Margaret Boden is not a historian, but she has been a prominent British cognitive scientist since the 1970s, when she wrote Artificial Intelligence and Natural Man. She also founded the cognitive science program at the University of Sussex. Having been part of something for over 30 years often entitles one’s opinions about its history to at least a careful hearing, and Professor Boden has offered up a rather extended opinion in her latest book, Mind as Machine: A History of Cognitive Science.
The “book” is actually spread across two volumes, totaling nearly 1500 pages in length (plus almost 200 more of references). Published in 2006 by Oxford University Press, it lists for a staggering $225 US, but it can be picked up at Amazon.com for a cool $178. My fellow blogger, Jeremy Burman, tells me that the paperback version will be out this coming July for a mere $60.48.
Boden’s book is a welcome addition to the historical literature on cognitive science, in no small part because cognitive science is such a new discipline that, despite there being many excellent focused studies, there is not very much yet available of an over-arching character. Nevertheless, historians of science usually approach with some trepidation when the scientists write their own history because, despite their vast technical and personal knowledge, vested interests often come into play (one is strongly inclined to play up the good and play down the bad and foolish when it comes to the science that one has spent one’s life helping along), and old battles and grudges frequently get replayed as one tries to get in the last word. (Insert “whiggish,” “presentist,” “internalist,” and “Carlyle” — as appropriate — among the historian’s typical anxieties when in the presence of scientist-wrought history of science).
Boden’s book has just been reviewed in American Scientist by the prominent Princeton philosopher of mind Gilbert Harman. He writes:
the relevant machine is usually a computer, and the cognitive science is usually concerned with the sort of cognition that can be exhibited by a computer. Boden does not discuss other aspects of the subject, broadly conceived, such as the “principles and parameters” approach in contemporary linguistics or the psychology of heuristics and biases. Furthermore, she also puts to one side such mainstream developments in computer science as data mining and statistical learning theory.
According to Harman, Boden’s analysis of the pitched battle between defenders of representational and connectionist computational architectures that took place in the late 1980s takes the following (externalist) line:
The disagreements were fueled by abrupt changes in U.S. government funding, which are noted in chapter 11. Much of the government money available was provided in the expectation that artificial intelligence would prove to be militarily useful. In the 1980s, funders decided to switch their support from proposition-based artificial intelligence to connectionism.
Tip o’ the hat to Mind Hacks for alerting me to this item.