DNA sequencers, Twitter, MRIs, Facebook, particle accelerators, Google Books, radio telescopes, Tumblr: what do these things have in common? According to the evangelists of “data science,” all of these are instruments for observing reality at unprecedentedly large scales and fine granularities. This perspective ignores the social reality of these very different technological systems, ignoring how they are made, how they work, and what they mean in favor of an exclusive focus on what they generate: Big Data. But no data, big (...) or small, can be interpreted without an understanding of the process that generated them. Statistical data science is applicable to systems that have been designed as scientific instruments, but is likely to lead to confusion when applied to systems that have not. In those cases, a historical inquiry is preferable. (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)

This article builds on the hypothesis that theoretical approaches to philosophy of technology are currently stuck in a false alternative: either embrace the “empirical turn” or jump back into the determinism, pessimism, and general ignorance towards specific technologies that characterized the “humanities philosophy of technology.” A third path is however possible, which consists of articulating an empirical point of view with an interest in the symbolic dimension in which technologies and technological mediations are always already embedded. Bourdieu’s sociology of the (...) symbolic forms represents an important and mostly unexplored resource in this respect. In this article, we introduce the notion of technological capital and its tree states—objectified, institutionalized, and embodied. In the first section, we briefly account of the empirical turn in philosophy of technology. Specific attention is then devoted to postphenomenology. We depict three perspectives in postphenomenology: standard postphenomenology, in which one single human-technology-world relation at a time is considered; the attempt of some technological mediation theorists to articulate postphenomenology and actor-network theory ; the original effort in Ihde, which is currently practiced by a minority of postphenomenologists, to combine an interest for the empirical dimension of technological mediations with an attention to the social and cultural conditions of possibility in which these mediations are embedded. In the second section, we consider some recent critiques of the limits of the empirical turn in philosophy of technology, especially related to postphenomenology. Furthermore, we argue that Pierre Bourdieu’s sociology may benefit the philosophy of technology. One might say that according to a Bourdieusian perspective, technologies are, in their invention, implementation, and use, embedded in symbolically organized interactions among social actors or groups. The notion of technological capital is introduced. A specific attention is given to its embodied state, which is related to the habitus. Such concept suggests that, to rephrase the famous sentence by Heidegger, “the essence of technology is not totally technological.” In the conclusion, we consider three risks related to a Bourdieusian approach to technology: transparency, determinism, and absolutism. (shrink)

I usually shock people by telling them about all sorts of possible wonders of the future, but it is probably impossible to shock an Extropian. If I am talking to a general audience I usually explain to them that if it weren't for their bad habits and superstitions they could live forever.

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)

Despite all the attention to Big Data and the claims that it represents a “paradigm shift” in science, we lack understanding about what are the qualities of Big Data that may contribute to this revolutionary impact. In this paper, we look beyond the quantitative aspects of Big Data and examine it from a sociotechnical perspective. We argue that a key factor that distinguishes “Big Data” from “lots of data” lies in changes to the traditional, well-established “control zones” that facilitated clear (...) provenance of scientific data, thereby ensuring data integrity and providing the foundation for credible science. The breakdown of these control zones is a consequence of the manner in which our network technology and culture enable and encourage open, anonymous sharing of information, participation regardless of expertise, and collaboration across geographic, disciplinary, and institutional barriers. We are left with the conundrum—how to reap the benefits of Big Data while re-creating a trust fabric and an accountable chain of responsibility that make credible science possible. (shrink)

Algorithms, or rather algorithmic actions, are seen as problematic because they are inscrutable, automatic, and subsumed in the flow of daily practices. Yet, they are also seen to be playing an important role in organizing opportunities, enacting certain categories, and doing what David Lyon calls “social sorting.” Thus, there is a general concern that this increasingly prevalent mode of ordering and organizing should be governed more explicitly. Some have argued for more transparency and openness, others have argued for more democratic (...) or value-centered design of such actors. In this article, we argue that governing practices—of, and through algorithmic actors—are best understood in terms of what Foucault calls governmentality. Governmentality allows us to consider the performative nature of these governing practices. They allow us to show how practice becomes problematized, how calculative practices are enacted as technologies of governance, how such calculative practices produce domains of knowledge and expertise, and finally, how such domains of knowledge become internalized in order to enact self-governing subjects. In other words, it allows us to show the mutually constitutive nature of problems, domains of knowledge, and subjectivities enacted through governing practices. In order to demonstrate this, we present attempts to govern academic writing with a specific focus on the algorithmic action of Turnitin. (shrink)

This paper discusses the problem of responsibility attribution raised by the use of artificial intelligence technologies. It is assumed that only humans can be responsible agents; yet this alone already raises many issues, which are discussed starting from two Aristotelian conditions for responsibility. Next to the well-known problem of many hands, the issue of “many things” is identified and the temporal dimension is emphasized when it comes to the control condition. Special attention is given to the epistemic condition, which draws (...) attention to the issues of transparency and explainability. In contrast to standard discussions, however, it is then argued that this knowledge problem regarding agents of responsibility is linked to the other side of the responsibility relation: the addressees or “patients” of responsibility, who may demand reasons for actions and decisions made by using AI. Inspired by a relational approach, responsibility as answerability thus offers an important additional, if not primary, justification for explainability based, not on agency, but on patiency. (shrink)

Big Data evangelists often argue that algorithms make decision-making more informed and objective—a promise hotly contested by critics of these technologies. Yet, to date, most of the debate has focused on the instruments themselves, rather than on how they are used. This article addresses this lack by examining the actual practices surrounding algorithmic technologies. Specifically, drawing on multi-sited ethnographic data, I compare how algorithms are used and interpreted in two institutional contexts with markedly different characteristics: web journalism and criminal justice. (...) I find that there are surprising similarities in how web journalists and legal professionals use algorithms in their work. In both cases, I document a gap between the intended and actual effects of algorithms—a process I analyze as “decoupling.” Second, I identify a gamut of buffering strategies used by both web journalists and legal professionals to minimize the impact of algorithms in their daily work. Those include foot-dragging, gaming, and open critique. Of course, these similarities do not exhaust the differences between the two cases, which are explored in the discussion section. I conclude with a call for further ethnographic work on algorithms in practice as an important empirical check against the dominant rhetoric of algorithmic power. (shrink)

Bringing Pierre Bourdieu to Science and Technology Studies Content Type Journal Article Pages 263-273 DOI 10.1007/s11024-011-9174-2 Authors Mathieu Albert, Wilson Centre and Department of Psychiatry, Faculty of Medicine, University of Toronto, 200 Elizabeth Street , Eaton-South 1-581, Toronto, ON M5G 2C4, Canada Daniel Lee Kleinman, Department of Community and Environmental Sociology, University of Wisconsin-Madison, 348 Agricultural Hall 1450 Linden Drive, Madison, WI 53706, USA Journal Minerva Online ISSN 1573-1871 Print ISSN 0026-4695 Journal Volume Volume 49 Journal Issue Volume 49, Number (...) 3. (shrink)

The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. Other animals have stronger muscles or sharper claws, but we have cleverer brains. If machine brains one day come to surpass human brains in general intelligence, then this new superintelligence could become very powerful. As the fate of the gorillas now depends more on us humans than on the gorillas themselves, so the fate of (...) our species then would come to depend on the actions of the machine superintelligence. But we have one advantage: we get to make the first move. Will it be possible to construct a seed AI or otherwise to engineer initial conditions so as to make an intelligence explosion survivable? How could one achieve a controlled detonation? To get closer to an answer to this question, we must make our way through a fascinating landscape of topics and considerations. Read the book and learn about oracles, genies, singletons; about boxing methods, tripwires, and mind crime; about humanity's cosmic endowment and differential technological development; indirect normativity, instrumental convergence, whole brain emulation and technology couplings; Malthusian economics and dystopian evolution; artificial intelligence, and biological cognitive enhancement, and collective intelligence. (shrink)

This article builds on the hypothesis that theoretical approaches to philosophy of technology are currently stuck in a false alternative: either embrace the “empirical turn” or jump back into the determinism, pessimism, and general ignorance towards specific technologies that characterized the “humanities philosophy of technology.” A third path is however possible, which consists of articulating an empirical point of view with an interest in the symbolic dimension in which technologies and technological mediations are always already embedded. Bourdieu’s sociology of the (...) symbolic forms represents an important and mostly unexplored resource in this respect. In this article, we introduce the notion of technological capital and its tree states—objectified, institutionalized, and embodied. In the first section, we briefly account of the empirical turn in philosophy of technology. Specific attention is then devoted to postphenomenology. We depict three perspectives in postphenomenology: standard postphenomenology, in which one single human-technology-world relation at a time is considered; the attempt of some technological mediation theorists to articulate postphenomenology and actor-network theory ; the original effort in Ihde, which is currently practiced by a minority of postphenomenologists, to combine an interest for the empirical dimension of technological mediations with an attention to the social and cultural conditions of possibility in which these mediations are embedded. In the second section, we consider some recent critiques of the limits of the empirical turn in philosophy of technology, especially related to postphenomenology. Furthermore, we argue that Pierre Bourdieu’s sociology may benefit the philosophy of technology. One might say that according to a Bourdieusian perspective, technologies are, in their invention, implementation, and use, embedded in symbolically organized interactions among social actors or groups. The notion of technological capital is introduced. A specific attention is given to its embodied state, which is related to the habitus. Such concept suggests that, to rephrase the famous sentence by Heidegger, “the essence of technology is not totally technological.” In the conclusion, we consider three risks related to a Bourdieusian approach to technology: transparency, determinism, and absolutism. (shrink)