Anna Ridler – Price Per Stem

The walls of Anna Ridler’s studio are a garden of exhibition posters featuring cypress trees, orchids, night-blooming cactuses and, of course, her seminal tulips. In Anna’s conceptual practice, flowers represent complex ideas and systems like collectivisation, value, labour, desire and decay.

For our collaboration, Price Per Stem, Anna turns her attention to peonies. As we talk, her computer whirs as images flash across the screen. “It’s in training mode,” she explains. The AI model is busy constructing an idea of a peony based on a unique dataset of over a thousand photographs of real peonies. Hand-crafted datasets like this one are integral to Anna’s approach to machine learning. An arrangement of her tulip dataset, Myriad (2018), was recently acquired by the V&A Museum.

Price Per Stem pairs generative peonies with real photographs, presenting a layered account of the prized flower – from soil to symbol.

What is it about flowers?

I find that if you really look closely at a flower, you can see so much happening. Here are these beautiful transient objects that are exported from places like Colombia or Alaska, and travel through huge flower markets in the Netherlands before they reach all these different shops where you can pick them up for £3.

There are so many variables that go into that final price. There are the predictable bumps around holidays like Mother’s Day and Valentine’s Day, or wedding season. Then there are some people who want locally grown flowers, and in Britain that comes at a premium. Depending on the weather that year, there might be a glut or a shortage which could drive the price up or down.

This seems very removed from the cultural meaning of flowers as symbols of love, care and beauty. Can both be true? Does a price spike around Valentine’s Day, for example, suggest that love can also be expressed as a calculation of supply and demand?

I keep coming back to flowers as a way of working because they allow for these multiple meanings, rather than trying to collapse into one way of looking at things. I don't think that I've chosen one side or the other on what the art means.

A lot of my work is very absurd – taking these very big political ideas and putting them at the scale of something that is a bit ridiculous, like a flower, you get a grasp of the overall absurdity of life. It also feminises it a little.

How does your exploration of peonies in Price Per Stem differ from your other flower projects?

Rather than using flowers as a metaphor, this is explicitly thinking about the flower marketplace. I’m fascinated by how the flower market functions as a microcosm of collectivization and global trade. This industry is worth billions, and it raises questions around the impact of agriculture, climate change and labour rights. It's a really dirty business with super low margins, and people get paid next to nothing.

I wanted to foreground what these flowers are worth. From the point of view of the market, a flower is at its full potential in bud, then once it is dead and decayed it is essentially worthless. I spent a lot of time thinking about the full life cycle of the flower and how to manifest it in the dataset and moving image works.

How does that compare to how flowers have been represented in art history?

I remember looking at the original Dutch still lifes in the Rijksmuseum. They’re still trying to shine in that faded way. Lots of details, like the stripes on tulip petals, have been lost because of how the paint has degraded. The painters were essentially working with the latest technology of the time, but they didn't know that that paint would become unstable.

Your projects usually have both physical and digital components. Do you see digital technology as providing an alternative to that decay?

For me, it’s more about the mirroring and movement of the two together. Nobody knows how long these technologies will last. Even some of my work from three years ago, the code doesn't run anymore because dependencies are no longer there.

Does that affect your relationship with the work?

If they break, they break — I have no desire to go back and remake them. I'm very happy with them not existing forever.

That feels like an unorthodox approach to making art.

There’s no point aiming for the eternal. It's impossible. Even the most monumental artwork will eventually come to dust. This probably goes back to my interest in the natural world because I think that things should have a finite lifespan. If you look at the science of deep time – there was a start and there will be the heat death of the universe.

I think that awareness creates a different kind of relationship to things. I'm interested in how you can enjoy them outside of the normal value system. That is mirrored in my work where so often things will disappear or fade away or stop working after a period of time. It’s about how we appreciate the transience rather than treating it as a commodity.

A common criticism of NFTs is that they over-emphasise art as a commodity rather than as an aesthetic object. How do your works challenge that?

For me, it's never just about the image – it's always about how it acts in a wider system. Most of the time when I make works on-chain, they will have a custom smart contract which will define how it can behave in the marketplace. Maybe it can only be sold in specific ways or after huge time scales, or maybe if you move it around too much it might disappear.

What does it mean for something that exists on-chain to disappear?

It exists but only as traces of the original object – like a fossil compared to the real living thing.

You’ve talked about the similarities between your approach to machine learning and the practices of land artists. Are these traces another parallel?

Definitely. One of the things that really resonates for me with land artists and machine learning is the constant shift between what the artwork actually is. Is it the documentation? Is it what it looks like? Fifty years later, is it still the artist’s vision or has the landscape changed too much? It also raises questions of stewardship and who looks after the art. I think there's a lot of parallels with AI. Is the art the dataset, or is it what comes out? Is it the code or the training landscape?

In both cases, questions around “what makes the artwork?” lead to “who makes the artwork?” What is the role of the artist when it comes to generative art?

The artist creates the vision. It’s the same as using a font – you use it to bring an idea into being rather than composing each individual part.

So even though I use generative AI, I wouldn't necessarily call myself a ‘generative artist’ because I'm not that interested in seeing the different iterations from the same code. I’m more interested in variation in the dataset. Myriad was about how human perception works within technology and placing the dataset in the lineage of natural history as a record of the natural world that can be tied to other kinds of knowledge.

How does the tension between ecology and technology play out in your practice – particularly when thinking about the environmental impact of AI?

It’s something that I've always thought about and I think it lends itself to the way that I practise. I work with a single GPU. I have green energy and a heat pump. I can tell how much energy I’m using based on how much my bill goes up each month when I'm training.

But more generally, because I work a lot with the natural world, I think it’s also reflected in the subject matter. Because I’m making the dataset myself, I can see the flowers and the environmental costs that are obscured when you’re just dealing with an interface.

One of the things that drew me to peonies is that despite their popularity, they are quite hard to grow. They have to spend a certain amount of time in the ground when it’s below freezing in order for them to sprout, but they then need warmth to bloom. With climate change, a lot of the areas they were traditionally cultivated aren’t getting cold enough winters, whereas Alaska has become a huge exporter because it is now warm enough.

Your datasets are quite similar to those used in scientific research and natural history – whether it’s seed banks or fossil collections. Do you ever think of your datasets as archives that have potential outside of the arts? Or even for future generations?

I don't necessarily think of them as having a purpose for the future. I don’t know what might happen in the future, and I kind of like that fact. I think of them as a snapshot of what exists right now. These were the flowers that existed at this moment in time. These were the shells that we found in the Thames at this moment in time. These are the trees in different parts of Louisiana at this moment in time. They're these little graphs of moments.

There’s a poetic connection between how you talk about archives and how you talk about decay.

I hadn't connected that theory, but I think I’d agree. I keep circling back to the same thing – both in form and concept. It's always different expressions of the same idea that you can treasure something and want to preserve it while also knowing ultimately you can't do that forever.

There’s something deeply human about that impulse for preservation. In Price Per Stem, both the photographs and the AI works contain the idea of the original peonies, but we respond to all of them differently. How does making art affect your relationship to the real object?

There’s a line in a Borges short story where he talks about “copies of copies of copies” until there’s a “purity of line” not found in the original. I think a lot about that when I’m making. At some point, everything started out as a real object and as it gets abstracted further and further it becomes less ‘real’. The real peony becomes a photograph which then becomes a generative image, and each time it gets corrupted from its original state. But there’s this weird beauty that doesn’t exist in the original object. Weird in its original sense – unexpected or unnatural.