18 Automatic Processing Examples

18 Automatic Processing ExamplesReviewed by Chris Drew (PhD)

This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.

automatic processing examples and definition, explained below

Automatic processing refers to mental activity that does not require conscious effort or control. There are some cognitive tasks that an individual can perform without even thinking about it. In some cases, there simply is no need to expend a great deal of mental effort or concentration to perform a given task.

Researchers usually define automatic processing according to three criteria. For example, Posner and Snyder (1975) define automatic processing as conforming to three conditions:

  1. It occurs without intention
  2. It operates outside of conscious awareness
  3. It does not interfere with other cognitive processes

Schneider and Shiffrin (1977) state that automatic processing:

“…is activated automatically without the necessity for active control or attention by the subject” (p. 2).

Broadbent (1958) mentions the unconscious nature of automatic processing:

“A practised action may be brought to the point at which the performer does not remember whether he has performed it or not” (p. 55).

By combining the elements of these criteria, we can describe automatic processing as being unintentional, involuntary, mentally effortless, in parallel with other cognitive tasks, and occurring outside of conscious awareness.

Automatic Processing vs. Effortful Processing

There are three fundamental differences between automatic and effortful processing (aka controlled processing).

  1. First, automatic processing does not require attention or conscious awareness, whereas effortful processing requires both. In fact, automatic processing can occur without conscious awareness, but still impact thinking processes, judgments, and behavior.
  2. Secondly, automatic processing can occur in parallel with other cognitive activities, whereas effortful processing occurs serially. This difference is due to limits on cognitive capacity. Each person has limited cognitive capacity, which means that only a specific amount of cognitive resources can be devoted to a specific task. Automatic processing absorbs zero, or near zero, cognitive capacity. Therefore, it does not disrupt other mental activity. In can be carried out in parallel with other cognitive tasks. However, effortful processing uses up cognitive capacity and therefore cannot operate in parallel with other tasks.
  3. Third, automatic processing occurs without intention or control. In fact, it can be nearly impossible to stop some forms of automatic processing, such as those involved in priming or implicit memory and bias.

18 Automatic Processing Examples

  • In Advertising: At the heart of many ad campaigns is a repeated pairing of a product and celebrity. After enough repetitions, when the consumer walks through the aisle of a supermarket and sees the product, they automatically associate with the celebrity. This increases the probability of reaching for the product.
  • Brushing Teeth: This is a task so frequently performed that most people don’t need to think about it. They know how to put toothpaste on the brush, how to move the brush around their mouth, and how long to brush without any conscious thought.
  • Riding a bicycle: Although at first quite challenging, after months of practice it is possible to keep one’s balance, steer, and avoid obstacles with very little cognitive effort.
  • Reading: For most literate adults, the process of recognizing letters and words is automatic. They don’t have to think about each individual letter or word; instead, their brain automatically recognizes and processes them. However, for children learning to read, it may require significant effortful processing.
  • Processing Facial Images: When looking at a person’s face we immediately process the emotional valence of their expression. It is so automatic that it might be impossible to not do it.  
  • Handwriting: Similarly to reading, once someone has learned how to write, the act of handwriting is automatic. This includes recognizing and forming letters, spacing words, and even developing a personal style.
  • In Teacher Expectations: Although not intentional or conscious, a physics teacher may hold certain gender-based expectations that could affect how they interact with male and female students.
  • Recognizing Sounds: The sound of a car horn, a barking dog, or a ringing telephone are immediately recognized and processed without needing to consciously think about it.
  • Driving the Everyday Route: After months of driving the same route to work every day, it is possible to perform the task while on automatic pilot. Most people are fully engaged in other cognitive activities while driving, such as planning their day’s work or thinking about the weekend.
  • Typing on a Keyboard: For individuals who are proficient at typing, this is an automatic process. They don’t have to look at each key as they type; their fingers automatically go to the correct keys.
  • Delivering a Well-Rehearsed Speech: When a person has delivered the same speech time and time again, for years, they don’t have to think about what they are going to say. The words flow effortlessly. This allows them to monitor their pace and tone of voice to ensure maximum impact.
  • Walking: This is another task that becomes automatic with time. After a certain age, people don’t need to think about each step they take. They can walk and simultaneously engage in other tasks, such as talking or thinking about something else.
  • Playing a Musical Instrument: Any experienced musician will tell you that they can play many songs without needing to think about the process. The songs have been performed so often that they can play each automatically.
  • In Predicting Outcomes: Sometimes, based on past experiences, people can predict outcomes without even realizing it. For instance, catching a ball requires an automatic calculation of the ball’s trajectory based on its speed and direction.
  • Buttoning a Shirt: Although the dexterity to button a shirt may seem complex, after years of practice it no longer requires any cognitive effort at all. It can be accomplished while working out one’s to-do list for work later that day, being engaged in a conversation with one’s partner, or recalling past events.
  • In Stereotypes: When an elderly person enrolls in a class on Python and data visualization, younger students may possess stereotypes about their computer skills and ability to learn how to use modern software.
  • Playing a Video Game: After playing the same game for weeks, it is possible for a person to move seamlessly through the first stages of the game with almost no effort at all. All of the right moves have been memorized and engaged so many times before, that it might actually become boring to play.
  • Eating: This is a task that requires very little cognitive effort. People know how to use utensils, how to chew, and how to swallow without having to consciously think about each step in the process.

Origins of Automatic Processing

Schneider and Chein (2003) inform us that William James (1890) may have been the first to suggest that human cognition could consist of two types of processing.

Although not referring to “effortful” or “controlled” processing explicitly, James did use the term “automatic” to describe the relation between the two:  

“But actions originally prompted by conscious intelligence may grow so automatic by dint of habit as to be apparently unconsciously performed. Standing, walking, buttoning and unbuttoning, piano-playing, talking, even saying one’s prayers, may be done when the mind is absorbed in other things” (p. 18).

Relationship Between Automatic and Effortful Processing

Although usually discussed in terms of being a dichotomy, the relationship between automatic and effortful processing exists on a continuum (Hartlage et al., 1993).  

A task which began requiring effortful processing may become automatic with repetition.

For example, reading is a cognitive activity which is quite difficult in the beginning; it requires substantial mental effort.

When first learning to read a simple word such as “cat,” a child must think about how to pronounce each letter. This takes time, is performed sequentially (and slowly), requires control over one’s attention, and operates with conscious awareness.

However, with repetition, eventually the task becomes automatic. The child will be able to read the word without using much cognitive capacity at all. 

Fast forward after several years of reading, and the entire process is automatic. In fact, it is possible to actually engage in the task of reading without direct attentional control and in parallel to other cognitive activity.

How is that possible you say? Ever read a paragraph and then realize you didn’t actually comprehend any of it because your mind was a million miles away daydreaming?

This is an example of just how automatic a once demanding effortful processing task can become over time and with repetition.

Applications of Automatic Processing

1. Heuristics and Automatic Processing

Heuristics are metal shortcuts that people use to make decisions and form judgments (Simon, 1955). Heuristics became the focus of study in the 1970s by psychologists Tversky and Kahneman (1974).

Since then, the area of study has expanded and a large number of heuristics and cognitive biases have been identified. For instance, there has been an incredibly large number of studies conducted on heuristics in psychology, leading to an astounding 727,000 results in Google Scholar.

The availability heuristic and the representative heuristic are two of the most well-known. The availability heuristic posits that information that comes to mind most easily will be used in forming a judgment.

For example, when estimating the safety of traveling by plane or car, most will conclude that traveling by car is far safer. However, statistically speaking, air travel is safer.

The reason for this faulty estimate is that information regarding plane crashes is more strongly encoded in memory due to their dramatic nature. This makes recalling information about crashes easier, which then influences our judgment.

The representativeness heuristic involves making a judgment about an individual based on how closely they resemble a prototypical example.

For instance, if meeting someone for the first time that is calm, wearing thick glasses, and seems a bit nerdy, we may be more likely to conclude that they are an accountant than a heavy metal musician.

Reliance on these heuristics happens automatically, outside conscious awareness, and involve very little if any cognitive capacity.

Similarly, Chaiken and Ledgerwood (2012; Chaiken, 1980) propose a heuristic-systematic model that proposes two routes to persuasion and thinking about information. Systematic processing involves deep thinking and intensive reasoning.

Heuristic processing “involves focusing on salient and easily comprehended cues” and “is more efficient and relatively automatic” (Chaiken & Ledgerwood, 2012, p. 246).

Message characteristics will lead to one of the two routes being activated in the consumer, with the heuristic route being automatic.

2. Implicit Bias in Stereotyping and Prejudice

Modern research on stereotyping and prejudice often utilize a theoretical model which views these phenomenon as a result of automatically activated implicit bias (Devine, 1989; Dovidio, 2001).

Because stereotypes have been frequently encoded, the association between a member of a particular social group and the stereotype is automatically activated when encountering that a group representative (Smith & Branscombe, 1988; Dovidio, Evans, & Tyler, 1986).

For example, in one of the first studies on the automatic activation of stereotypes, Gaertner and McLaughlin (1983) demonstrated that research participants more rapidly identified racial stereotype-consistent versus racial stereotype inconsistent stimuli.

Other studies have found implicit biases in the form of stereotypes regarding: gender roles of self and others (Higgins & King, 1981), gender-biased perceptions of assertiveness (Rudman and Glick, 2001), in nursing practices (Narayan, 2019), young adults’ automatic bias against the elderly (Levy & Banaji, 2002), and how facial characteristics of defendants affect sentencing (Johnson & King, 2017).

3. Research on Inhibiting Automatic Implicit Bias

Blair (2002) identified over 50 studies on the malleability of automatic stereotypes and prejudice. For example, Sinclair and Kunda (1999) found that research participants could inhibit their use of negative stereotypes when it benefited their self-image.

Sechrist and Stangor (2001) found that automatic stereotypes could be moderated if those stereotypes were inconsistent with social norms.

Unfortunately, the bulk of these studies only assessed short-term malleability of automatic implicit bias (Lai et al., 2016).

A meta-analysis of 585 studies on changing implicit bias by Forscher et al. (2016) found that only 22 examined if the change persisted beyond a single experimental session.

Lai et al. (2016) conducted two studies involving over 6,000 participants, applying nine interventions designed to reduce implicit bias. The results indicated that:

“these interventions did not change explicit racial preferences and were not reliably moderated by motivations to respond without prejudice” (p. 2).

Despite these disheartening results, there are examples of successful interventions. For instance, taking a semester-long class on prejudice (Rudman, Ashmore, & Gary, 2001) or having a college roommate of a different race (Shook & Fazio, 2008) can produce longer-term changes in stereotype beliefs.

These studies took place in real-world settings, which may be more effective in changing biases for a variety of reasons (Lai et al., 2016).

Conclusion

Automatic processing occurs without using a lot of cognitive resources, requires no attentional control or intention, and occurs outside conscious awareness.

Many tasks in daily life can be performed more or less automatically as a result of repetition. Driving to work, getting dressed, even typing on a keyboard are tasks which have been done so frequently that they no longer require significant mental effort.

One of the most heavily researched applications of automatic processing concerns the activation of stereotypes. Because of the frequency of associations between certain social groups and specific characteristics, those stereotypes can be easily activated from memory and then affect behavior.

Although research has attempted to identify strategies to inhibit automatic activation of stereotypes, most have failed to demonstrate long-term effects.   

References

Banaji, M. R. (2001). Implicit attitudes can be measured. The nature of remembering: Essays in honor of Robert G. Crowder, 117-150.

Bertrand, M., & Duflo, E. (2017). Field experiments on discrimination. Handbook of Economic Field Experiments, 1, 309-393.

Blair, I. V. (2002). The malleability of automatic stereotypes and prejudice. Personality and Social Psychology Review, 6(3), 242-261.

Broadbent, D. E. (1958). Perception and communication. New York: Pergamon.

Chaiken, S. (1980) Heuristic versus systematic information processing and the use of source versus message cues in persuasion. Journal of Personality and Social Psychology, 39, 752–766

Chaiken, S., & Ledgerwood, A. (2012). A theory of heuristic and systematic information processing. Handbook of Theories of Social Psychology, 1, 246-266.

Cohen, R., Lohr, I., Paul, R., & Boland, R. (2001). Impairments of attention and effort among patients with major affective disorders. The Journal of Neuropsychiatry and Clinical Neurosciences, 13(3), 385-395.

Cohen, R. A. (2013). The neuropsychology of attention. Springer Science & Business Media.

Devine, P. G. (1989). Stereotypes and prejudice: Their automatic and controlled components. Journal of Personality and Social Psychology, 56(1), 5.

Dovidio, J. F., Evans, N., & Tyler, R. B. (1986). Racial stereotypes: The contents of their cognitive representations. Journal of Experimental Social Psychology, 22(1), 22-37.

Dovidio, J. F., Gaertner, S. L., & Saguy, T. (2009). Commonality and the complexity of “we”: Social attitudes and social change. Personality and Social Psychology Review, 13(1), 3-20.

Gaertner, S. L., & McLaughlin, J. P. (1983). Racial stereotypes: Associations and ascriptions of positive and negative characteristics. Social Psychology Quarterly, 46, 23-30.

Hartlage, S., Alloy, L. B., Vázquez, C., & Dykman, B. (1993). Automatic and effortful processing in depression. Psychological Bulletin, 113(2), 247.

Hasher, L., & Zacks, R. T. (1979). Automatic and effortful processes in memory. Journal of Experimental Psychology: General, 108(3), 356.

James, W. (1890). The principles of psychology (Vol. 1). New York: Holt.

Johnson, B. D., & King, R. D. (2017). Facial profiling: Race, physical appearance, and punishment. Criminology, 55(3), 520-547.

Kahneman, D. (1973). Attention and effort (Vol. 1063, pp. 218-226). Englewood Cliffs, NJ: Prentice-Hall.

Lai, C. K., Skinner, A. L., Cooley, E., Murrar, S., Brauer, M., Devos, T., … & Nosek, B. A. (2016). Reducing implicit racial preferences: II. Intervention effectiveness across time. Journal of Experimental Psychology: General, 145(8), 1001.

Levy, B. R., and Banaji, M. R. (2002). Implicit Ageism. In T. D. Nelson (Ed.), Ageism: Stereotyping and Prejudice against Older Persons. Cambridge. MA: The MIT Press.

Narayan M. C. (2019). CE: Addressing Implicit Bias in Nursing: A Review. The American journal of nursing, 119(7), 36–43

Posner, M. I., & Snyder, C. R. R. (1975). Attention and cognitive control. In R. L. Solso (Ed.), Information processing and cognition: The Loyola symposium (pp. 55–85). Hillsdale, IN: Erlabaum.

Posner, M. I., Snyder, C. R., & Solso, R. (2004). Attention and cognitive control. Cognitive Psychology: Key Readings, 205, 55-85.

Petty, R.E. and Cacioppo, J.T. (1986). The Elaboration Likelihood Model of Persuasion. Advances in Experimental Social Psychology, 19, 123-205.
https://doi.org/10.1016/S0065-2601(08)60214-2

Rudman, L. A., & Glick, P. (2001). Prescriptive gender stereotypes and backlash toward agentic women. Journal of social issues, 57(4), 743-762.

Rudman, L. A., Ashmore, R. D., & Gary, M. L. (2001). ” Unlearning” automatic biases: The malleability of implicit prejudice and stereotypes. Journal of Personality and Social Psychology, 81(5), 856.

Schneider, W., & Chein, J. M. (2003). Controlled & automatic processing: behavior, theory, and biological mechanisms. Cognitive Science, 27(3), 525-559.

Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing: I. Detection, search, and attention. Psychological Review, 84(1), 1–66.

Sechrist, G. B., & Stangor, C. (2001). Perceived consensus influences intergroup behavior and stereotype accessibility. Journal of Personality and Social Psychology, 80(4), 645.

Shook, N. J., & Fazio, R. H. (2008). Interracial roommate relationships: An experimental field test of the contact hypothesis. Psychological Science, 19(7), 717-723.

Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics, 99-118.

Sinclair, L., & Kunda, Z. (1999). Reactions to a black professional: motivated inhibition and activation of conflicting stereotypes. Journal of Personality and Social Psychology, 77(5), 885.

Smith, E. R., & Branscombe, N. R. (1988). Category accessibility as implicit memory. Journal of Experimental Social Psychology, 24(6), 490-504.

Tversky, A. & Kahneman, D. (1974) Judgment under uncertainty: Heuristics and biases. Science, 185, 1124–31.


Tversky, A. & Kahneman, D. (1981) The framing of decisions and the psychology of choice. Science, 211, 453–8.

Wang, C. E., Brennen, T., & Holte, A. (2006). Automatic and effortful processing of self‐statements in depression. Cognitive Behaviour Therapy, 35(2), 117-124.

Website | + posts

Dr. Cornell has worked in education for more than 20 years. His work has involved designing teacher certification for Trinity College in London and in-service training for state governments in the United States. He has trained kindergarten teachers in 8 countries and helped businessmen and women open baby centers and kindergartens in 3 countries.

Website | + posts

This article was peer-reviewed and edited by Chris Drew (PhD). The review process on Helpful Professor involves having a PhD level expert fact check, edit, and contribute to articles. Reviewers ensure all content reflects expert academic consensus and is backed up with reference to academic studies. Dr. Drew has published over 20 academic articles in scholarly journals. He is the former editor of the Journal of Learning Development in Higher Education and holds a PhD in Education from ACU.

Leave a Comment

Your email address will not be published. Required fields are marked *