Last week it was revealed that The Conservative Party have attempted to erase their historical speeches from the internet.

Understandably, this has caused much scorn, prompting a Streisand effect of drawing more attention to this misdeed.

But the internet never forgets, and the speeches are still available, if you know where to look. Whilst the idea of actually reading this historical record of lies and broken promises is rather unappealing, I have built something that turns them into poetry.

Poems are much nicer than speeches.

Click the image below to create a new poem.


Here are a couple of other poems I generated while working on the project, based on the obvious linguistic idiosyncrasies of the politician:

We will

We will be tested.
We will change that.
We will confront it.
We will reform the NHS.
We will be accountable.
We will protect the NHS.
We will always defend it.
We will be radical reformers.
We will make a start in 2010.
We will do all of these things.
We will be there to protect you.
We will scrap the ID Card scheme.
We will get Britain moving again.
We will create new river crossings.
We will spend more on it, not less.
We will reduce this deficit together.
We will fight that every step of the way.
We will start by doubling that to two years.
We will keep flexible working, and extend it.
We will play our part in breaking the log-jam.
We will be the government for people who aspire.
We will continue our ruthless pursuit of tax evasion.
We will also give our schools the final say over expulsion.
We will give doctors back their professional responsibility.
We will need to make big changes to fix our broken politics.
We will put responsibility at the heart of our national life.
We will be unashamedly pro-enterprise and pro-wealth creation.
We will give the same relief from bureaucracy to our employers.
We will publish every item of government spending over £25,000.
We will more than halve the cost of facility time to the taxpayer.
We will make aggressive tax avoidance more and more uncomfortable.
We will continue to expand cycle hire and plant thousands of trees.
We will want a complete opt-out from the Charter of Fundamental Rights.
We will come out with the mission completed and British heads held high.


Promises, Promises

I promise you this.
Our aid promise – kept.
He promised “full employment”.
He promised to end boom and bust.
Not a promise of a perfect country.
And he promised three million new homes.
Where are the laws that we were promised?
Every promise he’s made has turned to dust.
I’m not going to make promises I can’t keep.
So I won’t promise things I cannot deliver.
I can promise you – these are lies, lies, lies.
Labour promised they’d do something about this.
Not vague aspirations or vacuous pledge card promises.
You can read my lips, that is a promise from my heart.
And I promise that we will continue to show that resolve.
We were promised Second Reading before the summer recess.
And we’ve kept our promises to the poorest at home too.
We do not stand here and make the usual politicians’ promises.
Think back to those big promises on the steps of Downing Street.
Just as promises on aid need to be kept, so do promises on trade.
Don’t promise action on immigration – it’s simpler to say nothing.
It is, and it does, and I promise you this: I will see it through.
Now I know you’ve heard politicians promise this kind of thing before.
That’s why we promise to oppose all wasteful spending throughout the EU.
He promised to make Britain “the great global success story of this century”.
Won’t that sap people’s faith in these meetings and the promises that are made?
He promised it when he launched his leadership for the Labour Party two years ago.
I’ve challenged the Prime Minister about his broken promise at every opportunity.
By signing this pledge, Conservative candidates promise to act on all these fronts.
Because government got too big, promised too much and pretended it had all the answers.
I’m not going to stand here and promise you a country where nothing bad ever happens.
And I make this promise to everyone in Britain: you will not be left on your own in this.

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Machine Imagined Artworks (2013)

Taking another look at the Tate Data, the most interesting categories, for me, are the more subjective ones, the categories which feel like they’re furthest along the ‘I need a human to make this judgement’ axis. This dataset goes beyond simple ‘fact based’ descriptions, which means it contains a whole lot more humanity than most ‘big data’.


We can imagine machines which spot the items within a representational work (look at Google Goggles, for example) but algorithms which spot the ‘emotions and human qualities’ of an artwork are more difficult to comprehend. These categories capture complex, uniquely human judgements which occupy a space which we hold outside of simple visual perception. In fact I think I’d find a machine which could accurately classify an artwork in this way a little sinister…

The relationships between these categories and the works are metaphorical in nature, allusions to whole classes of human experience that cannot be derived from simply ‘looking at’ the artwork. The exciting part of the Tate data is really the ‘humanity’ it contains, something absolutely essential when we’re talking about art – after all, culture cannot exist without culturally informed entities experiencing it.

It struck me that these are not only representations of existing artworks, but actually the vocabulary and structure required to describe new, as yet un-made, artworks.


So, inspired by an online conversation with Bjørn Magnhildøen, I built a machine which explores this idea space, and suggests new artworks. It can be used as a source of inspiration for artists or just a tool to investigate into an unknown aesthetic domain. By using a small subsection of the Tate categories as starting point, new descriptions are created. There are 88,577,208,667,721,179,117,706,090,119,168 possible artworks in waiting to be described.

Click Here to explore this world of machine imagined art.

It makes me wonder whether the whole process, from generating an idea through to the actual production of the artwork could perhaps be automated. Maybe a hook into the Thingiverse API and a 3d printer? In the meantime, please enjoy exploring an area of idea space, created purely by a machine.

UPDATE 27/04/15

MIA is now on twitter:

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Another experiment with the Tate Collection big data. I’m still working on how best to navigate the huge collection, so I thought it might be nice if Nicholas Serota himself (or at least an automated version of him) could show you around.

Click the image below to start your personalised tour of the Tate Collection.

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get into the glitch

Get into the Groove, by Madonna, stretched to an hour alongside a datamoshed version of the video.

This was a quick experiment to see how much of the process could be scripted from the commandline. The video was created without any editing software, an hour of content that no one has ever seen, created by a machine and uploaded to YouTube. The glacial pace allows us to see the beauty in each compression-distorted frame. Aesthetic decisions made blindly by an algorithm.

It has a surprising number of pleasing frames, and the audio reminds me of Voix Bulgares.

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Exploring The Tate Collection

The Tate Collection recently released their metadata on github, the first ‘big data’ set that has piqued my interest enough to download it and have a play.

Here we present the metadata for around 70,000 artworks that Tate owns or jointly owns with the National Galleries of Scotland as part of ARTIST ROOMS. Metadata for around 3,500 associated artists is also included.

For the record, I’m a big data skeptic, to me it seems to be a buzzword which translates as: “We’ve spent all this time and money collecting lots of disparate data, surely there’s something interesting in there if we look hard enough?”.

I particularly like this definition:

by giladlotan via @doctorow

However, with that caveat, it was with a mixture of excitement and trepidation that I stepped into the data. The Tate data has all the expected attributes about the artworks, title, artist, date, media etc. but more interestingly there are hierarchical metadata associated with each artwork – effectively a tree of tags.

My first investigation was to see how the top level categories are represented in the data over time, perhaps it would reveal an interesting shift in themes, showing the changing nature of artistic expression (and/or curatorial fashions).

Here’s a graph of numbers of artworks tagged with the top level metadata. Be aware this isn’t a true representation of the actual numbers of artworks, rather the number of tags (artworks can have multiple tags, or appear in multiple top level categories). There are interesting peaks around the early/mid 19th C. and the 1970s.


Here are the actual numbers of artworks by year.


The graphs are very similar, suggesting that there is a consistent level of tagging for all artworks.

Here’s the same view, normalized to show the variation in proportion of main subject over time.


What’s interesting in this view is that this is not about the quantity of artworks in each category, per se, but rather about the distribution of the tags. These metadata tags are human curated, someone looked at the artwork and made a judgement about a range of attributes. Some are simple enough, particularly for representational works – people, places, activities etc.

However if we travel deeper into the tree some of the categories are much more subjective, and these categories are often the most interesting to explore.

For example, the category ‘emotions and human qualities’ contains the following: fear, love, horror, despair, suffering, grief, shame, anger, innocence, strength, compassion, foolishness, happiness, sadness, wisdom, tenderness, guilt, shock, chastity, desire, humility, pride, nostalgia, contemplation, isolation, condescension, complacency, anxiety, vulnerability, psyche, hope, creativity, vitality, disillusionment, memory, concentration, inspiration, exhilaration, boredom, courage, muse, victim, hedonism, aggression, disgust, dignity, mischievousness, gratitude, serenity, heroism, avarice, laziness, devotion, frustration, anonymity, virtue, deceit, jealousy, pessimism, disbelief, hatred, triumph, antihero, narcissism, uncertainty, escapism, subconscious, gluttony, loyalty, pomposity and hypocrisy

Imagine how it feels to look at an artwork and decide that it represents any of the above qualities. It seems quite difficult to me, but thankfully The Tate have invested the resources into the endeavour and we get to reap the benefits.

The dataset contains over fifteen thousand subjects, so it’s not immediately obvious how to approach the problem of navigating the data.

To get a feel for the data I built a rudimentary tool which allows you to drill down through the categories and find the artworks which match. It’s already proving to be a fascinating rabbit hole into the collection, throwing up interesting and exciting juxtapositions of works.

Click the image below to try it out.


This dataset is a machine-readable representation of the artistic space of the Tate Collection. There are meanings implicit in the hierarchy of labels of the artworks. Whilst machines that can truly ‘see’ artworks remain in the realm of science fiction, the augmentation of these artworks with human-curated metadata massively expands the ways in which a large collection can be automatically navigated.

The data effectively offers a new representational landscape overlaid on top of the collection. There are an infinite number of paths through this landscape. Normally our path through a collection is in the hands of the curator – works are grouped by artist, period, movement or other curatorial perspective and we are to an extent bound by their decisions.

With this metadata, we could curate our own collection based on our personal preferences and desires, or perhaps at the whims of an algorithmic curator. Don’t get me wrong, the role of the human curator can be integral to the artistic experience, however these kinds of data open up a new realm of possibilities.

Playing with the dataset so far has prompted a number of ideas about how to auto-curate paths through the collection, but I’ve also become aware of the dangerously seductive nature of slicing and dicing something as complex as an art collection on the basis of metadata alone. I am navigating a space one level removed from the artworks, a space defined by the Information Architecture decisions of the designers, and the tagging decisions of the humans who actually entered the data.

I can already see how the contours of this landscape can lead to automated decisions about the relative relevance of one artwork over another. Are we looking at a future where poorly marked up artworks effectively condemned to a dusty backroom gallery of the internet? and perhaps the art stars of the machine-readable future are those with the best tag clouds?


I’ve made an automated version of Sir Nicholas Serota out of the data.

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