23 Jan 2018 – 2019

Exhibition at the Open Data Institute, London
Curated by Julie Freeman and Hannah Redler-Hawes

In these meme-fuelled, statistically ‘mythological’ times, data, and the algorithms that thrive on it, are often presented as a privacy-obliterating risk-based menace. But there are always two sides to a story: with so much potential to benefit our lives data can also be a force for good, as well as game for a laugh.

As the data revolution gains momentum it is becoming clear that it is vital infrastructure – our social networks, information and entertainment systems function on layers of data which help, as well as hinder, what we consume. We need to tackle issues like ethics and equity if we are to have trust in data.

Humour helps us reveal failures and cracks in the system. In ‘😹  LMAO’, the ODI’s latest art exhibition, we reveal the funny side of data. The works have been selected for their playful yet critical approach to data and its uses. Irreverent, provocative, unconventional and plain silly, they ask us to challenge our preconceptions of data, and consider the humanity behind our technologies. Participating artists poke fun at the ineptitude of Google’s image search capabilities or the expectation that ‘big data’ will predict the future, and persuade us that sharing poop is a Good Thing.

Compelled to test developments in machine learning-based image recognition, Riitta Oittinen created hand-made mini rugs and uploaded photographs of her creations in 2014 and 2017 to test Google Image Search’s rug-awareness levels. Google’s earlier image AI mostly saw Riitta’s mini rugs as female figures, but her installation, Mini Rugs and their Friends (2017) which includes the original rugs and the returned images, shows it has subsequently learned to be a little more discerning… (spoiler alert: the algorithm is still, like, WTF is a mini rug??).

Dan Hett painted, and then defaced, two street art inspired commissions for the ODI. Transmission One and Transmission Two (2017) are two large painted canvases which each openly conceal encrypted personal data. Triggered by political rhetoric about banning end-to-end encryption, Dan challenges the viewer to seek out the key which will lead to the message decryption. This won’t be straightforward. Half of it is embedded in a chip in his hand, and half hidden at an undisclosed location.

Signalling at the false promise of big data’s ability to predict the future, Lee Montgomery’s Stupidity Tax UK (2017) uses a variety of data analysis techniques to predict the next Lottery draw. This year Lee is predicting the UK lottery after collating all the winning results to date. It is a personal crusade to expose the futility of gambling, with the added twist that based in the US he himself can’t actually purchase a ticket. At the ODI we are feeling the resulting pressure – what if Lee generates the winning numbers and we don’t buy a ticket?

Caitlin Foley & Misha Rabinovich tackle a subject that is a major taboo and a source of amusement in their work Shareable Biome (2016). Exploring ideas of waste as a human construct, the artists ask us to think about sharing our poop by demonstrating with data from the OpenBiome project that human waste is a valuable resource, one that we can disseminate and recycle. Their series of Sphinctergraphs play with traditional data visualisation and depict bacterium groups in the biomes of seven individuals. A map-based animation and series of prints visualises the flow of poop sharing across the US, questioning whether politics and religion play a part in the acceptability of the process.

Ellie Harrison’s hacked crisp dispensing device, Vending Machine (2009), donates a packet of crisps each time news of a fiscal downturn or other economic bad news is received from the BBC news website. Receiving a snack to help us through austerity is one way we can consume data, but we might also consider the darker questions it raises about access to food not at the touch of a machine button to our whim but at the machine’s discretion, regardless of our desire or hunger.

Pip Thornton’s {Poem}.py (2017) asks us to consider linguistic capitalism – the idea that algorithms process text without context and place a different set of economic rather than knowledge or meaning-based value on each word. Pip feeds Google AdWords with existing poetry to establish a price per word, then reprints the poem, listing each words’ monetary value. Through her work Pip demonstrates the disparity between human interpretation of word importance and the value of obtaining attention in an online search: it’s cheaper to elevate ‘lonely’ than it is to boost a ‘cloud’.

The artworks, and the entire ODI headquarters, are presided over by Ceiling Cat (2016), Franco and Eva Mattes’ physical Internet meme. The half-hidden real cat’s omnipresence ensures that we remember to reflect on both sides of the data story. As the artists say “It’s a taxidermy cat peeking through a hole in the ceiling, always watching you. It’s cute and scary at the same time, like the internet.”

In a world where we are challenging and adapting to the discomfort of being surveyed at every turn it also makes sense to spend some time laughing at the predicament we’ve created for ourselves where, in the words of Schumpeter, “More than 1.3 billion people have donated some of their most valuable personal data to Facebook in return for the ability to “like” and “share” cat photos” and let’s not forget the screaming goats.

Julie Freeman and Hannah Redler-Hawes
Data as Culture, 2018

Exhibition graphics and design by Adrian Philpott, Philpott Design.

View the artworks

LMAO joycat