Using clear language and numerous examples, each chapter of this guide analyses an individual plateau from Deleuze and Guattari's A Thousand Plateaus, interpreting the work for students and scholars.

Algorithms increasingly make managerial decisions that people used to make. Perceptions of algorithms, regardless of the algorithms' actual performance, can significantly influence their adoption, yet we do not fully understand how people perceive decisions made by algorithms as compared with decisions made by humans. To explore perceptions of algorithmic management, we conducted an online experiment using four managerial decisions that required either mechanical or human skills. We manipulated the decision-maker, and measured perceived fairness, trust, and emotional response. With the mechanical (...) tasks, algorithmic and human-made decisions were perceived as equally fair and trustworthy and evoked similar emotions; however, human managers' fairness and trustworthiness were attributed to the manager's authority, whereas algorithms' fairness and trustworthiness were attributed to their perceived efficiency and objectivity. Human decisions evoked some positive emotion due to the possibility of social recognition, whereas algorithmic decisions generated a more mixed response – algorithms were seen as helpful tools but also possible tracking mechanisms. With the human tasks, algorithmic decisions were perceived as less fair and trustworthy and evoked more negative emotion than human decisions. Algorithms' perceived lack of intuition and subjective judgment capabilities contributed to the lower fairness and trustworthiness judgments. Positive emotion from human decisions was attributed to social recognition, while negative emotion from algorithmic decisions was attributed to the dehumanizing experience of being evaluated by machines. This work reveals people's lay concepts of algorithmic versus human decisions in a management context and suggests that task characteristics matter in understanding people's experiences with algorithmic technologies. (shrink)

How the new conspiracists are undermining democracy—and what can be done about it Conspiracy theories are as old as politics. But conspiracists today have introduced something new—conspiracy without theory. And the new conspiracism has moved from the fringes to the heart of government with the election of Donald Trump. In A Lot of People Are Saying, Russell Muirhead and Nancy Rosenblum show how the new conspiracism differs from classic conspiracy theory, why so few officials speak truth to conspiracy, and what (...) needs to be done to resist it. Classic conspiracy theory insists that things are not what they seem and gathers evidence—especially facts ominously withheld by official sources—to tease out secret machinations. The new conspiracism is different. There is no demand for evidence, no dots revealed to form a pattern, no close examination of shadowy plotters. Dispensing with the burden of explanation, the new conspiracism imposes its own reality through repetition and bare assertion. The new conspiracism targets democratic foundations—political parties and knowledge-producing institutions. It makes it more difficult to argue, persuade, negotiate, compromise, and even to disagree. Ultimately, it delegitimates democracy. Filled with vivid examples, A Lot of People Are Saying diagnoses a defining and disorienting feature of today's politics and offers a guide to responding to the threat. (shrink)

In controversies about technology and society, there is no idea more pro vocative than the notion that technical things have political qualities. At issue is the claim that the machines, structures, and systems of modern material culture can be accurately judged not only for their contributions of efficiency and pro-ductivity, not merely for their positive and negative environmental side effects, but also for the ways in which they can embody specific forms of power and authority. Since ideas of this kind (...) have a persistent and troubling presence in discussions about the meaning of technology, they deserve explicit attention... (shrink)

There are possible artificially intelligent beings who do not differ in any morally relevant respect from human beings. Such possible beings would deserve moral consideration similar to that of human beings. Our duties to them would not be appreciably reduced by the fact that they are non-human, nor by the fact that they owe their existence to us. Indeed, if they owe their existence to us, we would likely have additional moral obligations to them that we don’t ordinarily owe to (...) human strangers – obligations similar to those of parent to child or god to creature. Given our moral obligations to such AIs, two principles for ethical AI design recommend themselves: (1) design AIs that tend to provoke reactions from users that accurately reflect the AIs’ real moral status, and (2) avoid designing AIs whose moral status is unclear. Since human moral intuition and moral theory evolved and developed in contexts without AI, those intuitions and theories might break down or become destabilized when confronted with the wide range of weird minds that AI design might make possible. (shrink)

This article responds to recent debates in critical algorithm studies about the significance of the term “algorithm.” Where some have suggested that critical scholars should align their use of the term with its common definition in professional computer science, I argue that we should instead approach algorithms as “multiples”—unstable objects that are enacted through the varied practices that people use to engage with them, including the practices of “outsider” researchers. This approach builds on the work of Laura Devendorf, Elizabeth Goodman, (...) and Annemarie Mol. Different ways of enacting algorithms foreground certain issues while occluding others: computer scientists enact algorithms as conceptual objects indifferent to implementation details, while calls for accountability enact algorithms as closed boxes to be opened. I propose that critical researchers might seek to enact algorithms ethnographically, seeing them as heterogeneous and diffuse sociotechnical systems, rather than rigidly constrained and procedural formulas. To do so, I suggest thinking of algorithms not “in” culture, as the event occasioning this essay was titled, but “as” culture: part of broad patterns of meaning and practice that can be engaged with empirically. I offer a set of practical tactics for the ethnographic enactment of algorithmic systems, which do not depend on pinning down a singular “algorithm” or achieving “access,” but which rather work from the partial and mobile position of an outsider. (shrink)

Algorithms, once obscure objects of technical art, have lately been subject to considerable popular and scholarly scrutiny. What does it mean to adopt the algorithm as an object of analytic attention? What is in view, and out of view, when we focus on the algorithm? Using Niklaus Wirth's 1975 formulation that “algorithms + data structures = programs” as a launching-off point, this paper examines how an algorithmic lens shapes the way in which we might inquire into contemporary digital culture.

How the new conspiracists are undermining democracy—and what can be done about it Conspiracy theories are as old as politics. But conspiracists today have introduced something new—conspiracy without theory. And the new conspiracism has moved from the fringes to the heart of government with the election of Donald Trump. In A Lot of People Are Saying, Russell Muirhead and Nancy Rosenblum show how the new conspiracism differs from classic conspiracy theory, how it undermines democracy, and what needs to be done (...) to resist it. (shrink)

This article proposes an analytical approach to algorithms that stresses operations of folding. The aim of this approach is to broaden the common analytical focus on algorithms as biased and opaque black boxes, and to instead highlight the many relations that algorithms are interwoven with. Our proposed approach thus highlights how algorithms fold heterogeneous things: data, methods and objects with multiple ethical and political effects. We exemplify the utility of our approach by proposing three specific operations of folding—proximation, universalisation and (...) normalisation. The article develops these three operations through four empirical vignettes, drawn from different settings that deal with algorithms in relation to AIDS, Zika and stock markets. In proposing this analytical approach, we wish to highlight the many different attachments and relations that algorithms enfold. The approach thus aims to produce accounts that highlight how algorithms dynamically combine and reconfigure different social and material heterogeneities as well as the ethical, normative and political consequences of these reconfigurations. (shrink)

Suggests an open system of psychological exploration to cut through accepted norms of morality, language, and politics.

This article examines whether and how a particular research practice is overseen and supervised, and by whom. This investigation fills notable gaps in the literature on science, including a lack of emphasis on larger sociopolitical structures, a neglect of regulation, and indifference toward ethics. The author focuses on the oversight of a particular research practice; data editing; which embodies qualities that are intriguing to sociologists of science: invisibility, uncertainty, heterogeneity, and reliance on tacit knowledge. These characteristics pose unique challenges to (...) oversight efforts. An analysis of in-depth interviews with gatekeepers reveals that although the methodological and ethical implications of data editing strategies can be substantial, oversight of such practices falls outside the stages and domains of current gatekeeping activity. These findings serve as the basis for recommendations to ensure data integrity while maintaining the professional autonomy of researchers. (shrink)

Studies on societal path dependencies tend to focus on mechanisms that anchor and stabilize national trajectories while paying less attention to transnational interactions and multilevel governance. This paper explores processes of path transformation in societies that are presumed to have the characteristics of open systems. Two pairs of case studies are presented and compared. The first illustrates institutional change through collision, when a national path meets with another. The second describes the emergence of transnational institutional paths and the impact of (...) that process on national institutions and their (potential) transformation. The results indicate that path transformation often stems from a gradual succession and combination of incremental steps and junctures – change is gradual but consequential. They also point to increasing co-evolutionary interaction between national path transformation and transnational path creation. This implies a need for analytical tools that are adapted to the analysis of multi-level, nested processes of institutionalization and de-institutionalization. The paper suggests that the concept of path generation allows for a better specification of the conditions for change in existing societal paths and for the emergence of new paths in the case of open systems than the concept of path dependency. (shrink)

Food retailers are powerful actors of the agro-industrial food system. They exert strong lock-in effects that hinder transitions towards more sustainable agri-food systems. Indeed, their marketing practices generally result in excluding the most sustainable food products, such as local, low-input, small-scale farmers’ products. Recently in Belgium, several initiatives have been created to enable the introduction of local products on supermarket shelves. In this article, we study three of those initiatives to analyse if the development of local sourcing in supermarkets opens (...) up an opportunity for a transition towards more sustainable agri-food systems. We conceptualise transitions as a shift in governance and ethical values and adopt a pragmatist approach of ethics combined with the systemic perspective of transition studies, to evaluate the impact of these initiatives. Our analysis shows that they mainly contribute to the reproduction of the incumbent agri-food system. It also highlights that first, to be a driver for sustainability transitions, food ethics need to be systemic i.e. relate to a systemic understanding of problems and perspective of sustainability, including social justice. And second, it highlights that governance arrangements involving not only representative organisations of the various agri-food and non-agricultural actors, but also actors upholding ethical values that are currently missing in conventional supply chains and representing excluded and marginalised interests, favour the uptake of such systemic ethics by incumbent actors. Hence, systemic ethics and inclusive governance are key features for initiatives to contribute to a sustainability transition. (shrink)

The power of algorithms has become a familiar topic in society, media, and the social sciences. It is increasingly common to argue that, for instance, algorithms automate inequality, that they are biased black boxes that reproduce racism, or that they control our money and information. Implicit in many of these discussions is that algorithms are permeated with normativities, and that these normativities shape society. The aim of this editorial is double: First, it contributes to a more nuanced discussion about algorithms (...) by discussing how we, as social scientists, think about algorithms in relation to five theoretical ideal types. For instance, what does it mean to go under the hood of the algorithm and what does it mean to stay above it? Second, it introduces the contributions to this special theme by situating them in relation to these five ideal types. By doing this, the editorial aims to contribute to an increased analytical awareness of how algorithms are theorized in society and culture. The articles in the special theme deal with algorithms in different settings, ranging from farming, schools, and self-tracking to AIDS, nuclear power plants, and surveillance. The contributions thus explore, both theoretically and empirically, different settings where algorithms are intertwined with normativities. (shrink)