acrylic on canvas 250mm x 300mm
acrylic on canvas 250mm x 300mm
Approximately 4 million years ago, our ancestors adopted Bipedalism, freeing up their hands for more dexterous activities.
However, in recent years, our sophisticated tool making skills have resulted in the creation of the smart phone. A scrying mirror so compelling, that we willingly give up the use of one of our hands, disengage from the present moment, and hunch over our devices, literally deforming us.
You can buy the original, and prints at Saatchi Online
Like pretty much everyone in the developed world, I like to find things on the internet. The act of discovery is thrilling, and we like to think, informative (though one must wonder how to quantify the intellectual value of another cat video). For the artist, the web offers an inconceivably large corpus of inspiration, visual or otherwise.
When I find an image which appeals to me, I frequently copy it onto my local computer, building a scrapbook of inspiration (or provocation). Some people like to use services like Pinterest to collate these things, but I am old school, and prefer to keep my data on spinning hard-disk platters under my control. As a result, I have collected hundreds of images over the years, mainly sitting in a single unordered directory.
These images lie dormant, just 1s and 0s amongst millions of others. Every now and then I flick through them, looking for a spark. Often I can no longer remember when or why (of from where) I copied them.
I decided to present them back to myself, in an algorithmic manner, to see what they might inspire in a new context. Every day, at 8:31am, a picture is selected at random and posted onto my Twitter timeline. I have no interaction with this process, the images just appear, as if from me, at the same time each day.
A tiny act of self cyborg-ification.
At some point in the past, I selected these images. Each one represents an aesthetic choice made by a historical version of myself. And now they are being presented back to me, algorithmically, for fresh appraisal.
Kind of like a visual version of Oblique Strategies.
As I upgrade my hardware, I dutifully copy these images from one place to another. During this transfer, the files themselves are re-created on a new disk, entirely new digital records which perfectly replicate their parent. The idea of the ‘original’ image ceases to make sense – you can’t point to a specific copy of the data and claim it is any more authentic than any other.
However, in theory, each image has the potential to retain it’s provenance and history. Many cameras record EXIF data, which can be used to store technical details (the camera model and settings), information about the creator (artist name, copyright) and the circumstances of creation (time taken, GPS coordinates). These data are ideally created when the image is taken, and then augmented as the image makes it’s way out into the world.
I wondered what history had been recorded in my directory of collected images and whether this could be brought to the surface. Generally this data refers to the act of creation, but in theory, the act of sharing the photo could also be recorded inside the image. I could leave my mark, and perhaps watch it move around the network, like some sort of ‘message in a bottle’.
This was an exciting proposition, until I actually ran few tests. It transpires that EXIF data can be stripped, and Twitter is one of the worst offenders.
Consider these two seemingly identical images of Alan Moore:
First, the ‘original’ which I copied from the web.
It contains all sorts of information:
ExifTool Version Number : 9.90 File Name : alan-viking.jpg MIME Type : image/jpeg JFIF Version : 1.01 Exif Byte Order : Little-endian (Intel, II) Image Description : SAMSUNG Make : SAMSUNG Camera Model Name : GT-I9000 Orientation : Horizontal (normal) X Resolution : 72 Y Resolution : 72 Resolution Unit : inches Software : fw 49.01 prm 49.103 Modify Date : 2015:01:21 15:50:35 Y Cb Cr Positioning : Centered Exposure Time : 1/26 F Number : 2.6 Exposure Program : Program AE ISO : 100 Exif Version : 0220 Date/Time Original : 2015:01:21 15:50:35 Create Date : 2015:01:21 15:50:35 Components Configuration : Y, Cb, Cr, - Shutter Speed Value : 1/26 Aperture Value : 2.6 Brightness Value : 1.54 Exposure Compensation : 0 Max Aperture Value : 2.6 Metering Mode : Center-weighted average Light Source : Unknown Flash : Off, Did not fire Focal Length : 3.5 mm Warning : [minor] Unrecognized MakerNotes Flashpix Version : 0100 Color Space : sRGB Exif Image Width : 640 Exif Image Height : 480 Interoperability Index : R98 - DCF basic file (sRGB) Interoperability Version : 0100 Sensing Method : One-chip color area File Source : Digital Camera Scene Type : Directly photographed Custom Rendered : Normal Exposure Mode : Auto White Balance : Auto Digital Zoom Ratio : undef Focal Length In 35mm Format : 0 mm Scene Capture Type : Standard Contrast : Normal Saturation : Normal Sharpness : Normal GPS Version ID : 18.104.22.168 GPS Latitude Ref : North GPS Longitude Ref : East GPS Altitude Ref : Above Sea Level Compression : JPEG (old-style) Thumbnail Offset : 1316 Thumbnail Length : 9350 Image Width : 480 Image Height : 640 Encoding Process : Baseline DCT, Huffman coding Bits Per Sample : 8 Color Components : 3 Y Cb Cr Sub Sampling : YCbCr4:4:4 (1 1) Aperture : 2.6 GPS Altitude : 0 m Above Sea Level GPS Latitude : 0 deg 0' 0.00" N GPS Longitude : 0 deg 0' 0.00" E GPS Position : 0 deg 0' 0.00" N, 0 deg 0' 0.00" E Image Size : 480x640 Megapixels : 0.307 Shutter Speed : 1/26 Thumbnail Image : (Binary data 9350 bytes, use -b option to extract) Focal Length : 3.5 mm Light Value : 7.5
Now compare it to this photo, which has been passed through Twitter:
ExifTool Version Number : 9.90 File Name : CDHLzOyW8AEGvpx.jpg MIME Type : image/jpeg JFIF Version : 1.01 Resolution Unit : None X Resolution : 1 Y Resolution : 1 Image Width : 480 Image Height : 640 Encoding Process : Baseline DCT, Huffman coding Bits Per Sample : 8 Color Components : 3 Y Cb Cr Sub Sampling : YCbCr4:2:0 (2 2) Image Size : 480x640 Megapixels : 0.307
The image you see on Twitter no longer contains a single trace of information related to it’s creation. The image has been reborn as an anonymous, amnesiac clone of the original.
The act of ‘sharing’ has stripped it of it’s identity.
Sure, there are services like TinEye which offer to find the history of online images. However, they are not perfect, particularly for images on low traffic sites.
Here Tineye has identified the first citation of this image as coming from a social media aggregation site. Whereas I actually lifted it from here.
In an attempt to thwart this algo-revisionism, I am publishing some of the EXIF data in the text of the tweet. There’s not room for much, but where possible I publish details of when it was created, and by whom along with a record of the software used to manipulate it.
Unfortunately, many of the images have already been through an anonymisation process before I came across them. There is no record of their origin, and their future is stored in proprietary systems, beyond scrutiny.
Whilst we worry about networked systems recording ever more data about us, perhaps we should also consider the data which is being selectively ignored, and why.
Parody accounts are one of the prevailing cultural forms of Twitter. The combination of lazy anonymity and the 140-characters-of-wit format make it the perfect place to assume a character and play it out to a potential audience of millions. Back in the prehistoric days of Twitter, one of the first parody accounts to come to my attention (and hold it) was @osbornedrunk, wherein our erstwhile Chancellor, Gideon George Osborne, was beautifully portrayed as a bumbling idiot, bouyed by frequent hits of vodka jelly and magic mushrooms.
Drunk George ran his course and the author moved on to other things, briefly reappearing as @osbornedead around Halloween, but effectively the horrific bufoonery of the real-life Osborne outpaced the character and he quietly retired.
It turns out that the creator of @osbornedrunk is a friend of mine, a fact revealed accidentally, at the great crossing of the Brighton Ley lines (hail Eris). With the upcoming General Election, it seemed appropriate that George should come out of retirement and play out the last fevered month of the campaign. After all, parliament has now been dissolved, leaving plenty of time for vodka jelly.
One of the defining features of this government has been the revelation that we are all being surveilled, apparently for our own good. This project brings this to our attention by generating a redacted report about anyone who sends an @ message to @DrunkGeorgeOsb.
The reports are generated by scanning your last 100 tweets and finding out who you’ve been talking to and what they are talking about. When presented with a redacted report one cannot help but imagine what words might be behind those black oblongs, even more so when the report is about ourselves.
In a sense, drunk George has now become a cyborg, partly controlled by his author, and partially by algorithm.
As we approach the election, it becomes apparent that the narrative landscape of politics has changed. In the past, the discourse was led by inky newspapers and the satirical sniping of broadcaster-sanctioned comedians. The last election, in 2010, certainly had a social media component – manifested by the American-aping ‘televised debates’ and the associated back-channel chatter on Twitter. However, in the intervening five years, the size of this channel has increased enormously (approx 30m users in Q1 2010, to 288m users in Q4 2014)
It’s now possible to use this ‘big data’ to get a handle on the mood of the nation. Tweets can be read by algorithm and classified as positive or negative. Sentiment analysis is big business, harvesting the millions of opinions expressed online, and turning them into numerical values.
Brandwatch recently released sentiment data for David Cameron and Ed Miliband during the BBC Paxman interviews. In the video below I have used these data to plot the mood towards the two leaders during the broadcast – represented by red and blue backed emoticons. If the mood towards to politician is positive, the emoticon smiles, if the mood is negative, the emoticon cries.
Thousands of tweets, reduced first to numbers, and then to emoticons. Watching the result I’m struck by how the mood seems mainly negative towards both men. Is this a reflection of a national disenfranchisement with politics, or is it simply a reflection of social media itself – a place we go to complain, rather than praise?