Robots as cognitive tools

Artificial intelligence is by its very nature synthetic, its motto is “Understanding by building”. In the early days of artificial intelligence the focus was on abstract thinking and problem solving. These phenomena could be naturally mapped onto algorithms, which is why originally AI was considered to be part of computer science and the tool was computer programming. Over time, it turned out that this view was too limited to understand natural forms of intelligence and that embodiment must be taken into account. As a consequence the focus changed to systems that are able to autonomously interact with their environment and the main tool became the robot. The “developmental robotics” approach incorporates the major implications of embodiment with regard to what has been and can potentially be learned about human cognition by employing robots as cognitive tools. The use of “robots as cognitive tools” is illustrated in a number of case studies by discussing the major implications of embodiment, which are of a dynamical and information theoretic nature.

“The end of the Dreyfus affair”

In this paper, the possibility of developing a Heideggerian solution to the Schizophrenia Problem associated with cognitive technologies is investigated. This problem arises as a result of the computer bracketing emotion from cognition during human-computer interaction and results in human psychic self-amputation. It is argued that, in order to solve the Schizophrenia Problem, it is necessary to first solve the ‘hard problem’ of consciousness since emotion is at least partially experiential. Heidegger’s thought, particularly as interpreted by Hubert Dreyfus, appears relevant in this regard since it ostensibly provides the basis for solving the ‘hard problem’ via the construction of artificial systems capable of the emergent generation of conscious experience. However, it will be shown that Heidegger’s commitment to a non-experiential conception of nature renders this whole approach problematic, thereby necessitating consideration of alternative, post-Heideggerian approaches to solving the Schizophrenia Problem.

A walk on the WILD side

Designs for CSCL (Computer-Supported Collaborative Learning) applications usually presume a desktop or laptop computer. Yet future classrooms are likely to be organized around Wireless Internet Learning Devices (WILD) that resemble graphing calculators, Palm, or Pocket-PC handhelds, connected by short-range wireless networking. WILD learning will have physical affordances that are different from today’s computer lab, and different from classrooms with 5 students per computer. These differing affordances may lead to learning activities that deviate significantly from today’s images of K-12 CSCL activities. Drawing upon research across a range of recent handheld projects, we suggest application-level affordances around which WILD-based CSCL has begun to organize: (a) augmenting physical space, (b) leveraging topological space, (c) aggregating coherently across all students, (d) conducting the class, and (e) act becomes artifact. We speculate on how CSCL research may consequently evolve towards a focus on kinds of systemic coupling in an augmented activity space.

Looking under the rug

Technological progress allows for the development of “intelligent” gadgets that are much smaller and more powerful than the bulky desktop computers that were around just a few years ago. Technology-oriented research communities understand these gadgets as enablers of scenarios that were widely considered science fiction just a few years ago: the expectation is that embedded and invisible technology calms our lives by removing the annoyances. Everyday life, however, is shaped by what people do, how they do it, and how they perceive what they are doing. The idea is that technology becomes context-aware in order to suit everyday life. So far, however, artifacts do not exhibit context-awareness beyond trivial notions of context. The question I address in this paper is to what extent artifacts can reasonably by expected to become context-aware. My impression is that the very idea of context-aware artifacts is closely related to much older ideas about intelligent machines pursued (with limited success) in the realm of classical artificial intelligence.

Modeling a cognitive tool for teaching the addition/subtraction of common fractions

The case study reported here models a Cognitive Tool (CT) for primary school children to learn common fraction addition/subtraction with unlike denominators. In the study, we developed a CT based on a cognitive task analysis of the domain. We then observed how 12 learners used this CT to understand fraction operations based on a knowledge of fraction equivalence. Results of the study indicate that the support offered by the CT aids learners with higher ability in mathematics to produce cognitive residues. The graphical partitioning model helps to link the concrete operations of partitioning with the abstract idea of a common denominator required for adding/subtracting fractions with unlike denominators. However, learners who have failed to develop the knowledge of fraction equivalence, which includes the concept of equivalence and the ways of finding it, cannot gain much from working with the CT. A model of affordances for improving the design of the CT to meet the diverse needs of learners is discussed.

Language as a cognitive technology

Ever since Descartes singled out the ability to use natural language appropriately in any given circumstance as the proof that humans — unlike animals and machines — have minds, an idea that Turing transformed into his well-known test to determine whether machines have intelligence, the close connection between language and cognition has been widely acknowledged, although it was accounted for in quite different ways. Recent advances in natural language processing, as well as attempts to create “embodied conversational agents” which couple language processing with that of its natural bodily correlates (gestures, facial expression and gaze direction), in the hope of developing human-computer interfaces based on natural — rather than formal — language, have again brought to the fore the question of how far we can hope machines to be able to master the cognitive abilities required for language use. In this paper, I approach this issue from a different angle, inquiring whether language can be viewed as a “cognitive technology”, employed by humans as a tool for the performance of certain cognitive tasks. I propose a definition of “cognitive technology” that encompasses both external (or “prosthetic”) and internal cognitive devices. A number of parameters in terms of which a typology of cognitive technologies of both kinds can be sketched is also set forth. It is then argued that inquiring about language’s role in cognition allows us to re-frame the traditional debate about the relationship between language and thought, by examining how specific aspects of language actually influence cognition — as an environment, a resource, or a tool. This perspective helps bring together the contributions of the philosophical “linguistic turn” in epistemology and the incipient “epistemology of cognitive technology” It also permits a more precise and fruitful discussion of the question whether, to what extent, and which of the language-based cognitive technologies we naturally use can be emulated by the kinds of technologies presently or in the foreseeable future available.

Relevance, goal management and cognitive technology

An accumulating body of research suggests that it is profitable to treat human cognition as a system that is primarily concerned with goal management. More specifically, it appears that the symbolic representation of goals, the location of relevant objects and operations and the construction of plans to achieve them, using objects and operations as components, are processes which are central to human cognition. The aim of the present paper is to suggest that relevance-based goal management processes are consistent with recent neuropsychological evidence that the human cognitive apparatus is duplex in nature. Furthermore, relevance information can provide a much-needed bridge between connectionist networks and the symbolic planning modules that characterise mature human cognition. The paper explores some phenomena, such as ethical reasoning, that have not been explained within previous theoretical frameworks. Finally, it is argued that, in addition to offering new explanations of familiar phenomena, the theoretical analysis of cognitive processes developed in the early part of the paper also suggests a range of novel technological interventions.

The origins of narrative

This article presents work in progress towards a better understanding of the origins of narrative. Assuming an evolutionary and developmental continuity of mental experiences, we propose a grounding of human narrative capacities in non-verbal narrative transactions in non-human animals, and in pre-verbal narrative transactions of human children. We discuss narrative intelligence in the context of the evolution of primate (social) intelligence, and with respect to the particular cognitive limits that constrain the development of human social networks and societies. We explain the Narrative Intelligence Hypothesis which suggests that the evolutionary origin of communicating in a narrative format co-evolved with increasingly complex social dynamics among our human ancestors. This article gives examples of social interactions in non-human primates and how these can be interpreted in terms of narrative formats. Due to the central role of narrative in human communication and social interaction, we discuss how research into the origins of narrative can impact the development of humane technology which is designed to meet the biological, cognitive and social needs of human story-tellers.

Towards a science of the bio-technological mind

The study of Cognitive Technology is, in a very real sense, the study of ourselves. Who we are, what we are, and even where we are, are all jointly determined by our biological natures and the web of supporting (and constraining) technologies in which we live, work and dream. But what general principles and concepts will allow us to make systematic sense (indeed, to make a science) of the bio-technological mind? I offer a brief, personal sketch of the underappreciated intimacy of human organisms and technological scaffoldings, and then rehearse 7 questions that such a science needs urgently to address.