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Record W3108590730 · doi:10.5204/mcj.2726

A Flattering Robopocalypse

2020· article· en· W3108590730 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueM/C Journal · 2020
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

RACHAEL. It seems you feel our work is not a benefit to the public.DECKARD. Replicants are like any other machine. They're either a benefit or a hazard. If they're a benefit it's not my problem.RACHAEL. May I ask you a personal question?DECKARD. Yes.RACHAEL. Have you every retired a human by mistake? (Scott 17:30) CAPTCHAs (henceforth "captchas") are commonplace on today's Internet. Their purpose seems clear: block malicious software, allow human users to pass. But as much as they exclude spambots, captchas often exclude humans with visual and other disabilities (Dzieza; W3C Working Group). Worse yet, more and more advanced captcha-breaking technology has resulted in more and more challenging captchas, raising the barrier between online services and those who would access them. In the words of inclusive design advocate Robin Christopherson, "CAPTCHAs are evil". In this essay I describe how the captcha industry implements a posthuman process that speculative fiction has gestured toward but not grasped. The hostile posthumanity of captcha is not just a technical problem, nor just a problem of usability or access. Rather, captchas convey a design philosophy that asks humans to prove themselves by performing well at disembodied games. This philosophy has its roots in the Turing Test itself, whose terms guide speculation away from the real problems that today's authentication systems present. Drawing the concept of "procedurality" from game studies, I argue that, despite a design goal of separating machines and humans to the benefit of the latter, captchas actually and ironically produce an arms race in which humans have a systematic and increasing disadvantage. This arms race results from the Turing Test's equivocation between human and machine bodies, an assumption whose influence I identify in popular film, science fiction literature, and captcha design discourse. The Captcha Industry and Its Side-Effects Exclusion is an essential function of every cybersecurity system. From denial-of-service attacks to data theft, toxic automated entities constantly seek admission to services they would damage. To remain functional and accessible, Websites need security systems to keep out "abusive agents" (Shet). In cybersecurity, the term "user authentication" refers to the process of distinguishing between abusive agents and welcome users (Jeng et al.). Of the many available authentication techniques, CAPTCHA, "Completely Automated Public Turing test[s] to tell Computers and Humans Apart" (Von Ahn et al. 1465), is one of the most iconic. Although some captchas display a simple checkbox beside a disclaimer to the effect that "I am not a robot" (Shet), these frequently give way to more difficult alternatives: perception tests (fig. 1). Test captchas may show sequences of distorted letters, which a user is supposed to recognise and then type in (Godfrey). Others effectively digitize a game of "I Spy": an image appears, with an instruction to select the parts of it that show a specific type of object (Zhu et al.). A newer type of captcha involves icons rotated upside-down or sideways, the task being to right them (Gossweiler et al.). These latter developments show the influence of gamification (Kani and Nishigaki; Kumar et al.), the design trend where game-like elements figure in serious tasks. Fig. 1: A series of captchas followed by multifactor authentication as a "quick security check" during the author's suspicious attempt to access LinkedIn over a Virtual Private Network Gamified captchas, in using tests of ability to tell humans from computers, invite three problems, of which only the first has received focussed critical attention. I discuss each briefly below, and at greater length in subsequent sections. First, as many commentators have pointed out (W3C Working Group), captchas can accidentally categorise real humans as nonhumans—a technical problem that becomes more likely as captcha-breaking technologies improve (e.g. Tam et al.; Brown et al.). Indeed, the design and breaking of captchas has become an almost self-sustaining subfield in computer science, as researchers review extant captchas, publish methods for breaking them, and publish further captcha designs (e.g. Weng et al.). Such research fuels an industry of captcha-solving services (fig. 2), of which some use automated techniques, and some are "human-powered", employing groups of humans to complete large numbers of captchas, thus clearing the way for automated incursions (Motoyama et al. 2). Captchas now face the quixotic task of using ability tests to distinguish legitimate users from abusers with similar abilities. Fig. 2: Captcha production and captcha breaking: a feedback loop Second, gamified captchas import the feelings of games. When they defeat a real human, the human seems not to have encountered the failure state of an automated procedure, but rather to have lost, or given up on, a game. The same frame of "gameful"-ness (McGonigal, under "Happiness Hacking") or "gameful work" (under "The Rise of the Happiness Engineers"), supposed to flatter users with a feeling of reward or satisfaction when they complete a challenge, has a different effect in the event of defeat. Gamefulness shifts the fault from procedure to human, suggesting, for the latter, the shameful status of loser. Third, like games, gamified captchas promote a particular strain of logic. Just as other forms of media can be powerful venues for purveying stereotypes, so are gamified captchas, in this case conveying the notion that ability is a legitimate means, not only of apportioning privilege, but of humanising and dehumanising. Humanity thus appears as a status earned, and disability appears not as a stigma, nor an occurrence, but an essence. The latter two problems emerge because the captcha reveals, propagates and naturalises an ideology through mechanised procedures. Below I invoke the concept of "procedural rhetoric" to critique the disembodied notion of humanity that underlies both the original Turing Test and the "Completely Automated Public Turing test." Both tests, I argue, ultimately play to the disadvantage of their human participants. Rhetorical Games, Procedural Rhetoric When videogame studies emerged as an academic field in the early 2000s, once of its first tasks was to legitimise games relative to other types of artefact, especially literary texts (Eskelinen; Aarseth). Scholars sought a framework for discussing how video games, like other more venerable media, can express ideas (Weise). Janet Murray and Ian Bogost looked to the notion of procedure, devising the concepts of "procedurality" (Bogost 3), "procedural authorship" (Murray 171), and "procedural rhetoric" (Bogost 1). From a proceduralist perspective, a videogame is both an object and a medium for inscribing processes. Those processes have two basic types: procedures the game's developers have authored, which script the behaviour of the game as a computer program; and procedures human players respond with, the "operational logic" of gameplay (Bogost 13). Procedurality's two types of procedure, the computerised and the human, have a kind of call-and-response relationship, where the behaviour of the machine calls upon players to respond with their own behaviour patterns. Games thus train their players. Through the training that is play, players acquire habits they bring to other contexts, giving videogames the power not only to express ideas but "disrupt and change fundamental attitudes and beliefs about the world, leading to potentially significant long-term social change" (Bogost ix). That social change can be positive (McGonigal), or it can involve "dark patterns", cases where game procedures provoke and exploit harmful behaviours (Zagal et al.). For example, embedded in many game paradigms is the procedural rhetoric of "toxic meritocracy" (Paul 66), where players earn rewards, status and personal improvement by overcoming challenges, and, especially, excelling where others fail. While meritocracy may seem logical within a strictly competitive arena, its effect in a broader cultural context is to legitimise privileges as the spoils of victory, and maltreatment as the just result of defeat. As game design has influenced other fields, so too has procedurality's applicability expanded. Gamification, "the use of game design elements in non-game contexts" (Deterding et al. 9), is a popular trend in which designers seek to imbue diverse tasks with some of the enjoyment of playing a game (10). Gamification discourse has drawn heavily upon Mihaly Csikszentmihalyi's "positive psychology" (Seligman and Csikszentmihalyi), and especially the speculative psychology of flow (Csikszentmihalyi 51), which promise enormously broad benefits for individuals acting in the "flow state" that challenging play supposedly promotes (75). Gamification has become a celebrated cause, advocated by a group of scholars and designers Sebastian Deterding calls the "Californian league of gamification evangelists" (120), before becoming an object of critical scrutiny (Fuchs et al.). Where gamification goes, it brings its dark patterns with it. In gamified user authentication (Kroeze and Olivier), and particularly gamified captcha, there occurs an intersection of deceptively difficult games, real-world stakes, and users whose differences go often ignored. The Disembodied Arms Race In captcha design research, the concept of disability occurs under the broader umbrella of usability. Usability studies emphasise the fact that some technology pieces are easier to access than others (Yan and El Ahmad). Disability studies, in contrast, emphasises the fact that different users have different capacities to overcome access barriers. Ability is contextual, an intersection of usability and disability, use case and user (Reynolds 443). When used as an index of humanness, ability yields illusive results. In Posthuman Knowledge, Rosi Braidotti begins her co

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.079
GPT teacher head0.362
Teacher spread0.283 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it