What is Latour’s Actor-Network Theory?

Actor-network theory, often abbreviated as ANT, is an influential but controversial approach to understanding the interactions between people and non-living things (Cresswell, Worth, & Sheik, 2010). This theory aims to counter, competing theories of social and technological determinism, which assume that all phenomena can be explained only by social or technological factors.

Actor-network theory emerged from French and British studies dealing with the sociology of science and technology from the 1980s onwards. The most notable, early researchers in this field, were Bruno Latour and John Law. Originally, Law and Latour developed actor-network theory as a means of understanding how innovation and knowledge creation occur in science and technology. Law and Latour’s actor-network theory is based on existing work in science and technology studies, and the study of many contemporary French intellectuals.

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Many of the tools characteristic of actor-network theory, such as the idea of translation, generalized symmetries, and “heterogeneous networks,” were developed in the 1980s by Latour in his book Science in Action (Latour, 1987). In the early 1990s, actor-network theory became popular as an analytical tool in many fields beyond science and technology studies, including computer science, health research, geography, sociology, anthropology, feminist studies, technical communication, and economics.

Understanding Networks and Social Dynamics

ANT focuses on non-living entities and their impact on social processes, defining actors as the “source of an action” regardless of their status. It considers the world as composed of networks, with the central idea being to investigate how networks come into being, trade associations, and how actors are enrolled. The aim is to gain insights into social effects like power.

ANT assumes that any actor, regardless of their position, can affect the functioning of the whole network. However, networks are always evolving, and the social world is made up of various mediators, which influence social outcomes in unexpected manners. ANT has been criticized for its extreme ontological assumptions (fundamental beliefs about what really exists that frequently contradict popular beliefs), yet it maintains a vision of the world as a network in which objects can play an important role in creating social relations.

Origins and development

ANT certainly comes from the study of “hard” science and technology formed its intellectual strength throughout its development. In fact, a lot. The major activities that define ANT tend to be the study of science and technology. However, some of the writings of later ANT authors have extended further “Hard” science as in Latour’s Reassembling the Social and Callon’s writings of economics.

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Whereas social explanations are thought to be flawed primarily because they use categories that are constructed as facts of the social situation, ANT argues that in most cases it is these categories that are being explained. It is argued that there is a need to enable a reversal between what is being explained and what is to be explained.

Principles

This theory is built on three fundamental principles: agnosticism, generalized symmetry, and free association. In their simplest form, these ideas convey the notion that there is no obvious separation between the social, natural, and technical. The first premise of actor-network theory, agnosticism, advises us to dismiss any assumptions the researchers previously held about the structure of networks, why they were developed, and the validity of their players’ estimates.

The second principle of actor-network theory is generalized symmetry, which uses the same explanatory framework when describing actors, human and non-human. According to this principle, researchers should never extend their methods to both individuals and objects being investigated, or objects and non-objects such as computers, and the people who design them.

The third principle of actor-network theory is an independent association, which advocates leaving no distinction between natural and social factors.

Applications and Criticisms

On a practical level, researchers find actor-network theory useful in helping to appreciate the complexity of reality and providing a lens for understanding how technology shapes social behavior. The theory can also be used to provide a theoretical epistemological approach to modeling by highlighting all informants associated with technology and providing a conceptual tool and vocabulary that can make this definition (Ritzer, 2004). Finally, actor-network theory is often used to explain networks, but its practical implications are limited. By identifying and explaining the features of a situation, actor-network theory ignores external social forces such as gender or religion.

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Actor-network theory has also been criticized for its tendency to overstate networks. In principle, a substance can be broken down to the atomic level, which is far beyond the level useful as sociologists to explain causal relationships. Scientists and technologists have used actor-network theory extensively in studying how social and economic worlds come into being. These symbols range from legislation to policy, religion, art, medicine, and architecture.

Technology

As such, actor-network theory has long been employed in the study of technology (Saito, 2010); not surprisingly, a number of other scholars have explicitly done so as well. For instance, Bloomfield(1991) offered a case study of the development of information systems in the UK National Health Service in which he then framed his conclusions in the language of actor-network theory.

His work, highlights how the same kinds of systems, in considerably different forms, can develop in diverse places due to the process of translation and network-building that took place, and the relationships between the people who were responsible for them coming to be.

Actor-Network Theory in Healthcare IT Implementation

ANT can be used just as practically to investigate what happens with the introduction of IT in healthcare settings. For example, as a tool for sampling by focusing on what Latour calls relevant informants, ie, all things that matter to, and are related to, the technology in question. ANT has indeed been used in this way in conjunction with multi-sited ethnography. Multi-sited ethnography is practiced by investigating multiple locations rather than the in-depth investigation of a single local setting typical for traditional ethnography. It aims to understand localities and how these are situated in a wider social system.

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ANT in Southern African Environmental Education Research

An example case for investigating the complexity, uncertainty, and controversy surrounding a new trend in environmental policymaking, namely waste product regulation, can be found in the Plastic Bags Regulations of 2003 (RSA, 2003).

The inquiry focused on understanding and exploring the tensions, debates, and responses arising from policy action as individuals and networks of individuals circulate the plastic bag regulation as a central agent (token). The objectives of the research consisted of the need to: explore selected international environmental policy practices involving waste and plastic shopping bag waste and how these influenced developments in South Africa recognize the individuals, actors, and network of individuals who shaped and were changed by South Africa’s plastic bag regulations, and illuminate the tensions, debates and responses emerging in political procedures; determine environmental policy outcomes and evaluate the implications of the creation and implementation of South Africa’s plastic bag regulations; and to establish trends in reforms to environmental policy practices around South Africa’s plastic bag regulations (Nhamo, 2004).

To address the complexity of policy research, the AANT hybrid inquiry framework was chosen for this study. Michael Callon and Bruno Latour first proposed some of the AANT components in 1981 (Callon).

The author’s early work highlighted two keywords that influenced the creation of AANT: actor (human) and actant (non-human artifact), as well as its process orientation towards data collection and analysis. The implementation of AANT allows for efficient tracing of relationship dynamics between actors and actants, as well as the evolving actor/actant network.