Abstract
Deception is a pervasive feature of the online marketplace: from phone calls by fake tech support workers at Microsoft, to fraudulent emails asking for advance fee payment, and fake postings for jobs on employment platforms. Building off interdisciplinary discussions within science and technology studies (STS), this special issue expands research on the underside, illicit, and irregular forms of digital behavior. Our focus is on how scams, fakes, and frauds are embedded in the digital economy. In particular, we look at the institutions shaping online scams, the labor involved in performing and/or navigating them, and the role of platforms in hosting them.
Introduction
Deception is a pervasive feature of the online marketplace: from phone calls by fake tech support workers at Microsoft, to fraudulent emails asking for advance fee payment, and fake postings for jobs on employment platforms. The US government received 2.8 million reports of fraud in 2021, with reported losses of $5.8 billion (Federal Trade Commission, 2022). Imposter scams accounted for $2.3 billion of that. More often than not, marginalized groups bear the brunt of this deception. Organizations are facing pressure to manage this chaos. Info security is on the list of fastest growing occupations in the United States (US Bureau of Labor Statistics, 2017).
This special issue examines how scams, fakes, and frauds are embedded in the digital economy. The impetus comes from my research on outsourced call centers. I had been writing since the 2000s about how faking arose as an unusual job requirement in global information and communications technology (ICT) services. Indian call center workers were being asked—while doing mundane tasks over the phone, like selling products or providing customer service—to pretend they were American (Poster, 2007). Then, a decade later, there was a twist. This trend was reappropriated and expanded by a shadow sector in India, which was now asking workers to pose as Internal Revenue Service (IRS) and Social Security officials for the US government. The simple of act of manufacturing identity had taken a deep turn into, or at least had become the conduit for, an entire scam industry of fake call centers (Poster, 2019a). I was hooked.
This raised many wider questions: what is the origin of fakery with employment? Why do legit industries turn to scams? What are the myriad ways that technologies are now used for scams in online employment? Given that so many online institutions are now mediating employment, how do scams intercede in the process of advertising jobs, matching jobs to employers, facilitating offline work, and conducting work itself online? What are the ways that scams are crossing over (and diversifying) from formal employment to the gig economy? More broadly, how has the expansion of the digital economy itself fostered or enabled the development of fraud?
These are some of the topics that we sought to address at the 2019 meetings of the Society for the Social Study of Science in New Orleans in a panel of the same title as this special issue. Building off interdisciplinary discussions within science and technology studies (STS), we wanted to elaborate research on the underside, illicit, and irregular forms of digital behavior. Continuing that discussion here, we take a socio-technical approach that considers the interplay of governance, policy, design decisions, and the behavior of communities, with the technical systems themselves. Our interest is in expanding literatures on fakes, frauds, and scams to focus on spheres of employment, entrepreneurship, finance, and ecommerce. We hope to highlight the political economies of deception and their implications. In particular, we look at the institutions shaping online scams, the labor involved in performing and/or navigating them, and the role of platforms in hosting them.
Articles here spotlight how scams are occurring across a wide range of online spaces. Some authors examine platforms for employment like Indeed.com, Care.com, and Amazon Mechanical Turk. Some look at gig economy apps like Uber and Lyft. Others highlight social media platforms like YouTube, Facebook, Instagram, and TikTok, which profit from the trade in real and fake identities of users. Blogging sites for anti-fan communities are examined for their influence as gatekeepers over the authenticity of online entrepreneurs. Financial sites are examined for their role in mediating practices of cryptocurrency markets. The cases are largely based in the United States, but we provide glimpses of transnational variations with attention to dynamics in places like Brazil.
For the most part, we’re interested in understanding these dynamics from the viewpoint of workers, online commentators, and users. The aim is to document how they understand, experience, respond to, resist, and even participate in these scams. Such groups include social media influencers, vloggers and bloggers, online investors, microworkers, nannies and cleaners, drivers, and delivery workers. The targets of scams in digital economies are oftentimes workers, we will note, especially those who are women, people of color, and in the global south. This also includes vulnerable groups of social media platform users, such as children and those who are under-educated about online privacy.
In-depth and firsthand ethnographic materials provide a glimpse into the many aspects of how scams, fakes, and frauds are socially constructed. Analyses consider how systems of class, gender, and nation shape the dynamics. They consider historical precedents for contemporary forms of online fraud. They discuss the institutional practices that both support and limit online scamming, by actors like states, legal systems, and firms. Indeed, we see how platforms at times enable these practices but also implement various kinds of measures to restrict them.
Before turning to the articles, I first lay out the core concepts of this special issue. These articles make important interventions towards reconceptualizing scams, fakes, and frauds. Instead of resting on individualized frameworks that point to a lone criminal or bad actor, these articles centralize the role of institutional dynamics and collective behaviors. They direct us to contextual factors and socio-technical formations, and provide us with a new language for talking about scams. Critically, they reveal unexpected dynamics and raise important questions about who’s involved and how to address it.
Revisiting the definitions
Three interrelated concepts, with slightly different emphases, are the focus of our discussion. Scams are generally thought of as particular events involving an act of trickery or dishonesty for the purpose of making money or taking something valuable (Cambridge English Dictionary, 2022). Fraud is often seen as a broader term for perversions of the truth and the use of misrepresentation as a tool for financial gain (Merriam-Webster, 2022). Fakery overlaps with scams and fraud as a mechanism for achieving those things, in that people pretend to be who they are not, or present false objects that look like the real thing.
At face value, these sound like straightforward processes. Likewise, the associated law and order narratives, which are so pervasive in popular culture, are often premised on individualized frameworks of how scams happen and what implications they bring. Yet, our analyses reveal many complications of how scams operate in online environments for employment, earning, and finance. Here are some of the premises they revisit and question.
What is the goal?
A core assumption about scams is an end goal of fleecing people’s money. However, our authors show that, in the context of digital economies, the issue can be more varied. Maybe the aim is encroaching on privacy to acquire user data. Maybe it is boosting online ratings, reviews, and traffic. Maybe it is evading regulations on the use of artificial intelligence in online spaces. Maybe it is corporate image-washing, and hiding globalized systems of labor, as in the case of outsourcing. Maybe it is gaining political influence, through things like troll farms. Of course, all of these things may be intermediate steps for other outcomes of financial gain. Nonetheless, they signal how the immediate purpose may not necessarily be a direct payout.
Who are the participants?
A typical narrative about the participants is that they include a con and a mark. In this dyadic relationship, there is a direct interaction between two actors—a single perpetrator and a single victim. Authors here contest this idea and also provide new language to describe these events. Here are some of the premises they challenge:
That it is an activity done by individuals
Our authors show how online scams can involve groups of people working together—sometimes an entire community. Rather than individual scams, these are “networked scams” [Swartz]. We see collectivities of online actors who participate in the dynamism of a scam. In other words, even if they didn’t start it, they help it to grow and perpetuate. Likewise, we see “platform scams” that are embedded in online organizations [McNealy, Grohmann, et al]. An important consequence of this institutionalization is a magnification of the number of people who are affected in online scams. Our authors show how online fraud can be large scale: rather than just affecting an individual or even a group, it can affect millions.
That the con and the mark are mutually exclusive categories
In some instances, there are so many people involved in a fraud event that the line between the actors becomes blurred. The difference between the criminal and the target dissipates in situations like crypto markets and clickfarms [Swartz, Grohmann, et al]. Here, everyone becomes a perpetrator just by joining an online community where scamming is the norm or where scamming is a precondition for entry.
By extension, the line between scams and authenticity can similarly become blurred. This happens in the world of social media entrepreneurs [Lewis and Christin]. For drama channel creators, and their pressures to generate viewership and advertising, the performance of realness is more important than the realness itself.
That humans are involved at all
Several authors point to patterns in which the scam itself is carried out by a technical system. In some cases, this happens with little or no direct human contact, and at scale [McNealy]. In other cases, technical systems set the parameters and thus direct the interfaces within which workers, consumers, and users experience fraud. Authors uncover many kinds of digital infrastructures for scamming, including algorithms, data collection systems, and automated management [Ticona]. Additional devices and online capacities enable everyday actors like workers to engage in faking and scams. These include bots, artificial intelligence, and systems for generating fake names and facial images [Grohmann, et al].
What are the features and sources?
Scams, fakes, and frauds are often identified by their features and how they operate. However, our authors question whether those indicators are wide enough in scope. More fundamentally, they question whether such incidents are outliers or in fact the core of our online institutions.
Overt versus hidden
A common assumption is that scams involve overt deception and fraud. Social engineering is a typical example: such scams involve a one-on-one exchange in which the victim hears the voice of the scammer on the phone or receives their personal texts and emails. Although a victim may not be aware of the scam while it is in progress, s/he will still have evidence of it later. In this way, the act itself and the existence of the perpetrator are both highly apparent.
In this special issue, however, we see a much more nuanced process of scams. The very occurrence or process of the fraud maybe be eclipsed. Some patterns are normalized to such an extent that the mechanisms of luring people in can look routine and harmless. It may happen through an ad on a job listing site (Gray and Suri, 2018) [Ticona, Ravanelle, et al] or a registration form on a platform [McNealy]. Scams may be hidden through a layering of steps: a job may start out seeming legitimate, but then lead to a deeper scam – and another job – that is illegitimate [Ravenelle, et al, Grohmann, et al].
Even more, frauds and fakes can be hard to detect because they may not happen through interactions at all. A victim may not experience any contact with a particular individual. Instead, these scams happen through platforms and their mechanisms. McNealy’s discussion of “deceptive design” highlights how algorithms behind the scenes are responsible for egregious forms of data theft against platform users.
A repeated theme in this special issue is that, rather than outright fraud, what platforms do is to create a misleading façade that contradicts their actual practices. This is apparent on sites like YouTube, for instance, as corporate narratives of inclusivity and openness directly oppose their selective policies for monetization and demonetization [Lewis and Christin]. It happens on platforms like Uber and AMT, which publicly advertise their gigs as high-earning and/or their practices as honest and beneficial for workers [Grohmann, et al]. However, workers discover quite the opposite after they’ve been lured onto those sites. Platforms put into place logistical and practical barriers for workers to achieve such a high level of rewards and earnings. These take the form of unfairness in surge pricing, blocked accounts, and failure to receive payments.
The outlier versus the rule
A related assumption to that above is that scams, fakes, and frauds are the outliers in the digital economy rather the rule [Swartz]. There’s a sense that fraud is infrequent or that only a small share of platform users are affected. By extension, a related premise is that institutions themselves are playing by the rules, while selected external agents (criminals, deviants, etc.) are entering those sites and then taking advantage of loopholes and weaknesses to commit fraud. They are “bad actors” in the sea of an otherwise well-behaving public [Ticona]. They are the clearly defined criminals who operate externally to a fair-operating system.
Through the many examples in this special issue, however, we see how platforms as organizations are in fact laying the groundwork for scams, fakes, and frauds. They are often allowing fraud to take place, either indirectly or directly. They may be failing to pay attention to what users are doing on their sites, and failing to respond once they know what’s going on.
Alternatively, the platforms may in fact be participating in the crafting, encouraging, and even mandating of scam behavior by their users [Grohmann, et al]. This happens for instance with clickfarms. These sites provide services to boost online presence and popularity, by hiring workers to click “likes” and “shares” on social media platforms. Such clickfarms are directing workers toward deceptive acts, like opening fake accounts and then hiring bots to amplify the activities they are already doing on social media sites. At a minimum, those platforms are steering workers to participate in fakery and cyborg identity management (Poster, 2019b). At worst, they are turning their workers into scammers.
In a similar way, social media platforms are incentivizing performances of fakery among their users [Lewis and Christin]. We learn from authors in this special issue how fakeness is a monetized activity on social media—particularly in reference to popular individuals like celebrities and influencers. Celebrities may intentionally construct and display fakeness to attract more viewership. Or, audiences may interpret celebrity behavior as being fake [Duffy, et al].
Either way, vloggers and bloggers respond with narrations and conversations about that fakeness. This may involve theatrics of uncovering the fakery (i.e. showing in detail how and why it is fake) as well as moral accusations of deception, fraud, and scams which are levied against those individuals. Visitors to these sites and channels participate through their comments, which contribute to dynamics of “policing authenticity.” All this increases audience metrics for vloggers and in turn their potential for accruing revenue on the platforms. Thus, whether you are being fake yourself or discussing someone else’s fakeness, content producers are making careers out of the spectacle of deceptive personas.
Something new versus historical groundings
From a wider viewpoint, our authors reflect on ways that scams are grounded in broader histories of capitalism, labor regimes, technology, and colonialism. Scams, fakes, and frauds may seem “new” because they are happening online in digital economy. But our authors show how they have been part of the early stages and building blocks of our social institutions. Nineteenth-century US capitalism operated basically as a scam, for instance, in that most speculations (however shaky) could turn a profit as long as people had “confidence” in them [Swartz].
Transnational relations, likewise, have set the stage for online labor systems that are taking advantage of workers. Platforms are building upon informal economies of labor which are, furthermore, much more prevalent in the global south than north. Historically, this work has been characterized by blatant forms of fraud through precarity, debt schemes, and so on. Now, these labor systems are being remodeled and repacked under the label of “gig work,” and those workers are being subject to scams through the platforms [Grohmann, et al].
Finally, long-standing effects of colonialism, combined with banking practices in the post-colonial era, are making state governments susceptible to online financial scams. Things like international debt programs have left states in the global south with devastated economies and political systems that are vulnerable to corruption and authoritarianism. Those very regimes (like Venezuela, Ecuador, and Iran) are turning to cryptocurrencies—with their propensity toward, and lack of oversight over, scam behaviors—as their state monetary systems. This underscores how scams are not just created through an insular online community or in isolated national contexts. Wider systems of global capitalism are fostering scams, fakes, and frauds as well.
Who gets to decide?
Authors here ask what is perhaps the most basic question: who has the authority to label something as a scam, fake, or fraud? These definitions are usually constructed in a top-down manner—by firms, employers, and the state. In the digital economy, this often means the platforms. Yet, their criteria and scope for determining what is a scam can be tied to their interests. A case in point is their agenda to counter collective action by workers. Uber, for instance, has called coordinated shutdowns by drivers (to trigger surge pricing) as “attempted fraud” [Grohmann, et al].
In response, our authors turn the tables to ask, “What if workers get to decide what was a scam?” And in doing so, what if they reversed the notion of who is scamming whom? Instead of simply members of the public scamming corporations, could it also be the opposite—that platforms are scamming workers and/or users? In this special issue, there are quotes from workers who state their views in exactly these terms [Grohmann, et al].
Such a perspective has other implications. It recasts how we understand scams that are developed by workers. Instead of being labeled a “crime,” worker strategies can at times be seen as direct responses and reciprocal actions to those of the platforms. Some authors argue that workers have few other choices. If they want to remain on gig platforms or maintain their living through them, workers must turn to scams as a survival mechanism [Grohmann, et al]. These “workaround” scams, in fact, become the solution or rational action by workers in the face of scams by platforms. Some authors, for this reason, describe worker actions as “scamming the scammers” or “counter-scams” [Ravenelle, et al].
Themes of scams as making a living on platforms are similarly reflected in the accounts of vloggers. Scams and fakery are go-to’s during times when social media content on their channels is otherwise lagging. If celebrities are not providing enough drama to boost metrics of viewership, vloggers manufacture fake feuds as a way to generate income. In such a light, worker scams can be interpreted as, or at least seen in the context of, entrepreneurial practices [Lewis and Christin].
How do we evaluate scams?
From the perspective of law enforcement and cybersecurity, a common approach is one of clear-cut solutions. Scammers are criminals and need to be caught. But articles in this special issue convey how the simple process of evaluating scams can be much more complicated and even problematic.
What do you do, for instance, when the very participants in digital economies see scams—not as something unethical or objectionable—but as part of the status quo and routine functioning of their industry? This has been the case in some crypto communities [Swartz]. Online investors justify their scamming behaviors as warranted and describe them as integral to certain financial markets. Or else, they categorize those scams as temporary, i.e., a necessary first-step in a long-term process. At the very least, this suggests that changing the system may be difficult when the participants themselves don’t see their behavior as deceptive.
In the wider STS literature, scholars have shown us how scams can be read in multiple ways—as criminality and exploitation, but also as managing and coping within broader systems of inequality. This is especially true in transnational contexts of global hierarchy. As Burrell (2008) notes, Ghanaian email scammers re-appropriate stereotypes from the global north to capture the attention of an otherwise disinterested consuming public. Brunton (2013) situates Nigerian “419” scams as an outgrowth of “failures of globalization.” Lewis (2020) documents how Jamaican lottery scammers frame their actions as “reparations” from an exploitative global north.
An important question is, then, when is a digital scam an unethical act versus a weapon of the weak (Brunton and Nissenbaum, 2015)? When is it fleecing the undeserved and marginalized, versus a tool to redress economic inequalities created by technical, financial, and global capitalism? Examples of the latter include ‘‘protest scams,” like when Yes Men activists posed as representatives of energy and chemical companies (Terranova, 2010), and when Anonymous hacked into financial systems (Coleman, 2014) for the purpose of returning funds to consumers who have been defrauded by corporations.
Such examples underscore how the framing of scams, fakes, and frauds is context-dependent and varied. The complicated layering of scamming practices may problematize the way we treat the issue and how we find solutions.
Outline of papers
Articles in this special issue focus on three types of online economies: employment platforms, social media platforms and forums, and cryptocurrency markets. Next, I discuss what each cluster of articles tells us about scams, fakes, and frauds.
Employment and gig economy platforms
Employment platforms are rife with scams, fraud, and fakery. Exploring a variety of job-related sites, our authors highlight how scams are carried out by third parties (i.e. neither the worker nor the employer), who get on those platforms to take advantage of workers. The articles also ask the deeper question of how platforms participate in scams themselves. This happens either indirectly, by allowing scams to take place in their digital spaces, or else directly by encouraging scammish behavior. The authors here provide a unique view of these experiences through the prism of workers who do platform work, and how they talk about, make meaning of, and respond to those scams.
Julia Ticona examines domestic, nanny, and in-home care workers on employment platforms, and how they encounter scams in the course of looking for postings. Because of this, workers have to do “scam detection labor” in vetting potential employers. This sometimes involves availing red flag procedures on the interface, which the employment platforms have borrowed from social media platforms. Ultimately, these flagging actions represent free labor for platforms, and do more to assuage the platform’s relations with external regulators than protect workers from scams. Platforms evade responsibility by passing on accountability to workers and telling them that it is their own job to protect themselves.
Elizabeth Watkins analyzes ridehail workers and the narratives about scams that they post in a forum for gig labor. In one small survey posted by a worker, a third of the respondents say they have encountered a scam. Some have experienced multiple scams. The typical scam is a fraudster posing as the ridehail platform (which is essentially their “employer”), asking for the worker’s login information to review their account. Or else, that person asks for their banking app login credentials to process a bonus. With this, they have tools to steal money from their account.
Through the forum and its discussions, workers share information about scams and create a sense of belonging within the community. Some of the posts are supportive of victims and informational in warning others on how to prevent future attacks. Other posts are divisive and mocking of the victims. Still, prowess in navigating scams becomes a source of inclusion and legitimacy. Several workers report intercepting and thwarting the scam while in progress.
Alexandrea Ravanelle, Erica Janko, and Ken Cai Kowalski examine job listing platforms (like Indeed and Google Jobs) and workers who apply to their positions. Their interviews with 200 precarious and gig workers who use these sites uncovers two types of scams. The first types are financial: fake credit checks for stealing identities; fake job listings (i.e., without an actual job attached) meant to elicit application fees; and overpayment schemes, in which workers are asked to deposit checks and send back the excess. The second type of scam involves listings for actual jobs (unlike the fake ones above), but are duplicitous in other ways. They divert the worker to secondary jobs with previously undisclosed and often illegal tasks. Such hidden jobs typically include reshipping fraud, check printing, and various kinds of sex-related work.
Workers use a repertoire of tools to detect scams. They look for red flags in things like repeated postings, undisclosed locations, requests for personal information (age, gender, ID), activities of modeling and nakedness, and bedroom based worksites. While some workers react by reporting scams to the platform, or even challenging the aggressors through payback and “scamming the scammer,” most workers tend to support the system.
Rafael Grohmann, Gabriel Pereira, Abel Guerra, Ludmila Costhek Abilio, Bruno Moreschi, and Amanda Jurno shed light on dynamics in Brazil through a study of workers on three kinds of employment platforms—ridehailing, microwork, and clickfarms. Some of those platforms are US-owned (like Uber and AmazonTurk), which Brazilians work on locally. Other platforms are Brazilian-owned (like GanharNoInsta, Dizu, and SigaSocial). The analysis covers several kinds of scam experiences, which the authors define as uncertainty and deception embedded in the systems of platform labor. One is when platforms scam workers through their policies of unfairness. The second is when workers, in response to those labor practices by platforms, scam them back by developing workarounds and collective actions. And the third is when platforms direct workers to scam other people, specifically users on social media platforms.
Social media forums and platforms
The second set of articles in this special issue examine scams, fakes, and frauds occurring on social media forums and platforms. These range in size from smaller online communities like hateblogs, to large-scale platforms like YouTube, Facebook, Instagram, and TikTok. Studies focus on the vloggers, channel hosts, bloggers, and forum commentators who participate in and work on those sites. Analyses reveal how, on one hand, fakeness becomes a spectacle of entertainment and in turn a source of earnings-generation for content producers. On the other hand, scams are built into the infrastructures of platforms as administrators seek to profit from the datafication of their users.
Rebecca Lewis and Angèle Christin study vloggers, specifically YouTube “drama channel” creators, who expose celebrities for scamming their audiences. Those celebrities are called out for not being authentic and lying to sell products. Celebrities are also critiqued for manufacturing fake feuds to drum up viewership and the financial gain it brings.
The authors offer a poignant analysis of how YouTube is implicated in this process—by incentivizing fake, fraud, and scam behaviors. Every bit of speech is monetized, and therefore performativity (even when it is fake, and perhaps because it is fake) is rewarded financially. YouTube puts this into practice, for instance, through various kinds of software systems: first through recommendation algorithms that boost content, and alternatively, through demonetization algorithms which exclude content from advertisements, and thus depress revenue for vloggers.
Brooke Erin Duffy, Kate Miltner, and Amanda Wahlstedt take us into the world of hatebloggers. These are online commentors who bring attention to fakeness and inauthenticity of influencers. They do this on specialized digital spaces for these discussions: “anti-fan” blogs and forums. The authors highlight how gender is a critical part of the dynamic on these sites. Not everyone is called for taking part in fakeness. Rather, the targets for these attacks are often women.
Female influencers experience heightened scrutiny by online commentators, particularly regarding how much they are staying with the boundaries of acceptable femininity versus straying from it. This is evident in posts about beauty, career, and relationships. Women are critiqued for things like photoshopping their images and showcasing their children to earn money. Likewise, popular bloggers and social media celebrities are disparaged for taking part in “fake careers” and using their sexuality or femininity as a tool for profit online.
This analysis has much to say about who wins and loses from the spectacle surrounding fakeness. It urges skepticism in public calls for “truth and authenticity” and assumptions that such activities are universally warranted. Instead, we see a selective process in which some online actors are given latitude to become digital entrepreneurs, while others are policed through vicious labels and accusations of fraud. It also underscores the linkage between digital careers and patriarchy.
Jasmine E McNealy illuminates the ways that social media platforms enact fraudulent behaviors toward the public through their interfaces, policies, and legal structures. They do this to induce users to hand over their personal data, which the platforms can subsequently sell to third parties and accrue revenue. In a revealing analysis, McNealy shows how platforms like YouTube and Facebook operate in ways that mirror the common scam of phishing. When this is done by individuals, a phisher will do things like recruiting their subjects by exploiting their trust, encouraging them to disclose personal information, and then hiding what they are doing to prevent informed decision-making. They may do this by presenting images, names, and URLs that mimic familiar things—like popular brands.
In “organizational phishing,” as McNealy terms it, the same fundamentals occur. However, platforms use alternative methods to manipulate consent: dark design and interactive tools (like registration forms) for exploiting familiar habits and building trust; attention-getting features (like videos) to distract users from data collection processes; and obtuse language (in things like terms of service) for masking what they are doing with personal information. The consequences of organizational phishing are far-reaching. This is in part because they are happening on a far greater scale. But in addition, with targeted advertising and automated practices, social media platforms are able to gather massive amounts of data and then sell this to other institutions which use it to further entrench inequalities.
Based on filings of the Federal Trade Commission in 2019 and 2020, McNealy grounds her analysis in legal policies and systems. She shows how at least some agencies of the US government are aware of the harm posed by these platforms and the need to regulate deceptive design. However, she also critiques these rulings as insufficient. More needs to be done in terms of comprehensive legislation on privacy and data protection.
Financial industries
The third arena of the digital economy addressed in this special issue is in crypto and financial industries. Online financial industries are especially unregulated and therefore have become sites where scams, fakes, and frauds are thriving.
Lana Swartz examines these dynamics through the example of the Initial Coin Offering (ICO) Bubble of 2017. During this boom for companies producing blockchain technology and cryptographic tokens, scams were rampant: 78% by one estimate. These were collective activities, promoted by a community of investors. In what Swartz calls “network scams,” two types of fraudulent activities took place. One was an exit scam, which was practiced by the ICO firms. This was a take-the-money-and-run tactic, whereby entrepreneurs would receive funds from investors and then fail to build the product. The second was a pump and dump scam, this time practiced by investors. They would buy an asset at low price, hype it on social media to raise its value, and then sell it off in a practice that would deplete the value for others. Sometimes this was done repeatedly and in cycles, representing what Swartz calls “coordinat[ed] market manipulation.” As these collective events are so integral to certain crypto markets, they “constitute” the digital economy and how define how it operates.
On the whole, articles in this volume urge us to reassess how we think scams, fakes, and frauds. They suggest that such practices may be embedded more firmly in social institutions and throughout our digital economies than we have previously considered.
Aside from what’s presented here, there are many additional stories and themes that these papers offer, and I invite readers to a follow-up piece that reflects on their important implications (Poster, 2022). This includes factors prompting the rise in scams, such as transnational networks and infrastructures for outsourcing, and digital industries organized entirely around selling or generating fakeness. It includes the range of technologies used in scams, from simple things like phone jacks to advanced systems like artificial intelligence and bots. It includes how digital identity management is used in the operations of scams, both in terms enabling transformation of online personas (masking) and in terms of detecting and outing the deceptive behavior of others (uncloaking). Critically, this analysis discusses how workers make meaning out of scams and oppose them collectively.It reviews what to do next: how platforms are instituting governance practices to address scams, and how state agencies are developing policies to reduce deception in the online economy.
Footnotes
Acknowledgements
Many thanks to Kiran Mirchandani for helping to inspire my exploration of this topic, based on scams we were seeing in our research on global call centers, and to Julia Ticona who helped in drafting the original conference announcement that lead to this volume. Formative ideas were presented in 2019 at the Society for Social Studies of Science meetings, and in 2022 at Technologies of Deception, Yale University, and California Dreaming: Regulating the Gig Economy, University of the Pacific.
Author’s note
Names in brackets are authors of the articles in this special issue.
Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.
