‘@AP: Breaking: Two Explosions in the White House and Barack Obama is injured’. So read a tweet sent from a hacked Associated Press Twitter account @AP, which affected financial markets, wiping out $136.5 billion of the Standard & Poor’s 500 Index’s value. While the speed of the Associated Press hack crash event and the proprietary nature of the algorithms involved make it difficult to make causal claims about the relationship between social media and trading algorithms, we argue that it helps (...) us to critically examine the volatile connections between social media, financial markets, and third parties offering human and algorithmic analysis. By analyzing the commentaries of this event, we highlight two particular currents: one formed by computational processes that mine and analyze Twitter data, and the other being financial algorithms that make automated trades and steer the stock market. We build on sociology of finance together with media theory and focus on the work of Christian Marazzi, Gabriel Tarde and Tony Sampson to analyze the relationship between social media and financial markets. We argue that Twitter and social media are becoming more powerful forces, not just because they connect people or generate new modes of participation, but because they are connecting human communicative spaces to automated computational spaces in ways that are affectively contagious and highly volatile. (shrink)

In recent years, attention has become a matter of increasing public concern. New digital technologies have transformed human attention materially and discursively, reorganizing perceptual practices and inciting debates about them. The essays in this special issue emerged from a set of panels focused on attention at the 4S conference in New Orleans in 2019. They are all, in various ways, concerned with shifts among attention’s many meanings: between payment and care, instinct and agency, or vulnerability and power. Drawing on Science (...) and Technology Studies sensibilities, these pieces examine how scientific and technical actors are invested in theorizing and capturing attention, while simultaneously engendering new forms of care, resistance, and critique. At a moment where the attention economy appears to be in transformative crisis, this collection maps a set of incipient directions that ask us to pay attention to not only attention itself but also to the many sociotechnical settings where experts and publics are shifting attention’s meaning and value. (shrink)

This paper examines a case where Amazon’s cloud-based AI assistant Alexa accidentally ordered a dollhouse for a 6-year-old girl. In the press, the case was defined as a technical recognition problem. Building on this idea, we argue that the dollhouse case helps us to analyze the limits of current AI applications. By drawing on the writings of Gilles Deleuze and François Laruelle, we argue that these limits are not merely technical but more deeply embedded in the structures where the thinking (...) of AI can potentially happen. We point out that AI research has been compromised by the concepts of what constitutes both ‘artificial’ and by what constitutes ‘intelligence’. First, we use the notion of artificial non-intelligence to explain how different modes of digital capitalism such as voice commerce establish limits for AI. Second, we use the notion of non-artificial intelligence to illustrate the limits of associating AI’s modes of thinking with human thought. (shrink)