Online research in philosophy

This outstanding collection is designed to address the fundamental issues and principles underlying the task of Artificial Intelligence.

This paper continues a strain of intellectual complaint against the presumptions of certain kinds of formal semantics (the qualification is important) and their bad effects on those areas of artificial intelligence concerned with machine understanding of human language. After some discussion of the use of the term epistemology in artificial intelligence, the paper takes as a case study the various positions held by McDermott on these issues and concludes, reluctantly, that, although he has reversed himself on the issue, there was (...) no time at which he was right. (shrink)

I discuss two questions: (1) would Duhem have accepted the thesis of the continuity of scientific methodology? and (2) to what extent is the Oxford tradition of classification/subalternation of sciences continuous with early modern science? I argue that Duhem would have been surprised by the claim that scientific methodology is continuous; he expected at best only a continuity of physical theories, which he was trying to isolate from the perpetual fluctuations of methods and metaphysics. I also argue that the evidence (...) does not support the conclusion that early modern doctrines about mathematics and physics are continuous with the subalternation of sciences from Grosseteste, Bacon, and the theologians of fourteenth-century Oxford. The official and dominant context for early modern scientific methodology seems to have been progressive Thomism, and early modern thinkers seem to have pitted themselves against it. (shrink)

When John von Neumann turned his interest to computers, he was one of the leading mathematicians of his time. In the 1940s, he helped design two of the first stored-program digital electronic computers. He authored reports explaining the functional organization of modern computers for the first time, thereby influencing their construction worldwide (von Neumann, 1945; Burks et al., 1946). In the first of these reports, von Neumann described the computer as analogous to a brain, with an input “organ” (analogous to (...) sensory neurons), a memory, an arithmetical and a logical “organ” (analogous to associative neurons), and an output “organ” (analogous to motor neurons). His experience with computers convinced him that brains and computers, both having to do with the processing of information, should be studied by a new discipline–automata theory. In fact, according to von Neumann, automata theory would cover not only computers and brains, but also any biological or artificial systems that dealt with information and control, including robots and genes. Von Neumann never formulated a full-blown mathematical theory of automata, but he wrote several important exploratory papers (von Neumann, 1951, 1956, 1966). Meanwhile, besides designing hardware, he developed some of the first programs, programming languages, programming techniques, and numerical methods for solving mathematical problems using computers. (Much of his work on computing is reprinted in Aspray and Burks, 1987.) Shortly before his death in 1956, he wrote an informal synthesis of his views about brains. Though von Neumann left his manuscript sketchy and unfinished, Yale University Press published it as The Com- puter and the Brain in 1958. The 2000 reprint of this small but informative book is an opportunity to learn, or be reminded of, von Neumann’s thoughts on the computational organization of the mind-brain. Von Neumann began by explaining computers, which for him were essentially number crunchers: to compute was “to operate on .. (shrink)