After Thought: The Computer Challenge To Human Intelligence

by James Bailey

Through the first fifty years of the computer revolution, scientists have been trying to program electronic circuits to process information the same way humans do. Doing so has reassured us all that underlying every new computer capability, no matter how miraculously fast or complex, are human thought processes and logic. But cutting-edge computer scientists are coming to see that electronic circuits really are alien, that the difference between the human mind and computer capability is not merely one of degree (how fast), but of kind(how). The author suggests that computers “think” best when their “thoughts” are allowed to emerge from the interplay of millions of tiny operations all interacting with each other in parallel. Why then, if computers bring to the table such very different strengths and weaknesses, are we still trying to program them to think like humans? A work that ranges widely over the history of ideas from Galileo to Newton to Darwin yet is just as comfortable in the cutting-edge world of parallel processing that is at this very moment yielding a new form of intelligence, After Thought describes why the real computer age is just beginning.

Genres: Nonfiction, Science

277 pages, Hardcover

First published June 27, 1996

Reviews

[Douglas Summers-Stay · Rating 4 out of 5]

The author helped build the Connection Machine (a classic parallel computer from the 80s). His thesis is that data heavy representations without an explicit model and cellular-automata-like systems will become as important for future understanding of the world as equations have been, and before them, geometric diagrams.

[Ralph · Rating 4 out of 5]

Describes the how the various types of math used reflect the nature of the problems they are trying to solve. As a result, the way we think about the world is influenced by the type of math we use.

[Erik Larsson · Rating 3 out of 5]

Maths fitting the form of thought, and then thought fitting the form of maths. Would’ve liked more on how “the description inexorably becomes the reality”. Nevertheless, Bailey describes the history of mathematical description as going from place (geometric diagramming of ancient astronomy), to pace (the equational language favored by Descartes and Newton fitting the Industrial Age) to pattern (the emergent behavior maths of complex social and biological systems). I hadn’t considered how Descartes’ centering of conscious thought meant centering sequentialism, one-step-at-a-time problem solving, which carried its way into the early development of computer systems (computers first having been people) as symbolic calculators. However, symbolic formulations are inadequate for behavior that adapts, and so as data becomes more abundantly available in the world, bit evolution that improves its performance over time will understand complex adaptive systems much better.

There’s not enough cognitive science in this book though, as Bailey can’t seem to make up his mind about whether human cognition is more sequential, as Descartes says, or is in fact closer to the parallel processes in neural networks that are biologically inspired. Conscious vs. unconscious reasoning? Perception feels like a holistic phenomenon, but it also progresses in levels of abstraction. Unclear how these come together. Another lack was of a more speculative nature, about what exactly it means to let go of human-interpretable decision making, which has probably been more ongoing of a process than we realize. (It may be the process of our lifetimes though. I guess the Kelly book he cites may be where to look). The connectiontionists won out though, and while this doesn’t raise any questions for deep learning (in fact I don’t think the term comes up), it’s useful contextually, probably ahead of its time in that sense.




“As soon as you write an equation, it is wrong, because reducing a complex reality to an equation is just too simplistic a view of things. Large parallel computers, with large amounts of memory, may allow us to develop and entirely new sort of physics where, instead of reducing the facts to equations, we can just store in the computer the facts.“ - Albert Tarantola. This quote is cited multiple times

[Greg · Rating 4 out of 5]

I really enjoyed the conceptual framing of Place, Pace and Pattern in discussing the history of math and science. I found the first two sections the most enlightening. For example, the prominence of diagrams in geometry given its use of shapes being replaced by the line-based equations of algebra that came to dominate after the proliferation of the printing press.

[Heskarioth · Rating 3 out of 5]

Interesting book that describes the evolution of math.

[James Hollomon · Rating 5 out of 5]

I thoroughly enjoyed this book. I highly recommend it to all who are interested in the development of artificial intelligence and the possibility that we will soon see machines develop self awareness.

[Paul Spencer · Rating 4 out of 5]

Quite revolutionary for its time.