A Sociological Study of the Official History of the Perceptrons Controversy

  title={A Sociological Study of the Official History of the Perceptrons Controversy},
  author={Mikel Olazaran},
  journal={Social Studies of Science},
  pages={611 - 659}
In this paper, I analyze the controversy within Artificial Intelligence (AI) which surrounded the `perceptron' project (and neural nets in general) in the late 1950s and early 1960s. I devote particular attention to the proofs and arguments of Minsky and Papert, which were interpreted as showing that further progress in neural nets was not possible, and that this approach to AI had to be abandoned. I maintain that this official interpretation of the debate was a result of the emergence… Expand

Figures from this paper

Generative linguistics and neural networks at 60: Foundation, friction, and fusion
Abstract:The birthdate of both generative linguistics and neural networks can be taken as 1957, the year of the publication of foundational work by both Noam Chomsky and Frank Rosenblatt. ThisExpand
The Other Side: Algorithm as Ritual in Artificial Intelligence
An analog apparatus for the ritualistic performance of neural network algorithms is presented, which draws on the interaction modes of the Ouija board to provide a system which involves the user in the computation. Expand
The rhetoric of psychological research and the problem of unification in psychology.
There has been in the field of psychology a long and well-documented discontent with an apparent disorganization in its literature, most often interpreted as reflecting the absence of a unifyingExpand
Attaining landmark status: Rumelhart and McClelland's PDP Volumes and the Connectionist Paradigm.
It is argued that McClelland and Rumelhart's volumes became classics largely as a result of a confluence of rhetorical factors and insight into both the history of cognitive science and rhetoric's role in establishing classic texts is offered. Expand
The Perceptron: A Partial History of Models and Minds in Data-Driven Educational Systems
This chapter considers some of the limit points of contemporary relations between International Large-Scale Assessments, learning analytic platforms, and theories of mind circulating in contemporaryExpand
Neurons spike back: The Invention of Inductive Machines and the Artificial Intelligence Controversy
This article retraces the history of artificial intelligence through the lens of the tension between symbolic and connectionist approaches to reformulate the symbolic AI project by reviving the spirit of adaptive and inductive machines dating back from the era of cybernetics. Expand
AI Development for the Public Interest: From Abstraction Traps to Sociotechnical Risks
It is shown that for each subfield, perceptions of PIT stem from the particular dangers faced by past integration of technical systems within a normative social order, and a roadmap for a unified approach to sociotechnical graduate pedogogy in AI is presented. Expand
From metaphors to practices
This paper explores the introduction of professional systems engineers and information management practices into the first centralized DNA sequence database, developed at the European MolecularExpand
Axes for Sociotechnical Inquiry in AI Research
A lexicon for sociotechnical inquiry is provided and illustrates it through the example of consumer drone technology and four directions for inquiry into new and evolving areas of technological development are proposed. Expand
Social and epistemological bases of technology transfer : the case of artificial intelligence
Social and Epistemological Bases of Technology Transfer: the Case of Artificial Intelligence This thesis addresses a problem in the literature on technology transfer of understanding the localExpand


Intellectual issues in the history of artificial intelligence
This paper sketches the history of artificial intelligence in terms of intellectual issues. These are the usually d ichotomous opposit ions that disciplines seem to generate for themselves inExpand
The perceptron: a probabilistic model for information storage and organization in the brain.
This article will be concerned primarily with the second and third questions, which are still subject to a vast amount of speculation, and where the few relevant facts currently supplied by neurophysiology have not yet been integrated into an acceptable theory. Expand
Three Models of Scientific Development
In this paper I am going to discuss three generalised accounts, or 'me)dels', of the processes by which sdence develops.' I shall call these the 'me)del of openness', the 'model of dewure', and theExpand
The Mathematical Foundations of Learning Machines
Learning Machines was an underground classic among the neural network modelers who were active during this "dark age" and deserves to be better known to the generation that is "relearning" what was once known about statistical learning machines. Expand
Parallel Models of Associative Memory
This chapter discusses G.E. Hinton's models of Information Processing in the Brain, Implementing Semantic Networks in Parallel Hardware, and R. Ratcliff's Parallel-Processing Mechanisms and Processing of Organized Information in Human Memory. Expand
Self-Organizing Systems-A Review and Commentary
The class of self-organizing systems represented by networks which learn to recognize patterns is reviewed from an historical standpoint, and some of the behavioral similarities between such nets andExpand
Competitive Learning: From Interactive Activation to Adaptive Resonance
Comparisons are mode between several network models of cognitive processing: competitive learning, interactive activation, adaptive resonance, and back propagation, which suggest different levels of processing and interaction rules for the analysis of word recognition. Expand
An introduction to computing with neural nets
This paper provides an introduction to the field of artificial neural nets by reviewing six important neural net models that can be used for pattern classification and exploring how some existing classification and clustering algorithms can be performed using simple neuron-like components. Expand
What Does a Proof Do if it Does Not Prove
One of the more interesting problems to arise from the Kuhnian (1) analysis of science is the problem of communication between scientists with differing cognitive commitments. By conceiving ofExpand