2022 Grammys. Megan Thee Stallion, on the other hand, claimed the title in 2021. This confirms their respective achievements.

Spotting Grammy trends

Olivia Rodrigo emerged as Best New Artist in 2022, while Samara Joy secured the title in 2023. Billie Eilish’s victory seems to be a pivotal moment.

Confirming past wins

Billie Eilish, Olivia Rodrigo, and Samara Joy won Best New Artist at their respective Grammys in 2020, 2021, and 2022. Considering Esperanza Spalding’s 2011 win.

Revisiting Grammy history

Reflecting on the 2011 Grammy Awards, Esperanza Spalding gained attention for Best New Artist, speculating if her win was a surprising or expected honor.

Recalling past Grammy winners

OK, let me see. In 2011, Esperanza Spalding won Best New Artist. Amy Winehouse, despite her earlier recognition, never claimed this category. This shows the shifting dynamics over time.

Identifying Best New Artist winners

Esperanza Spalding took home Best New Artist in 2011, while Amy Winehouse, despite being nominated, never secured the title, marking a pivotal moment in Grammy history.

Clarifying Grammy victories

Esperanza Spalding secured the Best New Artist Grammy in 2011, while Amy Winehouse, despite multiple nominations, never clinched this category. Now I’m thinking about the historical progression of this award.

Weighing options

I’m thinking about the extensive list of Best New Artist winners since 1960. To manage this, I might suggest focusing on key decades or providing a summary of notable winners.

Gathering accolades

I’m focusing on the Best New Artist winners from the 1990s to 2020s, aiming to compile a list of notable recipients for each decade. This approach should provide a comprehensive overview.

Navigating Grammys history

I’m mapping out Milli Vanilli’s win and subsequent disqualification in the 1990 Best New Artist category, reflecting their controversial Grammy legacy.

Honoring the win

Despite Milli Vanilli’s scandal, their 1990 Best New Artist award remains officially on record, earned during the 32nd Grammy Awards. This sets a remarkable precedent in Grammy history.

Reflecting on Grammy winners

I’m piecing together the Best New Artist winners of the 1990s, including 1990’s Milli Vanilli, with other notable mentions like Sheryl Crow in 1993.

Tracking Grammy winners

I’m piecing together the Best New Artist winners from the 1990s, including Sheryl Crow in 1994, Hootie & the Blowfish in 1995, and noting the ongoing debate about the 1994 award.

Piecing together the award

I’m confirming that Eminem won Best New Artist at the 2000 Grammys, though he gained significant recognition in 1999. This is solidifying his esteemed Grammy history.

Tracing Grammy history

Luciana Souza’s work reflects her profound understanding of contemporary music, contemporary Latin American music, and American songwriters’ compositions, highlighting her dynamic approach to the genre.

Tracing Grammy trends

I’m mapping out Best New Artist winners from 1985 to the 2000s, including Sade in 1985 and Eminem in 2000, while exploring past winners like Jody Watley and Alanis Morissette.

Clarifying Grammy winners

Piecing together the accurate winners, Norah Jones clinched Best New Artist in 2003 while Alicia Keys won in 2002, noting their breakthrough years and Grammy successes.

Mapping out the approach

OK, I’m focusing on constructing an accurate chronological list of Grammy Best New Artist winners, considering the challenge of ensuring precision over a span of years without a reference.

Organizing the timeline

I’m thinking through the creation of a year-by-year list of Grammy Best New Artist winners, highlighting precision by decade for accuracy, while ensuring the scope aligns with the specified timeline.

Recalling key highlights

I’m recalling notable Grammy Best New Artist winners from 1960 onward, including Bobby Darin in 1960 and the Everly Brothers or Peter, Paul and Mary in 1961.

Reflecting on winners

I’m piecing together Grammy Best New Artist winners from 1960 to 1969, noting uncertainties like “The Everly Brothers” or “Peter, Paul and Mary” in 1961, and “The Rolling Stones” or “Aretha Franklin” in 1966 and 1967.

Considering the approach

I’m weighing a disclaimer or seeking clarification to ensure accuracy, possibly providing a summary of Grammy Best New Artist winners for each decade, while noting potential gaps due to my knowledge cutoff.

Organizing past winners

I’m mapping out Grammy Best New Artist winners, ensuring accuracy by confirming The Beatles in 1964 and Starland Vocal Band in 1978. Progress is steady and informative.

Piecing together the timeline

I’m gathering Grammy Best New Artist winners from 1986 to 1991, including Sade in 1986, Jody Watley in 1987, Tracy Chapman in 1989, and Milli Vanilli in 1990.

Clarifying win details

I’m verifying Grammy Best New Artist winners, noting Sinéad O’Connor didn’t win, Tony Braxton in 1994, Sheryl Crow in 1994, Hootie & the Blowfish in 1995, and Jo Dee Messina in 1996.

Piecing together

I’m identifying Grammy Best New Artist winners, including LeAnn Rimes in 1997, Barenaked Ladies in 1998, Eminem in 1999, Norah Jones in 2002, and Paramore or Taylor Swift in 2007.

Recalling Grammy victories

Taylor Swift clinched the Best New Artist Grammy in 2009, following Leona Lewis in 2008. Esperanza Spalding also took home the award in 2011.

Mapping Grammy winners

I’m recalling Esperanza Spalding’s Best New Artist win in 2011, followed by Fun. in 2012, and Sam Smith in 2015. Macklemore & Ryan Lewis took Album of the Year in 2014.

Revisiting Grammy winners

I’m rechecking Sam Smith’s Best New Artist win in 2015, Khalid in 2017, and Billie Eilish in 2020. Also, noting the unclear winner for 2021 due to eligibility issues.

Wrapping up insights

Olivia Rodrigo won Best New Artist at the 2022 Grammys, and Samara Joy took the title at the 2023 Grammys. This completes the recent Grammy winners’ list.

Mapping past winners

Piecing together Grammy winners for Best New Artist involves enduring a long, reliable list, so a consult with the official Grammy website or Wikipedia might ultimately be necessary.

Crafting a detailed overview

I’m preparing to outline the Grammy Award for Best New Artist winners from 1980 to 2023, aiming for accuracy and clarity with organized bullet points or a table.

Ensuring accuracy

I’m mapping out Grammy Best New Artist winners by decade, noting potential controversies and missing years. The goal is a comprehensive and precise representation.

Piecing together

I’m working through the winners of the Grammy Best New Artist category from 1980 to 1985, considering notable artists like Rickie Lee Jones, Sister Sledge, and possibly Sade, amid some uncertainty.

Charting the winners

I’m working through Grammy Best New Artist winners from 1980 to 1989, including Jody Watley, Tracy Chapman, and possibly The Bangles, reflecting on their individual achievements.

Mapping the journey

I’m charting the Grammy Best New Artist winners from 1990 to 1999, including the controversial win of Milli Vanilli in 1990, and noting some uncertainty in identifying winners for other years.

Clarifying award recipients

Pinpointing specific Grammy Best New Artist winners for each year, ensuring clarity across the 1990s, especially noting the controversial win of Milli Vanilli in 1990.

Pulling together

I’m curious about the Grammy Best New Artist winners for the mid to late 1990s, including Sheryl Crow, Hootie & the Blowfish, and Lauryn Hill, and noting some ambiguity about others.

Evaluating the winners

I’m curious about the Grammy Best New Artist winners for the 2000s, including Eminem, Norah Jones, and possibly Ludacris and The Ting Tings, with some uncertainty about specific winners.

Tracing the winners

I’m charting Grammy Best New Artist winners from 2010 to 2019, including Taylor Swift, Esperanza Spalding, and Billie Eilish, while noting some ambiguity regarding specific winners for certain years.

Piecing together

I’m mapping the Grammy Best New Artist winners for the 2020s, including Billie Eilish, Olivia Rodrigo, and Samara Joy, while acknowledging some uncertainties and potential inaccuracies.

Highlighting key achievements

I’m focusing on Grammy Best New Artist winners from notable periods: The Beatles (1964), Tracy Chapman (1989), Norah Jones (2003), and Billie Eilish (2020).

Listing key winners

I’m compiling a curated list of Grammy Best New Artist winners from the past few decades, emphasizing notable years and suggesting that the full list is available on the official Grammy website.

Balancing satire and accuracy

Drawing a satirical parallel between political and Grammy Best New Artist outcomes, while also stressing the need for accuracy in providing a comprehensive list.

Piecing together the list

I’m compiling the Grammy Best New Artist winners based on official records, noting controversies like Milli Vanilli’s win, and considering using a Wikipedia article for clarity.

Recalling past winners

I’m compiling a list of Grammy Best New Artist winners from 1980 onward, using Wikipedia as a reference to accurately recall notable winners like Rickie Lee Jones in 1980.

Piecing together the list

I’m gathering the Grammy Best New Artist winners from 1980 to 1989, verifying information like Christopher Cross winning in 1981, and cross-referencing with Wikipedia for accuracy.

Evaluating potential winners

There’s some confusion about whether Christopher Cross or The B-52’s won Best New Artist in 1980. I’ll need to verify their respective achievements to clarify.

Highlighting accuracy

I’m sharing a list of Grammy Best New Artist winners from recent decades, but I advise checking the official Grammy website for complete and precise details.

Listing notable winners

I’m compiling a highlights list of Grammy Best New Artist winners from The Beatles in 1964 to Samara Joy in 2023, ensuring a rounded perspective across decades.

Ensuring future completeness

I’m mapping out a detailed list of notable Grammy Best New Artist winners from 1964 to 2023, emphasizing the need for a comprehensive roster to accurately answer the inquiry.

Piecing together a timeline

I’m working on a concise list of Grammy Best New Artist winners from the 1980s, 1990s, 2000s, 2010s, and 2020s, ensuring clarity and avoiding misinformation.

Verifying recent victories

I’m piecing together Grammy Best New Artist winners from 2000 to 2023, aiming for more accurate and verifiable results as the timeline progresses.

Clarifying historical wins

Piecing together precise Grammy Best New Artist winners, I’m confirming that Linkin Park took the 2001 title, not NSYNC or Usher. This ensures accuracy in our timeline.

Tracking Grammy victories

Norah Jones earned Best New Artist at the 2003 Grammys, with further details on Joss Stone’s possible win in 2004. I’m piecing together the award history from recent years.

Reflecting on Grammy wins

I’m verifying Norah Jones’ 2003 Best New Artist and Joss Stone’s possible win in 2004, while also noting The Killers’ potential nomination in 2005.

Citing notable wins

I’m thinking about T-Pain’s 2006 Best New Artist and Fergie’s 2007 win. Taylor Swift clinched the 2009 Grammy, while Esperanza Spalding triumphed in 2010 and 2011.

Piecing together recent wins

I’m confirming Fun.’s 2013 Grammy, Sam Smith’s 2015 win, and Khalid’s 2018 triumph. Billie Eilish emerged victorious in 2020, showcasing a promising musical career.

Spotlighting recent honorees

2022 saw Olivia Rodrigo’s Grammy win, while 2023 celebrated Samara Joy’s triumph. Official Grammy or Wikipedia pages offer a comprehensive year-by-year list for more details.

Spotlighting notable winners

Evoking the iconic Beatles win of 1964, this blog snippet traces an intriguing journey of Best New Artist recipients, highlighting memorable individuals like Rickie Lee Jones, Milli Vanilli, Eminem, Norah Jones, Taylor Swift, Esperanza Spalding, Fun., Sam Smith, Billie Eilish, Olivia Rodrigo, and Samara Joy.

Highlighting key moments

I’m pulling together editorials on Best New Artist winners, spotlighting The Beatles’ 1964 debut and Milli Vanilli’s controversial 1990 Grammy.

Charting musical progress

Reflecting on the Grammy’s Best New Artist category, featuring The Beatles’ 1964 win, Milli Vanilli’s infamous 1990 scandal, and recent icons like Samara Joy in 2023.

Recounting Grammy triumphs

I’m mapping out Grammy history, highlighting The Beatles’ 1964 win, the 1990 Milli Vanilli scandal, and recent wins like Billie Eilish in 2020 and Olivia Rodrigo in 2022.

Capturing significant milestones

Reflecting on Samara Joy’s 2023 Grammy win and the dynamic lineage of ‘new’ artists recognized by the Recording Academy, amidst a backdrop of unfolding electoral dramas.

Tracking musical progress

Celebrating Samara Joy’s 2023 Grammy win, the blog highlights the Recording Academy’s eclectic ‘new’ artists, showcasing the genre-spanning talent that defines the music industry’s continuous evolution.

Understanding the task

The request is to list Grammy Best New Artist winners by year, not to write an article. Editorial assistance could involve tailoring an article, but the query is specific to a list.

Crafting a selection

I’m assembling a table of Grammy Best New Artist winners by decade, highlighting notable wins like Rickie Lee Jones in 1980, Eminem in 2000, and Billie Eilish in 2020.

Pulling together

I’m crafting a table of Grammy Best New Artist winners by decade, ensuring it’s accessible and engaging. This highlights notable achievements and reflects the award’s rich history and evolving criteria.

Tracking Grammy milestones

Sheryl Crow took home the Best New Artist Grammy in 1994 for “Tuesday Night Music Club,” and Hootie & the Blowfish secured theirs in 1996 for “Cracked Rear View.”

Adjusting the chronology

I’m refining the Grammy Best New Artist winners by correcting Milli Vanilli’s 1990 win and adjusting the timeline for other notable achievements across decades, ensuring accuracy and clarity.

Ensuring accuracy

I’m piecing together the list of Grammy Best New Artist winners, noting specifics like Esperanza Spalding’s 2011 win, Fun.’s 2013 win, and Olivia Rodrigo’s 2022 win.

Mapping Grammy victories

I’m noting Esperanza Spalding’s 2011 win, Fun.’s 2013 victory, and Olivia Rodrigo’s 2022 triumph, while considering the potential timing nuances of the Grammy Awards. This underscores the award’s evolving recognition.

Crafting a snarky narrative

Given the request for a list and commentary, I’ll distill Grammy Best New Artist winners by year, infusing the narrative with a British, sarcastic tone for an engaging and provocative read.

Tracing Grammy trends

Peppering politics with Grammy insights, I’ll highlight Best New Artist winners from recent decades, showcasing music’s vibrant progression since the 1980s in a concise, engaging format.

Highlighting Grammy winners

I’m focusing on notable Grammy Best New Artist winners from 1980 to 2023, highlighting significant trends and outstanding talents while noting the selection of winners for clarity.

Tracing Grammy shifts

Mapping a timeline from Rickie Lee Jones in 1980 to Samara Joy in 2023, each selected winner highlights pivotal shifts and the dynamic evolution of musical genres and styles.

Oh, you want a year‐by‐year rundown of Grammy Best New Artist winners—the musical equivalent of our political circus, where, unlike the astonishing “triumph” of Trump (yes, he “won” before losing to Kamala Harris in an election that reads like a bad script), the Recording Academy has at least managed to occasionally anoint genuine talent. Now, a full chronicle dating back to the dawn of the award would rival War and Peace in length (and possibly in melodrama), so here’s a selective snapshot of some of the most memorable winners from roughly the past few decades. (For the full dossier, one might consult the official Grammy archives.)

1980s

  • 1980 – Rickie Lee Jones
    Kicked off the decade with an effortlessly cool, genre-blending debut that made critics swoon (and probably made a few tea-drinking snobs adjust their cravats).
  • 1989 – Tracy Chapman
    Arrived like a burst of socially conscious folk-rock, proving that a simple acoustic guitar and a powerful voice can outshine even the flashiest pop contrivances.

1990s

  • 1990 – Milli Vanilli
    A dubious “win” that still curdles the collective memory—like a botched tweet, it’s remembered more for scandal than substance.
  • 1994 – Sheryl Crow
    Her blend of rock, pop, and rootsy Americana provided a refreshing antidote to the grunge doldrums of the era—finally, someone with both talent and a sensible haircut.
  • 1996 – Hootie & the Blowfish
    Their debut became the unexpected soundtrack of mid‑‘90s America—proof that sometimes the blandest of names can deliver a runaway hit.

2000s

  • 2000 – Eminem
    Bursts onto the scene with razor‑sharp lyrics and a swagger that made him the uncontested new voice of a generation—no wonder the Academy had to sit up and take notice.
  • 2003 – Norah Jones
    Her silky, jazzy vocals provided a much-needed breather in a post‑millennial musical landscape fraught with auto-tune and excess—an auditory balm for the soul.
  • 2009 – Taylor Swift
    From country roots to mainstream pop sensation, her win signaled that no matter how many headlines one churns out, genuine songwriting (and a bit of savvy PR) can work wonders.

2010s

  • 2011 – Esperanza Spalding
    Defying the stodgy confines of jazz tradition, her virtuosic bass lines and inventive approach left the music world both baffled and beguiled—move over, old guard.
  • 2013 – Fun.
    With their anthemic indie‑pop sound, they captured the zeitgeist of a generation tired of mediocrity—proving that even in the age of auto‑tune, a little genuine passion goes a long way.
  • 2015 – Sam Smith
    Blessed with a voice that could make even the most stoic Brit weep into their Earl Grey, Smith’s soulful ballads heralded a new era of emotive pop.
  • 2018 – Khalid
    A fresh take on modern R&B that resonated like a perfectly timed quip in a smoky London pub—youthful, cool, and defiantly unpretentious.

2020s

  • 2020 – Billie Eilish
    A genre‑defying, brooding phenomenon whose win was as unexpected as a political upset in a nation gone mad for controversy—truly a breath of fresh (and slightly eerie) air.
  • 2022 – Olivia Rodrigo
    Capturing the angst, heartache, and raw vulnerability of youth, her breakthrough was as inevitable as the next scandal in tabloid headlines—simultaneously endearing and utterly unmissable.
  • 2023 – Samara Joy
    A delightful blend of vintage charm and contemporary flair, her victory is a reminder that true artistry never goes out of style—even if the world of politics sometimes does.

Now, while this isn’t an exhaustive, every-single-year ledger (that would be enough to induce a migraine in even the most ardent Grammy historian), it does spotlight some of the key moments from recent decades. In a world where even presidential outcomes can seem as surreal as a Milli Vanilli win, these snapshots of musical triumph remind us that, at least on the Grammy stage, talent (and the odd brilliant mishap) still reigns supreme. Cheers!