Data is everywhere and everyone is data. This is the mantra that has been commanding our lives for decades. But it has become even more dangerously pervasive and manipulative since the early 2000s, as the whistle-blower Edward Snowden has revealed by exposing several ways in which governmental agencies conducted unauthorised surveillance on citizens. The 2008 financial crisis further evidenced that data – economic, social, personal – is power. Courses are opened or closed based on data, infrastructure built or abandoned, countries attacked or protected, people selected, ignored or marginalised. Data is political.
Data is important, but not without context and a careful examination of the criteria used to make decisions. And surely not without asking who owns, funds, buys and profits from the data and to what ends it is put to use. The amount of data generated globally per minute floods our daily habits, particularly online and via social media, wearables and the use of private and public services. Silicon Valley sees this as a natural process of evolution and sells the datafication of everything, that is, the monetisation of everyday life, as an inevitable sign of progress under the guise of ‘innovation’. To be at home, as it’s being sold to us, is to be surrounded by several dozen wi-fi and Bluetooth-connected, all-listening devices that are permanently charged remotely and collecting profitable information. It’s no wonder design, too, became obsessed with data, as technology started to allow the processing of large amounts of information and give it some form based on established parameters.
Courses are opened or closed based on data, infrastructure built or abandoned, countries attacked or protected, people selected, ignored or marginalised. Data is political.
Since the introduction of the Macintosh, the experiments documented in Emigre Magazine throughout the mid-1980s and 1990s, the emergence of net art and then the programming language Processing in 2001, the precedents of this fascination are evident. Another example of this is the proliferation of information design, visualising vast quantities of data that perhaps is only possible due to computer processing capabilities. These data visualisations are in many cases impressively dense, beautifully crafted but simply unreadable objects. Through the beautification of data, designers often run the risk of making banal, or simply ignoring, the transformation of data into information, and finally knowledge.
A crucial challenge for design is to develop ways in which data and the technology that processes it are not left unscrutinised. That is, to not let data make decisions. But the seductive power of data and technology are difficult to escape. When the design agency The Partners presented their new visual identity for the London Symphony Orchestra (LSO), it was announced as being aligned with the orchestra’s innovative character. While it’s more than likely that “communications of orchestras across Europe” are “very traditional in their approach”, data rendered this visual identity precisely with the generic effect the designers say they wanted to avoid. The designers let computer parameters with no input or knowledge about music, the LSO or its history, define a standardised visualisation based on data generated by the movement of the orchestra’s conductor, aided by motion-capture technology. Some meaning was added to the data by transforming parts of it into smoke, or sharp lines to suggest the sound of violins. But at this point, were the designers already indulgently seduced by technology and ‘trapped’ by data, unable to be driven by an investigation of their object of study?
Grand and sweeping, as well as angular and intense gestures are common to virtually any conductor, depending on the pieces they are performing. Giving form to an orchestra (or music) is always symbolic and open to subjectivity. But despite LSO’s slogan “always moving”, by focusing on the limitations of technology and producing an element that will always be centric, the designers arguably became captive of data. LSO’s specificity is lost in the visual smoke of genericness with data-generated and computer-animated illustrations. Companies that actively seek to capitalise on technological trends and their visual qualities, such as Nike, could have done these illustrations a decade ago. For example, where it says ‘Debussy’, insert ‘Cristiano Ronaldo’.
If trend forecasting says that branding agencies should increasingly embed motion in their brands, then all agencies will sell such ‘innovation’ at the same time, rendering the word meaningless.
If trend forecasting says that branding agencies should increasingly embed motion in their brands, then all agencies will sell such ‘innovation’ at the same time, rendering the word meaningless. A recent project by Deloitte Digital confirms this, while underlining the familiarity of the LSO’s new visual identity. At a golf tournament, guests could have their swing measured with the use of sensors, which was followed by a live abstract visualisation that they would receive by email. They called this gratuitous marketing exercise ‘data-driven creativity’.
The Partners’ LSO project signals a tendency in design: to surrender elements of what should be a critical, research-led decision-making process, to data and technology. This attitude continues to endorse efforts to automate design practice.
The ubiquitous and growing influence of algorithms in Western societies, which export and impose their data-based models to the rest of the world, is still largely undebated in relation to design. Algorithmic accountability should be an unavoidable subject in contemporary discussions about design ethics. Without understanding the systems in which devices and algorithms operate – and the authority they exert over what they affect – it’s impossible to make informed decisions. This is valid to design.
“Algorithms are often understood to be calculation engines, making autocratic decisions between variables to produce a single output,” writes researcher Kate Crawford. “This view, which focuses solely on the moment of where an algorithm ‘acts’ to produce an outcome, forecloses more complex readings of the political spaces in which algorithms function, are produced and modified.”
Below: Deloitte Digital and Red Paper Heart created Signature Swing which used motion capture to translate golf swings into data-driven imagery
To see design algorithms reinforcing economic interests, historically famous visual styles, and universalising data despite constantly shifting contexts, is a very likely reality. That is, algorithms that continue to impose North American and typically North and Central European approaches to design, as the right way to use data. The future is not automation, but human/algorithm political negotiation.
In 1972, the sociologist Emanuel Schegloff noted that social critics were already complaining about the replacement of men by machines, with the example of the emergence of the automatic answering machine. Both this device and algorithms are constructed on social, and not only mechanical principles. Crawford further argues that algorithms may be rule-based mechanisms that fulfil requests but if they “present us with a new knowledge logic, then it is important to consider the contours of that logic, and by which histories and philosophies it is most strongly shaped”. To put it simply, designers must be able to understand and intervene in the way work is being generated.
Graphic magazine #37 (2016) focuses on computational design. It opens with the following question: “How might computational approaches inform contemporary graphic design practices?” What this issue reveals is that while it’s important for designers to build and question their own tools, computational approaches to design often end up being a straightjacket that exists in a rarefied vacuum of rules, mathematics, parameters and coding. That the computational process has an identifiable visual style, as designer Jürg Lehni suggests, seems to be undeniable. It’s therefore pertinent that a greater investment is put in questioning the promises of coding’s contribution to the improvement of design practice. If the limitless possibilities of computation, coding and automation are recurrently praised, an over-focus on the designer’s formal output with emphasis on typography is clearly not enough. Despite the often-mentioned relation between computer science and design, coding, thinking and tools, discourse and practice on computation continues to be predominantly depoliticised. As curator Andrew Blauvelt notes at the end of the issue, “it doesn’t matter that the tools have changed; it matters more what the person’s disposition is to the tools”.
Automation normally deserves attention by the design press because of a breakthrough in technical achievement. What is not revealed nor debated is how automated systems organise data into rankings and their decision-making criteria.
Automation normally deserves attention by the design press because of a breakthrough in technical achievement. What is not revealed nor debated is how automated systems organise data into rankings and their decision-making criteria. This is key, because if designers let obscurely-generated statistics be self-regulated by algorithms and go unquestioned, a universalising monopoly is likely. If this happens, design work will continue to overlook context and reproduce bad habits of marginalisation based on class, gender and geographic origins. Difference is an obstruction to optimised, streamlined innovation. As Crawford suggests, instead of fetishising algorithms, the spaces in which they are generated and informed should be contested spaces.
Below: The Trump Network maps power relations around the President
This will probably define the future of a great part of graphic design practice. In other words – and running the risk of being locked out of the system by the seductive power of technology –designers’ commitment to being key actors in these spaces will be essential. That designers will have to work increasingly with algorithms seems inevitable. But a fundamental challenge to the profession remains the same: the need for a constant examination of the ways in which designers produce work and how work designs them, and society, back. Technology’s main goal is now to replace intelligence with artificial intelligence. For designers, it’s time to choose between subservient indulgence and critical struggle.
Francisco Laranjo is a designer and editor of Modes of Criticism, a research platform, magazine and studio based in Porto.