Shadowy knowledge infrastructures

ABSTRACT

Changes associated with Internet technologies, including mobile devices, ubiquitous computing, and big data, have altered the basic mechanics whereby human knowledge is produced and circulated. This article discusses newfangled data-driven knowledge agents which emerged in the wake of these major transformations and which are termed here ‘Shadowy Knowledge Infrastructural Platforms’ (SKI). SKI, are conceived as data-driven infrastructural platform firms that have attained the scale and social utility that renders them vitally important to millions of individuals and to major institutions that have become dependent on the epistemic products and services they provide. The focus is on two representative examples of such enterprises, Waze and Moovit, both of which have rapidly fledged out into major producers and disseminators of human knowledge in the field of transportation and cartography. The article identifies the distinctive characteristics of these entities, points out to their obscure practices, and reveals the mechanism that governs their meteoric growth. The analysis demonstrates the high stakes involved when Shadowy Knowledge Infrastructural Platforms, having accumulated individual and institutional data for commercial purposes, establish forms of sovereign power over the creation and distribution of knowledge, on which both individuals and institutions become dependent.

KEYWORDS:

• Knowledge infrastructures
• platforms
• personal data
• institutional data
• Waze
• Moovit

Introduction

In 2013 Google announced that it had acquired – for a staggering $1.3 billion – an Israeli startup called Waze Mobile, which developed a smartphone navigation application. In an interview published in Probs, Waze’s CEO Noam Barding explained the rationale behind that seemingly startling acquisition:

Just like search became the interface for monetization on the web, [Waze’s] maps are going to be a big part of the monetization engine for mobile, because that’s what you open when you’re going places. (Olson, 2013)

In 2020, Intel Corp confirmed that it had acquired Israeli mobility-as-a-service (MaaS) company Moovit for $900 million. The Moovit app offers travelers a real-time picture and routes for their journey by combining information from public transit operators and authorities with live input from end users. Moovit board member and CEO of Intel’s sister company, Mobileye, Amnon Shashua explained the logic of this partnership:

Moovit’s massive global user base, proprietary transportation data, global editors’ community, strong partnerships with key transit and mobility ecosystem partners, and highly skilled team is what makes them a great investment. Moovit is a strong brand trusted by hundreds of millions of people globally. Together, with Mobileye’s extensive capabilities in mapping and self-driving technology, we will be able to accelerate our timeline to transform the future of mobility. (Zerachovitz, 2020)

As the statements of the two CEOs quoted above clearly indicate, their two firms, supported by established global titans (Alphabet/Google for Waze and Intel Corporation for Moovit) are turning into chief sources of human knowledge regarding transportation, mobility and cartography.

This article zooms in on newfangled powerful entities like Waze and Moovit and reveals their nature as shadowy knowledge infrastructural platforms (SKI). It demonstrates the high stakes involved when, through opaque practices, shadowy knowledge infrastructural platforms like Waze and Moovit, gain sovereign power over the creation and distribution of knowledge, both individuals and institutions become dependent on.

The article is divided into two parts. The first defines the concept of ‘shadowy knowledge infrastructural platforms,’ and characterizes the entities that fall under this rubric. The second part maps out facets of these entities’ power by making sense of the core elements in their business models and practices. The evolutionary trajectory of SKI is analyzed in terms of three main stages, referred to as invention, commercialization, and monetization. Tracking the gradual evolution of SKI reveals their operating practices, and the extensive power they have acquired – not through brute force, but through seemingly neutral mechanisms, seduction, and influencing choices taken by individuals, institutions and states.

Defining shadowy knowledge infrastructural platforms [SKI]

In the following section I characterize SKI (focusing on Waze and Moovit as representative examples), by unpacking the term Shadowy Knowledge Infrastructural Platforms, and examining its different constituent parts.

SKI as platform firms

SKI (Waze and Moovit included) are data-driven platforms developed and managed by platform companies, aka ‘industry platforms’ (Cusumano et al., 2019). As many critics show, these enterprises have fundamentally transformed many social domains, among them markets for goods (e.g., Amazon, eBay), mobility (e.g., Uber, Lyft), accommodation (e.g., Airbnb), labor (e.g., Upwork, TaskRabbit), delivery (e.g., Wolt), navigation (Waze and Moovit) and the entire field of online socializing and content production (e.g., Facebook, TikTok).

Data-driven platform companies bring together individuals and/or institutions, making it possible for them to interact in innovative ways that create nonlinear increases in utility and value (Cusumano et al., 2019). Put differently, the practical and economic value of a platform is increased not by simply adding another user or innovation. Rather, the increase in its value is geometrical, inasmuch as each additional actor on the platform can, in principle, connect to all the other actors or benefit from all the other innovative products and services that the platform affords. Importantly, such a platform enables more and more actors to join it and add value, provided they do so within the structures and protocols established by a central set of rules and procedures (Barns, 2020).

The rapid proliferation of data-driven platform companies – like Airbnb in accommodation, Upwork and TaskRabbit in labor, and Waze and Moovit in navigation – has given rise to an industry-centric research perspective that turns attention to practices of platform companies which produce services delivered through the platforms they establish and maintain. This line of inquiry assumes that a major key to understanding the growth of data-driven platforms is analyzing the practices employed by the owners of these platform companies, who provide and govern the use of critical productive assets and are therefore at the nexus of the complex relationships that are obtained on the platform.

Waze and Moovit are platform companies that operate data-driven platforms. These entities offer specific, designated software setups that are accessible at no cost to anyone with a smartphone or a Web browser. Waze operates an application for traffic and navigation services. Moovit, a mobility-as-a-service (MaaS) application, provides route planning to urban travelers, and transit data to transit companies. The products and services these companies develop are delivered through their platforms, which mediate their relationship with complementors (individual users, advertizers, public institutions, businesses etc.).

Owned by data-driven empires Google (Waze) and Intel (Moovit), the companies have built their local and global dominance by garnering data from individuals and institutions, and by incorporating many related lines of businesses (like organizing carpools in the case of Waze, and operating apps for public transportation payment in the case of Moovit – see discussion below). Due to their size and sphere of operation, Waze and Moovit do not merely facilitate useful tools (van Dijck, 2013), but shape sociocultural performance – as, for example, in the case of Waze, which in the fall of 2021, redirected its one million users to far-flung cities, causing major inconvenience.

Infrastructural platforms: the case of Waze and Moovit

I propose to call data-driven platforms like Waze and Moovit ‘shadowy knowledge infrastructural platforms’ because of their transformation from isolated platforms into infrastructures. Larry Beeferman and Allan Wain encapsulates the role infrastructures play in modern societies:

Facilities, structure, equipment, or similar physical assets – and the enterprises that employ them – that are vitally important, if not absolutely essential, to people having the capabilities to thrive as individuals and participants in social, economic, political, civic or communal, household or familial, and other roles in ways critical to their own well-being and that of their society, and the material and other conditions which enable them to exercise those capabilities to the fullest (2016, p. 17)

On this approach, an infrastructure is conceptualized not as a set of things but as relations – beween individual users, commercial and public institutions, governments and more – that shape, energize, and sustain the production and distribution of a variety of artefacts on global, national, and local scales (e.g., Star & Ruhleder, 1996; Larkin, 2013).

This line of research also encompassed the works of media and communication scholars, literature which used to refer to media infrastructures as ‘telecommunication networks’ (Parks & Starosielski, 2015). These scholars turn attention to the political, economic and regulatory structures that both enable and constrain the development of national, international and global telecommunication systems. Their studies tend to highlight the diverse and uneven conditions that shape and characterize media infrastructures in different parts of the world, the resources (both human and material) deployed to construct and maintain them, and the agendas or norms that impinge on their development.

In the digital domain, critics tend to focus on internet equipment, internet connections, internet protocols, etc. (e.g., Sandvig, 2013), seen metaphorically as the ‘roads’ or ‘railways’ that both facilitate and constrain online traffic. With the advent of data-driven platform companies that can establish infrastructural power (like Meta, Apple, and Amazon), scholars have increasingly taken note of these novel enterprises (See e.g., Peters, 2015; Plantin et al., 2018; Parks & Starosielski, 2015).

This growing corpus on the economic, political, and cultural power of ‘infrastructural platforms’ (Plantin et al., 2018), informs my study on SKI, which I define as data-driven infrastructural platform firms that have attained the scale and social utility that renders them vitally important, if not absolutely essential, to millions of individuals and to major institutions that have become dependent on the epistemic products and services they provide. This powerful position is arguably sustainable in the long run, since SKI are increasingly gaining control over huge amounts of data that constitute the raw martial of their epistemic services in the present, and probably in the future.

SKI as epistemic media

Of particular importance for the study of data-driven infrastructural platforms is the role these enterprises play as chief knowledge agents engendering novel ways of knowing the world. As past studies have shown, data-driven infrastructural platforms like Waze (Google Inc.), Moovit (Intel Inc.), Facebook (Meta, Inc.), or Uber (Uber Inc.) exercise significant control over the creation of knowledge, the course of its flow, and the terms of access to it, both at present and in future (e.g., Meese & Hurcombe 2021; Kleis Nielsen & Ganter, 2017; Fisher, 2022). Importantly, the power these epistemic agents wield is achieved not by force but through seemingly neutral mechanisms, seductions, and the ‘nudging’ of users’ choices (Yeung 2017).

I use the term ‘knowledge’ as a shorthand for the combination of structured and unstructured data, information, experience, and insights (Oxford dictionary) in the Habermasian sense (Habermas, 1972), that is, as rationalization conducive to exposing ‘true reality,’ with an object of people’s emancipation. In the title of Habermas’s 1970 book Knowledge and Human Interests, this conception is encapsulated in the word ‘interests,’ possibly intimating that humans are interested in the knowledge that serves their interests, or at least is perceived as such (See Fisher, 2022).

To the extent that Waze and Moovit do not only describe reality but enable their users to construct for themselves a reality they desire, these firms seem to be creating and disseminating the knowledge in the above, Habermasian, sense of this word. This is achieved by means of computational systems that collect huge amounts of data from different sources and, with the aid of algorithms, produce new knowledge about the world. To proceed along Habemas’s line of reasoning, Waze and Moovit, like many other data-driven platforms, are essentially epistemic media that create personalized knowledge for users on the basis of the knowledge they acquire about the latter. It follows that individuals who avail themselves of Waze’s or Moovit’s services receive information and knowledge they are interested in, that is, the kind of knowledge that serves their interests (Habermas, 1972) – for example, information regarding locations of police cameras. Similarly, institutions that partner with these firms and/or consume their products and services receive desired, tailor-made knowledge; thus, the knowledge and information state patrol agencies receive though their ‘Waze for Cities’ collaboration with Waze enable them to respond quickly to hazards in seemingly high-risk areas.

The novelty of data-driven platforms as epistemic media also lies in their ability to enhance users’ self-knowledge, or more specifically, their second-order self-knowledge. This can be achieved because users of these platforms (both individuals and institutions) become known to the platform companies that own the platforms. The platforms owners survey the users and, channel to the latter the knowledge reflecting what they know about them (see discussion in Fisher, 2022). An illustrative example of this dynamic is route suggestions through which Waze provides the individual user with a kind of self-image: his/her preferences, interests, routines etc.

A crucial characteristic of data-driven platforms relates to the obscure nature of the epistemic procedures they establish and perform. I use the metaphor ‘shadowy’ to describe such practices. A ‘shadow’ gives a basic outline of the object that casts it, but the object in its entirety cannot be visualized based on the shadow alone. As noted above, SKI create new knowledge about the world based on the huge amount of data they hold and make some of this knowledge visible to the platform users, both individuals and institutions. Yet, akin to the shadow that renders an object unidentifiable, the epistemic procedures employed by data-driven platforms are opaque. With regards to knowledge creation, these platform companies do not divulge either the sources of the raw data they collect and use, nor the nature and intended use of those data. They also do not allow access to their algorithmic systems or make transparent processes of data analyses. Importantly, they do not provide full information regarding their business partners, or the nature of their relationships with them (e.g., monetary exchanges). As a result, no one who uses the platform knows who gets access to the knowledge the platform has acquired about them, under which terms such an access is allowed, if at all, or the intended use of the data and information collected. In a boarder context, the shadowy nature of SKI as epistemic media relates to what Slota et al. (2020) described as ‘infrastructural occult’, namely, the hidden or insensible systems embedded in an infrastructure that inflect peoples’ actions in relation to infrastructure.

As will be discussed in detail, the epistemic work of Waze and Moovit is analogous to that of other data-driven infrastructural platforms. The two platform companies rely on resources (particularly raw data), arrangements, and activities (like forming partnerships with second and third parties) that are totally unknown to and unquestioned by most users, whether individuals or institutions.

I focus on the evolution and facets of the power of Waze and Moovit as representative examples of SKI, showing that the growth of these firms follows a pattern of three stages, to be termed invention, commercialization, and monetization. The analysis reveals how Waze and Moovit have succeeded in establishing infrastructural power through obscure and unaccountable practices conducted outside the realm of public institutions and states. Essentially, these enterprises have gained control of the material (particularly of data) and other indispensable elements which enable individuals, groups, and institutions to acquire knowledge that both interests them and serves their interests.

Picking up momentum

The analysis of the three-stage evolution of Waze and Moovit draws on the influential work of historian Thomas P. Hugher, and particularly on the methodological construct which he developed and called ‘technological momentum’ (1994). Hugher described how technological systems are formed and gain stability. He argued that, in the case of (emerging) technologies, mass as it is conceptualized in physics can metaphorically stand for the structural components of an emerging system. The element of speed in physics signifies, in this analogy, the pace of technological development, which involves innovations or scientific breakthroughs, as well as fund raising.

Phase one: inventing the technology

Hugher (1983) applied his analytical framework anchored in the momentum metaphor to trace the rise of electronic infrastructures in the US. He stressed the important role inventors – entrepreneurs played in generating these infrastructures. The contribution of these people stems from their ability to put an idea into practice (Hughes, 1983, p. 19). In a similar vein, the individuals who invented Waze and Moovit played a crucial role in turning these innovations into shadowy knowledge infrastructural platforms.

Waze was inaugurated by a young Israeli programmer Ehud Shabtai in early 2000. Shabtai’s immediate goal was to get from place to place quickly and without asking for directions. The GPS device he used had many annoying flaws. Shabtai was able to identify the problem: the difficulty of navigating Israeli roads using a hand-held GPS; he then found a solution to this problem: a data-base of all the roads in the country that would be accessible to all drivers, free of charge, via the hand-held GPS. Crucially, however, Shabtai managed to put his idea of the solution into practice. In 2006, he formed a team of 1,500 drivers, called FreeMap Israel, who like him traveled the country with hand-held GPS devices and mapped its roads on the move. In the course of four years, this crowd-sourcing community of ‘mappers’ produced a free Hebrew-language digital database of maps of Israel. The information thus delivered by hand-held GPS by drivers who had volunteered to be monitored by Shabtai’s team constitutes the material condition for constructing these epistemic media (See Figure 1. ‘Waze – Technological Momentum’).

Figure 1. ‘Waze technological momentum.’

The history of Moovit resembles that of Waze (See Figure 2. ‘Moovit – Technological Momentum’). The firm was initiated by two Israeli inventors-entrepreneurs: Nir Erez, a serial entrepreneur, and Yaron Evron, director of a leading Israeli public transit engineering firm. Moovit (formerly called Tranzmate) was launched in 2012 as a free data-driven app for iOS, Android and Web browsers to guide people in getting around town effectively and conveniently using any mode of transit. It combines data and information from public transit operators and authorities with live input from users. Moreover, it incorporates reports from a community of local volunteers called ‘mooviters,’ who map public transit information where it is not readily available.

Figure 2. ‘Moovit technological momentum.’

Unlike (vertical) printed maps which offer a top-down gaze, the navigations apps produced by volunteer mappers (drivers in the case of Waze, and travelers in the case of Moovit) use GPS systems that always situate the user at the center, and represent only a partial and situated information and knowledge of the space. By way of enacting the developed apps, the volunteer mappers of both Waze and Moovit have become, de facto, epistemic agents that took the right to the space away form other agents, traffic planners for example. Linking this insight to established legacies of radical geography surrounding spatial rights and justice (e.g., Lefebvre, 1996 [1967]; Cardullo & Kitchin, 2019), I argued that the contribution of volunteer mappers to special knowledge is political. A political implication of the creation and distribution of public knowledge about a space (in the context of Israel) involved, for example, disregarding Palestinian territories, like Palestinian villages that were destroyed by Israel in the so-called ‘Independent War’ in 1948 and in the ‘Six-days War’ in 1967 (Musih, & Fisher, 2021), or marking the occupied territories as ‘high risk’ areas (e.g., Quiquivix, 2014). The economic implications include presenting only places (like national parks or cities) and business (like restaurants and cinemas) that ‘interest’ the specific ‘mapper’. This marks an important shift to what can be termed the ‘privatization of space’, namely the accumulation of epistemic power in the hands of volunteer mappers (individual drivers/travelers) who, by way of enacting the developed apps, decide (and even determine) the (in)visibility of a place on the digital map.

A crucial role in the development of these two firms belongs to the Israeli economic and social climate. Israel is a world renowned ‘start-up nation’: it occupies the first place in the number of start-ups per capita, with 2,000 startups founded in the past decade, another 3,000 small and medium-sized startup and high-tech companies, 30 growth companies, 50 large technology companies, and 300 multinational corporations and R&D centers. In 2021 Israel ranked second in the world in R&D expenditure per capita. Israel invests about 4.1% of its GDP in R&D, while the average among the OECD stands at 2%. Due to the mandatory military service, many young people receive advanced technical training in the army. IDF Unit 8200, in particular, has become a prolific technology incubator, especially in the field of cybersecurity. With regards to navigation apps the military context becomes especially important as the representation of space often reflects security interests and biases. One example is eliminating from the map sensitive locations (like army bases). Another is reinforcing spatial segregations that discriminate the Palestinian people (e.g., Carraro, 2021).

Furthermore, the Israeli ecosystem has distinctive industrial norms, foremost among them a global mindset infused into everything a company and all of its employees do – the so-called ‘global-first’ market approach. These norms are inculcated and sustained by government practices like the founding of the Technology Incubator program in the early 1990s, and the establishment of a variety of support programs (Deloitte, 2021).

Particularly relevant to data-driven innovations like Waze and Moovit is the country’s antitrust regime on data-driven technologies. Israel does not have a clear-cut and uniform privacy policy regarding digital personal data, and hence companies can collect and aggregate personal data – mostly from drivers in the case of Waze, and from public transportation users in the case of Moovit. In Israel, as elsewhere, data-driven enterprises do not normally pay for the data and information they receive from individuals. That is, users get services (not money) in return for the personal data and information they provide. Wu (2015) aptly describes this pattern as ‘giving your customers stuff in exchange for their personal data, which you then use to make money.’ As will be demonstrated, Waze and Moovit collect individual data at no cost and ‘in return’ provide cartographic services. The data collected and processed are then given and/or sold to second and third parties.

Furthermore, in Israel, as elsewhere, almost no restrictions are in place regarding the utilization of aggerated data. Practically from the outset, Waze and later also Moovit were allowed to incorporate the collected data in the algorithmic systems they had developed and to use them in a variety of ways, including selling them. The nature of the ecosystem, both local and global, and the inventors’ personal qualities, mindset and determination formed a fertile ground for the second stage in the evolution of these technologies – commercialization.

Phase two: commercialization

This stage marks a transition whereby both Waze and Moovit as epistemic navigation/transportation media run by a community of volunteers became commercialized enterprises (See Figure 1. And Figure 2. above). As will be shown, the commercialization trend accelerated the ‘privatization of space’ process discussed above that relates to individual drivers (Waze) and travelers (Moovit), taking the right to the space away from other agents, particularly from public institutions like municipalities.

The commercialization of FreeMap Israel started in 2008. Together with co-inventor entrepreneurs Amir Shinar and Uri Levin, in 2009 Shabtai registered the company as Waze Mobile Ltd. Investors, both in and outside Israel, promptly recognized the potential of commodified information and knowledge produced by the company’s software using data and information volunteered by drivers. Thus, in 2010, Waze’s developers obtained $25 million, and in the following year an additional $30 million, from Israeli venture capital firms Magma and Vertex Ventures, and from the then nascent American venture capital firm Bluerun Ventures. These stakeholders provided money for further development, and thereby signaled to the public that experts had full confidence in the financial and technical sustainability of the innovation. By 2013 Waze numbered approximately 50 million global users.

The commercialization of Moovit as a for-profit data-driven platform began right upon its formation with the launching, in 2012, of the app called ‘Tranzmate.’ The firm’s economic potential was realized through major local and global investments, such that in early 2013 its founders raised $3.5 million in the first round of funding, and later obtained $28 million from Sequoia Capital, BRM Group, and Gemini Funds. In January 2015, the company raised $50 million in its Series-C funding round and was subsequently chosen as the official mobility partner for several sporting events and sports teams around the world; shortly thereafter, it gained momentum by wide sales of data-based mobility services.

As a vast repository of data from a large number of sources (individuals and public/commercial institutions), the company quickly became a major creator and disseminator of information and knowledge about public transportation, such as availability, routes, time-tables etc. In June 2017, Moovit announced a new tool for city authorities and transport agencies called ‘Moovit urban mobility analytics,’ which uses data and analytics on population movement to provide visual insights on public transport.

Having attracted multiple partners who deployed the company’s fast-developing tools and services, the company raised in February 2018 an additional $50 million. The funding was led by Intel Capital with the participation of former investors. In November 2018, Moovit entered into partnership with Microsoft, with the view of providing its public transit data to Azure Maps, and application programming interfaces (APIs) to developers. A year later, Moovit announced TimePro, a cloud-based GPS tool for transit agencies that apprizes users of bus arrivals in real time by displaying the information for all running vehicles on a web dashboard. In 2020, the app reached 720 million users and provided service in 100 countries.

To sum up, shortly after their inspection, Waze and Moovit established themselves as commercial platforms. In other words, they formed digital interfaces and utilized digital technologies which facilitate interactions between previously fragmented and unconnected individuals and institutions, making it possible for these end-users to extract value from the connections enabled by the platforms (Cusumano et al., 2019). More specifically, by collecting data from different complementors, and then analyzing and governing those data, both Waze and Moovit succeeded in offering platform users novel epistemic services. In practical terms these companies converted social interactions and economic transactions into products and services, turning themselves into necessary intermediaries that sit in the middle of other activities, serve as agents for capital extraction and socio-political supremacy by controlling access to asset, to services, and to physical (and imagined) locations (businesses, disputed territories etc.).

In the case of Waze, these include route suggestions and transportation information (like traffic jams) targeting individual drivers and institutions (like news organizations). The epistemic products and services provided by Moovit include information for urban travelers regarding public transportation (e.g., fastest routes to desired destinations, nearby bus or taxi stations, locations of available scooters and more). Institutions such as public transportation operators receive information about travelers’ movement patterns, trip planners aided by location sensors on public vehicles like buses and public vans, and more.

The establishment of Waze and Moovit as commercial data-driven platforms formed a fertile ground for the third stage in the evolution of these two firms – monetization.

Phase three: monetization

The third stage in the history of Waze and Moovit is monetization, namely, earning revenue from their epistemic products and services (See Figure 1 and Figure 2. above). This stage, like the previous one, is also characterized by a shift, as the two commercial data-driven platforms were turning into infrastructural platforms, in the sense of being vitally important, if not absolutely essential, to individuals’ and institutions’ participation in social, economic and political settings in ways that both interest them and serve their interests. Like traditional infrastructures, such as electrical or telecommunication networks, data-driven infrastructural platforms ultimately come to dominate others systems, shape the nature of their networks and determine the speed and direction of their involvement in everyday life (See, e.g., Plantin & Punathambekar, 2019).

It can be plausibly asserted that Waze and Moovit started monetizing when they received funding from local and global venture capitals (see above). Yet, the two companies’ definitive move toward monetization occurred when they started to earn revenues from the tools and service they had created.

The monetization of Waze began after the formation of a commercial firm, when it began to sell location data to advertizers (See Figure 1 above). Through an advertising scheme called ‘pin campaign,’ advertizers were offered to sponsor search results on Waze’s app. The details of this scheme published by Waze (2021) read:

Sponsored Search will allow you to display your brand logo alongside your business locations in the search results. Wazers [drivers who use Waze app] also have the opportunity to search using category terms such as “fuel,” “fast food,” or “coffee.” Businesses or locations that fall into these categories are eligible to appear in the search results at the optimal moment – when users are intently searching for their specific offering.

Apart from displaying various businesses on search results, Waze provides drivers, while on the move, with pop-up ads of sponsored sellers in nearby locations. This scheme benefits advertizers by allowing them indirect access to the firm’s huge repository of drivers’ profiles and their minute-by-minute location. On the basis of such data, advertizers are able to target drivers with personalized ads that are displayed on the driver’s app interface as search results and/or when the driver’s vehicle reaches the location of a sponsored business. The app was designed such that, upon tapping the ad, one receives navigation information that directs one to the location of the sponsoring business. It must be kept in mind, however, that only sponsoring businesses are displayed. Hence, the Waze-mediated knowledge fed to drivers regarding the ‘space,’ such as places of interests, businesses, and available routes, reflects the economic exchange between the company and advertizers, and does not necessarily correlate with ‘spatial reality.’ For example, on the route suggested by Waze, drivers will see only a coffee shop or a gas station that advertises with the company. Moreover, a business that pays more to Waze gets precedence on drivers’ search results even if it is further away than a similar business that pays less.

Although the actual payments to Waze come from advertizers/businesses, under the pin campaign model, it is the driver who is a de facto source of the company’s revenues. The reason is that the money Waze earns is derived from selling drivers’ personal data, as well as from maneuvering drivers’ movements to suit its paying customers. In a recent article, Han (2017) contends that today’s neoliberalism, which supports and incentivizes digital solutionism by for-profit companies, has tapped into, and is exploiting, the psychic realm – as opposed to exercising what Foucault termed as biopower through disciplining, punishing and perfecting the body. This critique echoes current scholarship on digital surveillance which demonstrates how data-driven entities embrace possibilities for control and behavioral modification in order to both ‘hypernudge’ (Yeung, 2017) individuals towards ‘better’ decisions, and surveil their inner moods and desires (e.g., Zuboff, 2019).

Moovit’s monetization practices resemble those of Waze (See Figure 1 above). Urban travelers who utilize the Moovit app have become a de facto source of the company’s revenues: Moovit earns money from selling travelers’ personal data, obtained free of charge, to third parties such as transportation providers, and as of 2021 also to advertizers. Analogically to Waze, Moovit’s commercial logic pursues the optimum for its commercial allies, hence the firm’s algorithm is designed to accommodate the interests of paying consumers (Kitchin & Dodge, 2011). Travelers are directed to providers of services such as electric scooters or taxis which collaborate with Moovit. Moreover, to the extent that its economic logic impels Moovit – as it also does Waze – to cater to individual users, the app is likely to direct a traveler to a route that is optimal for him or her rather than to one beneficial to the public.

These practices lend themselves to a broader critique, known as the ‘right to the city’ politics, promoted by opponents of neoliberalism (e.g., Sadowski, 2021). Henry Lefebvre (1996 [1967]), for example, saw the ideal city as one that grants its residents the right to participate fully in the production of urban space. Yet, as many writers on ‘smart urbanism’ and ‘platform urbanism’ now note, tech companies powered by corporate ecosystems such as Google-Android or Apple-iPhone are taking this right away from residents, as well as from public and private institutions (Cardullo & Kitchin, 2019; Sadowski, 2021). Unencumbered by legal restrictions and physical market boundaries, they establish, by means of their technologies, new forms of governmentality, disciplining, nudging and controlling inhabitants of ‘smart cities’.

Like traditional infrastructures, Waze and Moovit have achieved their infrastructural power by carefully choosing and implementing a set of practices, foremost among them, ‘embedment’ in other structures, social arrangements, and technologies (Star & Ruhleder, 1996). As shown above, from the outset, the apps were designed to be plugged into existing socio-technical arrangements, primarily internet systems comprised of internet equipment, internet connections, internet protocols, etc. Moreover, from the firms’ inception, the services they provide to both individuals and institutions have been based on massive data flow from multiple sources obtained by utilizing existing internet-based technologies, like sensors and mobile devices. Not less important are the means by which the epistemic services were designed to be disseminated to both individuals and institutions. With the increase in the popularity and accessibility of these devices and affordances, both individuals and institutions are now eager to avail themselves to the fullest of the epistemic tools and services supplied through them.

The means whereby Waze and Moovit distribute their products and services constitute an important source of their infrastructural power, by way of what is often termed ‘links with conventions of practice’ (Edwards et al., 2013). Because Waze’s and Moovit’s apps resemble the ones that are already available on mobile phones, particularly cartographic apps like Google maps, they were adopted easily by individuals and by institutions alike. Both technologies were ‘transparent to use’ (Star & Ruhleder, 1996), in the sense that the apps developed by the two firms need neither be reinvented each time, nor be assembled for each task. In principle, anyone with a smartphone or a Web browser can easily use the applications time after time.

The embedment in existing systems and transparency for use were crucial conditions for achieving infrastructural power. They also ensured the ‘scope of use,’ for, after receiving funding from national and global investors, both Waze and Moovit managed to establish themselves as global firms that serve millions of individuals as well as major public and commercial institutions around the world, all of which have become dependent of the service they provide.

Yet, a major development that secured the status of Waze and Moovit as infrastructures was their acquisition by two global titans (See Figure 1 above). In 2013, Waze was bought, for $966 million, by Google, which had already dominated the navigation market by means of its Google Map apps. Soon after its acquisition, the monetization of Waze picked up further momentum. In 2014, backed by Google, it launched the Connected Citizens Program (CCP) – a free, two-way data sharing program used by governments, departments of transportation, and municipalities for traffic analysis, road planning, and dispatching emergency workforce. On its website, the company explained (2021): ‘This partnership improved the quality of the Waze App [and] city planning, informed infrastructure decisions, and increased the efficiency of day-to-day operations.’ The city program was based on the transformation of data from public institutions that harvested it, sometimes focally, in the name of public interest, to a commodity, utilizing it for profit making. This collaboration, anchored in commodification of public data, promoted monetization of Waze: Gaining access to huge amounts of data from public institutions increased the reliability of information it supplied to users. As a result, Waze became a leading knowledge agent, and thereby increased its economic value.

Waze has further bolstered its position as a leading infrastructure that has tapped into, and is exploiting, both the physical and the psychic realm (Han, 2017) by collaborating with commercial institutions, for example, audio partners. On its platforms, it started advertising brands targeting drivers with audio applications. Under this alliance, drivers became the source of revenue for Waze’s commercial allies through purchasing and utilizing their outlets, but also for Waze by attracting more paying partners and by supplying data regarding their preferences, habits etc. To date, at least some of the information on music that Waze drivers have been exposed to has undoubtedly been determined by the commercial relationship between Waze and businesses collaborating with it. Indeed, the latter have received from Waze valuable information about drivers’ needs, enabling them to personalize their content and services. Recall that Waze is not obligated to expose the nature of the data it collects, the insights it obtains from analyzing them, or the uses to which they are put. Under such conditions, nothing prevents Waze from using data accrued from audio partners to serve its commercial interests, e.g., directing drivers who prefer a certain kind of music to a certain location, such as a paying bar, or offering shorter routes to drivers who consume the tools, services or products of paying audio companies.

Partnerships with commercial allies increase Waze’s data repository, and by implication its economic and social power. Yet, an important source of power is the firm’s ability to create and sustain information asymmetry regarding its modus operandi. Waze does not allow its partners access to its algorithmic systems, or make transparent processes of data analyses.

Moovit followed suit (See Figure 2. above). Fueled by torrents of data and information from individuals and institutions, Moovit’s monetization picked up momentum when, in 2020, the company was bought by Intel for 840 million dollars. Thus, Intel secured access to Moovit’s big data transportation repository, and to the firm’s vast partner network which includes titans like Microsoft and TomTom. But the company that has benefited the most from the vast amount of data Moovit has collected since its foundation in 2012 is Mobileye – an autonomous vehicle hardware-manufacturing startup that Intel acquired in 2017, and that is now its sister company. On the day of the acquisition, Intel announced that ‘Mobileye [would] be able to use Moovit’s large proprietary transportation dataset to optimize predictive technologies based on customer demand and traffic patterns’ (Intel Newsroom, 2020).

The monetization process accelerated when, in 2020, Moovit won the tender for digitized payment for transport through a mobile app. The system, which allows transport users to dispense with bus pass cards, applies automatically all relevant discounts and is subject to a daily cap. To implement this scheme, Moovit partnered with smart parking operator Pango Pay and Israel’s biggest bank – Bank Hapoalim. Moovit’s executives have conceded that the partnership will allow the firm to increase its economic value, by capitalizing on the big-data repository in the hands of the new allies to sell services to designated individuals (Shulman, 2020). In view of the shadowy nature of Moovit’s modus operandi, such stratagems are difficult, if not altogether impossible, to detect, or evaluate.

Having benefited from obtaining a huge amount of data from different sources on and via the platform, and with the support of their respective mother firms Google and Intel, Waze and Moovit monetized their epistemic services and thereby managed to establish themselves as infrastructural platforms. Akin to traditional infrastructures, they have attained the scale and social utility that renders them vitally important, if not absolutely essential, to millions of individuals and to major institutions that have become dependent on the epistemic products and services they provide. This powerful position is arguably sustainable in the long run, since both firms are increasingly gaining control over huge amounts of data that constitute the raw martial of their epistemic services in the present, and probably in the future. Metaphorically speaking, the data accumulated by Waze, Moovit and other SKI are the roads, railways and pipes that form the foundation on which infrastructures are commonly established and rest. However, SKI differ fundamentally from traditional infrastructures like transportation or water supply in that they are profit driven and are not bound by considerations of public interest. Furthermore, the nature of the data they collect, the use they put them to at present, their future intentions in this regard, and their epistemic practices are obscure, and hence not open to public judgment or critique.

Discussion and concluding remarks

Through a three-stage evolutionary process, Waze and Moovit have matured into infrastructures producing and disseminating information and knowledge regarding transportation, navigation and cartography on the basis of the massive amount of data and information they constantly collect (usually free of charge) from different sources. The scope of these two enterprises spans sophisticated trip planning, apprizing users of the state of road networks, assisting city planners, informing law enforcement bodies, supporting the automated vehicle revolution and more.

The stellar performance of Waze and Moovit in advancing the short-term interests of end users is obvious: Individuals and institutions – private and public, small and large – get massive and (usually) accurate information and knowledge as needed. These capabilities are rooted in the infrastructural nature of these platforms: Waze and Moovit lower their average costs in the long term through exploiting the economy of scale, and their magnitude outweighs their productive and allocative inefficiency. This structure is also conducive to innovation. The firms’ supernormal profit is invested into improving technology and dynamic efficiency. Yet, this unconditional and universal acceptance obscures the deficiencies of these companies’ structure and bearings. One generic explanation for this blindness is that positive outcomes are easy to detect and measure. Another explanation relates to these companies’ shadowy modus operandi. The metadata standards and ontologies that govern such infrastructures are hidden and often inaccessible to outsiders – a state of affairs permitted and even supported by the current regulatory regime. Such a black-box tactic, which SKI like Waze and Moovit inaugurated and have successfully sustained, makes it almost impossible to assess their conduct. Yet, through such concealment, SKI effectively control users’ perceptions, experiences, and utilization of space – and this, in itself, is worrying, all the gains notwithstanding.

On the economic level, the problem lies in that dominant commercial infrastructural platforms dictate what kind of information and knowledge will be produced, who will get access to to these commodities, and on what terms. Such a set-up of ownership of socio-economic interactions and the epistemic services that emerge from them, distorts the ecosystem within which they operate by prioritizing some stakeholders over others, exacerbating conflicts of interest between the actors involved, impairing competition between providers of tools and services, and creating bottlenecks and/or entry barriers. These and similar outcomes are bound not only to compromise the freedom of trade and competition, but also to impinge on individuals’ autonomy in choosing tools and service providers, and with this, the information and knowledge they may accurize and utilize. Related concerns are SKI’s exploiting personal and public data and damaging the bargaining power of users – both institutions and individuals (e.g., Zuboff, 2019).

On a social level, collaborations between profit-driven SKI and public institutions such as governments and municipalities with a view to strengthening these companies’ infrastructural platforms change the power dynamic between public and commercial entities and undermine the influence of public institutions over the production and consumption of information and knowledge (e.g., Kitchin & Dodge, 2011). As demonstrated above, Waze, Moovit and other SKI produce information and knowledge that mainly serve the interests of paying partners and clients, such as advertizers, businesses, and transportation operators, as well as of the individual consumer. More broadly, the dependency on the services SKI provide, their economic superiority, and position as market makers, marks a fundamental transformation in the sovereignty of space, as SKI like Moovit and Waze, move beyond treating spaces merely as places to extract profit from, but also as resources to exercise dominion over (Sadowski, 2021).

On a more technical level, SKI construct and operate massive amounts of data, individual as well as institutional. In consequence, a breakdown, or even a technical failure, would disrupt all the services that depend on them – including business, government, labor, and everyday commuting.

Studies on the history of information technologies have cautioned against the dangers posed by traditional infrastructural platforms that set the terms of a marketplace within which information and knowledge are produced and distributed. SKI like Waze and Moovit control a large and increasingly growing number of arenas and constantly encroach into new lines of business. The dependency of both individuals and institutions on the services these two companies produce and distribute is getting deeper and deeper with time. In view of these tendencies, a critical examination of these enterprises – their characteristics, as well as those of the environment that supports and incentives their structure and conduct – is an urgent need. Exploring these issues would constitute an important step in appraising the power of these entities, whose structure and bearings pose danger which we feel and dread but only just starting to comprehend.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Tamar Ashuri

Tamar Ashuri (PhD London School of Economics) is a faculty member at the department of communication at Tel Aviv University. With a keen interest in political economy of media technologies, her current research primarily delves into the development of data-driven platforms.