Involvement of Computers

In the latter part of the twentieth century, there were attempts to simulate
human reasoning with computers and to develop computers capable of humanlike reasoning. One notable attempt involved the work of Allen Newell
and Herbert Simon, who provided human subjects with various sorts of
problems to solve. Their human subjects would “think out loud,” and transcripts
of what they said became the basis of computer programs designed to
mimic human problem solving and reasoning. Thus, the study of human
logic and reasoning not only furthered the understanding of human cognitive
processes but also gave guidance to those working in artificial intelligence.
One caveat, however, is that even though such transcripts may serve
as a model for computer intelligence, there remain important differences
between human and machine “reasoning.” For example, in humans, the
correct application of some inference rules (for example, modus tollens) depends
upon the context (for example, the atmosphere hypothesis or the belief-
bias effect). Furthermore, not all human reasoning may be strictly
verbalizable, and to the extent that human reasoning relies on nonlinguistic
processes (such as imagery), it might not be possible to mimic or re-create it
on a computer.
After being assumed to be logical, or even being ignored by science, human
reasoning is finally being studied for what it is. In solving logical problems,
humans do not always comply with the dictates of logical theory; the
solutions reached may be influenced by the context of the problem, previous
knowledge or belief, and the particular heuristics used in reaching a solution.
Discovery of the structures, processes, and strategies involved in reasoning
promises to increase the understanding not only of how the human
mind works but also of how to develop artificially intelligent machines.
Sources for Further Study
Halpern, Diane F. Thought and Knowledge: An Introduction to Critical Thinking.
4th ed. Mahwah, N.J.: Lawrence Erlbaum, 2003. Presents a brief overview
of memory and language, then presents data and theory on performance
with different types of deductive arguments, analyzing arguments, fallacies,
reasoning with probabilities, and hypothesis testing. The author
provides numerous examples and exercises, and the text can be understood
by high school or college students.
Holland, John H., et al. Induction: Processes of Inference, Learning, and Discovery.
Reprint. Cambridge, Mass.: MIT Press, 1989. Presents a broad crossdisciplinary
account of induction and examines the role of inferential
rules in induction, people’s mental models of the world, concept formation,
problem solving, and the role of induction in discovery. The authors
provide an extensive bibliography of scholarly research on induction.
Johnson-Laird, Philip Nicholas. Mental Models. Cambridge, Mass.: Harvard
University Press, 1983. Presents an extensive review of data and theory on
syllogistic reasoning. The author presents a unified theory of the mind
based on recursive procedures, propositional representations, and mental
models. The text is very thorough and detailed, and many readers may
find it daunting.