We use all kinds of artifacts in our everyday life to accomplish different types of cognitive tasks. We write scientific articles and blog posts by using word-processing programs. We prepare to-do lists to organize work tasks, and those of us who engage in statistical or computational analysis of data use computer programs to perform complex calculations that would be impossible to perform without them.
In this post, I argue that cognitive sociologists should pay more attention to cognitive artifacts and their affordances since many cognitive processes in our everyday lives cannot be properly understood and explained without taking them into account. I will proceed by first characterizing the concepts of cognitive artifact, affordance, and external representation. Then I will briefly discuss my recent paper which analyzes college and university rankings by utilizing these three concepts and the conceptual theory of metaphor.
Cognitive Artifacts
Donald Norman coined the concept of cognitive artifact in the early 1990s. According to his definition, a cognitive artifact is “an artificial device designed to maintain, display, or operate upon information in order to serve a representational function” (Norman 1990: 17). Richard Heersmink (2013) has more recently proposed a taxonomy of cognitive artifacts that includes non-representational cognitive artifacts in addition to representational cognitive artifacts. Here, I will rely on Norman’s definition and focus exclusively on representational cognitive artifacts.
Norman (1990) emphasized that the use of cognitive artifacts changes the nature of the cognitive tasks that a person performs—instead of just amplifying the person’s brain-based cognitive abilities—and, thereby, enhances the overall performance of the integrated system that is composed of the person and her artifact. For example, consider the case of organizing your daily work tasks by means of a to-do list, thereby transforming the cognitive task of remembering and planning your work tasks into the following cognitive tasks:
- writing a list of the relevant work tasks that may be ordered according to their relative priority or some other principle
- remembering to consult the list during the workday
- reading and interpreting the items written on the list one by one.
To-do lists enhance ones’ overall work performance during the workday, for example, by eliminating the moments in which the person thinks about what to do next.
From a cultural-historical and developmental viewpoint, it can also be argued that the uses of cognitive artifacts and technologies have transformed our cognitive lives in profound ways. Norman (1991; 1993) and many others (e.g., Donald 1991; Tomasello 1999) have emphasized that one of the distinctive features of our species is our ability to modify our environments by creating new artifacts, refining the artifacts that our ancestors have invented, and transmitting these artifacts to subsequent generations. Here is a relatively random list of some important types of cognitive artifacts that our species has invented: cave paintings, bookkeeping documents, handwritten texts, maps, calendars, clocks, compasses, printed texts, diagrams, thermometers, physical scale models, computers, computational models, GPS devices, and social media messages.
This list illuminates at least two facts. The first is that cognitive artifacts are not a recent innovation in human history since, for example, the earliest cave paintings date back to over 30 000 years and the earliest writing systems were developed over 5 millennia ago. The second is that most of these artifacts have developed gradually over many generations. Many researchers have also emphasized how new cognitive artifacts, tools, and technologies transform the embodied cognitive processes and capacities of people when they become integral parts of their everyday environments and cultural practices, including those pertaining to cognitive development (e.g., Clark 1997; 2003; Donald 1991; Hutchins 1995; 2008; Malafouris & Renfrew 2010; Menary & Gillett 2022; Kirsh 2010; Vygotsky 1978). Hence, cognitive artifacts and technologies are important for understanding historical and cultural variation in human cognition.
Affordances
The concept of affordance provides a useful tool for analyzing the properties of cognitive artifacts in the contexts where they are used. James J. Gibson (1979) introduced the notion of affordance as a part of his ecological theory of visual perception. Gibson writes that “[t]he affordances of the environment are what it offers the animal, what it provides or furnishes, either for good or ill” (p. 127). Gibson’s theory addressed the question of how living organisms perceive their immediate natural environments and emphasized the action-relatedness of perceptual processes. Norman (1993: 106) extended the concept of affordance to the domain of human-made artifacts and technologies by arguing that “[d]ifferent technologies afford different operations” for their users, thereby making “some things easy to do, others difficult or impossible”. It is important to understand that the affordances of a particular technology or a cognitive artifact not only depend on its intrinsic properties but also on the user’s particular bodily and cognitive features, abilities, and skills. For example, a geographical map provides cognitive affordances for navigation only for those who can read cartographic symbols and compass points. In this sense, affordances are relational.
External Representations
Since cognitive artifacts serve representational functions, the notion of external representation can be used to analyze how the affordances of a cognitive artifact shape how its users process information. According to David Kirsh (2010: 441), external representations that are maintained, displayed, or operated by cognitive artifacts may transform our cognitive capacities in at least seven ways:
They change the cost structure of the inferential landscape; they provide a structure that can serve as a shareable object of thought; they create persistent referents; they facilitate re-representation; they are often a more natural representation of structure than mental representations; they facilitate the computation of more explicit encoding of information; they enable the construction of arbitrarily complex structure; and they lower the cost of controlling thought – they help coordinate thought.
Although not all cognitive artifacts do all these things, Kirsh’s list and his examples clarify that cognitive artifacts are not just external aids to internal cognitive processes. Instead, they tend to alter the cognitive processes of their users by enabling them to outsource cognitive tasks that they would otherwise have to (attempt to) perform internally and, in some cases, enable them to accomplish new cognitive tasks that would be impossible without using the cognitive artifact. In their recent article, Richard Menary and Alexander Gillett (2022) also emphasize that cognitive tools (or cognitive artifacts in my terminology) function as tools for enculturation, thereby transforming the embodied cognitive capacities of their users who participate in culturally specific cognitive practices (see also Hutchins 1995; 2008).
Implications: Explaining the Paradox of University Rankings
In my recent article (Kaidesoja 2022), I used Wendy Nelson Espeland and Michael Sauder’s (e.g., 2016) case study of the U.S. News and World Report (shortly: USN) magazine’s law school ranking as a springboard to develop a theoretical framework for explaining the paradox of university rankings, by which I refer to the process where the impact of global and national university rankings has increased at the same time as a growing number of researchers has documented their methodological flaws and counterproductive consequences for university-based research and education (Kaidesoja 2022: 129-130). One aspect of the theoretical framework was my suggestion that the published league tables of university rankings can be understood as cognitive artifacts that provide specific affordances for their audiences to perform cognitive tasks. For example, the latest USN league table of law schools (see here) provides at least the following affordances to the decision-making of prospective law students who, it is plausible to assume, are all literate and numerate:
- Affords them to perceive a hierarchical and transitive order represented by the spatial relations among the names of law schools such that highly ranked law schools are at the top;
- Affords them to make unequivocal, quick, and easy comparisons between any two law schools in terms of their rank;
- Affords them to coordinate information about the rank, location, tuition, and enrollment for each school;
- Affords them to compare the rank of a university to its ranks in the previously published tables;
- Affords them to share the ranking results with others (e.g., through social media);
- Provides them with a stable object that affords joint attention and references in conversations (either in web-mediated or face-to-face communication) (Kaidesoja 2022: 144–145).
These affordances relate both to the visual features of the league tables and their functional properties as parts of the socially distributed cognitive processes that involve more than one actor. An example of the latter could be a situation where a prospective student justifies her decision to apply to Yale University to her parents by showing them that it is the best law school in the league table.
However, my argument was not that the USN ranking of law schools is the only factor that affects the decision-making of prospective students, since it is obvious that other things also influence this process, such as law schools’ distance to home, the financial resources of their parents, their career plans, and their own LSAT scores. Despite this, there is evidence that the USN ranking of law schools is an important factor that influences how many prospective students end up with their choices between law schools (see Espeland & Sauder 2016: chapter 3). It seemed to me that one reason for this is that the published league tables afford such perceptions, comparisons, and communications to prospective students that would be difficult or impossible without the league table. Hence, I hypothesized that the affordances of these cognitive artifacts are part of the explanation of why and how many prospective law students use the USN league tables to outsource part of their decision-making to the USN rankings.
I also argued that we must consider the embodied cognitive processes of prospective law students through which they interpret the ranking results since these processes motivate them to integrate the USN rankings as a part of their decision-making. By relying on Lakoff and Johnson’s (e.g., 2003) conceptual theory of metaphor, I proposed that prospective law students use the league tables of team sports as a source system for a metaphorical analogy guiding their understanding of the law schools rankings (that are also published in the league table format by the USN). My hypothesis was that the league table metaphor of this kind leads many prospective students to assume that – just like the competition between teams in a sports league – the competition between law schools for ranking scores is a zero-sum game, in which excellent quality is a scarce resource, and in which the quality is objectively measured by the ranking scores that determine the law school’s ranking position (Kaidesoja 2022, 141–142). Although these assumptions provide prospective students a way of making sense of the ranking results, they are quite problematic given the methodological problems and biases that are involved in the USN rankings, such as the fact that they overlook contextual differences between law schools, overemphasize competitive relations between law schools, and include arbitrary value judgments concerning the quality of law education (Espeland & Sauder 2016: chapter 1; Kaidesoja 2022: 143).
Moving Forward
In a recent paper on two traditions of cognitive sociology co-authored with Mikko Hyyryläinen and Ronny Puustinen (2021), we argued, among other things, that interdisciplinary cognitive sociologists, who emphasize the importance of integrating cognitive scientific perspectives to cultural sociology, have not yet systematically addressed cognitive artifacts and their affordances. Rather, most of them have focused on how culture influences the intracranial cognition of individuals. Without denying the importance of this project, we argued that there are good reasons to also consider the extracranial elements of cognitive mechanisms and begin to develop new theoretical and methodological approaches for studying the role of cognitive artifacts and technologies in social actions and cognitive development (cf. Norton 2020; Lizardo 2022; Turner 2018). I hope that my paper on university rankings provides some ideas about how one could develop mechanistic explanations that include both extracranial and intracranial cognitive elements.
References
Clark, A. (1997). Being There: Putting Brain, Body, and World Together Again. MIT Press.
Clark, A. (2003) Natural-Born Cyborgs: Minds, Technologies, and the Future of Intelligence. Oxford University Press.
Donald, M. (1991). Origins of the Modern Mind: Three Stages in the Evolution of Culture and Cognition. Harvard University Press.
Espeland, W.N. & Sauder M. (2016) Engines of Anxiety: Academic Rankings, Reputation, and Accountability. Russell Sage Foundation.
Gibson, J.J. (1979) The Ecological Approach to Visual Perception. Houghton Mifflin Harcourt.
Heersmink, R. (2013). A Taxonomy of Cognitive Artifacts: Function, Information, and Categories. Review of Philosophy and Psychology, 4(3), 465–481. https://link.springer.com/article/10.1007/s13164-013-0148-1
Hutchins, E. (1995) Cognition in the Wild. The MIT Press.
Hutchins, E. (2008) The Role of Cultural Practices in the Emergence of Modern Human Intelligence. Philosophical Transactions of the Royal Society B: Biological Sciences 363 (1499): 2011–2019.
Kaidesoja, T. (2022) A Theoretical Framework for Explaining the Paradox of University Rankings. Social Science Information. 61(1) 128–153. https://journals.sagepub.com/doi/full/10.1177/05390184221079470
Kaidesoja, T., Hyyryläinen, M. & Puustinen, R. (2021) Two Traditions of Cognitive Sociology: An Analysis and Assessment of Their Cognitive and Methodological Assumptions. Journal for the Theory of Social Behavior. https://onlinelibrary.wiley.com/doi/full/10.1111/jtsb.12341
Kirsh, D. (2010) Thinking with External Representations. AI & Society 25: 441–454.
Lakoff, G. & Johnson, M. (2003) Metaphors We Live by (With a New Afterword). The University of Chicago Press.
Lizardo, O. (2022). What is Implicit Culture? Journal for the Theory of Social Behavior. https://onlinelibrary.wiley.com/doi/10.1111/jtsb.12333
Malafouris, L., & Renfrew, C. (Eds.). (2010). The Cognitive Life of Things: Recasting the Boundaries of the Mind. McDonald Institute Monographs.
Menary, R. & Gillett, A (2022) The Tools of Enculturation. Topics in Cognitive Science: 1–25. https://onlinelibrary.wiley.com/doi/10.1111/tops.12604
Norman, D.A. (1991) Cognitive Artifacts. In: Carroll, J.M. (ed.) Designing Interaction. Cambridge University Press, pp.17–38.
Norman, D.A. (1993) Things That Make Us Smart: Defending Human Attributes in the Age of the Machine. Addison–Wesley.
Norton, M. (2020). Cultural Sociology Meets the Cognitive Wild: Advantages of the Distributed Cognition Framework for Analyzing the Intersection of Culture and Cognition. American Journal of Cultural Sociology, 8, 45–62. https://doi.org/10.1057/s41290-019-00075-w
Tomasello, M. (1999). The Cultural Origins of Human Cognition. London: Harvard University Press.
Turner, S. P. (2018). Cognitive Science and the Social. Routledge.
Vygotsky, L. S. (1978). Mind in Society: The Development of Higher Psychological Processes. Harvard University Press.