The Following is an extract from a dialogue with James Auger and Jimmy Loizeau about their practice, the project as storytelling device and speculating on future scenarios:
1. Narrative Curves:
Q. The monomyth or hero’s journey, originally defined by writer and mythologist Joseph Campbell, is one of the better known story structures and can be seen to be repeated across multiple cultures and eras. In it, events and characters follow specific patterns which Campbell described in a simple and comprehensive diagram (see figure 001). Constructing a clear overview of a piece of fiction in this way is a fairly common technique for authors to keep track of the shape of their story and to plot how and when key scenes take place. However, in theory writers no longer need to define their story structures in this way but can now rely on software programs to create the strongest narrative arc.
My first question is directed towards your practice and a very simple diagram I drew to try to understand what was taking place in Real Prediction Machines (RPMs) in terms of the narrative structure that it followed [see fig 002]. The diagram borrows from Campbell in its attempt to look at the larger picture as a way of understanding the details. This is supposed to reflect the way that your project takes large multiple systems that are difficult to comprehend and funnels them down into tangible objects that mediate the information in the most simple way for an audience. The audience is then given the role of the author and asked to speculate or interpret how these objects operate or might mediate human relationships within such complex systems. Can you say a little about your system of narration, how the users interact with it and the relationships between the different players in the work?
A: The critical aspect here is the notion of ‘fiction.’ In The Pervert’s Guide to Cinema, the philosopher and cultural critic Slavoj Žižek describes the viewer’s reading (of cinema), stating that ‘if something gets too traumatic, too violent, even too filled in with enjoyment, it shatters the coordinates of our reality – we have to fictionalise it.’ Our approach aims not to shatter these coordinates but to stretch them in precise crafted ways, this has the effect of blurring the audience’s reality inviting them to participate in the evolving narrative through a blend of cultural and technical verisimilitude.
With this project the cultural coordinates are informed by historical and mystical ideas of prediction and knowing the future – of astrology and fortune telling. These familiar concepts are then updated (stretched) by introducing very contemporary scientific techniques such as the use of Big Data and algorithms – technologies in development that make (scientifically validated) promises to predict (aspects of) the future.
The RPMs and supporting algorithmic diagrams effectively translate these complex emerging technologies into a plausible concept that entice the audience into postulating on their own preferred use of the system – “What would I choose to predict?” If we are successful we achieve the critical point you describe in fig.002 and the narrative continues in the imagination of the viewer as they play out what could happen should such devices and techniques become a reality.
2. Prediction Machines
Q. Where once science fiction novels were seen to speculate and predict the future, the current discussion on prediction centres on the Internet of Things and Big Data. The Internet of Things is a name given to the new generation of everyday items that have digital network connectivity - allowing them to generate, send and receive data. Big Data being the large scale collection of information gathered from such items as well as regular computers and mobile devices. The information now available is analysed through complex algorithms and technologies that make it more comprehensible and, significantly, useful in terms of forecasting future events. As such, when in the right hands, this otherwise impenetrable data is given meaning and a high value.
Can you say a little about your project and what it suggests about our developing relationship with data and the powers that control it? Can you also describe role that you seen design taking in this relationship?
A: Contemporary human behaviour such as interacting with and through smart media, the use of the Internet and various other digitally mediated activities has the side-effect of generating vast amounts of data. This raises two fundamental related questions:
1. Who has access to the data?
2. What might this data be used for?
The clear answer to the first question is the corporations responsible for providing and managing the media and content we consume. The second question provides a more complex and yet unknown answer – use of digital technology has effectively created a live global human behaviour laboratory with data scientists experimenting on an (often) unknowing pool of billions. Recently, for example, researchers at Facebook curated the emotional content of news feeds to see if their users could be emotionally manipulated; Google.org, the philanthropic arm of Google, analyse their user’s search content looking for specific terms that might indicate flu symptoms. This data is used to build real-world models that can identify and predict epidemics two weeks quicker than conventional methods. Commercial models, used by the likes of Amazon, can predict a customer’s next purchase. So confident are they in these systems that a patent was recently awarded for ‘anticipatory shipping’ – the despatch of items before the customer has actually pressed the purchase button. On the more extreme end of the scale is the FuturICT project – a €1 billion European Commission funded project to build a Living Earth Simulator. This will effectively model the myriad streams of Big Data - the social, political, ecological, cultural, biological and physical factors that shape the world in order to better understand the future.
Big Data and algorithms operate invisibly, behind the scenes. We do not yet know of their true potential but they will undoubtably be playing a much larger role in the shaping of future everyday life. This shaping is currently in the hands of the data scientists, directed by the agendas of the companies they are employed by.
Our intent is to reclaim Big Data by employing it in more personal, surprising and transparent ways. Here design acts as a translator and intermediary between big science and everyday life showing what could happen in the near-future so we can make more educated democratic decisions about what is preferable.
3. Our private lives writ large
A: The US retailer Target recently triggered what has been described as a modern day Kafkaesque story. The incident involved an unfortunate father who discovered a gift coupon for pregnant women sent by Target, in his daughter’s name, to their house. The Father confronted the retailer upset that Target was sending unsuitable material to his young daughter. It subsequently turned out that the daughter actually was pregnant but that the retailer knew before the father; Target's hunch was based on its analysis of online searches and products purchased by the daughter - in particular for an unscented lotion that in some cases is used by pregnant women.
The prediction machines seem like they are a catalyst for these types of stories where whoever controls them ends up with a better overview and understanding of the flow of our lives than we do. Can you discuss some of your imagined stories and the implications of this type of technology. And specifically can you expand on how you think these prediction capabilities, and the way they present us individually with a clarity that we ourselves may not posses, might affect our everyday lives?
A: The science fiction writer Frederick Pohl once said that ‘a good science fiction story should be able to predict not the automobile but the traffic jam.’ Not to say that traffic jams make for good stories but it is frequently through the unforeseen side-effects that a newly-introduced technology imparts its most powerful narrative potential. By inserting prediction algorithms into everyday life situations we aim to explore, unravel and tell the strange ways in which our lives might unfold should we be given the power to know specific future events.
For this exhibition we have proposed several subjects of various scales and complexity to predict – from the relatively mundane and everyday such as a domestic argument; the personal and profound such as one’s own death; aspirations for the future such as the success of one’s offspring and the effect of nature/nurture; to vast complex involved systems such as a political outcome – in this case a Labour victory at the next general election.
The Kafkaesque moments emerge from the conflicts/insights that might arise (or not) from the mechanisation of very emotive (non-rational) human states and behaviour – a father’s hopes and ambitions for his footballer son, the device showing the fluctuating likelihood of his future professional career based on events as diverse as moving country or the child being small; affirmative feedback loops showing how conciliatory gestures could retard the onset of an imminent argument; how a political party leader eating a bacon sandwich badly can impact on his party’s electability.
RPMs are effectively supreme cause and effect devices computing the combined consequences of all relevant events - from the seemingly insignificant to the profound and obvious. With the knowledge of knowing outcomes do we become more machine-like? More predictable?
