What is a cognitive model?
A cognitive model is a computational process (akin to
a computer program) that aims to think and behave like a person.
While many flavors of cognitive models exist today, the most
popular are those developed in the context of a
cognitive
architecture—something like a computer programming
language that incorporates the abilities and limitations of the
human system (e.g., accounting for how people forget information, or
the limits of their hand or eye movements). Cognitive models
developed in a cognitive architecture (such as
ACT-R,
Soar, and others) then inherit the
predictions of the architecture and thus more closely represent
human thought and behavior.
How do
cognitive models simulate thoughts and behaviors?
Modern cognitive models, especially those developed
in cognitive architectures, generally run as computer simulations
along with a simulated task environment. For example, our own
models of driver behavior interact with a
driving simulator and thus must deal with all the intricacies of the
driving task (like handling the steering wheel and pedals in the
face of realistic vehicle dynamics). Some cognitive models even
interact directly with the external world using computer vision and
robotic movements.
What kinds of tasks
can cognitive models perform?
Cognitive models have been developed to
perform all kinds of tasks ranging from simple psychological
experiments to complex real-world tasks. Some models have accounted
for basic psychological phenomena, such as list memory, time
perception, visual search, and analogy. Other models have focused on
applied tasks including driving, mathematical learning, complex
decision-making, and air-traffic control. For example, the
ACT-R web site
lists applications of the ACT-R architecture for a
variety of tasks. Our own laboratory has focused
on developing cognitive models of tasks related in some way to human
multitasking, as described in our
recent book.
What's so interesting about multitasking?
Multitasking comes in a variety of flavors, but
generally speaking can be thought of in two ways.
Concurrent multitasking occurs
when these tasks occur simultaneously, like the classic example of
tapping your head while rubbing your belly.
Sequential multitasking involves doing multiple tasks
one after another, usually when one task is interrupted for the
other task to proceed, like dealing with a phone call or email in
the midst of writing an essay. From a scientific standpoint,
multitasking is fascinating in that it can be very easy in some
situations (like walking and talking) but extremely difficult in
other situations (like texting while driving, or listening to two
voices at the same time). These ideas are discussed in detail in our
book
The Multitasking
Mind.
How do people do two things at
the same time?
We have developed a theory
called
threaded cognition that aims to explain
how people multitask. The theory says that each task can be
represented as a
thread that
weaves its way through the brain's processing resources. Several
threads can run independently, especially when there is little to no
overlap in terms of the type of processing; for example, if a
reading thread is using vision and a movement thread is typing,
these threads can largely run without interference from each other.
However, there is also a central bottleneck (called the
procedural resource) that is
needed by all threads, and thus limits the amount of independence
between threads. This interplay between independent threads and a
central bottleneck allows the theory to account for both our
multitasking abilities and the limitations of those abilities.
How do people manage and recover from
interruptions?
A recent theory called
memory for goals says that,
when interrupted, people rehearse the current mental context so that
it can later be retrieved from memory when returning from an
interruption. Viewed under the lens of threaded cognition, people
actually multitask during an interruption: while performing the
interrupting task (email, chat, whatever), they maintain a
concurrent cognitive thread that performs this rehearsal of mental
context (see the
book). Thus, interruptions are not only
disruptive for the original task, they can even be disruptive for
the interrupting task due to interference from this concurrent
rehearsal.
When are interruptions most
disruptive?
There have been several studies in the
past decade reporting that interruptions are most disruptive in the
middle of a subtask, when people are trying to hold information
mentally while doing the task. Building on these studies, we have
recently shown that in the context of
deferrable interruptions,
people show a strong tendency to defer dealing with interruptions
while they are mentally holding information, instead waiting for a
point of lower workload when this information is no longer
needed.
How do people drive, cognitively speaking?
When steering a car, drivers rapidly
scan two distinct visual areas: the
lane directly in front of them to keep the car centered, and the
lane in the distance to guide smooth steering especially around
curves. This information is used to adjust the steering wheel and,
when another car is in front, adjust the car's speed as well. We
have developed a computational
model of steering and lane changing that
demonstrates how people can adjust steering roughly 4-5 times per
second -- typically adequate for normal driving, but when
distracting tasks interrupt these adjustments, performance can
quickly degrade.
How does cell-phone
dialing affect driving?
There have been a
number of studies showing the negative effects of cell-phone dialing
(and conversation) on driving performance. In
our own study, we found that
manually dialing a phone (by pressing keys) was significantly more
distracting than voice dialing, leading to an decreased ability to
keep the car centered in the lane.
Dialing using an address book-style menu
also degrades driving. These effects are present for hands-free
devices mounted on the dashboard; thus, our studies have agreed with
previous studies in that hands-free and handheld phones can both be
distracting.
How does iPod use affect
driving?
A recent GMAC survey reported
that 20% of drivers age 18-24 have used an iPod while driving.
Knowing how distracting cell phones can be, it may not be surprising
that using an iPod while driving can also be distracting. More
surprising is the size of the effect. Our
study of iPod distraction found that
selecting a song on an iPod can degrade performance almost twice as
much as dialing a cell phone. Even more surprisingly, selecting a
song can degrade performance twice as much as
watching a video on the iPod. The
level of distraction for iPod use is severe and warrants further
consideration as an important source of driver distraction.
Can just thinking about something affect
driving?
Yes! We ran a
laboratory study in which people simply
memorized a list of numbers, similar to trying to remember items to
buy at a grocery store or directions to a new location. Drivers only
had to think about this list while driving, and yet they exhibited a
50-millisecond slowdown in their brake reaction times (for a 9-item
list). While 50 milliseconds may not seem like much, consider that a
car on a highway can travel about 10 feet in that short time,
potentially being the difference between a crash and a
near-miss.
How can we predict the
distraction potential of new devices?
Many areas of engineering have tools at
their disposal for making predictions about new devices and
machines, such as design systems for automobiles or planes that can
predict wind resistance, drag, lift, etc. before the vehicle is
actually built. Such tools have been difficult to come by for
predictions of cognition and behavior. However, we have developed an
initial system called
Distract-R in which a
design can specify a prototype of a new in-vehicle device, like a
new radio interface or cell-phone dialing technique. The system uses
a
model of driver behavior to predict the
distraction potential of this new device based on common measures of
driver performance. Our hope is that this system can facilitate
rapid prototyping of many possible devices and pare down the number
to a few (say 2-4) devices that would then be developed and
rigorously tested within real vehicles.