Since computers entered the mainstream in the 1960s, the efficiency with which data can be processed has raised regulatory questions. This is well understood with respect to privacy. Data that was notionally public – divorce proceedings, say – had long been protected through the ‘practical obscurity’ of paper records. When such material was available in a single hard copy in a government office, the chances of one’s acquaintances or employer finding it were remote. Yet when it was computerized and made searchable through what ultimately became the Internet, practical obscurity disappeared. Today, high-speed computing poses comparable threats to existing regulatory models in areas from securities regulation to competition law, merely by enabling lawful activities – trading in stocks, or comparing and adjusting prices, say – to be undertaken more quickly than previously conceived possible. Many of these questions are practical rather than conceptual and apply to technologies other than AI. Nevertheless, current approaches to slowing down decision-making – through circuit-breakers to stop trading, for example – will not address all of the problems raised by the speed of AI systems.

In folklore, a will-o’-the-wisp is a supernatural ghostly floating light found in swamps and marshes that leads unfortunate travelers off safe paths and into dangerous areas. Although “spoof” orders for trades in futures contracts (and other financial instruments) are neither supernatural nor found in swamps, they are similar to will-o’-the-wisps in that spoof orders are fleeting presences intent on leading others astray. Modern futures market will-o’the-wisps, however, are often software algorithms that travel through trading platforms at superhuman speeds, and not the fiery fairy beings portrayed in legends.

One of the potential disadvantages of recent innovations in trading technology is that the markets now move with lightning speed in both good times and bad. With trading in futures and securities regularly counted in milliseconds (i.e., one thousandth of a second) and even microseconds (i.e., one millionth of a second), market crashes and rallies now also can occur – and, indeed, have occurred – at breakneck speeds that make human reaction times seem tortoise-like. The same algorithmic trading technologies that have enabled the markets for futures, securities, and options to incorporate information into the prices of financial instruments more quickly than ever before also have resulted in occasional high-speed crashes and rallies whose causes have, at times, confounded market participants and experts.

This book is about how the technological advances in automation and artificial intelligence (AI) that have fundamentally changed the nature of the US markets for futures contracts and other derivatives are necessitating, in some areas, changes to the legal and regulatory framework for these markets. To arrive at policy solutions to address the ways that AI systems are altering the markets, this book examines how algorithmic robots – algo bots, for short – have largely taken over trading in the futures markets, analyzes how regulators have responded to these changes thus far, and explores what steps policy makers should take in the future. But before diving into any of those topics, allow me to put the societal impact of these advances in computer science technologies in a broader context, beyond finance and derivatives.

This chapter focuses on financial markets and how these markets have enjoyed close ties to cities. It also demonstrates that social avalanches and tensional individuality have played a central role in how financial markets work and are conceived. I discuss this by examining the historical design of the trading floors of stock and commodity exchanges, introduced to avoid emergence within these exchanges of the avalanching of metropolitan life, as well as contrarian investment advice, which suggested techniques for how to avoid the avalanching properties of markets, techniques that ultimately subscribed to a tensional notion of individuality. The chapter also discusses more recent market developments such as the increasing computerisation of financial markets. I focus on the rise of algorithmic finance, in which fully automated computer algorithms are behind the majority of activity in financial markets. Through a discussion of the Flash Crash that took place in US markets in May 2010, I argue that fully automated algorithms may engage in social avalanching, meaning that sociality can indeed be ascribed to non-human algorithms.

This chapter argues that the big, brainy, intricately structured American novel that goes by the name of the “encyclopedic” or “systems” novel is shaped by an ambivalent relation to the correspondingly capacious, complex, and informationally rich sphere of the financial markets. It begins by tracing the idea of the all-knowing market from Adam Smith to the “efficient market hypothesis” that continues to dominate the discipline of financial economics today, and shows how this intellectual history has intersected with the history of the novel. The chapter challenges the critical consensus that reads the contemporary "big novel" as defined by the determinism of conspiracy plotting, and argues that it is more closely aligned with the contingent – yet collectively synchronized – dynamics of the classically “efficient” market. The latter portion of the chapter shows how major encyclopedic or systems texts – by Thomas Pynchon, William Gaddis, Richard Powers, Jonathan Franzen, David Foster Wallace, and Garth Risk Hallberg – position the omniscient financial market as performing both a redemptive mapping and an oppressive (and aggressively masculine) surveilling of the social totality.

This chapter devotes extended attention to two novels from either end of the “efficient market era” – Don DeLillo’s Players (1977) and Hari Kunzru’s Gods Without Men (2011) – that model their narrative forms on the information-crunching prowess of the financial markets’ price mechanisms, only to leave absences in the textual fabric that defy a totalitarian logic of epistemological capture. The juxtaposition of these two novels highlights how changing technological instantiations of efficient market theory have elicited shifting formal responses, and underscores both why the ideology of the efficient market has retained a hold over the imaginations of novelists, and why that hold is subject to increasing self-critique. The chapter argues, moreover, that Kunzru overtly presents his novel’s lack of conclusiveness as opposed not only to the market epistemology of contemporary finance, but also to the norms of the literary marketplace, with its own preference for narrative closure and transparency.