Computing Capacity and Performance
The researchers began with an analysis of psychometric tests and discovered that such tests do not take into account the statistical skew of increased knowledge or human experience. As a consequence, when these tests are used to compare age groups, they paint a misleading picture of cognitive development in older adults because they do not “control for” these elements. The researchers hypothesized, then, that many of the assumptions scientists make about cognitive decline are seriously flawed and, for the most part, formally invalid because common measures of cognitive performance do not control for age or experience. The researchers then set out to prove that what is typically taken as measures of or evidence for decline actually is quite the opposite. In fact, basic principles suggest that older adults exhibit greater sensitivity to the nuances of test items than younger adults, and for this reason, their comparative performance on tests may shine a little less brightly.
To prove their theory, the researchers trained computers as though they were humans, reading a certain amount each day, and learning new things along the way. When the computer “read” only so much, its performance on cognitive tests resembled that of a young adult. But when the same computer read as much as a human might over a lifetime, its performance appeared more like that of an older adult. In a word, the computer was slower. This, though, was not a sign that its processing capacity had declined but that its database had grown, giving it more data to process, which inevitably takes more time. In another test, the researchers, with a little help from technology, estimated the number of words an adult could be expected to learn over a lifetime. Then, they loaded their computer with a similar-sized word dataset and performed vocabulary tests, then compared the results to those of a computer loaded with a younger-adult-sized word dataset. Unsurprisingly, the computers took much longer to search for words as the size of their database grew.
“Given that the models run (and can be rerun) on computers, the possibility that any differences in their performance are due to aging hardware can be eliminated; instead, their patterns of performance reflect the information-processing costs that must inevitably be incurred as knowledge is acquired,” wrote the authors, whose work also shows how what is taken to be “evidence” of cognitive decline actually demonstrates an older person’s greater mastery of acquired knowledge. “Once the cost of processing this extra information is controlled for in studies of human performance, findings that are usually taken to suggest declining cognitive capacities can be seen instead to support little more than the unsurprising idea that choosing between or recalling items becomes more difficult as their numbers increase.” If you have more clothes in your closet, it’s harder to pick out an outfit in the morning.
By 2030, 72 million Americans will be aged 65 or older and by 2050, that number should swell to nearly 89 million people, or more than double the number of older adults in the U.S. in 2010. False ideas about cognitive decline, then, could very well exert a negative influence on the lives of millions and millions of adults. Very simply, the researchers concluded, “We hope this can change.”
Source: Ramscar M, Hendrix P, Shaoul C, Millin P, Baayen H. The myth of cognitive decline: Nonlinear dynamics of lifelong learning. Topics in Cognitive Science. 2014.
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