Routine Cognitive Tasks Research Articles

Employment, Wages and Inequality in India: An Occupations and Tasks Based Approach

This paper analyzes the employment and wage trends for Indian workers for the period 2005–2012 by computing the task-content of occupations (Autor et al. in Q J Econ 118(4):1279–1333, 2003a; Autor et al. in Rising Wage Inequality: The Role of Composition and Prices, National Bureau of Economic Research, Cambridge, MA, 2003b; Acemoglu and Autor in Skills, Tasks and Technologies: Implications for Employment and Earnings, 2011; Autor and Dorn 2013). Three main occupation categories are obtained- routine manual, routine cognitive and non-routine cognitive. The analyses reveal evidence of job polarization for India - middle skilled jobs that are most likely to be routine cognitive, have the lowest share in employment, whereas routine manual jobs have much higher shares in employment. Further, the share of non-routine cognitive jobs has been increasing over the period under consideration at the expense of routine manual jobs. While the share of routine cognitive jobs is low, it does not reflect a substantial decline over the period. Finally, while analyzing wage trends the author finds that the average wages of workers engaged in non-routine cognitive tasks is rising the fastest, followed by those engaged in routine cognitive tasks, while average wages of workers in routine-manual tasks have witnessed the lowest rate of growth.

Will the future of knowledge work automation transform personalized medicine?

Today, we live in a world of ‘information overload’ which demands high level of knowledge-based work. However, advances in computer hardware and software have opened possibilities to automate ‘routine cognitive tasks’ for knowledge processing. Engineering intelligent software systems that can process large data sets using unstructured commands and subtle judgments and have the ability to learn ‘on the fly’ are a significant step towards automation of knowledge work. The applications of this technology for high throughput genomic analysis, database updating, reporting clinically significant variants, and diagnostic imaging purposes are explored using case studies.

The Robot as Radiologist

Which tasks are best performed by machines, and which are best performed by humans? Frank Levy and Richard Murnane of the Massachusetts Institute of Technology tackled this question in their 2004 book The New Division of Labor: How Computers Are Creating the Next Job Market [1]. They divided the tasks performed by American workers into 5 broad categories. At the time of publication, technology had already substituted for many workers engaged in 2 of the categories, routine manual tasks and routine cognitive tasks.

A Meta-Analytic Investigation of the Relationship of State and Trait Anxiety to Performance on Figural and Verbal Creative Tasks

Extensive research suggests when and how anxiety has debilitating or facilitating effects on routine cognitive tasks or motor tasks. However, research examining anxiety's relation to performance on creative tasks such as divergent thinking and artistic tasks is less conclusive despite a rather substantial literature. The authors' meta-analytic investigation of 59 independent samples finds that anxiety is significantly and negatively related to creative performance. In addition, the findings provide insights into factors such as task complexity, type of task (i.e., figural or verbal), and type of anxiety (i.e., state or trait) that moderate the relationship between anxiety and creativity-all of which are consistent with the idea that anxiety and creativity present competing cognitive demands. In addition to identifying gaps in the literature such as the need for research using a two-component model of anxiety in relation to creativity, the authors' results have practical implications for those seeking to increase individual creativity.

Sequential list-learning by an adolescent lowland gorilla (Gorilla gorilla gorilla) using an infrared touchframe apparatus

The ability to appropriately sequence a list of discrete items is an important facet in performing routine cognitive tasks and may play a significant role in the acquisition of early communication skills. Though the serial learning abilities of some species, such as chimpanzees and rhesus macaques are well documented, there is virtually no information on the extent of these skills with gorillas. In this study, a young female western lowland gorilla has demonstrated the ability to learn a list of seven Arabic numerals by selecting them on a monitor behind an infrared touchframe. As list length increased (from three to seven), Rollie required fewer trials to reach the criterion, suggesting an acquisition of skills associated with serial learning. Rollie was most likely to correctly select the first item in the sequence and least likely to select the penultimate item in the sequence. Her performance suggests serial learning abilities in the range of other non-verbal species and provides preliminary evidence that supports the assertion that gorillas can succeed at this form of serial learning task.

The Returns to Pencil Use Revisited

Many researchers believe that the observed positive association between computer use and wages simply reflects unobserved heterogeneity: like pencils and other “white-collar” tools, computers are assigned to employees who possess productive attributes that would attract higher wages in any event. This study evaluates that claim by identifying the mechanisms through which computers changed the wage structure in West Germany in the late 1990s. The author finds that the spread of computers—but not of pencils—shifted the task composition of occupations toward analytical and interactive tasks that are complementary to computers' capabilities, and away from routine cognitive and manual tasks for which computers tend to substitute. Employees possessing computer-complementary skills enjoyed wage increases because computers both raised the demand for their skills and increased their marginal product.

The Returns to Pencil Use Revisited

Many researchers believe that the observed positive association between computer use and wages simply reflects unobserved heterogeneity: like pencils and other whitecollar tools, computers are assigned to employees who possess productive attributes that would attract higher wages in any event. This study evaluates that claim by identifying the mechanisms through which computers changed the wage structure in West Germany in the late 1990s. The author finds that the spread of computers - but not of pencils - shifted the task composition of occupations toward analytical and interactive tasks that are complementary to computers’ capabilities, and away from routine cognitive and manual tasks for which computers tend to substitute. Employees possessing computer-complementary skills enjoyed wage increases because computers both raised the demand for their skills and increased their marginal product.

The Skill Content of Recent Technological Change: An Empirical Exploration

We apply an understanding of what computers do to study how computerization alters job skill demands. We argue that computer capital (1) substitutes for workers in performing cognitive and manual tasks that can be accomplished by following explicit rules; and (2) complements workers in performing nonroutine problem-solving and complex communications tasks. Provided these tasks are imperfect substitutes, our model implies measurable changes in the composition of job tasks, which we explore using representative data on task input for 1960 to 1998. We find that within industries, occupations and education groups, computerization is associated with reduced labor input of routine manual and routine cognitive tasks and increased labor input of nonroutine cognitive tasks. Translating task shifts into education demand, the model can explain sixty percent of the estimated relative demand shift favoring college labor during 1970 to 1998. Task changes within nominally identical occupations account for almost half of this impact.

The Skill Content of Recent Technological Change: An Empirical Exploration

We apply an understanding of what computers do -- the execution of procedural or rules-based logic -- to study how computer technology alters job skill demands. We contend that computer capital (1) substitutes for a limited and well-defined set of human activities, those involving routine (repetitive) cognitive and manual tasks; and (2) complements activities involving non-routine problem solving and interactive tasks. Provided these tasks are imperfect substitutes, our model implies measurable changes in the task content of employment, which we explore using representative data on job task requirements over 1960 -- 1998. Computerization is associated with declining relative industry demand for routine manual and cognitive tasks and increased relative demand for non-routine cognitive tasks. Shifts are evident within detailed industries, within detailed occupations, and within education groups within industries. Translating observed task shifts into educational demands, the sum of within-industry and within-occupation task changes explains thirty to forty percent of the observed relative demand shift favoring college versus non-college labor during 1970 to 1998, with the largest impact felt after 1980. Changes in task content within nominally identical occupations explain more than half of the overall demand shift induced by computerization.