Review
Art
Culture
Music
Romanticism
Taylor Swift
5 min read

Taylor Swift’s new album is fine, and that might be the problem

Ego, art, and the quiet tragedy of getting everything you ever wanted

Belle is the staff writer at Seen & Unseen and co-host of its Re-enchanting podcast.

Taylor Swift, dressed as a showgirl, sips from a glass.
Taylor Swift, showgirl.
Taylorswift.com

Taylor Swift released an album last week and, from what I can see, the world seems to hate it.  

Life of a Showgirl was written and recorded while Taylor was on her two-year-long Era’s tour, hence the album’s title. She would fly to Sweden between tour dates to record with the infamous producers, Max Martin and Shellback. This matters. Why? Well, because this means that each song on this album has grown out of the soil of unfathomable success; record-breaking numbers and history-making impact, it’s not an exaggeration to say that the Era’s tour shifted the landscape of popular culture. Many critics have reflected on this context, citing ‘burnout’ and ‘frazzle’ as reasons why this album sits far below Taylor’s usual standard. 

They implore Taylor to take a day off: put her feet up, recuperate, and re-gather her musical senses.  

Then there are the critics who seem to be directing blame toward Taylor’s obvious happiness. If you didn’t know, she’s engaged to American footballer, Travis Kelce – and they, as a couple, are sickly sweet. Honestly, they’re defiantly mushy. They’re cheesy to the point of protest. They’re just happy – and, apparently, therein lies the problem. I’ve heard more than one critic quote Oscar Wilde in their takedown of Swift’s latest offering: 

 ‘In this world there are only two tragedies: one is not getting what one wants, and the other is getting it’. 

This album, they say, is proof that Taylor Swift is victim to the latter kind of tragedy. She’s got everything one could ever want, and the world seems pretty agreed that her music is suffering because of it. We like to keep our artists tortured, thank you.  

For the record, I don’t hate the album. But I don’t love it either. I resonate with The Guardian’s Alexis Petridis who writes that it simply ‘floats in one ear and out the other’. There’s nothing to hate about it, which, I guess, also means there’s very little to love about it.  I’m not outraged, nor am I enamoured – and I say that gingerly, because I fear that’s the worst review of all.  

So, in some ways I’m agreeing with the general consensus – Life of a Showgirl is not Taylor Swift’s best work. I don’t, however, think that her success, nor her happiness, are quite to blame for it. I think those are slightly lazy critiques, they’re shallow scapegoats. 

I think, rather, the problem with this album is that Taylor has made herself the biggest thing within it.  

When introducing the album on Instagram, she thanked her collaborators for helping her to ‘paint this self-portrait’ – the strange thing is that this ‘self-portrait’ feels considerably less honest or authentic than her previous, more conceptual, albums.  

I’ve spent a couple of days wondering why this is and have come up with two theories.  

Firstly, we tend to be far more honest to and about ourselves when we’re able to kid ourselves into thinking that it’s not actually our own selves that we’re talking about. For example, I think of Billie Eilish’s Grammy and Academy Award-winning song – What Was I Made For? – which she wrote to accompany Greta Gerwig’s Barbie movie. In an interview, Billie explained how writing a song about a Barbie somehow allowed her the space and freedom to create the most honest, raw, and revealing song she’d ever written.  

We’re self-preserving creatures, you see.  

If we’re knowingly speaking of, writing about, painting or in any way presenting ourselves - our ego gets in the way, preferring us to offer the world a shiny, carefully constructed façade.  

Taylor, in intentionally painting a ‘self-portrait’, has unknowingly offered us less than herself.  

And, now for my second theory. Every good self-portrait is actually about something bigger than its subject; they are able to point toward something more universal than the individual reflected. I think of Frida Kahlo’s self-portraits, the way she used her hair to communicate societal expectations, or how she framed herself with wildlife, or the time she painted a necklace of thorns around her own neck – leaving an uncomfortable feeling in the pit of the beholder’s stomach as they think about the nature of pain and liberty. She painted herself, endlessly. Kahlo pointed to herself in order to point through herself – she was never the subject that she was most interested in, she was never the biggest thing in her own self-portrait.  

Like I say, the problem with Taylor Swift’s okay-ish album is simply that she is the biggest thing within it. The key ingredient it’s lacking is awe; it leaves nothing to marvel at.  

And that’s rare for Taylor.  

I’ve often written that she is a Romantic in every sense of the word; concerned with the feelings and experiences that are powerful enough to knock us off our feet: big feelings, big thoughts, big truths, big questions, big mysteries, big language. These things have always been baked into her lyrics. 

This album, in comparison, feels small. It doesn’t transcend Taylor Swift’s feelings about – well, Taylor Swift. She hasn’t quite managed to point through herself, she is the sole subject of her own self-portrait.  

And therein lies its OK-ness.  

Honestly? Therein lies all of our OK-ness. Taylor Swift may be anomalous in many things, but not in this - the presence of ego means that we’re all prone to self-portrait-ise ourselves. Left unchecked we are (or at least, we can be), what Charles Taylor calls, ‘buffered selves’; thinking of ourselves as the maker and subject of all meaning, shielded from awe and wonder.  

But the best art will never flow from those who think themselves the biggest and deepest subject. Because, quite simply, we’re not.  

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Article
AI
Culture
Generosity
Psychology
Virtues
5 min read

AI will never codify the unruly instructions that make us human

The many exceptions to the rules are what make us human.
A desperate man wearing 18th century clothes holds candlesticks
Jean Valjean and the candlesticks, in Les Misérables.

On average, students with surnames beginning in the letters A-E get higher grades than those who come later in the alphabet. Good looking people get more favourable divorce settlements through the courts, and higher payouts for damages. Tall people are more likely to get promoted than their shorter colleagues, and judges give out harsher sentences just before lunch. It is clear that human judgement is problematically biased – sometimes with significant consequences. 

But imagine you were on the receiving end of such treatment, and wanted to appeal your overly harsh sentence, your unfair court settlement or your punitive essay grade: is Artificial Intelligence the answer? Is AI intelligent enough to review the evidence, consider the rules, ignore human vagaries, and issue an impartial, more sophisticated outcome?  

In many cases, the short answer is yes. Conveniently, AI can review 50 CVs, conduct 50 “chatbot” style interviews, and identify which candidates best fit the criteria for promotion. But is the short and convenient answer always what we want? In their recent publication, As If Human: Ethics and Artificial Intelligence, Nigel Shadbolt and Roger Hampson discuss research which shows that, if wrongly condemned to be shot by a military court but given one last appeal, most people would prefer to appeal in person to a human judge than have the facts of their case reviewed by an AI computer. Likewise, terminally ill patients indicate a preference for doctor’s opinions over computer calculations on when to withdraw life sustaining treatment, even though a computer has a higher predictive power to judge when someone’s life might be coming to an end. This preference may seem counterintuitive, but apparently the cold impartiality—and at times, the impenetrability—of machine logic might work for promotions, but fails to satisfy the desire for human dignity when it comes to matters of life and death.  

In addition, Shadbolt and Hampson make the point that AI is actually much less intelligent than many of us tend to think. An AI machine can be instructed to apply certain rules to decision making and can apply those rules even in quite complex situations, but the determination of those rules can only happen in one of two ways: either the rules must be invented or predetermined by whoever programmes the machine, or the rules must be observable to a “Large Language Model” AI when it scrapes the internet to observe common and typical aspects of human behaviour.  

The former option, deciding the rules in advance, is by no means straightforward. Humans abide by a complex web of intersecting ethical codes, often slipping seamlessly between utilitarianism (what achieves the most amount of good for the most amount of people?) virtue ethics (what makes me a good person?) and theological or deontological ideas (what does God or wider society expect me to do?) This complexity, as Shadbolt and Hampson observe, means that: 

“Contemporary intellectual discourse has not even the beginnings of an agreed universal basis for notions of good and evil, or right and wrong.”  

The solution might be option two – to ask AI to do a data scrape of human behaviour and use its superior processing power to determine if there actually is some sort of universal basis to our ethical codes, perhaps one that humanity hasn’t noticed yet. For example, you might instruct a large language model AI to find 1,000,000 instances of a particular pro-social act, such as generous giving, and from that to determine a universal set of rules for what counts as generosity. This is an experiment that has not yet been done, probably because it is unlikely to yield satisfactory results. After all, what is real generosity? Isn’t the truly generous person one who makes a generous gesture even when it is not socially appropriate to do so? The rule of real generosity is that it breaks the rules.  

Generosity is not the only human virtue which defies being codified – mercy falls at exactly the same hurdle. AI can never learn to be merciful, because showing mercy involves breaking a rule without having a different rule or sufficient cause to tell it to do so. Stealing is wrong, this is a rule we almost all learn from childhood. But in the famous opening to Les Misérables, Jean Valjean, a destitute convict, steals some silverware from Bishop Myriel who has provided him with hospitality. Valjean is soon caught by the police and faces a lifetime of imprisonment and forced labour for his crime. Yet the Bishop shows him mercy, falsely informing the police that the silverware was a gift and even adding two further candlesticks to the swag. Stealing is, objectively, still wrong, but the rule is temporarily suspended, or superseded, by the bishop’s wholly unruly act of mercy.   

Teaching his followers one day, Jesus stunned the crowd with a catalogue of unruly instructions. He said, “Give to everyone who asks of you,” and “Love your enemies” and “Do good to those who hate you.” The Gospel writers record that the crowd were amazed, astonished, even panicked! These were rules that challenged many assumptions about the “right” way to live – many of the social and religious “rules” of the day. And Jesus modelled this unruly way of life too – actively healing people on the designated day of rest, dining with social outcasts and having contact with those who had “unclean” illnesses such as leprosy. Overall, the message of Jesus was loud and clear, people matter more than rules.  

AI will never understand this, because to an AI people don’t actually exist, only rules exist. Rules can be programmed in manually or extracted from a data scrape, and one rule can be superseded by another rule, but beyond that a rule can never just be illogically or irrationally broken by a machine. Put more simply, AI can show us in a simplistic way what fairness ought to look like and can protect a judge from being punitive just because they are a bit hungry. There are many positive applications to the use of AI in overcoming humanity’s unconscious and illogical biases. But at the end of the day, only a human can look Jean Valjean in the eye and say, “Here, take these candlesticks too.”   

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If you enjoy Seen & Unseen, would you consider making a gift towards our work?

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