The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Mind as machine: a history of cognitive science
Abstract
The development of cognitive science is one of the most remarkable and fascinating intellectual achievements of the modern era. The quest to understand the mind is as old as recorded human thought; but the progress of modern science has offered new methods and techniques which have revolutionized this enquiry. Oxford University Press now presents a masterful history of cognitive science, told by one of its most eminent practitioners. Cognitive science is the project of understanding the mind by modeling its workings. Psychology is its heart, but it draws together various adjoining fields of research, including artificial intelligence; neuroscientific study of the brain; philosophical investigation of mind, language, logic, and understanding; computational work on logic and reasoning; linguistic research on grammar, semantics, and communication; and anthropological explorations of human similarities and differences. Each discipline, in its own way, asks what the mind is, what it does, how it works, how it developed - how it is even possible. The key distinguishing characteristic of cognitive science, Boden suggests, compared with older ways of thinking about the mind, is the notion of understanding the mind as a kind of machine. She traces the origins of cognitive science back to Descartes's revolutionary ideas, and follows the story through the eighteenth and nineteenth centuries, when the pioneers of psychology and computing appear. Then she guides the reader through the complex interlinked paths along which the study of the mind developed in the twentieth century. Cognitive science, in Boden's broad conception, covers a wide range of aspects of mind: not just 'cognition' in the sense of knowledge or reasoning, but emotion, personality, social communication, and even action. In each area of investigation, Boden introduces the key ideas and the people who developed them. No one else could tell this story as Boden can: she has been an active participant in cognitive science since the 1960s, and has known many of the key figures personally. Her narrative is written in a lively, swift-moving style, enriched by the personal touch of someone who knows the story at first hand. Her history looks forward as well as back: it is her conviction that cognitive science today--and tomorrow--cannot be properly understood without a historical perspective. Mind as Machine will be a rich resource for anyone working on the mind, in any academic discipline, who wants to know how our understanding of our mental activities and capacities has developed.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Maternal emotional signaling: Its effect on the visual cliff behavior of 1-year-olds.
Sorce, J. F., Emde, R. N., Campos, J. J., & Klinnert, M. D. (1985) · Developmental Psychology · doi:10.1037/0012-1649.21.1.195 · Cited by 885
Cited by
Building machines that learn and think like people
Lake, B. M., Ullman, T. D., Tenenbaum, J. B., & Gershman, S. J. (2017) · Behavioral and Brain Sciences · doi:10.1017/s0140525x16001837 · Cited by 2,550
ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks
Lu, J., Batra, D., Parikh, D., & Lee, S. (2019) · arXiv · doi:10.48550/arxiv.1908.02265 · Cited by 2,109
Boden, M. A. (2009) · AI Magazine · doi:10.1609/aimag.v30i3.2254 · Cited by 527
Self-citationQuality Diversity: A New Frontier for Evolutionary Computation
Pugh, J. K., Soros, L. B., & Stanley, K. O. (2016) · Frontiers in Robotics and AI · doi:10.3389/frobt.2016.00040 · Cited by 514
Mind: introduction to cognitive science
(1997) · Choice Reviews Online · doi:10.5860/choice.34-5985 · Cited by 423
Metadata
- Venue
- Choice Reviews Online
- Publisher
- American Library Association
- Published
- 2007-07-01
- Volume
- 44
- Issue
- 11
- Pages
- 44-6202-44-6202
- ISSN
- 0009-4978 (ISSN-L)
- 1523-8253
- OpenAlex
- W1957780744
- Cited by
- 743
- References
- 1
- Type
- book review
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Mind as machine: a history of cognitive science. https://app.cochat.ai/papers/10.5860/choice.44-6202
- The paper
- Mind as machine: a history of cognitive science. (2007). Choice Reviews Online. https://doi.org/10.5860/choice.44-6202
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.