Mediated Geographies of Everyday Life

—Navigating the Ambient, Augmented and Algorithmic Geographies of Geomedia



Peta Mitchell & Tim Highfield




Over the past two decades, geospatial technologies have increasingly and profoundly influenced how everyday users conceive the space around them and how they navigate their ever-converging physical and virtual environments. These geospatial technologies have become both ubiquitous and mundane, and can be seen embodied in the GPS-enabled smartphone with its fully integrated location-based services. What we have witnessed, since around the year 2000, is, in effect, a digital spatial turn to rival if not eclipse the spatial turn identified by Fredric Jameson and Ed Soja in the late 1980s and early 1990s.


This digital spatial turn is the result of the convergence or entwined emergence of a number of technologies or technological affordances. At its centre is the advent of ubiquitous locative media, locative devices, and location-based services, but also critical are the related development of the geospatial web in the mid-2000s. Going hand-in-hand with and underpinning this new spatial turn is an exponential growth of spatial information—information that users of digital media are increasingly producing or volunteering, whether actively (e.g., through geotagging social media content or participating in geographic-information based crowdsourcing) or passively or unconsciously (e.g., location information gathered via urban wireless sensor networks or public transport smartcards).


As both users and producers of this burgeoning geocultural or socio-spatial form of data, citizens are also, as never before, engaged in complex ways with the geospatial. The entangled relationships between everyday users of mobile, locative media, and these large, often live, geodata sets pose new questions such as how and why everyday users use and produce spatial information; how their engagement with geomedia and geodata might change their perceptions of the space around them; and, increasingly, how those perceptions are being shaped and determined by, through, and with digital media. In this paper, we provide an overview of the near pre-history of what we are referring to as the digital spatial turn before turning our focus to the increasingly ambient, augmented, and algorithmic nature of our engagement with geomedia.



The Digital Spatial Turn and the Rise of Geomedia

In their influential book Net Locality: Why Location Matters in a Networked World, published in 2011, Eric Gordon and Adriana de Souza e Silva argued that our increasing and increasingly ubiquitous engagement with location and locative digital media has led to ‘an emerging form of location awareness’ that they call ‘net locality’ (2). Net locality, according to Gordon and de Souza e Silva, is about ‘what happens to individuals and societies when virtually everything is located or locatable’, but it is also, and ‘more importantly, ... about what individuals and societies can do with the affordances of this location awareness—from organizing impromptu political protests to finding nearby friends and resources’ (ibid.). Indeed, the emergence of this form of networked locality has changed our experience and relationship to place, requiring a hybrid (physical/digital) form of placemaking in which, as Federica Timeto, puts it ‘the experience of being somewhere increasingly merges with media as the environment of experience’ (‘Locating Media’, 95). Or, as Jason Farman has put it,


our experience of place through mobile technologies is at once a phenomenological engagement with this particular medium and a mode of reading the significance of that mode of engagement. Our bodies sense the world as a collaboration between material and digital spaces while simultaneously interacting with the cultural inscriptions written into the experience, such as the privacy implications of disclosing your location to businesses and other users. (Mobile Interface Theory, 45)


More recently, Agnieszka Leszczynski has mapped the emergence of what she terms, after Jeremy Crampton (‘Cartography’), ‘spatial media’—the ‘new technological objects (hardware, software, programming techniques, etc.) with a spatial orientation, as well as [the] nascent geographic information content forms produced via attendant practices with, through, and around these technologies’ (Leszczynski, ‘Spatial Media/tion’, 729)—while Scott McQuire proposes the term ‘geomedia’ to encompass ‘the heterogeneous family of technologies—devices, platforms, screens, operating systems, programs and networks—that constitutes the contemporary mediascape’ (Geomedia, 5). McQuire’s study of digital media and urban spaces argues that the development of this ‘geomedia’ has in part come about by ‘the enhanced role of location in framing both the functionality of media devices and the ‘content’ they access and generate’ (3).


Central to the formation of this new, digitally mediated sense of place and to the rise of spatial or geomedia is, as Gordon and de Souza e Silva note, the emergence and now pervasiveness of the location-enabled smart phone but also the development of the geospatial Web (20). The first commercially available GPS-enabled cellular phone, the Benefon Esc! ‘personal navigation phone’, was released nearly 20 years ago in 1999. Compared to today’s smartphone with its fully integrated location-based services, the Benefon Esc! was, unsurprisingly, relatively limited even in terms of using GPS for wayfinding, let alone the broad range of location-based services we’ve become familiar with. Standard promotional images for the phone show a map centred on Chamonix, suggesting its intended use scenario was off the beaten track, not everyday urban or suburban wayfinding. At the time of its release, Benefon described the Esc! as the ‘compact survival kit of the contemporary nomad’ and as having an ‘outdoor-loving character’ (Benefon, 8). Nevertheless, what is perhaps of note is that even on this, the very first mass-market GPS phone, the locative technology had a social, communicative and performative, not to mention surveillant, dimension in its ‘friend find’ feature, which, when enabled, would allow Benefon Esc! users to locate each other on a map.


While the advent of mobile technologies like the GPS-enabled smartphone is a key marker of the digital spatial turn and the growth of the kind of ‘location awareness’ identified by Gordon and de Souza e Silva, this new form of location awareness isn’t just confined to mobile locative devices. As Richard Rogers has noted, one of the enduring myths of the Internet is that it is a ‘placeless space’ (Digital Methods, 23). This has certainly never been wholly true, but it has also never been less true than in the past two decades. Since around the same time that the first GPS phone came onto the market, location awareness has also been built into the web services that a user might access from a fixed computer. That is, whenever we type a search string into Google, for instance, not only are we located via our IP address, the results being returned to us are being filtered according to our location. This IP to Geo technology stems from a French court case (LICRA v. Yahoo!) in 2000 that revolved around whether the auction of Nazi memorabilia via Yahoo!’s online marketplace contravened French territorial law, which forbade the sale of Nazi goods. In its defence, Yahoo! claimed it was impossible to block the US-based websites from French web users and that, at base, it would be unfair to remove the sites simply because they contravened one country’s rules. As Yahoo’s vice president at the time argued, ‘We have many countries and many laws and just one Internet’ (qtd. in Goldsmith & Wu, Who Controls, 2)—tapping into and reinforcing the myth of the Internet as a placeless space not beholden to territorial law.


In their account of the Yahoo! trial, Jack Goldsmith and Tim Wu write that when the company was presented with new technology that could convert IP addresses to geographical location and could effectively block 90% of French users to the Nazi memorabilia sites, Yahoo! eventually ‘surrendered’ and removed all Nazi memorabilia from its auction sites. In addition, however, they note, ‘Yahoo’s resistance to geographical screening began to wane’, and the following year they partnered with a ‘content delivery company ... to deliver geographically targeted advertising’ (9), and in 2002, Yahoo moved into China, where the company’s ability to ‘tailor’ information to geographic location was understandably welcome. As Goldsmith and Wu note, ‘the Yahoo story encapsulates the Internet’s transformation from a technology that resists territorial law to one that facilitates its enforcement’ (10). Since the early 2000s, then, it has been impossible to escape our location, even in an environment such as the Internet, which has typically been portrayed as a virtual and placeless space. We not only leave traces of our location wherever we virtually go, what we see is determined by our location. As Rogers puts it, the Web is thoroughly ‘grounded’ (Digital Methods, 23). In his account of the Yahoo! story Rogers describes the trial as definitively marking the ‘death’ of the myth of cyberspace—a death brought about by the nothing less than the ‘revenge of geography’ (40).


At around the same time as the development of IP to geo technology, one of the earliest geosocial networking apps, Dodgeball, was founded. Unlike later geosocial networking apps or location-based social networks (LBSNs), Dodgeball, which was founded in 2003, did not use GPS to track its users’ location. Rather, the service required users to actively ‘check in’ to a location via SMS, thereby sharing their location within their Dodgeball network (Humphreys, ‘Mobile Social Networks’, 343). Within six years of being founded, Dodgeball had become defunct: Google acquired the service in 2005 (the same year as the release of Google Maps) and discontinued it in 2009, yet its legacy can be seen in the fact that one of its founders, Dennis Crowley, notably went on to launch Foursquare in the year of Dodgeball’s demise. Since the mid-2000s a whole range of LBSNs or geosocial networking apps and platforms have appeared, most notably check-in or recommendation apps such as Foursquare, Swarm, and Yelp; location-based discussion apps such as Yik Yak (which announced it would shut down in 2017); athletic activity-tracking apps such as Strava; meetup or hookup apps that revolve around the user’s location, including Meetup, Tinder, and Grindr, among others.


And yet, in the last few years, the category of LBSN has effectively been hollowed out, due to the increasing pervasiveness of location within and across all mobile networking apps and platforms. All major social media platforms, including Facebook, Twitter, Instagram, and Snapchat, enable and encourage the sharing of location via geotagging. Indeed, as the very recent controversy over Snapchat’s new ‘Snap Map’ feature indicates, harnessing location is one of the key current drivers within social media platform development. The expanding geolocative substratum that underlies and increasingly underpins social media platforms now means that virtually all social media platforms can be considered to be geosocial ones (see, for instance, Wilken, ‘Twitter’, and ‘Places Nearby’, on Twitter and Facebook respectively as locative platforms). Additionally, the rise of mobile services such as Uber (which launched in 2011) that are not social per se, but that are similarly predicated on the sharing of location, have drawn attention to the criticality of location across the whole mobile media ecosystem.


In the past half-decade, we have also seen the rise of major geosocial network games, the most notable of which perhaps is Pokémon Go, released in July 2016. Pokémon Go was developed as an augmented reality game by Niantic Inc., which had previously developed the location-based augmented reality game Ingress. While not as wildly successful as Pokémon Go, Ingress, which was released in 2012, has had a dedicated following. At the time it developed Ingress, Niantic—then Niantic Labs—was a startup within Google (it is now a separate entity), and there was speculation at the time of Ingress’s release that the data being generated by pedestrian users was being fed back into Google Maps’s pedestrian directions, via a kind of gamified, augmented-reality crowdsourcing (see, for instance, Hodson, ‘Why Google’s Ingress’). While the relationship between Ingress and Google Maps data remains unclear, what is apparent is that data generated by Ingress users was used to identify the landmarks that would become Pokéstops and gyms within Pokémon Go (for more on Pokémon Go as geosocial game, see Hjorth & Richardson, ‘Pokémon GO’, and other pieces in the accompanying special issue of Mobile Media & Communication).



A New Kind of Data: From Volunteered to Ambient Geographic Information

These locative and geosocial media apps and platforms have not only brought with them a new kind of engagement with place and space, but also a new kind of geodata, with its own particular sensibilities and sensitivities. In the mid-2000s, geographer Michael F. Goodchild coined the term Volunteered Geographic Information (or VGI) to describe user-directed mapping projects such as OpenStreetMap or Ushahidi’s approach to crisis mapping as ‘a special case of the more general Web phenomenon of user-generated content’ (Goodchild, ‘Citizens’, 212). VGI data, as its name makes clear, is volunteered: a user knowingly and consciously submits geographic information to build up a bigger geographic picture of a particular issue. Geosocial media platforms, however, are blurring the boundaries of VGI in that the volunteered nature of this data is less apparent, and neither is it necessarily shared as a result of a direct prompt. Further, geosocial data is around us at all times and is being generated in real time. Geoinformatics researchers have instead suggested a different acronym—AGI, or ambient geographic information (Stefanidis, Crooks, & Radzikowski, ‘Harvesting’)—to suggest the difficulties inherent in extracting this embedded information, the challenges and potential posed by its real-time nature, as well as the ambiguity of intent around its sharing.


The ambient nature of geosocial data has been of particular interest to researchers focused on mapping and understanding the ways in which networked digital media intersect with, reframe, and augment space, place, and geography. ‘Big’ spatial data has, historically, tended to be relatively static, well gate-kept, and uniform, unlike big geosocial media data that are streamed in real- or near real-time, are ‘non-curated’, and tend to be demographically skewed (Croitoru et al., ‘Geoinformatics’, 211-212). From both a media and communication and geoinformatics perspective, the benefits of analyzing and mapping geosocial media data are clear, enabling researchers to focus on real-time dynamics and to explore social media as a ‘sensor network’ for crisis events with the potential to provide new insights into the spatio-temporal spread of ideas and actions as well as human mobilities and human behaviour (Caverlee et al., ‘Towards Geo-social Intelligence’, 34). Moreover, social media’s ubiquity and their use for documenting everyday, mundane experiences—especially the depiction of locations and places, from cafes to beaches to festivals—and sharing content socially with friends and followers, also serves to create a habitual social mediation of place.


Georeferenced social media data create augmented geographies in that they constitute ‘spatial stories’ or micronarratives of place that are acutely involved in processes of place-making. By explicitly tagging their location or simply mentioning a place in a shared image or tweet, social media users are certainly engaging in a broader public conversation about space and place—one that is not always apparent at the level of the individual tweet or image. When aggregated and visualised via social media mapping projects, such as the Livehoods Project (, which mines and maps geotagged social media content from Foursquare and Twitter, we begin to see the geosocial overlay that ambient geographic information creates, particularly in dense urban environments, and which has the potential to ‘reconceptualize the dynamics of a city’, revealing ‘subtle changes in local social patterns and the effects they have on the character of the city’ (Cranshaw et al., ‘Livehoods Project’, 65). Specific augmented reality projects like the mobile browser Layar, for example, further extend and challenge engagement and narratives around place; by allowing users to create content around particular locations, such projects have the potential to impact upon urban life and, especially, the everyday (media) practices surrounding it (Liao & Humphreys, ‘Layar-ed Places’).


In some cases, geosocial media data is having even more tangible effects on urban planning—in 2016 The Guardian reported that 76 regions and cities worldwide were now purchasing and using user-generated Strava data ‘to help assess and shape transport policy’ (Walker, ‘City Planners’). While on the face of it, this seems like a generally benign if not positive use of anonymised, individually contributed geodata for public ends (much like the conjectured use of Ingress data to supplement Google Maps), it does draw attention to the fact that user-generated ambient geodata is also, increasingly, big business. In his 2015 book Smartphones as Locative Media, Jordan Frith effectively sets everyday use of mobile media within the context of commercial harvesting of personal location data, and particularly notes the growth of location-based advertising (199-204).


The increasing interconnection and industry value of location data and digital and social media is highlighted in the Global Geospatial Industry Outlook report recently released by Geospatial Media (2017). This report on the state of play of the geospatial industry worldwide, sponsored by industry partners including leading Geographic Information Systems (GIS) developer Esri and satellite imagery vendor DigitalGlobe, notes that the sector is worth $500 billion and is a ‘core enabling technology’, fuelling disruptive business models (8). According to the report, the geospatial industry is now characterised by a digital ecosystem driven by platforms, by mobile and social media, and increasingly by automation, AI and algorithmic processing of big spatial data. This big spatial data is fundamentally unlike ‘traditional geospatial data’, which could be ‘structured and stored for analysis?post facto in analytical systems like GIS’ (24). By contrast, this ‘modern’ data, which the report estimates now constitutes 80% of all geospatial data, is overwhelmingly geosocial, comprising ‘photos, social media chats, video, voice and messages’ (24). It is particularly telling that the report expressly notes that ‘most’ of this data is shared by users in a way that doesn’t constitute a ‘conscious decision’, notably without flagging this lack of informed consent as a potential ethical issue.


The Global Geospatial Industry Outlook report also makes clear that the companies within this new digital ecosystem are not ‘traditional’ geospatial companies. The geospatial industry, the report says, is no longer focused on 20-30 core ‘geo’ companies, but instead encompasses any company that works with or builds on location. The report identifies a range of companies that are ‘spatially enabled’ (i.e., companies that capitalise on location), which in turn the report argues, gives them more potential to be disruptive. This ‘spatial enablement’ of companies is, in turn, set to grow rapidly over the coming years: in a 2016 report on the future of location-based advertising and location-based marketing, Forbes reported that ‘the number of location-driven apps is set to skyrocket. Over the next five years, location-based ads will make up over 40% of mobile spend [and] the number of location-aware apps is expected to triple by 2019, making it a significant subset of the mobile application marketplace’ (Location, 2).



Geoprivacy and the Sensitivity of Location as a Datapoint

Although neither the Forbes report nor the Geospatial Media report pay much mind to the question of privacy in relation to this highly valuable and largely user-generated locational data, the question of geoprivacy is unsurprisingly becoming a more burning one. As both producers and consumers of this ambient cloud of valuable geodata flowing through media platforms and services, digital media users are increasingly subjected to a new form of algorithmically enhanced geosurveillance, particularly in the spatially enabled smart city. Everyday users of digital or locative media are, as we know, on a daily basis knowingly or unknowingly trading details of their own location in return for other locational information (e.g., directions to somewhere they want to travel, recommendations for a restaurant nearby, locations where they might catch a Pokémon, or even unwanted Facebook ads notifying them of property sales in their suburb). For many users, this is a daily tradeoff of their own geoprivacy for other useful geodata. A 2013 Pew Research Center study of the use of location-based services by US-based mobile phone users found that 74% of adult smartphone users use their mobile device for wayfinding or directions based on their current location (Zickuhr, Location-Based Services). In addition, it found that 30% of adult users included location in their social media posts, up from 14% two years prior. Yet it also found that teen users seemed more aware of privacy issues around location sharing, with 46% saying they had turned off location services due to concerns about geoprivacy, compared with 35% of adult users.


While Leszczynski suggests that spatial media are ‘sites of potential relations between individuals; persons and places; and people, technology, and space/place’ (‘Spatial Media/tion’, 729), she also draws attention to the ways in which their ‘rapid proliferation and resulting pervasiveness ... are radically reconfiguring norms and expectations around locational privacy’ (‘Geoprivacy’, 235). Moreover, according to Leszczynski, it is precisely the ‘uniquely sensitive’ nature of personal geodata that makes ‘spatial big data’ of particular value to corporations and to law, security, and intelligence agencies (‘Spatial Big data’, 966-7). This is a point underscored by a 2016 location privacy report from the European Commission’s Joint Research Centre, which argues that location data is a looming privacy concern for public administrations. Although individuals ‘recognise the importance of protecting health or financial data,’ the report notes, ‘they are not yet aware of the value of the data they make available by constantly using their GPS, Wi-Fi and Bluetooth on their mobile devices. Location data not only says where you are, it says who you are’ (Bargiotti et al., Guidelines, 5). Similarly, a more recent Pew Research Center study into US mobile users, information-sharing and privacy drew particular attention to the particular sensitivities around location data, which is considered ‘especially precious in the age of the smartphone’, as it offers a ‘special intimacy’ for the individual user (Rainie & Page, Privacy, 5).


As Frith writes, ‘chances are, if someone accesses a mobile application that uses location, her data is being stored on a server somewhere. Even if she uses applications that do not need location, her location is still likely to be stored on a server somewhere’ (Smartphones, 203-204), and that location data is being used for a range of purposes (such as location-based advertising or improving local services) that the person may—but more likely may not—be consciously aware of. Moreover, when that personal location information is visualised on a map—when it is grounded and made apparent in ways that the user might not have anticipated, it puts these privacy questions into even starker relief, and indeed geovisualisation itself can have unintended or even perverse consequences.


Patrick Meier provides a case very much in point in his book Digital Humanitarians (44-45). In late 2012, a suburban New York newspaper released an interactive, digital map titled ‘The Gun Owner Next Door’, which used publicly available information to map the locations of over 33,000 handgun permit holders across two counties. The online map was intended to draw attention, following the Sandy Hook school shooting, to the problem of escalating levels of gun ownership. It didn’t quite have that effect: gun owners maintained their privacy had been violated, prison guards whose names and addresses were published were targeted and threatened by prison inmates, concerns were raised that criminals might use the map to target houses without guns (or conversely to target ones that did have guns because of the street value of guns), and some citizens who didn’t own guns said they felt compelled to go and buy one because they felt they might be targeted. It bears repeating that the data the map geo-visualised was effectively public data, but that the spatial visualisation showed patterns that might not otherwise be visible in tabular data.


The fact that location is a particularly sensitive datapoint was underscored again in an Australian Broadcasting Commission (ABC) online data journalism feature published in late 2015. In response to mooted changes to Australian metadata retention laws, ABC journalist Will Ockenden requested his metadata from his mobile phone provider and shared that data with readers to see what they could find out about him. It was, as the reporters described it, a kind of crowdsourced ‘surveillance selfie’ (Ockenden & Leslie, ‘What Reporter’). What is particularly notable in the resulting online analysis, is that all of the visualisations of Ockenden’s data are map based. This is not explicitly acknowledged in the online piece, but what we can infer from this is that both Ockenden and his readers saw location (the where rather than the who) as being the most sensitive or telling data to be gleaned from his metadata.



Algorithmic Location and Software-sorted Geographies

Concerns about geoprivacy are further underlined by the surrounding digital media context, where data awareness, the impact of algorithms, data sharing, and platform politics all play a part in how users engage with location, and what is done with users’ geodata. Indeed, the rise of algorithmic culture (Striphas, ‘Algorithmic Culture’) has further problematised the notion of user agency in accessing, using, and sharing location data. Algorithms are and have been for some time, of course, a stock-in-trade component of computer science, and in a recent article for Big Data and Society, Paul Dourish writes that, from the perspective of a computer scientist (for whom algorithms are simply part of the ‘intellectual furniture’), it seems ‘odd’ that algorithms have now become ‘objects of public attention’, appearing in newspapers and general conversation (‘Algorithms’, 1). And yet, he continues, when digital media and ‘digital processes become more visible as elements that shape our experience, then algorithms in particular become part of the conversation about how our lives are organized’ (ibid.). And this conversation about the emergence of a perceived ‘algorithmic culture’ that goes hand-in-hand with the rise of digital culture has filtered outwards, across and through a range of academic disciplines and into the public domain. In his recently published book What Algorithms Want, Ed Finn suggests that ‘many of the most powerful corporations in existence today are essentially cultural wrappers for sophisticated algorithms’ (20). These algorithms are, Finn argues, increasingly doing real-time cultural arbitrage: ‘they are authoring and creating, but they are also simplifying and abstracting, creating an interface layer between consumers and the messy process of, say, getting a cab or hiring a housekeeper’ (12). And this algorithmic arbitrage, he adds, ‘depends on gaps of understanding and cultural latency to generate profit or valuable information’ (111).


Algorithms have similarly played a central role in the processing of geographical information since well before the advent of the geoweb and locative/geo media—algorithms have been, as Mei Po Kwanputs it, a ‘fundamental reality of the geographic knowledge production process’ even ‘before the widespread use of computerized procedures’ (‘Algorithmic Geographies’, 276). Just as spatial information has played a defining role in the development of algorithmic culture, so too have algorithms changed spatial information in the era of big data. Kwan points out that the traditional notion of ‘data-driven geography’ is now all but defunct. Despite the fact that data-driven geographical research has always employed algorithms, in an age in which ‘no big data can reach researchers or the public untainted by some algorithmic uncertainty’, she argues that researchers should refer to ‘algorithm-driven geographies (or algorithmic geographies) rather than data-driven geography’ and should emphasise a ‘critical reflexivity with respect to both the knowledge production process and the data used in the process’ (281).


The IP to geo technology developed in the early 2000s, and which the Yahoo! case was so instrumental in drawing attention to, is an early and salient instance of algorithmic geofiltering enabling web service providers not only to restrict web content based on location but also to serve spatially proximate and geographically relevant content to users. It is also an early indicator of the digitally mediated algorithmic culture to come, and with the emergence of the geoweb, and the development of locative and spatial media, geoharvesting and geofiltering have become key processes in the workings of algorithmic culture. Moreover, the filtering or ‘software sorting’ processes that everyday users of locative media engage with and are subject to in turn have critical implications for how those users see, can understand, and navigate the physical world around them. When combined with ubiquitous mobile media and location-based services, algorithmic culture has been seen to exacerbate the problem of ‘software-sorted geographies’: a conjunction of code and space that algorithmically ‘orchestrates inequalities through technological systems embedded within urban environments’ (Graham, ‘Software-sorted Geographies’, 562).


As Sarah Widmer explains, software sorting gives rise to ‘different regimes of visibility or invisibility of information’ and, by extension to differential geographies (‘Experiencing’, 60). The mediated geographies we have served to us via the geoweb and geo/locative media might, for instance, show us only the city an algorithm thinks we want to see. No less, and perhaps more so than a game like Pokémon Go, these are augmented geographies and ones that are often self-effacing in and of their biases and omissions. Finally, not only does algorithmic culture amplify software-sorted geographies or the software-sorted city, it also increasingly complicates the V in VGI and further removes the agency of the citizen-as-sensor model within the smart city and VGI paradigms. As data becomes increasingly ambient, surveillance becomes increasingly algorithmic (Kitchin, ‘Spatial Big Data’)—and, perhaps vice versa.


Although they draw specific and sustained attention to the question of privacy and location-sharing, Gordon and de Souza e Silva’s 2011 notions of ‘location awareness’ and ‘net locality’ were, on balance, positive, emphasizing a hybrid and co-creative digital-physical form of placemaking. The capacity for digital media to enable new forms of placemaking remains, we argue, but it must be tempered with an ever-more more critical understanding of the growing role of ambient, algorithmic, and augmented geographies in an environment in which personal geodata has become an increasingly valuable commodity. Stéphane Roche has recently argued that there is a need for ‘spatial literacy’ and ‘urban intelligence’ (‘Geographic Information Science’, 2), in the face of the ubiquity and ubiquitous access to and harvesting of spatial information: improving understanding of what users are making available, and what platforms and apps can do with this information. We would argue that in addition to this what is needed is an increasing algorithmic literacy to counter this growing algorithmic arbitrage increasingly put into service within everyday digital media.




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Ctrl-Z: New Media Philosophy

ISSN 2200-8616


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