Please Cite as: Büscher, M., Coulton, P., Efstratiou, C., Gellersen, H., Hemment, D. (2011) Connected, Computed, Collective: Smart Mobilities. In Grieco, M. and Urry, J. Mobilities: New Perspectives on

Transport and Society. Burlington: Ashgate, pp. 135-158.

Chapter 7

Connected, Computed, Collective: Smart Mobilities1

Monika Büscher, Paul Coulton, Christos Efstratiou, Hans Gellersen and Drew Hemment

The ‘smart’ in ‘Smart Transport’ usually refers to technologies, not people. From cars designed to be

‘stackable’, through signs that monitor parking spaces, to ‘automatic cruise control’ systems that

‘intelligently’ control distances through vehicle-to-vehicle and vehicle-to-infrastructure communication:

technologies are key to smart transport. And it is true, people – armoured with status symbol cars and

stuck in traffic – often do not behave intelligently, raging at other drivers and pedestrians, taking risks

that endanger themselves and others. However, underestimating human intelligence could be a damaging

oversight and missed opportunity for transport designers.

In this chapter we examine several related aspects of human sense-making practices on the move

and explore how these could be productively integrated with smart transport. Starting with a comparison

of a ‘view from above’ and a ‘view from on the ground’, key aspects of the social logics of our mobile

societies become visible. Then, new technologies are already an integral part of the social organisation of

mobilities – with some socio-technical innovations that form a kind of parallel universe to the intelligent

transport solutions envisaged by engineers and traffic planners. We discuss such ‘alternate smart

mobilities’ through some utopian visions of ‘collective intelligence’ (Levy 1997) and its more mundane

manifestations, including micro-coordination and an emergent digital economy of mobilities, based on

crowdsourcing, community sensing, and data mashups. These ‘bottom-up’ innovations could come

together productively with the pervasive ‘qualculation’ (Thrift 2004) that underpins traffic shaping and

other engineering and design efforts around ‘intelligent transport systems’ (ITS) (COM 2008). Moreover,

such a convergence of social and technological innovation could counteract the threat of ‘Orwellian’

surveillance that is part of a potentially Faustian bargain for more efficiency, convenience, sustainability

and security in transport (Dennis and Urry 2009). We conclude with suggestions for mixed mobile

research methods that can inform innovation.

The View from Above

Many engineering as well as social analysts look at phenomena of socio-technical order such as traffic

from above. A bird’s eye view is produced either literally, for example, through observation from a high

vantage point (Whyte 1980), or figuratively, through mapping, tracking, modelling, and simulation (Ahas

and Mark 2005, Gilbert and Troitzsch 2005). Detachment and abstraction seem useful not only because

they make patterns and regularities visible, but also because they can draw out complex multi-causal

1 This chapter develops an earlier discussion in Büscher et al. 2009.

connections, for example between individuals’ behaviours and cumulative phenomena such as traffic

jams (Resnick 1994) or – at the very large scale – the role of mobilities in climate change (Urry 2011).

From often arduously achieved analytical vantage points, emergent patterns can become visible. In

his simulation programme Star Logo, for example, Resnick and his students modelled vehicle movement

using two simple rules:

1. if you see another car, slow down;

2. if there’s nothing ahead, speed up.

The result amazed them. With no obstructions, red lights or radar traps, common sense might suggest that

cars would soon move smoothly and at similar speeds. However, in the simulation, even if all cars started

with the same speed, a ‘phantom’ traffic jam soon formed. Exploring new forms of traffic modelling

using ‘string instability’ theory, mathematician Eddie Wilson explains:

… stop-and-go waves are generated by very small events at the level of individual vehicles. In certain situations a tipping point is reached that magnifies small effects to create large changes that can involve hundreds of vehicles … The record phantom jam was about 50 miles long – the entire M6 from Birmingham to the Lake District was stop-go the whole way. (Wilson 2010)

A deciding factor seems to be the distance between vehicles. If vehicles are placed at certain equal

distances in the modelling software, traffic flows. In the real world this suggests that ‘automatic cruise

control’ – a technology that uses vehicle-to-vehicle and vehicle-to-infrastructure communication to

maintain standard distances to other vehicles – may be an effective tool for prevention of phantom traffic

jams (COM2008). However, ITS technologies such as automatic cruise control are also very likely to

seriously undermine critical resources for the social organisation of orderly traffic on the ground.

The View from on the Ground

With their study ‘The view from the road’ (Appleyard, Lynch and Myer 1964), Kevin Lynch and his

colleagues sought to inspire planners, architects and designers to look at innovation from the road. Their

focus was on the aesthetic experience and individual sensory phenomenology of driving and way-finding.

But mobilities are also, critically, social: a matter of everyday practices and routines (MacDonald and

Grieco 2007). And more recent mobile methods of research – for example ethnographic ‘ride alongs’ with

mobile workers (Laurier 2004) and experimental implementations of prototype technologies in

technology design and art (Hemment 2006, Bamford et al. 2008, Büscher et al. 2010) – place researchers

amongst drivers, pedestrians, and otherwise mobile persons. Changing perspective like this raises critical

questions: how do participants on the ground understand, orient and contribute to the orderliness of

mobile societies? They do not have a view from above, so to be able to fit into the flow, order must

manifest for them on the ground. Events that cause complex phenomena such as phantom traffic jams are

produced here, on the ground, in motion, and they must be addressed at this level, too. Important research

questions arise: where, when and how do the relevant activities unfold? What causes them? How are they

socially organised? What is the relationship between order on the ground and order as seen from above?

In research on artificial intelligence, human-computer interaction, computer-supported cooperative

work and participatory design, similar questions have given rise to a powerful concept of ‘situated action’

and design approaches that seek to support its operation (Suchman 2007). Actions are situated, firstly, in

the sense that they are social: contingent and negotiated in collaboration with others. Secondly, actions

are situated through their emplacement: they involve interaction with designed as well as natural

environments, material artefacts, infrastrucures and technologies. Studies show that plans, rules, models,

theories as well as emotions and psychological dispositions are important resources or elements, but

uncovering them does not sufficiently explain situated action. Drawing on this work, we can highlight

some key interrelated aspects of mobility ‘on the ground’. Providing a vocabulary and brief descriptions,

we will draw out major challenges and opportunities for innovation.

Phenomenal Field

Movement makes social settings linear. People orient along routes, using – especially in the case of car

traffic – minimal embodied cues such as car indicators to read other participants’ intentions. Like a man

queuing to check in for a flight, a driver at a junction will consider questions of sequence and

organisation: ‘How many persons are in line? How long does it take to service the parties ahead in line?

… Are more parties joining the line?’ (Garfinkel and Livingston 2003: 21). Many of these questions are

answered experientially, in ‘synaesthesias of witnessed particulars’ (ibid.: 22), delicately spatio-

temporally organised (Sudnow 1972, Jonasson 1999). A driver sneaking into a roundabout under the

shadow of another car, a pedestrian avoiding eye contact, indicating that she is about to cross the road –

their placement in the sequential linear organisation of traffic provides detail for those behind to read their

intentions. Moreover, triangulating impressions from the phenomenal field enables people to know speed

not only by looking at their instruments, but also the number and kind of vehicles passing. This

negotiation locally defines ‘too fast’ and ‘too slow’ – often in line with official limits, but also open to

drift, depending on collectively perceived safety and circumstance. As we will argue in more detail later,

today this world contains technology which is – crucially – ‘known in no less immediate a fashion than is

any other experiential life world’ (Lynch 1993: 156). The contemporary phenomenal field is an

intersubjective field, that is, it is experienced as for all practical purposes the same for everyone (allowing

for cultural, biographical, or physiological differences).

Reciprocity of Perspective

A collectively performed phenomenal field enables people to put themselves in other people’s shoes, to

feel their feet itch for the accelerator at a traffic light. Reciprocity of perspective means that if I changed

place with you, I would see what you see and experience what you experience (Schutz 1970). This

principle matters enormously in the actively produced order of mobility on the ground, because it makes

other people’s behaviour intelligible and predictable.

Scenic Intelligibility

Traffic is visibly socially organised. People modulate gaps between vehicles not just according to the

rationally reasoned risk avoidance and self-interest in speedy progress encapsulated in Resnick’s

simulation. Subject to interactional particulars, their position and demeanour in relation to others

documents relationships of geniality, indifference, aggression. These are tenuous relationships and

‘cooperativeness can shift to extreme competition in the blink of a taillight’ (Vanderbilt 2008: 105). For

example, a perceived snub from a late lane merger on the motorway can prompt tailgating as revenge.

Complex social relations are thus visibly made in the gaps between vehicles (Garfinkel, quoted in Lynch

1993) and their ‘scenic intelligibility’ (Jayyusi 1988) is a critical resource for others. It underpins people’s

ability to fit into traffic, including when travelling in a foreign country, further documenting creative

contextual reasoning rather than simple rule following behaviour.

Accountability

People can be asked to account for their own and others’ actions explicitly and retrospectively, for

example, when trying to determine culpability in an accident. This may access some ‘personal’, ‘internal’

knowledge. But actions (and, at least to a degree, intentions, motivations, emotions) are also ‘account-

able’, that is, observable and reportable in real time, because they are documented in embodied conduct

(Garfinkel 1967, see also Dekker 2005). That embodied accountability, in turn, is inferential or ‘scenic’.

Studying behaviour in public places, for example, Goffman (1971) describes how pedestrians ‘diagnose’

opportunities for passage between lone walkers and parties ‘whose coordinated gait accountably achieves

their “togethering”’ (Mondada 2009). The embodied clues available for similar coordination in traffic are

simplified, but potent. The car’s body (personalised by choice of designs and ‘accessories’ ranging from

A-bars to bumper stickers), indicators and brake lights are standardised for interaction in a fast, linear

phenomenal field. In their interactions, drivers merge with their cars (Dant 2004) as others seek

intelligibility mainly from the external automobile body and only in few and slowed down circumstances

human eyes, hands, bodies.

Recipient Design

People’s sense of how others experience the world includes a sense of how others see them. This allows

for ‘recipient designed’ accounts, that is, documentary behaviour deliberately or precognitively designed

to make sense to others (Garfinkel 1967). For example, approaching a motorway traffic jam, a driver may

flick on her warning lights to enable fast approaching others to reduce their speed early.

Indexicality

Actions are ‘indexed’ by unfolding, sequentially, spatially and socially organised events and this is what

makes them meaningful. For example, a slow driver turning on his left indicator on a wider stretch of a

narrow road with no turn-offs is likely to be inviting cars stacked up behind him to pass, rather than

indicating that he will turn left at the next turn. A flash of left-right-left indicators by a passing driver can

be read as a ‘thank you’ in response, rather than an emergency warning or confusion over where to turn.

Reflexivity

Action is produced and made meaningful prospectively and retrospectively, and in the process context is

shaped. For example, a glance in the rear mirror may reveal the driver left behind above waving and

shouting, defining the indicator signal to have all along been, or to now be, a request for help. It

retrospectively characterises the context of the situation as troublesome rather than easy, revealing

‘context’ to be a fluid effect of action rather than a fixed ‘container’ for action

Against this backdrop, mobilities emerge as local, practical, collaborative, situated achievements.

They are ordered, but through contingent, embodied and emplaced situated human reasoning and socially

organised action rather than just rule following or internalised cultural consensus. In other words, a

mobile ‘interaction order’ (Goffman 1983) is made on the ground. This explains how traffic can remain

(relatively) orderly even when people do not follow rules or when unforeseen events occur, and it

illuminates how unspoken cultural traffic conventions in different countries can be intelligible (enough)

for safe driving. Indeed it highlights how traffic is as much a matter of improvisation as it is of following

rules.

From Smart Transport to Smart Mobilities

Contemporary design and engineering efforts are usually geared towards suppressing or constraining

improvisation. However, there are important opportunities to constructively support it and generate a

different kind of control. This approach hinges on a more nuanced understanding of the relationship

between order seen ‘from above’ and order made ‘on the ground’. Most importantly, it is necessary to

accept that the former does not sufficiently explain the latter nor provide control over lived mobile

practices. A view from above materialised in plans, theories, models, or technologies is good as a

resource for improvised situated action (if it is shared). But no matter how well conceived it is (e.g. in

intelligent transport systems), a view from above does not provide complete control if humans are to be

served humanely. Plans and situated actions are mutually performative, that is, how mobile lives are

conceived of in theories, models and technologies shapes how they are lived and vice versa: plans, rules,

theories, models, and technologies become what they are in and through lived mobile practices.

Some innovative analytical, engineering and design solutions are trying to leverage how these two

dimensions are coming together in ‘code/space’ (Dodge and Kitchin 2004, cited in Graham 2005) for a

more improvisation-friendly approach. Through the use of databases, mobile phones, location based

services, loyalty and credit cards, human behaviour on the ground is becoming increasingly locatable,

trackable and calculable, providing a new kind of ‘from above’ view, one that is less abstract and more

documentary, richer, although not necessarily more precise (Thrift 2004). This makes the relationship

between software and space ‘qualitatively different from the relationship between code and other types of

built or techno-social environment’, Stephen Graham (2005) argues. Software, space and people’s

physical and virtual movements could be said to have the potential to give collective phenomena a ‘body’

or documentary accountability as they unfold.

Since Georg Simmel’s seminal analysis of the importance of the pocket watch for co-ordinating

financial, personal and business meetings in the fragmented and transient cities of the late nineteenth

century (1903) knowledge of timing and location has become pervasive in the computerised, connected

and co-dependent just-in-time flows of people, goods, money, and information in the ‘network society’

(Castells 1996, Thrift 2005). At a personal level, teenagers use their mobile phones to coordinate

meetings and family arrangements on the spur of the moment, thus ‘micro-coordinating’ multiple

participants’ movements (Ling and Yttri 2002). At a commercial level, actuarial data-mining and

imprecise but richly detailed ‘qualculation’ of financial, insurance, marketing and food organisations’

data enable unprecedented dynamic judgements about futures based on past and present behaviour

(Callon and Law 2005, Thrift 2004). For example, ongoing calculation of consumer choices based on

loyalty card use enables food producers, logistics companies and warehouse operators connected to

supermarkets to become increasingly ‘dynamic to sale’ (Harvey et al. 2002), that is, able to watch

demand, anticipate change, harvest and move goods when needed. For transport designers, two key

challenges/opportunities arise from these considerations.

Firstly, the social organisation of mobilities on the ground needs to be understood. Where it is

conducive to a common good (e.g. traffic flow) it should be supported. Where it is not, interventions

should enable socio-technical innovation that is sensitive to the social organisation of mobile order

production on the ground.

Secondly, in view of the varied manifestations of intelligence in coordinating mobilities, it

becomes possible to envisage a move from intelligent transport systems (where the technologies are

smart) to smart mobilities (where multiple intelligences are augmented). This is challenging, not least

because of the complexities and dynamics it introduces. However, it also opens up opportunities to

support social practices and intersections between different modes of social and technical innovation,

most significantly around the convergence of physical and virtual mobilities brought about through

growing use of data-mining and qualculation for commercial and insurance purposes, but also amongst

the mobile public, based on increasing use of mobile Internet, Web 2.0, mobile phones and location based

services on the move.

An approach to integrate multiple intelligences for smart mobilities might involve designing for:

• situated human sense-making practices: drawing on approaches of augmenting human intellect

(Engelbart 1962), we call for approaches that support people in making the scenic,

phenomenological, and experiential intelligibility of mobile societies and environments;

• collective intelligence. This describes two forms of public intelligence:

1) the possibility to crowd-source ‘intelligence’ about real time movement, weather, road

conditions, and more through mass public participation in defining, collecting and

sensing relevant data (Ganti et al. 2010);

2) The (unconscious) synergy of collective reasoning – ‘a form of universally distributed

intelligence, constantly enhanced, coordinated in real time, and resulting in the

effective mobilization of skills … [where] No one knows everything, everyone knows

something …’ (Levy 1997: 13);

• more extrovert system reasoning. Given the complexity of our mobile lives, computational

automation, context awareness, and self-configuration are critical tools. However, these forms of

system intelligence need to be designed in a way that supports alignment with human

intelligence (Bellotti et al. 2002, Anderson et al. 2003, Andersen et al. 2007).

We now develop these ideas through discussion of emergent innovation in collaboration,

creativity, citizenship and a shared sense of crisis. We would like to suggest that developing design

capabilities that integrate multiple intelligences may make a combination of grassroots and ‘official’

qualculation possible, developing a new form of ‘collective qualculative intelligence’ and control. This

could enable more broad based socio-technical innovation, because it would develop and support public

understanding and capacity of actuarial qualculations, data-mining and information visualisation to make

sense of the complexity of transport where details currently are ‘too far, too small, too fast, or too slow, or

too big to be experienced by us’ (Harré, 1981: 29). Moreover, it could support a better understanding of

the dangers, especially around surveillance and state control, enabling development of new ethical

practices of personal data and privacy protection (Introna 2007), and allow societies to fold such

understanding into innovation.

Collaboration, Communication, Coordination

The efficiency and flexibility of smart mobilities depends on rich, live information. Automatic sensing

and data collection is useful, but not enough because there can never be enough data, and it is hard to

know what to sense, and sensors fail, and many activities cannot be made sense of by machine sensors.

Moreover, the cost of installation/commissioning of distributed ad hoc sensing is high. Research in the

areas of multisensory fusion (Luo et al. 2002) and sensor data visualisation (Shen and Ma 2008) has the

potential to offer solutions for these challenges.

Existing travel information systems, such as electronic signage on motorways, are designed to

consider travellers as crowds, lacking any form of personalised information format and delivery.

Moreover, most advanced traffic management systems rely on a centrally controlled infrastructure and

information source. These two characteristics hinder the development of trust and credibility of the

particular systems. Indeed, a travel information system that more often than not delivers information

unrelated to someone’s journey, gradually becomes ‘noise’ in the travellers’ environment. As shown by

Foo and Abdulhai (2006) the reaction of drivers to electronic signage messages decreases over time,

showing a potential distrust of the displayed messages. An information system that relies on a single

source of information (for example, the Highway Agency is the primary source for reporting congestions

or accidents in the UK) is at risk of becoming untrustworthy. Incidents where wrong or inaccurate

information is delivered by the single information source, would damage trust levels on the system as a

whole.

An alternative approach is to consider recent trends in mobile computing, for example, context-

aware applications and participatory sensing, along with trends in internet technology, for instance, user

generated content and social networking web applications. Location based applications are the most

common examples of context-aware applications (Cheverst et al. 2001) but context aware systems may

also include attributes such as user preferences, time, or proximity of other users to allow people to adapt

their behaviour (Dey 2001).

The concept of participatory sensing is a more recent phenomenon and describes systems in which

users actively participate in a project as ‘sensors’ (Ganti et al. 2010). For example, a new service may be

constructed by accessing fuel sensors to create and share information about the most fuel-efficient routes.

These do not always coincide with the shortest or fastest routes, and may be a function of vehicle type.

Ganti et al.’s study shows that a participatory sensing system can influence routing decisions of individual

users. Another example, ‘biomapping’ (Nold 2009), provides insight into how people experience different

environments. Participants wear sensors to record their Galvanic Skin Response. Sharing this data can

visualise a population’s changing states of emotional arousal in relation to location. This can be annotated

with textual messages (such as ‘busy junction’ linked to a spike in emotional arousal). More content

related participatory mapping can also be achieved through such ‘mashups’ (Zang et al. 2008). For

example, Coulton and Lochrie (2010) captured geolocated ‘tweets’ that contained the words ‘world-cup’

or ‘wimbledon’ and processed them into ‘memetic maps’ with ‘heatspots’ overlaid on Google maps to

indicate the discursive engagement of global mobile populations. Participatory mapping projects can also

be supported in real time by visualising the connection between measurements and measurers, enabling a

sense of community to evolve. Comob (Southern and Speed 2009), for example, is a mobile phone

application developed to map the spatial relationship between people (family, friends, social networks, or

more short term dedicated community sensing groups). Web 2.0 technologies such as social networking

sites and user generated content allows such information to be shared among large numbers of users in a

reliable manner, and the social dynamics that operate in such venues have been shown to scale to very

large numbers and to ensure users are able to develop appropriate motivation and trust practices, for

example in car pooling communities (Benkler 2005).

From a planning perspective, participatory sensing is attractive also for economic reasons. It costs

road network operators time and money to plan/commission/de-commission sensors on the road while it

is cheap in time/money to have sensors in cars and personal mobile devices. Another benefit is higher

precision/granularity of information from distributed sensing. But the combination of such technologies

also has the potential to allow the design/emergence of real-time travel information systems that are built

around relationships between people. Trust models in these systems can be based on social relationships.

For example: ‘if particular travel information is provided by my colleagues I will/will not trust it’.

Moreover, as we will discuss further below, by turning each individual user into a source of information,

designers create more space for developing flexible models for privacy control: ‘I will share my location

with my family, and, when arranging a meeting, with my colleagues.’ Aggregation of information on a

community level can also help develop a constructive sense of crisis (see below): ‘What is the carbon

footprint of my neighbourhood?’

Primary challenges for context awareness and participatory community sensing are the

development of the right mechanisms in order to collect and deliver the right information in the right

context. Intelligence lies in the discovery of each person’s context and the correct filtering of the

delivered information. Human intelligence is augmented through collection, computation and

visualisation of crowd-sourced data.

Creativity, Comfort and Control

Creativity, comfort and control are important elements of contemporary mobility systems, reaching from

the cultural creativity inherent in expressing status and individuality through car design and driving

practices, to discourses of safety, privacy and cocooning comfort (Shove 2003), and notions of control

over one’s destination on the open road (Urry 2007). Here, we focus on one particular aspect that cuts

across these practices. How do people probe, perceive, make sense of technologies of mobility? How do

they find their bearings or ‘moorings’ amongst them (Hannam et al. 2006)? How does this allow them to

be creative, comfortable, in control? How can technology design support people in finding their bearings?

What new forms of creativity, comfort and control might become possible?

Mark Weiser’s pioneering work on ‘ubiquitous’ computing has been a powerful visionary tool in

this regard – for good and ill. Almost 20 years ago he called for computing to ‘disappear’, drawing an

analogy to motors in cars:

A glance through the shop manual of a typical automobile, for example, reveals twenty-two motors and twenty-five more solenoids. They start the engine, clean the windshield, lock and unlock the doors, and so on. By paying careful attention it might be possible to know whenever one activated a motor, but there would be no point to it. Most of the computers that participate in embodied virtuality will be invisible in fact as well as in metaphor. (Weiser 1991: 95)

Weiser’s concept of ‘embodied virtuality’ seeks to make computation invisible in two ways. First

of all, by embedding it in the environment, the computer should become literally invisible. Secondly,

metaphorical invisibility should be experienced: the ‘highest ideal [is] to make a computer so imbedded,

so fitting, so natural, that we use it without even thinking about it’ (Weiser 1988). The first part of this

call to make the computer ‘invisible’ has been enthusiastically embraced by technology designers,

assuming that it would automatically also yield experiential invisibility. For all the right reasons – for

example, to protect car drivers from complexity overload – designers seek to hide computing by

embedding it in devices and environments, making it ‘autonomous’ (Satyanarayanan 2001), self-healing,

and context-aware (Dey 2001). These approaches can be powerful, but they can also – paradoxically –

impede what they seek to support by undermining principles of scenic visibility, intersubjectivity and

reciprocity as well as people’s practices of making sense of the phenomenal field. For example, if speed

is sometimes, for some drivers, regulated automatically (e.g. through automatic cruise control), practices

of negotiating embodied accountabilities are disrupted and people’s behaviour becomes more erratic for

others rather than more transparent. However, Weiser’s concern was not literal invisibility alone, but also

‘invisibility-in-use’, synonymous with the phenomenological notion of ‘ready-to-hand’ (Heidegger 1962),

meaning that users should be able to find their bearings in computationally augmented environments and

focus on their activities rather than on their technologies. This actually requires that people are able to

sense and understand (in a basic way) the processes of computation.

Weiser’s call for invisibility-in-use prompted early attempts to make machine reasoning visible,

for example through computer-based coaching to enable novice computer users to ‘diagnose’ machine

capabilities (Suchman, [1987] 2007). More recently, Bellotti et al. (2002), have highlighted the challenges

of ‘making sense of sensing systems’. They focus on problems of addressing embedded systems, of

coordinating attention and alignment between a house-full of sensors and actuators and their human

beneficiaries, noticing and addressing accidents. In a similar vein, drawing directly on Weiser’s work,

Chalmers (2003) proposes ‘seamful design’, revealing system ‘sutures’ (for example, between areas

where location information is or is not available), and Dourish calls for ‘accountable’ computing:

[which] means that the interface is designed so as to present, as part of its action, an “account” of what is happening. The goal of the account is to make the action of the system concrete as part of an ongoing interaction between the system and the user. So, the account should not simply be an abstract description of the system’s behavior, but rather an explication … (Dourish, 2001: 84)

However, given the indexical, reflexive, situated sociality of mobility practices discussed above, it

should be clear that accountability in this sense is extremely hard to design ‘into’ intelligent mobility

technologies. Yvonne Rogers eloquently captures why:

A fundamental stumbling block has been harnessing the huge variability in what people do, their motives for doing it, when they do it and how they do it. Ethnographic studies of how people manage their lives … have revealed that the specifics of the context surrounding people’s day-to-day living are much more subtle, fluid and idiosyncratic than theories of context have led us to believe. (Rogers 2006: 405)

While a human driver can relatively easily ‘read’ the situations described above and respond in

ways that other participants in the mobile interaction order can understand, machines flounder. As

Sebastian Thrun, director of the Artificial Intelligence Laboratory at Stanford, and co-designer of

DARPA driverless car Grand Challenge winner ‘Stanley’, states in an interview: the technology that

would enable Stanley to drive intelligently and intelligibly like a human ‘just doesn’t exist’ (Vanderbilt

2008: 53).

From a human perspective, Anderson et al. (2003) articulate how autonomy undermines the little

‘natural’ accountability that computing systems have by way of deterministic behaviours. Most notably

they argue that ‘recipient designed’ accounts – required to ‘explicate’ in ways that are relevant and

understandable in specific use situations – are hugely difficult to design for in encounters of man and

machine, where asymmetries of sentience place technology at a disadvantage in the reflexive production

of meaningful socio-technical interaction. Anderson et al. recommend participatory engagement with

prospective end users, because this will give designers at least an inkling of the kinds of accounts that

would be required and in what kinds of situations.

We build on this research. However, given the inherent difficulties of intelligent and intelligible

machine behaviour, we shy away from notions of ‘accountable’ computing. Instead, we study and design

for the ‘diagnostic’ methods of how people find their bearings by making material artefacts, environments

and technologies within their phenomenal fields ‘speak’. We describe this as supporting people in making

computing ‘palpable’ through an architectural, open source and participatory approach to computational

design (Andersen et al. 2007, Kyng et al. 2007, Büscher and Mogensen 2009). Translating a palpable

computing approach to transport entails participatory co-design with potentially vast numbers of people,

raising interesting questions about the potential for ‘scaling up’ forms of ‘collective experimentation’

(Wynne and Felt 2007) – a question we will return to in our discussion.

Citizenship

Producing, sharing and collaboratively analysing mobility data, utilising computation that non-experts

can make palpable opens up visions of desirable mobile futures where technologies augment human

reasoning about, and control of, the mobile societies people enact every day. However, by virtue of its

geo-referenced and ‘documentary’ code/space character, this intelligence is incredibly potent also for

surveillance and state control. Deliberately documented as part of participatory sensing as well as

unwittingly tracked through the use of social networking or location based services, mobile phones or

chipped cards, people’s actions are becoming accountable in new ways.

Concerns that already exist regarding the storage, processing and cross-referencing of personal

information become amplified by the increasing inclusion of detailed movement data. Users may

willingly grant operators almost unlimited use of mobility information, in exchange for enhanced social

and mobility experience. But this is not the worst. While the use of location-based services clearly has the

potential to accidentally share information with someone, it is the automated categorisation of

qualculation that poses the biggest threat. Beresford and Stajano (2003) have shown how even

anonymous traces can yield the identity of the user when combined with profile information. Krumm

(2007) analysed GPS data from 172 drivers and was able to infer the actual home address in 13 per cent

of all cases, and the actual names in 5 per cent. Matsuo et al. (2007) showed how indoor mobility data can

be used to infer detailed demographic information, such as the user’s age. Bettini et al. (2005) have thus

argued that location history can act as a quasi-identifier of users. One of the key challenges of creating

smart mobilities is the fact that by making the mapping, tracking, interrogating of movement in physical

and digital spaces possible, designers and users not only enable ‘intelligent’ mobility behaviour, and

intelligence to be collected and ‘qualculated’, but they also enable large scale, potentially intrusive

surveillance and discriminatory software-sorting (Graham 2005). This could erode democratic equality,

civil liberties and people’s privacy.

Clearly, this threat should be addressed and some promising approaches are emerging. Many

technical approaches to preserve location privacy have been proposed – from separation of who from

where and when in mobility data (e.g., k-anonymity, Gruteser and Grunwald 2003), to obfuscation by

blurring detail in the data (Duckham and Kulik 2005). However these approaches generally assume a

dichotomy in the use of location data, as either authorised or unauthorised. The act of sharing mobility-

related data is then reduced to a binary decision: friends are granted access, strangers are blocked. Yet,

privacy is not just about anonymisation or confidentiality, but a ‘boundary negotiation process’ that

depends on many contextual factors (Altman, cited in Palen and Dourish 2003). Dourish, whose call for

‘accountable’ computing pioneered the use of reflection to support human-computer interaction is

working with a group of researchers to explore how this approach might support people in understanding

and modulating privacy settings (de Paula et al. 2005) in pervasive computing environments. An

important challenge here is to understand sharing practices for mobility-related data, and to develop

usable technologies that support the situated negotiation of privacy.

Social science studies are beginning to address these questions, examining how people are

developing new sensitivities and senses in engagement with new mobile technologies, and new social

practices of managing privacy of their augmented mobile ‘cyborg’ bodies more effectively. Licoppe

(2009), for example, describes such emergent new practices in his analysis of a real world community of

mobile game players in Japan, where users tried to manage the implications of being tracked and thus

visible to unknown fellow players. People would, for instance, go to great lengths to acknowledge the

possibility of face-to-face meetings when two players happened to be close, but employ elaborate excuses

for why such meetings could not happen. This constitutes an evolution of mobile interaction order

practices (Boyko et al. 2010).

Design, policy and practice should encourage and engage with such studies and support such

emergent practices. But managing mobile personal data and location privacy in code/space in ways that

are respectful of civil interests cannot be delegated to developments in social conventions and legal

regulation. The view that technologies are neutral tools, made good or bad through human intentions and

actions, is too simplistic. The view that foolproof technical solutions can be found is similarly flawed.

Ethical considerations must be folded into the whole process of socio-technical innovation (Introna 2007).

Engagement through participatory design and design transparency through support for ‘diagnostic’

practices of making computing palpable are important mechanisms, especially when dovetailed with a

more participatory and transparent legal regulation process, for example through ‘law observatories’

(Wahlgren 2004). However, to generate momentum for such rather arduous tasks not only amongst

experts, but also amongst the general public, a constructive sense of crisis and responsibility must be

established.

A Sense of Crisis?

Cumulative or collective effects of situated action within mobility systems – from phantom traffic jams to

the role of transport in climate change – are ill understood by those causing them, and only partially

understood by those studying them. This makes it difficult to change practices and to design strategies,

policies, technologies, infrastructures to bring about desirable effects and avoid or mitigate undesirable

ones. A key problem in moving smart mobilities forward is the fact that with creeping troubles such as

congestion or climate change, people often struggle to establish a sense of crisis until it is too late, which

can be seen in histories of environmental crises (Mosley 2008). Thus, not only can designers, politicians,

policy-makers, urban planners, or citizens never know enough to reliably ‘engineer’ functioning new

socio-technical mobility systems, but without a constructive sense of crisis, they also lack motivation.

Without a sense of crisis (and an accompanying sense of the possibility of and responsibility for

constructive action) acceptance and investment in smart mobilities will be too patchy to make the whole

work. Critical mass is needed for a working intelligent mobility system. The rejection of the 2008

Transport Innovation Fund application in Manchester is a potent example (Sturcke 2008).

Community sensing that combines quantitative with qualitative geo-referenced data and data

analysis through qualculation promises some leverage here. Participatory sensing projects resonate

powerfully with ideas of participatory mass observation and citizen science (Hemment et al. 2010) and

‘reality mining’, coined by Eagle and Pentland, who processed mobile phone data to ‘map social patterns

in daily user activity, infer relationships, identify socially significant locations, and model organisational

rhythms’ (2006: 255). However, a key challenge is to move beyond people as data collectors, to people

collectively making sense of data that is ‘reality-mined’. For example, providing home energy data could

be used not just so that energy supplies can be improved in some way, but so that personal energy-

consuming practices can be understood and reflected upon in the context of consumption at many layers,

from family to friends to community.

The provision of in situ feedback on energy consumption has been shown to affect the behaviour

of people and raise awareness about the environmental impact of everyday activities (Hopper and Rice

2008). In the CSK Energy project in Cambridge smart energy meters were installed in the houses and

workspaces of 30 participants. In Taherian et al. (2010) they report how the feedback on energy

consumption triggered a change in the behaviour of the participants towards more energy aware usage of

domestic appliances. The UbiGreen toolkit (Froehlich et al. 2009) showed similar effects when offering

in situ feedback on the environmental impact of transportation choices of individuals. In earlier work

Mankoff et al. (2007) examine the role that social networking websites can play in supporting large-scale

group action to reduce their ecological footprints. Experimenting with existing social networking sites

they explore motivational schemes and frequent feedback about performance to motivate ecological

awareness and to allow participants to make their own energy-related decisions. In the context of smart

mobilities, on-line social networking sites offer a new playground for motivating environmentally aware

mobility, based on pre-existing and new social structures.

The concept of ‘collective intelligence’ and its two connotations as (1) data collected by

collectives and as (2) self-organising, synergetic collective reasoning (Levy 1997) is helpful here.

Examples of the latter abound in both popular and academic literature, ranging from Wikipedia’s ‘we-

think’ (Leadbeater 2008), through Rheingold’s ‘smartmobs’ (2003) to crisis informatics (Vieweg et al.

2008) and demand responsive transport (Benkler 2005, Zeddini et al. 2008). What seem to be at the heart

of synergetic collective reasoning are mechanisms for participation, recognition given by peers, and

mechanisms for effective self-governance (Leadbeater 2008). Building on this notion, Malone and Klein

(2007: 15) argue that it may also be possible to ‘harness computer technology to facilitate “collective

intelligence” … to address systemic problems like climate change’ through collaborative deliberation and

simulation support technologies such as the ‘climate change collaboratorium’. Perhaps the ‘smart chaos’

of collective intelligence can produce some leverage over the complex material chaos caused by

humanity’s increasingly mobile lives (Elliott and Urry 2010). It has the potential to infuse broader

awareness of complexity and more public demand for caution into the design of ‘intelligent’ mobility

systems (and other complex socio-technical systems).

However, is collective intelligence really ‘best understood as being emergent and collective rather

than orchestrated’ (Vieweg et al. 2008)? In light of analyses by insiders such as Jane McGonigal, some

scepticism seems appropriate. Reporting on her role in the celebrated ‘we-think’ example of the alternate

reality game ‘We love bees’ (Leadbeater 2008), she states:

I was … one of four puppet masters designing the live missions … The gamers’ exercise of free will has long been assumed to be a core aspect of gaming. But the rise of the puppet master … suggests that in the new ubiquitous computing landscape, many gamers want to experience precisely the opposite ... (McGonigal 2006:263)

What participants in collective intelligence efforts seem to need above all is careful orchestration

by people who ‘move with’ the participants, able to spot and encourage positive emergent behaviour and

discourage behaviour that does not suit the overall aims.

Discussion

Collectives can be just as stupid as any individual, and in important cases, stupider. Jaron Lanier 2006

Perhaps somewhat pessimistically, we feel ambivalent about the challenges and opportunities we have

discussed in this chapter. On the one hand, connected, computed and collectively sensed, visualised and

analysed mobilities could enable societies to work with, rather than against, situated reasoning and

everyday improvisation in the organisation of mobile interaction orders (see also Juhlin 2010, on the

potential of ‘interactive roads’). On the other, the increasingly connected and qualculated nature of

mobilities enables software-sorting, surveillance, actuarial commercial interventions and policing with a

frightening level of precision. Gerd Leonard, a media analyst or ‘futurist’ speaking at the 2008

Futuresonic festival, compared the power and danger of digital technologies to that of nuclear fission.

The entanglement of social, technical, political and ethical issues at this juncture calls into

question not only the role of researchers, but also the role of the planner, designer or engineer, citizen,

politician, bureaucrat and security professional. Mobility systems are nested systems within systems

within systems, with often contradictory forces at work, positive and negative feedback loops, and ripple

effects for every attempt to constrain or enable collaboration, creativity, comfort or control, citizenship

and sense-making practices. A key challenge is to juggle these forces and ripple effects. This cannot be

done through conventional ‘design and implement’ approaches. Iterative, experimental, mixed mobile

approaches are needed. The ‘living laboratory’ approach (Hemment 2006, Büscher et al. 2008,

Schumacher and Niitamo 2008) builds on participatory ‘provotyping’ approaches (Mogensen 1991),

enabling experimental appropriation or ‘colonisation’ and shaping of prototype mobility systems. The

‘open data movement’ (Shadbolt 2010) resonates with this. In the context of mobility, particular

challenges of engaging diverse stakeholders and ‘the public’ in such design endeavours arise. Hemment

et al. (2010) identify a series of ‘best practice’ guidelines:

• simplicity – starting with simple goals enables groups to ‘complexify’ later;

• coherence – engagement requires clear meaning and motivation;

• reciprocity – the outcome produced needs to be shareable and individual contributions should be

recognised;

• participatory project design – the parameters of the overall project, methods and goals need to

be defined collaboratively;

• open to the unexpected – leave room for the uninvited/unanticipated and be prepared to manage

failures constructively;

• think creatively about ‘mass’ – what does it mean and is a relatively small number of participants

enough if there is the potential to scale up?;

• usefulness – what is defined as useful and how? Who is defining this?;

• collective reflection – ensure it is built into project practice.

In return, engaged, mixed mobile methods of research can allow all stakeholders to abandon

notions of control ‘from above’ through technology and/or engineering for a different kind of control

from above and below, where all stakeholders are actively involved in gaining a bearing in the shifting

socio-technical, socio-political/ethical landscape, safe enough to experiment (Wynne and Felt 2007), to

retain reversibility (Introna 2007) and seek deliberative engagement (Jones et al. 2009).

Is this realistic? Our review of innovative endeavours suggests that it is. In a way the kinds of

innovations that are coming into view here conjure up a vision of societies able to make their collective

actions accountable, embodying them through (1) collective intelligence/data collection on the move,

producing real-time data and (2) mashup visualisations. This chimes with the embodied virtuality called

for by Mark Weiser. Only, this embodied accountability is produced not by making computing invisible

and rendering it a domain of (ITS) experts, but by engaging non-expert mobile publics to utilise and

thereby understand computation themselves. In this context living laboratories for smart mobilities may

not just be understood as a method or means to an end of designing more effective socio-technical

systems. The mixed mobile methods they use to make designers and analysts move with, and be moved

by, the people whose mobilities they seek to support may actually become part of a permanent state of

socio-technical innovation. This approach of playing to improvisation and emergence as a strength rather

than trying to ignore or suppress it may give rise to ‘better’ mobile futures.

Acknowledgements

For debate and comment we would like to thank the Lancaster ‘Amobs’ group and participants in the

workshop ‘Alternative mobility futures’ (Lancaster Centre for Mobilities Research, 17 March 2009),

Gareth Matthews, James Tomasson, Julien McHardy, Martin Pedersen, Bashar Al Takrouri, Paula

Bialski, John Delap, Javier Galetrio Garcia, Anil Namdeo, Tom Roberts, Jen Southern, Agnieszka

Strzeminska, Paul Upham, Laura Watts, Matt Wilson, and John Urry.

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