Multitasking: Switching costs
Subtle “switching” costs cut efficiency, raise risk.
What the research shows
Doing more than one task at a time, especially more than one complex task, takes a toll on productivity. Although that shouldn’t surprise anyone who has talked on the phone while checking E-mail or talked on a cell phone while driving, the extent of the problem might come as a shock. Psychologists who study what happens to cognition (mental processes) when people try to perform more than one task at a time have found that the mind and brain were not designed for heavy-duty multitasking. Psychologists tend to liken the job to choreography or air-traffic control, noting that in these operations, as in others, mental overload can result in catastrophe.
Multitasking can take place when someone tries to perform two tasks simultaneously, switch . from one task to another, or perform two or more tasks in rapid succession. To determine the costs of this kind of mental “juggling,” psychologists conduct task-switching experiments. By comparing how long it takes for people to get everything done, the psychologists can measure the cost in time for switching tasks. They also assess how different aspects of the tasks, such as complexity or familiarity, affect any extra time cost of switching.
In the mid-1990s, Robert Rogers, PhD, and Stephen Monsell, D.Phil, found that even when people had to switch completely predictably between two tasks every two or four trials, they were still slower on task-switch than on task-repeat trials. Moreover, increasing the time available between trials for preparation reduced but did not eliminate the cost of switching. There thus appear to be two parts to the switch cost — one attributable to the time taken to adjust the mental control settings (which can be done in advance it there is time), and another part due to competition due to carry-over of the control settings from the previous trial (apparently immune to preparation).
Surprisingly, it can be harder to switch to the more habitual of two tasks afforded by a stimulus. For example, Renata Meuter, PhD, and Alan Allport, PhD, reported in 1999 that if people had to name digits in their first or second language, depending on the color of the background, as one might expect they named digits in their second language slower than in their first when the language repeated. But they were slower in their first language when the language changed.
In experiments published in 2001, Joshua Rubinstein, PhD, Jeffrey Evans, PhD, and David Meyer, PhD, conducted four experiments in which young adults switched between different tasks, such as solving math problems or classifying geometric objects. For all tasks, the participants lost time when they had to switch from one task to another. As tasks got more complex, participants lost more time. As a result, people took significantly longer to switch between more complex tasks. Time costs were also greater when the participants switched to tasks that were relatively unfamiliar. They got up to speed faster when they switched to tasks they knew better.
In a 2003 paper, Nick Yeung, Ph.D, and Monsell quantitatively modeled the complex and sometimes surprising experimental interactions between relative task dominance and task switching. The results revealed just some of the complexities involved in understanding the cognitive load imposed by real-life multi-tasking, when in addition to reconfiguring control settings for a new task, there is often the need to remember where you got to in the task to which you are returning and to decide which task to change to, when.
What the research means
According to Meyer, Evans and Rubinstein, converging evidence suggests that the human “executive control” processes have two distinct, complementary stages. They call one stage “goal shifting” (“I want to do this now instead of that”) and the other stage “rule activation” (“I’m turning off the rules for that and turning on the rules for this”). Both of these stages help people to, without awareness, switch between tasks. That’s helpful. Problems arise only when switching costs conflict with environmental demands for productivity and safety.
Although switch costs may be relatively small, sometimes just a few tenths of a second per switch, they can add up to large amounts when people switch repeatedly back and forth between tasks. Thus, multitasking may seem efficient on the surface but may actually take more time in the end and involve more error. Meyer has said that even brief mental blocks created by shifting between tasks can cost as much as 40 percent of someone’s productive time.
How we use the research
Understanding the hidden costs of multitasking may help people to choose strategies that boost their efficiency – above all, by avoiding multitasking, especially with complex tasks. (Throwing in a load of laundry while talking to a friend will probably work out all right.) For example, losing just a half second of time to task switching can make a life-or-death difference for a driver on a cell phone traveling at 30 MPH. During the time the driver is not totally focused on driving the car, it can travel far enough to crash into an obstacle that might otherwise have been avoided.
Meyer and his colleagues hope that understanding switching costs and the light they shed on “executive control” may help to improve the design and engineering of equipment and human-computer interfaces for vehicle and aircraft operation, air traffic control, and many other activities using sophisticated technologies. Insights into how the brain “multitasks” lend themselves to a range of settings from the clinic, helping to diagnose and help brain-injured patients, to the halls of Congress, informing government and industrial regulations and standards.
This research is also taken into account by states and localities considering legislation to restrict drivers’ use of cell phones.
Sources & further reading
Gopher, D., Armony, L. & Greenspan, Y. (2000). Switching tasks and attention policies. Journal of Experimental Psychology: General, 129, 308-229.
Mayr, U. & Kliegl, R. (2000). Task-set switching and long-term memory retrieval. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 1124-1140.
Meuter, R. F. I. & Allport, A. (1999). Bilingual language switching in naming: Asymmetrical costs of language selection. Journal of Memory and Language, 40(1), 25-40.
Meyer, D. E. & Kieras, D. E. (1997a). A computational theory of executive cognitive processes and multiple-task performance: Part 1. Basic mechanisms. Psychological Review, 104, 3-65.
Meyer, D. E. & Kieras, D. E. (1997b). A computational theory of executive cognitive processes and multiple-task performance: Part 2. Accounts of psychological refractory-period phenomena. Psychological Review, 104, 749-791.
Monsell, S., Azuma, R., Eimer, M., Le Pelley, M., & Strafford, S. (1998, July). Does a prepared task switch require an extra (control) process between stimulus onset and response selection? Poster presented at the 18th International Symposium on Attention and Performance, Windsor Great Park, United Kingdom.
Monsell, S., Yeung, N., & Azuma, R. (2000). Reconfiguration of task-set: Is it easier to switch to the weaker task? Psychological Research, 63, 250-264.
Monsell, S. & Driver, J., Eds. (2000). Control of cognitive processes: Attention and Performance XVIII. Cambridge, Mass.: MIT Press.
Rogers, R. & Monsell, S. (1995). The costs of a predictable switch between simple cognitive tasks. Journal of Experimental Psychology: General, 124, 207-231.
Rubinstein, J., Evans, J. & Meyer, D. E. (1994). Task switching in patients with prefrontal cortex damage. Poster presented at the meeting of the Cognitive Neuroscience Society, San Francisco, CA, March, 1994. Abstract published in Journal of Cognitive Neuroscience, 1994, Vol. 6.
Rubinstein, J. S., Meyer, D. E. & Evans, J. E. (2001). Executive Control of Cognitive Processes in Task Switching. Journal of Experimental Psychology: Human Perception and Performance, 27, 763-797.
Yeung, N. & Monsell, S. (2003). Switching between tasks of unequal familiarity: The role of stimulus-attribute and response-set selection. Journal of Experimental Psychology-Human Perception and Performance, 29(2): 455-469.
American Psychological Association, March 20, 2006