Timothy Graham
Epistemic Infrastructure At 13:07 on 23 April 2013, the Associated Press (AP) tweeted: “Breaking: Two Explosions in the White House and Barack Obama is Injured”. Within seconds, automated trading systems detected the news. The Dow Jones dropped 143 points. The S&P (Standard & Poor’s) 500 lost $136.5 billion in market value. Six minutes later, everything returned to normal. The tweet was fake – the AP account had been hacked by the Syrian Electronic Army. The hack was a security failure. But the market’s reaction revealed something larger: by 2013, Twitter had become the world’s epistemic infrastructure for breaking news – the system through which claims about current events circulated, were attributed to authoritative sources, and thereby gained credibility. Markets monitored it. Governments issued official statements through it. Journalists treated it as a primary source. The market panicked not because of a blue checkmark but because the tweet appeared to come from the Associated Press – one of the most trusted news organisations on Earth. The verification badge confirmed identity – this really is AP – but on infrastructure this central, identity authentication became inseparable from epistemic authority. To be verified on Twitter was to have your claims amplified through the world’s most consequential channel for breaking news. This article examines what happened when a platform that positioned users in a reportorial posture became a global infrastructure through which all manner of claims flowed. Twitter’s central prompt – originally “What are you doing?”, changed to “What’s Happening?” in November 2009 (Burgess and Baym) – oriented users as witnesses to reality, whether the reality of personal experience or of public events. The prompt presupposed a relationship between speaker and world: you have encountered something, experienced something, and you are reporting it. This framing enacted what John Durham Peters identifies as the discursive structure of witnessing – the triangulation of presence, testimony, and authority that grounds a speaker’s claim in their relationship to the real (Peters). Yet as Zizi Papacharissi has shown, platforms like Twitter generate affective publics in which personal sentiment and public discourse flow through the same channels; “What’s Happening?” invited both registers, but always within an implicit orientation toward correspondence between utterance and world (Papacharissi). Empirical assertions, political interpretations, shitposts, contested narratives, normative arguments: they all moved through the same system, governed by the same design features, sorted by the same engagement metrics. The problems that followed stem not from a betrayal of the platform’s stated purpose, but from a mismatch between the epistemic posture the infrastructure assumed or imagined and the epistemic plurality of the discourse it came to carry. A note on terminology: I use “epistemic infrastructure” to denote the sociotechnical systems through which claims circulate, credibility is conferred, and validation occurs. This follows Susan Leigh Star’s understanding of infrastructure as the often-invisible arrangements that enable and constrain knowledge production. I reserve “truth” for the property of propositions – what makes a claim true – and distinguish this from “truth-determination”, the epistemic processes through which we establish whether claims possess that property. This distinction matters because, as I will argue, the failures of platforms like Twitter are primarily epistemic failures – failures of verification procedures – rather than failures concerning truth itself. Truth Markets and Truth-Determination In 2015, communication scholar Jayson Harsin introduced a concept that illuminates what was happening. Drawing on Foucault’s notion of “regimes of truth” – the mechanisms through which societies “distinguish true and false statements” and designate “those who are charged with saying what counts as true” (130) – Harsin argued we had shifted toward “regimes of posttruth” (ROPT), characterised by proliferating “truth markets” (327). Harsin’s concept requires careful interpretation. “Truth markets” are not markets in truth itself – as if truth were a commodity that could be bought and sold. Rather, they are competitive arenas of truth-determination: fragmented spaces where claims compete for credibility without authoritative institutions capable of settling disputes. In traditional regimes of truth, authoritative institutions – credentialed journalism, scientific consensus, official records – coordinated society’s processes for validating claims. In truth markets, no such coordination obtains. Every claim competes for attention, and engagement metrics determine visibility regardless of whether claims are true. Crucially, Harsin observed, “there is no authoritative Debunker” in truth markets. Fact-checkers and verification organisations proliferate, yet none “can suture fragmentation through a judgment for an entire society, and certainly cannot endure temporally” (331). A correction might reach thousands while the original claim reaches millions. Even when corrections spread widely, the false claim continues circulating long after attention has moved elsewhere. This temporal asymmetry – the structural advantage of first claims over corrections – would prove central to understanding Twitter’s trajectory as epistemic infrastructure. Harsin’s framework also highlights how truth markets demand participation. Unlike older regimes where citizens adhered to institutionally sanctioned knowledge, ROPT require “popular attention to/participation in its discursive games” (331). Resource-rich actors exploit this participatory dynamic, multiplying claims “whose meaning, if not veracity, is not easily or quickly confirmed” (331). The goal is not always persuasion but attention management – occupying the field of perception to shape what claims gain visibility. Twitter became the infrastructure through which these truth markets operated. The platform’s design – including the reportorial posture embedded in “What’s Happening?” – shaped market dynamics: which claims spread, which languished, whose voice carried weight. That posture posed fewer problems when Twitter primarily carried claims about current events – the kind of information the AP hack exploited. “Explosions at the White House” is an empirical claim whose truth is grounded in correspondence to observable states of affairs. Within minutes, other sources can verify whether explosions occurred. The truth market corrects relatively quickly because participants share epistemic standards: everyone agrees that the claim is true if and only if it corresponds to what actually happened. The problem emerged when Twitter became the channel for claims that cannot be verified the same way – political interpretations, normative arguments, claims whose truth, if they possess it, is grounded not in simple correspondence to observable facts but in coherence with frameworks, values, or standards that communities do not share. The same infrastructure, the same design features, the same engagement-driven sorting – but fundamentally different epistemic domains requiring different verification approaches. “The Free Speech Wing of the Free Speech Party” Twitter’s leadership never recognised that they had built epistemic infrastructure. In 2012, Tony Wang, Twitter’s UK general manager, described the company as “the free speech wing of the free speech party”. CEO Dick Costolo repeated this framing. The philosophy was clear: Twitter was a neutral conduit. Information flowed through it; the company did not adjudicate that information. This was a category error. Neutral conduits do not have verification systems that determine whose voice carries institutional authority. They do not have algorithms that decide which claims get amplified. They do not have trending topics that shape what millions perceive as significant. Twitter had all of these design features, and each one shaped the epistemic dynamics operating within it. The “free speech wing” philosophy meant Twitter disclaimed responsibility for design choices that determined which claims would gain credibility and which would fade into obscurity. The consequences were visible early. During the Boston Marathon bombing in April 2013 – the same month as the AP hack – researcher Kate Starbird found that 29% of the most viral content consisted of rumours and false claims (Starbird et al.). Corrections emerged quickly, often within the same hour. But they did not spread as far or persist as long. For claims about current events, this was damaging but self-correcting: eventually the verified account of what happened in Boston prevailed because everyone applied shared epistemic standards for evaluating empirical claims. Throughout this period, Twitter had no policy addressing false claims. None. While Facebook introduced “disputed” labels in 2016, Twitter would not implement any such labelling until 2020 – a four-year gap. For empirical claims about current events, this might have been defensible; verification eventually occurs through independent sources. But Twitter was no longer only carrying such claims. It had become infrastructure for political discourse, ideological argument, and contested interpretations where no single verification procedure could establish which claims were true. In July 2016, Twitter opened verification to public applications. The move exposed confusion about what verification meant on infrastructure this consequential. White supremacist Jason Kessler, organiser of the 2017 Charlottesville rally, was verified. So was white nationalist Richard Spencer. Twitter had confirmed their identities – verification performing its technical function. But on infrastructure that had become the global channel for authoritative claim-making, verification appeared to confer epistemic legitimacy.