David Kirsh

This chapter explores four conditions for operationalizing the concept of cognitive extension. (1) Temporal tightness of the coupling—interaction between inner and outer processes must be fast, tight, and fluid, interacting at the speed of thought. (2) External mind parts must be transparent extensions of ourselves like glasses or prosthetic limbs that are psychologically absorbed into the subject’s body sense. We act through these parts or processes rather than on them. (3) Cognitive extensions are “owned”; they are not independent functioning units that could be a source of cognition themselves; inner processes confer cognitive status on the outer. (4) Extended parts or processes interact bidirectionally; causation is reciprocal, though controlled from the biological side. The chapter concludes that extension does exist. Through interaction we create an extended cognitive envelope. The parts of this envelope are episodic processes enacting external thinking rather than being an enduring assemblage of parts. To make the final leap to durable mind parts—external assemblages that are parts of a person even when not in use—requires reasoning of the sort lawyers and judges do best, not scientists.

From building a new piece of furniture to replacing a lightbulb, people must often figure out how to assemble an object from its parts. Although these physical assembly problems take on many different forms, they also pose common challenges. Chief among these is the question of how to break a complex problem down into subproblems that are easier to solve. What principles determine why some strategies for decomposing a problem are favored over others? Here, we investigate the decisions that people make when considering different visual subgoals in the context of attempting to build a series of virtual block towers. We hypothesized that people favor subgoals achieving a balance between how much progress the subgoals would help achieve toward the final goal and how effortful they would be to solve. We tested this hypothesis by defining several computational models of planning and subgoal selection, then evaluating how well these models predicted human planning and subgoal selection behavior on the same problems. Our results suggest that participants rapidly differentiated the computational costs of otherwise similarly ambitious subgoals, and used these judgments to drive subgoal selection. Moreover, our findings are consistent with the possibility that participants were not only sensitive to the immediate computational costs associated with solving the very next subgoal, but also future costs that might be incurred when attempting the rest of the problem. Taken together, these results contribute to our understanding of how humans make efficient use of cognitive resources to solve complex, grounded planning problems.

The ability to reason about how things were made is a pervasive aspect of how humans make sense of physical objects. Such reasoning is useful for a range of everyday tasks, from assembling a piece of furniture to making a sandwich and knitting a sweater. What enables people to reason in this way even about novel objects, and how do people draw upon prior experience with an object to continually refine their understanding of how to create it? To explore these questions, we developed a virtual task environment to investigate how people come up with step‐by‐step procedures for recreating block towers whose composition was not readily apparent, and analyzed how the procedures they used to build them changed across repeated attempts. Specifically, participants (N = 105) viewed 2D silhouettes of eight unique block towers in a virtual environment simulating rigid‐body physics, and aimed to reconstruct each one in less than 60 s. We found that people built each tower more accurately and quickly across repeated attempts, and that this improvement reflected both group‐level convergence upon a tiny fraction of all possible viable procedures, as well as error‐dependent updating across successive attempts by the same individual. Taken together, our study presents a scalable approach to measuring consistency and variation in how people infer solutions to physical assembly problems.

Time-motion studies revolutionized the design and efficiency of repetitive work last century. Wouldtime-ideastudies revolutionize the rules of intellectual/creative work this century? Collaborating with seven professional dancers, we set out to discover if there were any significant temporal patterns to be found in a timeline coded to show when dancers come up with ideas and when they modify or reject them. On each of 3 days, the dancers were given a choreographic problem (or task) to help them generate a novel, high quality contemporary dance phrase. They were videoed as they worked on this task for sessions of 15, 30, and 45 min. At the end of each 15 min interval during each session, we had them perform the phrase they were creating. They recorded and then coded the video of themselves dancing during these sessions by using a coding language we developed with them to identify when ideas are introduced, modified, and rejected. We found that most ideas are created early and that though these early ideas are aggressively pruned early on, many still make it into the final product. The two competing accounts of creativity in design research make predictions for the temporal structure of creativity. Our results support neither account, rather showing a more blended version of the two. The iterative design view, arguably the dominant view, is that good ideas are the product of generating many ideas, choosing one fairly early, committing to it, and iteratively improving it. The “fail fast fail often” view is that good ideas are the product of rapidly generating and discarding ideas and holding back from early commitment to any one in particular. The result of holding back commitment, typically, is not that an idea is taken up later and then incrementally improved at the last minute, as much as that later designs are not completely novel, instead incorporating the best parts of the entire sequence of ideas. In our study, we found no evidence that one account or the other was more predictive for the domain of contemporary dance. The behavior of the dancers that we studied revealed elements of both, calling into question how predictive these theories are.

A complementary strategy can be defined as any organizing activity which recruits external elements to reduce cognitive loads. Typical organizing activities include pointing, arranging the position and orientation of nearby objects, writing things down, manipulating counters, rulers or other artifacts that can encode the state of a process or simplify perception. To illustrate the idea of a complementary strategy, a simple experiment was performed in which subjects were asked to determine the dollar value of collections of coins. In the no-hands condition, subjects were not allowed to touch the coin images or to move their hands in any way. In the hands condition, they were allowed to use their hands and fingers however they liked. Significant improvements in time and number of errors were observed when S's used their hands over when they did not. To explain these facts, a brief account of some commonly observed complementary strategies is presented, and an account of their potential benefits to perception, memory and attention.

To explore the question of physical thinking – using the body as an instrument of cognition – we collected extensive video and interview data on the creative process of a noted choreographer and his company as they made a new dance. A striking case of physical thinking is found in the phenomenon of marking. Marking refers to dancing a phrase in a less than complete manner. Dancers mark to save energy. But they also mark to explore the tempo of a phrase, or its movement sequence, or the intention behind it. Because of its representational nature, marking can serve as a vehicle for thought. Importantly, this vehicle is less complex than the version of the same phrase danced ‘full-out’. After providing evidence for distinguishing different types of marking, three ways of understanding marking as a form of thought are considered: marking as a gestural language for encoding aspects of a target movement, marking as a method of priming neural systems involved in the target movement, and marking as a method for improving the precision of mentally projecting aspects of the target.

Why do people create extra representations to help them make sense of situations, diagrams, illustrations, instructions and problems? The obvious explanation— external representations save internal memory and com- putation—is only part of the story. I discuss seven ways external representations enhance cognitive power: 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. Jointly, these functions allow people to think more powerfully with external representations than without. They allow us to think the previously unthinkable.

A videographic study of origami is presented in which subjects were observed making four different origami objects under five modes of instruction: photos + captions, illustrations-only, illustrations with small captions, illustrations with large captions, and text-only as control. The objective of the study was to explore the gestures and other actions that subjects produce as they try to follow instructions rather than to determine the most effective style of instruction per se. We found that the task of situating instructions to the context at hand is error prone and that to facilitate it subjects gesture, point, re-orient illustrations, and generally do things that have no function other than to change the epistemic and interactive landscape of activity so they can more easily understand what is to be done. These studies bear on the new questions designers are asking about the placement, timing, and pace of instructions that digital aids now provide and on the fundamental question of how humans embed themselves in an activity by framing their task in a situation specific manner.

This paper examines some of the methods animals and humans have of adapting their environment. Because there are limits on how many different tasks a creature can be designed to do well in, creatures with the capacity to redesign their environments have an adaptive advantage over those who can only passively adapt to existing environmental structures. To clarify environmental redesign I rely on the formal notion of a task environment as a directed graph where the nodes are states and the links are actions. One natural form of redesign is to change the topology of this graph structure so as to increase the likelihood of task success or to reduce its expected cost, measured in physical terms. This may be done by eliminating initial states hence eliminating choice points; by changing the action repertoire; by changing the consequence function; and lastly, by adding choice points. Another major method for adapting the environment is to change its cognitive congeniality. Such changes leave the state space formally intact but reduce the number and cost of mental operations needed for task success; they reliably increase the speed, accuracy or robustness of performance. The last section of the paper describes several of these epistemic or complementary actions found in human performance.

In dance, there is a practice called ‘marking’. When dancers mark, they execute a dance phrase in a simplified, schematic or abstracted form. Based on our interviews with professional dancers in the classical, modern, and contemporary traditions, it is fair to assume that most dancers mark in the normal course of rehearsal and practice. When marking, dancers use their body-in-motion to represent some aspect of the full-out phrase they are thinking about. Their stated reason for marking is that it saves energy, avoids strenuous movement such as jumps, and sometimes it facilitates review of specific aspects of a phrase, such as tempo, movement sequence, or intention, all without the mental and physical complexity involved in creating a phrase full-out. It facilitates real-time reflection.

Can virtual engagement enable the sort of interactive coupling with objects enjoyed by archaeologists who are physically present at a site? To explore this question I consider three points: 1) Tangible interaction: What role does encounter by muscle and sinew play in experiencing and understanding objects? 2) Thinking with things. What sorts of interactions are involved when we manipulate things to facilitate thought? 3) Projection and imagination. Archaeological inquiry involves processes beyond perception. Material engagement of things stimulates these processes. What must be present in a virtual environment to recreate the feel of material engagement? I conclude that nothing, in principle, prevents future virtual environments from supporting this material engagement of digital versions of artifacts. But, there is much that remains to be understood about how to realize this material engagement, both at a technological and a cognitive level.

We are quickly passing through the historical moment when people work in front of a single computer, dominated by a small CRT and focused on tasks involving only local information. Networked computers are becoming ubiquitous and are playing increasingly significant roles in our lives and in the basic infrastructure of science, business, and social interaction. For human-computer interaction o advance in the new millennium we need to better understand the emerging dynamic of interaction in which the focus task is no longer confined to the desktop but reaches into a complex networked world of information and computer-mediated interactions. We think the theory of distributed cognition has a special role to play in understanding interactions between people and technologies, for its focus has always been on whole environments: what we really do in them and how we coordinate our activity in them. Distributed cognition provides a radical reorientation of how to think about designing and supporting human-computer interaction. As a theory it is specifically tailored to understanding interactions among people and technologies. In this article we propose distributed cognition as a new foundation for human-computer interaction, sketch an integrated research framework, and use selections from our earlier work to suggest how this framework can provide new opportunities in the design of digital work materials.

A complementary strategy can be defined as any organizing activity which recruits external elements to reduce cognitive loads. Typical organizing activities include pointing, arranging the position and orientation of nearby objects, writing things down, manipulating counters, rulers or other artifacts that can encode the state of a process or simplify perception. To illustrate the idea of a complementary strategy, a simple experiment was performed in which subjects were asked to determine the dollar value of collections of coins. In the no-hands condition, subjects were not allowed to touch the coin images or to move their hands in any way. In the hands condition, they were allowed to use their hands and fingers however they liked. Significant improvements in time and number of errors were observed when S's used their hands over when they did not. To explain these facts, a brief account of some commonly observed complementary strategies is presented, and an account of their potential benefits to perception, memory and attention.

In the course of daily life we solve problems often enough that there is a special term to characterize the activity and the right to expect a scientific theory to explain its dynamics. The classical view in psychology is that to solve a problem a subject must frame it by creating an internal representation of the problem’s structure, usually called a problem space. This space is an internally generable representation that is mathematically identical to a graph structure with nodes and links. The nodes can be annotated with useful information, and the whole representation can be distributed over internal and external structures such as symbolic notations on paper or diagrams. If the representation is distributed across internal and external structures the subject must be able to keep track of activity in the distributed structure. Problem solving proceeds as the subject works from an initial state in mentally supported space, actively constructing possible solution paths, evaluating them and heuristically choosing the best. Control of this exploratory process is not well understood, as it is not always systematic, but various heuristic search algorithms have been proposed and some experimental support has been provided for them.

A complementary strategy can be defined as any organizing activity which recruits external elements to reduce cognitive loads. Typical organizing activities include pointing, arranging the position and orientation of nearby objects, writing things down, manipulating counters, rulers or other artifacts that can encode the state of a process or simplify perception. To illustrate the idea of a complementary strategy, a simple experiment was performed in which subjects were asked to determine the dollar value of collections of coins. In the no-hands condition, subjects were not allowed to touch the coin images or to move their hands in any way. In the hands condition, they were allowed to use their hands and fingers however they liked. Significant improvements in time and number of errors were observed when S's used their hands over when they did not. To explain these facts, a brief account of some commonly observed complementary strategies is presented, and an account of their potential benefits to perception, memory and attention.

This article addresses three main questions: What causes cognitive overload in the workplace? What analytical framework should be used to understand how agents interact with their work environments? How can environments be restructured to improve the cognitive workflow of agents? Four primary causes of overload are identified: too much tasking and interruption, and inadequate workplace infrastructure to help reduce the need for planning, monitoring, reminding, reclassifying information, etc… The first step in reducing the cognitive impact of these causes is to enrich classical frameworks for understanding work environments, such as Newell and Simon’s notion of a task environment, by recognizing that our actual workplace is a superposition of many specific environments – activity spaces – which we slip between. Each has its own cost structure arising from the tools and resources available, including the cognitive strategies and interpretational frameworks of individual agents. These cognitive factors are significant, affecting how easy or difficult it is to perform an action, such as finding a specific paper in a “mess” desk. A few simple examples show how work environments can be redesigned and how restructuring can alter the cost structure of activity spaces.

We present data and argument to show that in Tetris—a real-time interactive video game—certain cognitive and perceptual problems are more quickly, easily, and reliably solved by performing actions in the world rather than by performing computational actions in the head alone. We have found that some translations and rotations are best understood as being used to implement a plan, or to implement a reaction. To substantiate our position we have implemented a computational laboratory that lets us record keystrokes and game situations, as well as allows us to dynamically create situations. Using the data of over 30 subjects playing 6 games, tachistoscopic tests of some of these subjects, and results from our own successful efforts at building expert systems to play Tetris, we show why knowing how to use one’s environment to enhance speed and robustness are important components in skilled play.

A startling amount of intelligent activity can be controlled without reasoning or thought. By tuning the perceptual system to task relevant properties a creature can cope with relatively sophisticated environments without concepts. There is a limit, however, to how far a creature without concepts can go. Rod Brooks, like many ecologically oriented scientists, argues that the vast majority of intelligent behaviour is concept-free. To evaluate this position I consider what special benefits accrue to concept-using creatures. Concepts are either necessary for certain types of perception, learning, and control, or they make those processes computationally simpler. Once a creature has concepts its capacities are vastly multiplied.

The influence of imagery on perception depends on the content of the mental image. Sixty-three students responded to the location of the 2 hands of a clock while visualizing the correct or an incorrect clock. Reaction time was shorter with valid cueing. Could this have resulted from visual acquisition strategies such as planning visual saccades or shifting covert attention? No. in this study, a crucial control condition made participants look at rather than visualize the cue. Acquisition strategies should have affected equally both types of cueing, but we observed that the effect of the visual cue was smaller and limited to a particular subcase in which one expects visual acquisition strategies. Thus, what matters is the similarity of the content of the mental image with the visual scene. In addition, an interaction involving the hand used for responding supports the notion that composite imagery is lateralized.