Architecture : The Agile Urbanism Manifesto – Critical Transhumanism – Medium
A citizen-led blueprint for smart cities, smart communities, and smart democracy
By 2050, 70% of the world’s population or 2.5 billion people will be living in cities, forcing more people to live on less land, consume more global energy, and generate more CO2 emissions. These pressures suggest new urban design infrastructures are needed to optimize functionality and effectiveness of systems (Desa, 2014).
One solution is to build smart cities — urban areas that harness information communications technologies (ICT) and networked devices (aka the Internet of Things or IoT). This citizen-led utopia is predicted to not only reduce costs but also solve many of the technical challenges related to rapid urbanization, such as traffic congestion, unsustainable resource allocation, and extreme weather events (Townsend, 2013). Smart user-led urban design systems may also deliver “smart health communities” which could help tackle some of the inequality-related epidemics harming populations worldwide such as obesity, poverty, and crime (Feliziani et al., 2014).
Despite evidence that “bottom-up” citizen-led projects provide better value and sustainability, most smart cities projects have applied top-down technocentric methods to improve city infrastructure (Lea, Blackstock, Giang, & Vogt, 2015). In addition, architectural practice suffers from a “fear of the body” which prevents architects from making investments in human-centred design. the fact human bodies are central to our environment suggests architects must accepted this reality, and develop new integral methods that encourage proﬁtable “investments in corporeality” (Grosz, 2001, p.14).
Architecture’s inability to make corporeal investments is complex, but likely stems from the schizophrenic nature of practice itself. While operating outside the humanities, there is ongoing debate whether it belongs to the arts or the sciences (Cook, Llewellyn-Jones, & Norment, 1991; Grosz, 2001). This identity crisis may sound trivial to the layperson, however internal divisions have seriously impacted knowledge across the board. Not only for educators and professionals, who find design methods confused and contradictory (Dorst, 2006; Kimbell, 2009a) but also for people outside practice looking to measure its progress (Buchanan, 2001). Rather than making things better, adoption of digital open source tools has amplified fragmentation (Luke et al., 2004; Margolin, 2000), incurring great biases on the minds of architects, which has continued to disrupt decision-making within practice (Cuff, 2001; Robertson & Radcliffe, 2009).
Biased minds, biased decision-making
The idea that certain worldviews or “paradigms” bias our thoughts and actions is not new. Bias was writ large in the Apollonian-Dionysian dichotomy of Ancient Greece: Apollo (god of the sun) stood for rational thinking, logic, and order; whereas Dionysus (god of wine and dance) embodied irrationality, emotions, and instinct (Nietzsche, 1967).
Ancient and Western philosophy has continued to adopt these two paradigms, either in the form of linear-based analytical thinking (e.g., Aristotle, Democritus, Bacon) or systems-based holistic thinking (e.g., Plato, Anaxagoras, Hegel, Marx), with rare examples of overlap (Brumbaugh, 1992; McKeon & Mann, 1954). Art history reflects a similar dichotomy (Figure 1) maintaining psychic tensions between the rationality of Apollo and irrationality of Dionysius (McGilchrist, 2009; Paglia, 1990). Science by contrast continually undergoes paradigm shifts, depending on the changing methods of those living within them (Kuhn, 1970).
Shifts in worldviews are not surprising. From a biological perspective, our brain processes sensory information differently. Split-brain studies of patients receiving a corpus callosotomy (an operation severing the bundle of nerve tissue or corpus callosum connecting brain hemispheres) confirmed the left side specializes in analytical tasks, whereas the right deals with spatial perception (Sperry, 1968). Studies of human development also show analytical process are specialized between analytical left brain and holistic right brain processes (Nisbett, Peng, Choi, & Norenzayan, 2001; Pask, 1976; Witkin, Moore, Goodenough, & Cox, 1977). Differences also appear to occur across genders, with men favouring left side verbal reasoning, and women using left and right areas to map emotional, verbal, and visual cues (Frederikse, Lu, Aylward, Barta, & Pearlson, 1999). Radical changes to our environment also biases thoughts and actions over time (Doidge & Bond, 2008; McLuhan, 1964).
Within architecture, construction methods during the Medieval Age meant architects had no sense of the scale or wholeness of building (Pérez-Gómez, Gómez, & Pelletier, 2000). Guttenberg printing during the Renaissance meant architects generated ideas via perspectival drawings (Evans, 1995; Pérez-Gómez et al., 2000). Mechanical clocks in the Industrial Age destroyed natural circadian cycles and individuality (Mumford, 1934). Mechanical reproduction in the Modern Age sparked cultures of distraction as a result of people’s nervous systems attempting to filter out noise (Benjamin, 2008; Kracauer & Levin, 1987; McLuhan, 1964; Selye, 1956). Personal computing during our current Digital Age has ultimately reduced human thought to information processing (Weizenbaum, 1976) and nature itself as data to be processed (Postman, 1993).
The scientification of architecture
To render architecture more scientific and less susceptible to biased thinking, leaders at the 1956 Oxford Conference of Architectural Education introduced Design Science into the curriculum (Glanville, 1999). The role of Design Science was to apply a systematic and rational approach to design thinking by breaking problems down into small parts and synthesizing them into grand solutions (Alexander, 1964; Fuller & McHale, 1967). To do this, Design Science drew heavily from the world of artificial intelligence (AI) in order to clarify “existing situations” and manipulate them towards “preferred ones” (Jones, 1992; Simon, 1969). These rationalist methods have been further amplified with the rise of digital computing tools and networks (Lawson, 2005), to the extent that it’s virtually impossible to imagine design problems being tackled any other way (Dorst, 2006; Rowe, 1991).
While digital tools have improved production, architecture’s rationalist bias has constrained diversity and made architects insensitive to user experience (de Graft-Johnson, Manley, & Greed, 2003; Grosz, 2001). These cultural norms not only negatively impact communities but also constrain innovation (Page, 2008). However, it would be wrong to blame Design Science for architecture’s rational bias. Rationalism is but one of four worldviews that have shaped architecture for millennia (Lawson, 1980; Rowe, 1991): (a) the rationalist paradigm, guided by mathematics; (b) the ecological paradigm, guided by science;(c) the technocratic paradigm, guided by engineering; and (d) the humanistic paradigm, guided by psychology (Figure 2).
While there is considerable overlap between worldviews and design methods (Cross, 2007), professional divisions still dominate practice. The following review examines each four worldviews in detail. Then, a final synthesis of models is created to fuel communications between worldviews and harness the kind of citizen-led knowledge cities need to thrive and prosper.
In reviewing the design literature, we found new modelling tools are increasingly making our buildings and cites more human. Many of these human-centred methods however are governed by the limits of the tool’s function, which place constraints on human knowledge and communication (Norman, 2005). In other words, we become tools of our own tools (Flusser, 1999; McLuhan, 1964; Thoreau, 2006). In the case of the design studio, specific technological revolutions have shaped how architects map, visualize, and create interactions between people and places (Dodds & Tavernor, 2002). Such radical shifts in practice confirm that design technologies, rather than influencing incremental change are totalitarian in their effects. It is perhaps not surprising such effects have, in many cases, resulted in the perceptual sensory capacities of people either overlooked (Bloomer, Moore, & Yudell, 1977) or ignored (Marble, 1988; Tschumi, 1994). This lack of technological convergence has come to standardize and ultimately constrain user experience. Such constraints are likely the result of four dominant paradigms that still continue to shape development and delivery of services.
The rationalist paradigm (mathematics-based)
Mathematical-based methods using CAD’s built-in geometric shape grammars enable architects to sharpen their design skills (Lawson, 2002) and increase production (Kalay, 2006). While more recent tools have amplified and exploited these capabilities, CAD nonetheless places a rationalist bias on architectural thinking and practice (Till, 2009). This bias has rendered most architects insensitive to more nuanced spatial aspects of the environmental such as building scale, land usage, and boundary conditions (Ratti, 2005). These digital advances have also outpaced any critical understanding of their psychophysiological effects (Cuomo & Sharif, 1989). As a result, geometric shape grammars still cast human-environment relations as standardized norms, failing to engage diverse populations in the creation of meaningful urban experiences (Gottdiener & Hutchison, 2010). The ambiguous ways people apply meaning to objects and environments (Hayles, 1993) implies shape grammars should only be used and interpreted in their original sense (Chomsky, 1968) i.e., as devices which specify language above all else (Krishnamurti & Stouffs, 1993) (Figure 3).
The ecological paradigm (science-based)
Science-based methods using reality mining tools enable architects to control entire systems, helping them accomplish in days what traditional methods would take months to achieve. While these tools have been useful in guiding architects towards more sustainable concerns, most of the top-down methods fail to account for the complexity and vulnerability of systems (Poynter, 2006). Over emphasis of system needs not only ignores the exponential rise of virtual communities (Herrmann, 2009) but also comes at the expense of individuals (Veltman, 2006) and the need for society to critique its own institutions (Ryan & Bohman, 1998). Bottom-up crowdsourcing systems that gather crowdsourced data from mobile smartphones has created a new citizen-led participatory sensing paradigm for measuring urban spaces (Kanhere, 2011). Despite its ability to gather citizen data, crowdsourcing remains poor at evaluating and controlling data or providing citizen feedback (Brabham, 2011). Middle-out smart city apps, which fuse the best features of top-down (centralized) and bottom-up (decentralized) methods allows data to be accessed and used by many agents at different times and places. Greatly improving the delivery of responsive city services (Figure 4).
The technocratic paradigm (engineering-based)
Engineering-based methods using testing suites enable architects to evaluate complex interactions between people, objects, and places. The problem with these methods is they tend to encourage a technocratic bias that favours mechanistic function over humanistic concerns. Recent replacement of physical testing suites with CAE programs has amplified this technocratic bias, creating knowledge gaps between people and environments. These knowledge gaps are rendered visible in the many of the post-occupancy studies showing conflicts between idealized functional models and end-user comfort (Purves, 2002). The fact CAE tools are too complex to use during vital early design stages (Oxman, 2008) mean they tend to be poor generators of ideas (Charlesworth, 2007). These findings support the reality that computers are language-bound and that thinkers who rely on them are often utilizing that small part of their brain that is like a computer (McKim, 1972, p.22). As Koestler prophetically observed: “Language can become a screen which stands between the thinker and reality. This is the reason that true creativity often starts where language ends” (Koestler, 1964) (Figure 5).
The humanistic paradigm (psychology-based)
Psychology-based methods using human-centric data enables architects to build user interfaces into systems to ensure they are responsive and meaningful. While this humanistic bias is long overdue, cynical applications manipulate design features to fuel erratic consumer behaviour (Michon et al., 2005). In projects that harness features to support wellbeing, studies show different people respond to different features in different ways (Kaplan & Kaplan, 1989; Kellert & Wilson, 1995; Lynch, 1960; Ulrich, 1984). It follows that buildings and cities design must incorporate more flexible (i.e., agile) elements beyond the visual, to ensure multisensory experiences can be adapted to user needs (Lathia, Quercia, & Crowcroft, 2012). The ability of citizens to proactively create urban experiences with user-centred tools offers architects the unique opportunity to fuel urban engagement at every turn. Thus, improving the overall development and delivery of responsive city services. These benefits are also likely to spark healthy brain plasticity not only in the minds of people (Damasio, 1994; Varela, Thompson, & Rosch, 1999) but also across broader realms of architectural practice (Figure 6).
Agile Urbanism: a citizen-led blueprint for smart cities
The idea that people who use public spaces and buildings should have a say in designing them is central to the notion of building smart communities (Deakin & Al Waer, 2011). Citizen-led initiatives were put forward in a Green Paper titled Open Sourced Planning in an effort by Britain’s Conservative Party “to rebuild Britain’s broken economy” (Conservative Party UK, 2012). This paper proposed a shift away from centralized regional planning towards decentralized local community development, where public design workshops (charrettes) could fast-track design proposals. Despite the potential of such radical decentralized planning to reinvigorate industry and society, our review found best design practices need to adopt a multi-layered approach. Any future proposal to build responsive urban services must therefore integrate such multi-layered design approaches into its structure.
To ensure organizations and architects make the kinds of corporeal investments our communities and cities need to thrive, a more cohesive model is required. Ideally, one that mitigates biases by helping designers choose the right tools for the right tasks. One useful solution, based on our review, is to integrate multiple design paradigms into one urban design continuum. At the left of the spectrum determinism is the norm (i.e., cause and effect can be analysed, predicted, understood). At the right end of the spectrum, non-determinism is the norm (i.e., cause and effect are unclear, thus prediction and control are virtually impossible). At the centre, real-time feedback tools enable rapid response to change. We call this continuum model the Agile Urbanism Blueprint (AUG) (Figure 7):
- At the left side of the blueprint, top-down algorithmic methods apply. Rule-based machine learning technologies such as CAD/CAE, generative apps, and data mining help architects harness “machine intelligence” to solve rather simple problems that can be clearly defined and reduced to their constituent parts.
- At the right side of the blueprint, bottom-up humanistic methods apply. Human-based tools such as experience maps, crowdsourcing apps, and reality mining help architects harness “human intelligence” to solve volatile, unpredictable, complex, ambiguous (VUCA) problems that lie beyond their prediction or control.
- At the centre of the blueprint, middle-out synthetic methods apply. Real-time feedback tools such as brain-computer interfaces fuse top-down and bottom-up design methods, ensuring future urban infrastructures respond and adapt to rapid change.
The AUB’s simple aim is to help architects and urban planners understand that certain design tools and methods are only effective in certain scenarios. For example, in VUCA contexts such as cities, neither rationalist, technocratic, ecological, or humanistic design methods alone can map interactions fast or accurately enough to solve problems. In this VUCA context, a more optimal solution would be to create an urban infrastructure that harnesses intelligence amplification with the support of brain-machine interfaces and wearable sensors. These new tools may help architects and planners collect powerful user data sets and build reflexive solutions that adapt and change to real-time events. Such tools also have the potential to boost levels of user engagement and interaction in citizen-led urbanism. Ultimately rendering our cities, communities, and democracy smarter and more resilient to future challenges.
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Grant Munro is director of London’s Digital Health Advisory Board and honorary academic at the National Institute of Health Innovation, University of Auckland, New Zealand. He is cofounder of the Innovation Party, Britain’s first political movement dedicated to fostering agile governance through peer-to-peer networks. His health blogs Shockism.com and Luman.life focus on charting frontier advances in digital health to help people get the most from life. He can be reached at Medium, Twitter, Facebook, GrantMunro.com or via email at firstname.lastname@example.org.
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