Problem Solving by Computer

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Chapter 7 Thought, Language, and Intelligence
under way. He was about to alert his superiors to launch a counterattack on the United
States when it occurred to him that if this were a real nuclear attack, it would involve
many more than five missiles. Fortunately for everyone, he realized that the “attack” was
a false alarm (Hoffman, 1999). As this near-disaster shows, the absence of symptoms or
events can sometimes provide important evidence for or against a hypothesis. Compared
with evidence that is present, however, symptoms or events that do not occur are less
likely to be noticed (Hunt & Rouse, 1981). People have a difficult time using the absence
of evidence to help eliminate hypotheses from consideration (Hyman, 2002). In the
“trapped kitten” case, when the “meowing” stopped for several days after the stove was
unplugged and reconnected, rescuers assumed that the animal was frightened into
silence. They ignored the possibility that their hypothesis was incorrect in the first place.
FIGURE
7.8
Two Creative Solutions to the
Nine-Dot Problem
Many people find problems like this difficult because mental sets create artificial
limits on the range of solutions. In this
case, the mental sets involve the tendency
to draw within the frame of the dots and
to draw through the middle of each dot. As
shown here, however, there are other possibilities.
Confirmation Bias Anyone who has had a series of medical tests knows that diagnosis is not a one-shot affair. Instead, physicians choose their first hypothesis on the basis
of observed symptoms and then order tests or evaluate additional symptoms to confirm
or eliminate that hypothesis (Trillin, 2001). This process can be distorted by a
confirmation bias: Humans have a strong bias to confirm rather than reject the hypothesis they have chosen, even in the face of strong evidence against the hypothesis. In other
words, people are quite willing to perceive and accept data that support their hypothesis,
but they tend to ignore information that is inconsistent with it (Groopman, 2000). Confirmation bias may be seen as a form of the anchoring heuristic. Once you’ve “anchored”
to your first hypothesis, you may be unwilling to abandon it. The would-be rescuers of
John Gatiss’s “trapped kitten” were so intent on their efforts to pinpoint its location that
they never stopped to question its existence. Similarly, as described in the chapter on social
psychology, we tend to look for and pay extra attention to information that is consistent
with our first impressions of other people. This tendency can create positive or negative
bias in, say, a teacher’s views of children’s cognitive abilities or an interviewer’s judgments
of a job candidate’s skills (Jussim & Eccles, 1992; Reich, 2004). (For a summary of problem solving and its pitfalls, see “In Review: Solving Problems.”)
Problem Solving by Computer
Researchers have created artificial limbs, retinas, cochleas, and even hearts to help disabled people move, see, hear, and live more normally. They are developing artificial
brains, too, in the form of computer systems that not only see, hear, and manipulate
objects but also reason and solve problems. These systems are the product of research
in artificial intelligence (AI), a field that seeks to develop computers that imitate the
processes of human perception and thought.
confirmation bias The tendency to pay
more attention to evidence in support
of one’s hypothesis about a problem
than to evidence that refutes that
hypothesis.
An IBM computer known as Deep
Blue has won chess games against the world’s best chess masters. This result is not surprising, because chess is a clearly defined, logical game at which computers can perform
effectively. However, it is precisely their reliance on logic and formulas that accounts for
the shortcomings of today’s artificial intelligence systems. For example, these systems are
successful only in narrowly defined fields, not in general problem solving. This limitation
stems from the fact that AI systems are based on logical symbolic manipulations that
depend on “if-then” rules. Unfortunately, it is difficult to tell a computer how to recognize the “if” condition in the real world. Consider this simple “if-then” rule: “If it is a
clock, then set it.” Humans recognize all kinds of clocks because they have the natural
concept of “clock,” but computers are still not very good at forming natural concepts.
Doing so requires putting into the same category many examples that have very different physical features, from your bedside digital alarm clock to London’s Big Ben.
artificial intelligence (AI) The field
that studies how to program computers
to imitate the products of human
perception, understanding, and
thought.
Neural Network Models Recognizing the problems posed by the need to teach
computers to form natural concepts, many researchers in AI have moved toward a
connectionist, or neural network, approach. This approach uses computers to simulate
Symbolic Reasoning and Computer Logic
263
in review
Problem Solving
SOLVING PROBLEMS
Steps
Pitfalls
Remedies
Define the problem.
Inexperience: the tendency
to see each problem
as unique
Gain experience and
practice in seeing the
similarity between present
problems and previous
problems.
Form hypotheses
about solutions.
Availability heuristic: the
tendency to recall the
hypothesis or solution that
is most available to memory
Anchoring heuristic, or
mental set: the tendency
to anchor on the first
solution or hypothesis, and
not adjust your beliefs in
light of new evidence or
failures of the current
approach
Force yourself to write
down, and carefully
consider, many different
hypotheses.
Break the mental set,
stop, and try a fresh
approach.
Test hypotheses.
The tendency to ignore
negative evidence
In evaluating a hypothesis,
consider the things you
should see (but don’t) if
the hypothesis were true.
Look for disconfirming
evidence that, if found,
would show your
hypothesis to be false.
Confirmation bias: the
tendency to seek only
evidence that confirms
your hypothesis
?
1. People stranded without water could use their shoes to collect rain, but they may
not do so because of an obstacle to problem solving called
.
2. Because of the
heuristic, once sellers set a value on their house, they
may refuse to take much less for it.
3. If you tackle a massive problem one small step at a time, you are using an
approach called
.
the information processing taking place at many different, but interconnected, locations in the brain. Neural network models have helped researchers develop computers that are able to recognize voices, understand speech, read print, guide missiles, and
perform many other complex tasks (Ashcraft, 2006). Some of these computer simulations are being used to improve speech recognition software and to test theories of
how infants learn to recognize speech (e.g., Roy & Pentland, 2002; Sroka & Braida,
2005). Others have been used to improve on human decision making. One program,
called PAPNET, can outperform human technicians at detecting abnormal cells in
smears collected during cervical examinations (Kok & Boon, 1996). Indeed, computerized expert systems can now perform as well as humans, and sometimes better, at
solving complex problems in medical diagnosis and business decision making (Khan
et al., 2001; Workman, 2004).
Unfortunately, however, most computer models of neural networks still fall well
short of the capacities of the human perceptual system. For example, computers are
slow to learn how to classify visual patterns, which has led to disappointment in efforts
to develop computerized face recognition systems capable of identifying terrorists and
other criminals in public places (Feder, 2004). But even though neural networks are
far from perfect “thinking machines,” they are sure to play an important role in