Wednesday, December 25, 2019

The Effect of Cognitive Load on Processing Resources, Inhibition, and Thought Revision

I developed the following manuscript intending to submit if for peer review. I never submitted or published it, but I post it here because it contains original data, and a literature review that might help someone research a related topic.

The Effects of Cognitive Load on Covert Stereotype Propensity

In cognitive psychology people are often considered to be limited capacity processors and when their capacities are strained, they are susceptible to making mistakes and omissions. The literature has demonstrated that cognitive load, by means of task engagement, facilitates overt stereotyping by decreasing the capacity to self-monitor evidence of biases. The present study was designed to test whether covert stereotyping, where the participant is not aware of the stereotype being activated, is also facilitated by cognitive load.  This study featured a 2 (Presentation: no task requirement vs. digit rehearsal task) X 2 (sex: male vs. female) X 2 (race: white vs. black) mixed factorial design with the task condition manipulated within subjects.  In the experimental group, a number rehearsal task was used to administer cognitive load.  Half of the participants were engaged in this task and the other half, the control group, were simply given the same number to observe, but they were not instructed to rehearse it.  Both groups completed the Modern Racism Scale. Because the scale assesses stereotyping propensity under the guise of surveying political attitudes the scores on this scale are well accepted to show a reliably positive correlation with covert stereotyping propensity. The study found that there was not a statistically significant difference between the control and experimental groups. Gender, but not race, produced significant differences. The findings of this study suggest that cognitive load, through digit rehearsal, does not lead to an increased propensity for covert stereotyping.

A great deal of research supports the idea that both information processing demands (e.g. Bodenhausen & Wyer, 1985; Stangor and Duan, 1991) and information processing concerns (e.g. Erber & Fiske, 1984; Pendry & Macrae, 1999) can strongly influence a perceiver’s propensity to activate and apply stereotypes.  Whether stereotyping, which is the formulation an oversimplified or biased opinion, is intentional or automatic it all too often results in the attribution of unfair negative characteristics to out-group members (Pendry & Macrae, 1999).  These are normally the kind of negative associations that people do not want to share publicly, and so if they can, they will attempt to monitor these, disallowing them from their outward communications (Bodenhausen, 1990). Monitoring outward communications in this way requires cognitive processing resources, something that people have in limited supply.
A large body of research has shown that when processing resources are low due to the fact that they are distributed between different tasks, performance on each task suffers. Cognitive load (the detrimental effect that task engagement has on the performance of working memory) can affect many forms of parallel processing and can even impact the ability to monitor prejudice within verbal discourse (Bodenhausen & Wyer, 1985).  This literature has suggested explicitly that most people continually utilize their processing resources to censor evidence of their own biases and that this is made even more difficult under the condition of cognitive load (Wyer & Martin, 1986).  A deficit in mental resources caused by multiple task engagement has been shown to influence individuals to make more prejudiced responses by diminishing their capacity to inhibit biased personal thoughts and subsequently to revise biased interpersonal language (Fiske & Neuberg, 1990). 
Research has shown that a variety of dissimilar methods for limiting a subject’s cognitive resources can result in the preferential recall for stereotype-consistent information.  Methods that involve distracting subjects with an unrelated audio broadcast (Stangor & Duan, 1991), overwhelming them by expecting them to observe multiple groups items (Stangor & Duan, 1993), instructing them to engage in digit rehearsal tasks (Sherman, Lee, Bessenoff & Frost, 1998), using other forms of rehearsal tasks (Pendry & Macrae, 1999) and implementing a variety of other methods for administering cognitive load (Sherman & Frost, 2000) have all been shown to increase the propensity for stereotype formation.  Each of the 5 studies cited above uses procedures to study stereotype formation that are obvious to the participants.  Even the particular stereotype that they were trying to invoke can clearly be discerned and each study assumed that the majority of participants would have wanted to inhibit evidence of their prejudice but were less able to due to the diminishment of their processing resources.
Stangor and Duan (1991) found that by simply asking participants to attend to specific sounds during a radio broadcast, that they could create cognitive load during task engagement.  Here cognitive load vastly decreased the ability of the participants to censor stereotype formation (p<.05). Two years later, Stangor and Duan (1993) required that participants attend to associations related to multiple out-groups, making it more difficult to determine which stereotypes were being tested.  Again the experiment showed that cognitive load results in significant (p<.05) increases in the number of stereotype related biases.  Sherman et al. (1998) found similar results five years later when distracting participants with a digit rehearsal task.  This study, and their next one, (Sherman & Frost, 2000) showed that digit rehearsal caused their participants to become significantly (p<.05) less likely to inhibit evidence of bias despite the fact that they recognized the majority of stereotypes presented to them. Pendy and Macrae (1999) used either a series of letters or symbols for their rehearsal task and, interestingly, they found that a significant (p<.05) proportion of the participants in the experimental group reliably chose the biased response while completing their stereotype identification task.  Subsequent studies have replicated these findings, lending support to the present research hypothesis.  However, each of these studies relied on overt stereotype formation, where the stereotype presented in each task is easily identified and evidence of the subject’s identification of the stereotype is clearly indicated by their response to the tasks questions (Sherman & Frost, 2000). In other words, in these experiments, the subject was should have been relatively aware each time they gave a biased response.
            This is the first experiment that uses a carefully constructed, covert survey instrument like the Modern Racism Scale in an experiment involving cognitive load. The Modern Racism Scale is designed to be a nonreactive measure of prejudice presented under the guise of surveying political attitudes (McConahay, Hardee & Batts, 1981). This guise puts those surveyed at ease and makes them less conscious about the biases that might be found in their responses. The use of such an instrument should test a different hypothesis because, unlike the procedures used in the aforementioned studies, it measures implicit as opposed to explicit stereotype formation. 
This study was designed to determine how cognitive load, in the form of a number rehearsal task, effects information processing demands and relates to the propensity to activate stereotypes. Prejudice will be assessed by the numerical score on the Modern Racism Scale (McConahay, 1986). This controlled experiment required subjects to evaluate a questionnaire while performing a task designed to increase cognitive load.  The task consisted of the memorization and constant rehearsal of a seven digit number throughout the experimental proceedings, a common procedure for inducing cognitive load (Sherman & Frost, 2000).  While the subject rehearsed this number the experimenter administered the Modern Racism Scale, a survey where the subject finds it more difficult to identify the stereotypes that they unwittingly activating and committing to (Bodenhausen, 1990). The present researcher predicts that engagement in the digit rehearsal task might lead to a diminishment in processing resources but that because the stereotypes in this particular questionnaire are covert, cognitive load will not will not increase stereotyping propensity. If this hypothesized effect does occur it should be because when stereotype assessment is covert, cognitive processing resources cannot help a person to inhibit evidence of their mental biases. 
Many people in modern society are known to rely on stereotypes and use them as cognitive heuristics to inform their schemas and to facilitate everyday information processing.  Many group based stereotypes, though, have the potential to harm ingroup and outgroup members.  By determining which types of processing modalities facilitate stereotyping, we can better understand how stereotypes are actualized within an individual, how stereotypes are perpetuated and possibly how prejudice, a culturally derisive phenomenon, can be better mitigated. 
A total of 302 Pepperdine undergraduate students of ages 18 to 23 took part in this study. Each of the 134 male and 168 female students had graduated from high school and lived in the greater Los Angeles area. 40 subjects were black, 262 subjects were white.  Participants were recruited through the use of flyers, and by word of mouth. 
The study was an experimental, randomized controlled trial featuring a 2 (Presentation: no task requirement vs. digit rehearsal task) X 2 (sex: male vs. female) X 2 (race: white vs. black) mixed factorial design with the task condition manipulated within subjects.
The variables in studies like this one have been clearly operationally defined and this so should be relatively easy to replicate.  One factor that may affect internal validity is the assumption that digit rehearsal increases stereotype propensity due to cognitive load.  It is possible that frustration with task requirements increase negative affect and for this reason increase stereotype propensity.  This is a very difficult confounding factor to control but the literature generally accepts the notion that digit rehearsal is a reliable task to administer cognitive load. Experimenters were instructed to present the task requirements to participants in a friendly, amiable manner in an effort to minimize negative affect.
The materials used included the McConahay (1986) Modern Racism Scale, which is administered to test for subtle forms of racism that are prevalent in the modern day US.  This scale uses a response format that asks participants to indicate their agreement numerically; with numbers ranging from -2 (strongly disagree) to 0 (neither agree nor disagree) to +2 (strongly agree).  A higher score on this scale indicates more blatant racism, which will give us our measure of stereotype formation.  
A separate demographic questionnaire followed the scale.  This questionnaire requested information about age, race, handedness, sex and number of years in college.  This questionnaire did not request any information that would allow the participant to be identified, allowing complete anonymity.
Individuals from this sample of convenience chose to participate in this experiment after encountering flyers or verbal requests.  The study began with the participant being welcomed into the office by the experimenter, escorted to a private room with a desk where they would remain for the duration of the study.  Next, the participant was given a cover letter (Appendix B) and asked to fill out an informed consent form (Appendix C) that advised them about the risks associated with the study and required them to signature, indicating that they understood and agreed to the details of the experiment.
Before the administration of the questionnaires, one half of the subjects were randomly assigned to the task engagement group and given 25 seconds to rehearse an 8 digit number.  The participants in the task condition were informed that upon completion of the experiment they will be required to reproduce this number.  Previous research has consistently demonstrated that digit rehearsal tasks such as this one have debilitating effects on processing resources.   That is, throughout the experimental task, they expend conscious resources rehearsing the 8-digit number and this influences their allocation of attentional resources to the experiment proper.
The control group was given 25 seconds to rehearse the same 8 digit number. Like the other group they were asked to memorize it but then were told that they would not be asked to reproduce the number upon completion of the experiment.
To ensure anonymity all subjects were isolated from the other participants and, after the necessary instructions had been given, from the experimenter as well.  Written instructions informed subjects that the questionnaire that they were expected to respond to was created to help researchers better understand political attitudes. 
Subjects were then required to complete the seven-item Modern Racism Scale.  This scale is designed to measure subject’s racial stereotyping behavior in a covert, nonreactive fashion.   Subjects responded to the questionnaire by indicating if they agree or disagree with specific race-oriented statements.  The questionnaire took none of the participants more than 20 minutes to complete.
Before participants in the experimental group placed their questionnaires in their envelope, as instructed, they were visited by an experimenter who requested that they reproduce the number that they had been rehearsing.  The experimenter then discarded any questionnaires taken by subjects that could not reproduce the entire series of numbers, these were not included in the statistical analyses.  These questionnaires were discarded because they may represent a case where the participant did not carefully rehearse their number, did not experience cognitive load, and so did not fulfill the requirements of the experiment. In fact, 27 questionnaires were discarded for this very reason.
Subjects placed their responses in an unmarked envelope, and then dropped the envelope into the box that corresponded to their experimental group, both of which contained many envelopes.  Finally subjects were debriefed and thanked for their participation. 
Data Analysis
            The data collected were analyzed by computing the mean scores on the Modern Racism Scale and using them to perform a linear regression with score as the dependent variable and gender, race and experimental group as the independent variables.  It was assumed that the independent variables might be correlated with one another, so a multiple regression analysis was also performed in order to find out if the predictor variables add independent information to the prediction equation.  Differences between groups would only be interpreted as significant if they satisfy a p-value less than .05.
Supporting the hypothesis, there was no significant difference in scores between the control group (M= -.403 ,SD= 1.212) and the experimental group (M= -.423, SD=1.114) as measured by the participant’s scores on the Modern Racism Scale (p-value <.05).  It seems that task engagement did not increase the propensity for a racist score (a higher score) on the racism scale. The averages for individual groups are shown in table 1 below. The means for each group were calculated by using the average score, from -2 to 2 for each item on the scale rather than from the total score for each participant.

Table 1: Mean Scores for Control and Experimental Groups
                        Control                                                Experimental
                        M            SD         n                            M             SD        n
Male                -.561       2.42       70                           -.580        2.07      64
Female             -.286       1.03       83                           -.305        1.19      85
Black               -.413       2.13       18                           -.391        2.22       22
White              -.418       1.81       135                         -.421        2.10      127
Total                -.403       1.21        153                        -.423        1.11       149
A linear regression was performed with score on the Modern Racism Scale as the dependent variable, and 3 predictor or independent variables: gender, race and experimental group. The regression equation from the data set was:
Predicted Score = -.726 + .133*Experimental Group + .160*Gender + .149*Race   
It seems that only gender, with a significance level of .022, played a role as a significant factor (at a p level <.05) in racism score.  Neither experimental group nor race was significant contributors to racism score. The regression coefficients, starting with an intercept constant of -.726, for each predictor were as follows: .133 for the experimental group, .160 for gender, and .149 for race. 
The main hypothesis that task engagement will have no effect on score on the Modern Racism Scale was supported. This experiment suggests that sometimes situational characteristics may play a smaller role in stereotype formation than once thought by others such as Spears and Haslam (1997), Oakes and Turner (1990) and Medin (2000).  Since the participants in the present study were not exposed to blatant, overt depictions of stereotypical behavior, they may not have formed stereotypes due to conscious, deliberative attempts to understand social groups, but instead have automatically activated the heuristic based stereotypes due to a paucity of processing resources.  Why race did not produce significant results is not known and the paucity of research in this area leaves this question open to further investigation. 
            Because the scale that was used measures covert bias, and because cognitive load did not affect stereotyping, the current findings suggest that people do not engage in conscious self-monitoring when they take the Modern Racism Scale. Knowledge that some forms of stereotyping and racism can increase even when processing resources are at their fullest may be informative for social psychology researchers (Fiske and Taylor (1991). This may be an important issue and should motivate psychologists to determine exactly how and under what circumstances cognitive load can create subconscious biases.
Previous studies have emphasized the importance of analyzing the effects of cognitive load on stereotype formation from a variety of perspectives in order to determine how stereotypes are formed (Stangor & Duan, 1991; 1993).    It is suggested that future studies increase the sample size of the experimental group to increase validity.  It may also be important to ensure that the number of black participants and the number of male participants are increased in these samples because the present study had a relatively low number of both of theses groups.  The use of a more ethnically diverse sample, along with other means of stereotype assessment should shed even more light on the issue.  It is also recommended that future replications of this study design implement alternative forms of task engagement (besides digit rehearsal) to administer cognitive load.  This will allow researchers to better understand how and why stereotypes are formulated outside of the experimental sphere, in everyday interpersonal interactions.

Bodenhausen, G. V. (1987). Social stereotypes and information-processing strategies: the impact of task complexity. Journal of Personality and Social Psychology, 52,871-880.
Bodenhausen, G. V. & Wyer, R. S. (1985). Effects of stereotypes on decision making and information processing strategies. Journal of Personality and Social Psychology, 48,267-282.
Erber, R. & Fiske, S. T. (1984). Outcome dependency and attention to inconsistent information.  Journal of Personality and Social Psychology, 47, 709-726.
Fiske, S. T., & Neuberg, S. L. (1990). A continuum of impression formation, from category based to individuating processes: Influences of information and motivation on attention and interpretation. In M.P. Zanna (ed.), Advances in Experimental and Social Psychology, (Vol. 23, pp. 1-74). New York: Academic Press.
Fiske, S. T. & Taylor, S.E. (1991). Social Cognition. New York: McGraw Hill.
McConahay, J. B. (1986). Modern racism, ambivalence, and the modern racism scale. In J. F. Dovidio & S. L. Gaertner (eds.), Prejudice, discrimination and racism (pp. 91- 126). New York: Academic.
McConahay, J. B., Hardee, B. B. & Batts, V. (1981). Has racism declined in America? It depends on who is asking and what is asked. Journal of Conflict Resolution, 25, 563-579.
Medin, D.L. (2000) Are there kinds of concepts? Annual Review of Psychology, 51,121-147.
Oakes, P.J. & Turner, J.C. (1990). Is limited information processing the cause of social stereotyping? European Review of Social Psychology, 11,111-135.
Pendry, L.F. & Macrae, C.N. (1999). Cognitive load and person memory: the role of perceived group variability. European Journal of Social Psychology, 29,925-942.
Sherman, J. & Frost, L.A. (2000). On the encoding of stereotype-relevant information under cognitive load. Personality and Social Psychology Bulletin, 26, 26-34.
Sherman, J.L.A., Bessenoff, G. & Frost L. (1998) Stereotype efficiency reconsidered: Encoding flexibility under cognitive load. Journal of Personality and Social Psychology, 26, 132-138.
Spears, R., Oakes, P.J., Ellemers, N. & Haslam, S.A. (eds.) (1997) The social psychology of stereotyping and group life. Oxford, UK and Cambridge, MA: Blackwell.
Stangor, C. & Duan C. (1991). Effects of multiple task demands upon memory for information about social groups. Journal of Experimental Social Psychology, 27,357-378.
Stangor, C. & Duan C. (1993). Effects of task demand upon stereotype formation. Journal of Experimental Social Psychology, 29, 121-127.
Wyer, R. S. & Martin, L. L. (1986). Person memory: The role of traits, group stereotypes, and specific behaviors in the cognitive representation of persons.  Journal of Personality and Social Psychology, 50, 661-675.

Appendix A
Demographic Survey

1. What is your age? ______

2. How many years have you been in college? _______

3. What is your ethnicity? _______

4. Are you male or female? _______

5. Are you right or left handed? _______

Appendix B

Cover Letter for Proposed Research Study

June 1, 2006

Dear Prospective Participant,

You have been selected to participate in an experiment that may have important ramifications for psychological research.  Please review the information on the following page in order to make a decision concerning your consent to participate in this study.  Also if you choose to participate in this study please make an effort to follow the guidelines given.


Primary Investigator

Appendix C

Pepperdine University, Los Angeles
Office for Protection of Research Subjects
General Campus Human Subject Protection Committee


Consent to Participate in Research

The Effects of Task Engagement on Stereotype Propensity and Score on the
Modern Racism Scale: An Experimental Study

You are asked to participate in a research study conducted by Jared Reser, from the psychology department at the University of Pepperdine. You were selected as a possible participant in this study because you are in the psychology undergraduate subject pool.

Purpose of the Study
This study has been designed to investigate the subtleties of stereotype formation.

If you volunteer to participate in this study, we would ask you to do the following things:
You will be placed in a room by yourself and asked to look at or memorize an 8 digit number, you will then be asked to complete a questionnaire known as the Modern Racism Scale.  When you are finished you will be asked to place your responses to the scale in an envelope to ensure anonymity.

Potential Risks and Discomforts
You may feel uncomfortable while rehearsing the 8 digit number or you may feel uncomfortable while filling out the scale.  If the discomfort is appreciable we ask that you inform an experimenter and we will discontinue the study.

Potential Benefits to Subjects and/or Society
There are no expected benefits for the subject, however, this study should contribute to knowledge about stereotype formation that may help to palliate stereotypy and racism.

Payment for Participation
The subject will not receive payment for participation, but is eligible to receive class credit as specified by their current course instructors.

Any information that is obtained in connection with this study and that can be identified with you will remain confidential and will be disclosed only with you permission or as required by law.

Identification of Investigators
If you have any questions or concerns about the research, please contact Jared Reser at

Rights of Research Subjects
You may withdraw your consent at any time and discontinue participation without penalty.

I understand the procedures described above. My questions have been answered to my satisfaction, and I agree to participate in this study.  I have been given a copy of this form. 

Name of Subject

Signature of Subject


Wednesday, December 18, 2019

Rehabilitate and Detraumatize Your Ability to Chug Water

Drinking water used to be slow, and stressful for me. This happened because my swallowing reflex had become discoordinated from hyperventilation commonly causing me to choke on my drink. Swallowing involves temporary closure of the epiglottis to keep food and drink out of the lungs. If it is not synchronized properly then the inhaling of liquid (pulmonary aspiration) can occur. Drinking fast felt perilous. Chugging felt like I was being waterboarded. Difficulty swallowing is known as dysphagia, everybody has a little bit of it and you want to minimize your bit. Use the exercise below so that you drink mightily with no unnecessary encumbrances. 
Healthy Weight Activity #2: Chug Water Mightily
Pour yourself a large glass of room temperature or warm water. Tell yourself that there is no rush, and that you have nothing better to do at this moment than to observe your swallowing apparatus at work. Take a deep breath, and drink the water slowly and mindfully. Start with small gulps and make each one voluntary. Pay very close attention to the cadence of your gulping. It should be steady. Focus on the following:
1) During each gulp the muscles involved should move through their full range of motion decisively and uninterrupted.
2) Much of the swallowing process is an automatic reflex controlled by unconscious neurological mechanisms in the brainstem. You must give each swallow time to progress entirely through its reflex arc before you attempt to swallow again. You don’t want to interrupt a swallow by swallowing again too early.
3) It takes practice to get to know when, at the soonest, it is safe to initiate another swallow. It is like two people passing sand bags to each other down a line. The first person has to wait until the second person’s hands are free before they can pass another bag. Passing each bolus of water from the cup to your mouth, and then to the back of your throat should be efficient and quick, but not at all rushed.
4) You can hold your breath while you chug, or you can try to coordinate nasal breathing along with drinking. Either way, don’t let involuntary gasps interrupt the chugging process. You can’t breathe and swallow at the same time, and you must teach the involuntary aspects of breathing and swallowing to cooperate, and wait for their turn.

Using this exercise twice per day for two weeks will make is so that you will have no problem chugging 4 large glasses of water in 20 seconds. You will be able to put away a bottle of water, a fruit shake, or a smoothie in very short time. And you will never be afraid of choking on water. 

For more health building exercises visit

Rehabilitate and Detraumatize Your Cough

A cough is a protective reflex that acts to clear the large breathing passages of foreign particles, microbes, phlegm, saliva, other fluids. Cough ejects obstructions to breathing, and stretches and contracts various muscles. It involves a forced exhalation of air against a closed glottis. The diaphragm creates the pressure and when this pressure reaches a certain level the glottis and vocal cords open resulting in a violent release of air from the lungs. It is very similar to a laugh, and in a sense is like a hiccup in reverse. I believe that it may also be a mechanism for delivering blood to sensitive respiratory tissues and play an important function in health. By the time they are old many people have a very weak, highly strained cough that probably no longer performs its most important functions. For this reason, this short section will guide you in rehabbing your cough.

Most people’s coughs are full of so much tension that each cough pits different muscles against each other, damaging and wearing each other down. Most people cough violently or not at all. This maybe because we are accustomed to thinking of coughing as a negative thing, associated with disease and death. Instead, think of it as positive and healthy, and do it gently.
Vocal Exercise #4: Detraumatize Your Cough
Cough one hundred times in under five minutes. Start very gently and find a safe, sustainable cough. Build up to a more forceful cough while ensuring that there is zero associated pain or strain. Inhale slowly and deeply then cough until you have no air left, and repeat. Focus on coughing in different ways, at different levels of depth, intensity and pitch. Stick out your tongue. Experiment with a barking cough, a whooping cough, and a staccato cough. Try to extend a cough creating a single raspy sound over several seconds. Think of this as an antifrailty exercise intended to rehabilitate your cough. Search for dormant muscle. Afterwards pay attention to any tension or bracing that may have been caused by the exercise and quell it.

For more health building exercises visit

Wednesday, October 30, 2019

Comparing Information Processing in the Brain to That in the Computer

There are many interesting comparisons between the way the human brain processes information and the way a computer does it. By looking at the similarities and differences between the two I believe it is possible to understand each much better. The table below introduces a few of these comparisons, and the rest of this post will expound on these and others:

Computer Components Listed Next to Their Corresponding Brain Components




Hard Drive

Cortical Structure & Connections

Long-term Memory


Working Memory

Short-term Memory

CPU Cache

Sustained Firing

Focus of Attention


Synaptic Potentiation

Short Term Store


Prefrontal Cortex

Instruction Processing

Programmed Code

Associations / Cortical Search

Instruction Selection

Operating System




Peripheral Nervous System

Connecting Structure

BIOS / Firmware

Instincts and Reflexes



Anatomy, Wetware

Physical Structures


Associations, Schemas, Beliefs

Mental Structures

Microphone, Camera, Keyboard, Mouse

Ears, Eyes, Touch, Smell, Taste


Monitor, Speakers

Voice, Muscles



Visuospatial Sketchpad

Internal Video

Sound Card

Phonological Loop

Internal Audio




Clock Cycles in hz

Oscillations in hz

Cycles per Second



Memory Unit



Fundamental Processing Unit

Logic Gate

Neural Circuit

Secondary Processing Unit

Humans were designed over 100s of millions of years of evolution. Computers were designed over the last 100 years.

Brains learn from every experience they have. Most computers (outside of machine learning) do not learn from experience, although they can save data from operations if you ask them to. Bytes in a program remain unaltered after every use. However, every time a brain’s memory is used it is at least slightly altered.

Brains can never do the same thing, or have the exact same state twice. Asked to perform the same operation a computer will perform each step in an identical manner over and over again with no variation.

A brain is a piece of biology. A computer is a piece of technology. Brains are electrochemical. Computers are electronic and electromechanical. Brains are analog, and computers are digital. Brains are flexible, computers are inflexible.

A computer can be rendered useless if a single microscopic part is damaged. A brain shows graceful degradation and can work near flawlessly in many tasks even after severe damage. For example, cutting one wire in a CPU or motherboard can completely incapacitate a computer. But humans can often still think, move, and speak even after extensive traumatic brain injury.

Humans search for novelty, food, sex, resources, and are driven by curiosity. Computers simply process exactly what we ask them to. They have no choice, no discretion at all. They are incapable of altering their own processing stream.

Both brains and computers are designed to retrieve and activate (recall) specific information on command.

They both store information in long-term memory. They both also retrieve information from long-term memory when it is needed by placing it into short-term memory. When this happens, the information goes from dormant to active and can be used in processing.

Both brains and computers transition from state to state as a function of time. Their present state is based on what long-term information is currently active in short-term memory. The very next state is determined by how the currently active information interacts with preset rules. In computers, these rules come from programmed lines of code. In brains, they come from associative memories.

Both take inputs, combine them with short-term memory, and use this to determine the output. When computers do this they take user input (mouse and keyboard) and reference them against instructions, coded by programmers, to create output (sound and video). Humans, on the other hand, take environmental input and use their memories, encoded by experience, to create behavior.

Humans and computers can both complete tasks. How to complete the task is often described by an algorithm held memory. To go about the task they transition from one state to the next in a serial manner, where each state prompts the next state. This causes them to progress through the algorithm until the task is complete.

A computer employs algorithms created by a programmer. A brain’s algorithms derive from guesswork, memes, trial and error, process of elimination and insight.

They can both multitask. Humans can switch between tasks several times per minute. Computers often switch between tasks thousands of times per second. In both brains and computers, separate tasks can be called “streams.” When you run a program on your computer it looks like its only running one thing at a time, but it is actually running dozens of programs, applications, and services simultaneously. The simultaneity is an illusion, however. Because it can only focus on one task at a time, the CPU actually switches between tasks rapidly, in an effort to keep them all up to speed. During this switching it often stays with a single program for just a few millionths of a second at a time. Your serial conscious mind is much slower, spending at least a few seconds on each thought.

Some computer processors have multiple CPU cores making it possible for them to have several separate information streams running at the same time. However, each core in a CPU (even multithreaded cores) must process information in a strict serial or linear manner. Similarly, thoughts can only involve one serial stream of information at a time. But the brain accomplishes its serial stream of consciousness through massive parallel processing. Your massively parallel unconscious mind performs thousands to millions of operations in a second, and they truly occur simultaneously.

The brain is decentralized. Every memory is distributed over many neurons. One isolated neuron cannot hold a memory all by itself. It holds a tiny fragment of a memory. These fragments combine with other fragments from other neurons to form words, concepts, and ideas. The computer on the other hand stores bits in definite physical locations that either contain a certain amount of electrical charge, designating a 1, or does not contain that charge, designating a 0. Groups of 8 bits create binary words that have meanings that include letters, numbers, and mathematical and logical operations for the CPU to perform.

Because each memory is distributed over many neurons, each neuron must play a role in many completely separate memories. Not so in a computer. A computer’s bits are stored in microscopic capacitors. Each capacitor can only hold one bit each. Its memory is not distributed, it is localized.

A bit can only have one of two states (0 or 1). This is because a transistor can either be on or off. Similarly, a neuron is either firing or not firing.

The brain uses neurons to hold memories. Computers use registers to hold their memories. Each register is made up of capacitors, and each capacitors can hold a bit. There are 8 bits in a byte (e.g. 01101100), and bytes are shuttled from register to register.

The brain uses circuits of neurons to process memories. Computers use transistors and logic gates to process bytes.

Neurons and the information that they encode do not move around, they remain stationary. Despite being set in a fixed point in space, they do send signals to each other, but the informational content held by one neuron is unique to it, and cannot be transferred to another. The registers (made of capacitors) in a computer also do not move, but the bits and bytes of information they hold are constantly and rapidly copied, and transferred from register to register.

The average computer today has billions of capacitors, and around 4 billion transistors. The brain wins in sheer number of processing units. The average human brain has 100 billion neurons. Each of these neurons makes many, many connections (synapses) with other neurons, and typical estimates for the number of synapses in the brain vary between 100 trillion, and a quadrillion.

Neurons and transistors both integrate an input to create an output. The neuron, has many more inputs and outputs than the transistor though. Neurons can have thousands of inputs, and tens of outputs, whereas transistors have two inputs and one output. The elementary logic of a transistor can be made much more complex when transistors are used together to construct logic gates, but even logic gates (AND, NOT, XOR, NAND etc.) do not even have tens of inputs or outputs. However. despite their low connectivity, transistors are much faster.

Transistors can switch billions of times per second, whereas neurons generally fire less than 400 times per second. Even logic gates (made of several transistors) are much faster than neurons.

Information is also carried through space far more quickly in computers. The buses, wires, and channels on a circuit board can move electrons a large fraction of the speed of light (299,792,458 meters per second). An axon can only propagate an action potential as fast as 150 meters per second.

A brain uses “content addressable memory, and spreads activation from active neurons to inactive neurons to search for associated concepts. A computer uses “byte addressable memory” to locate the next byte called upon by the CPU in the database using rows and columns.

The brain has electrical oscillations that organize and coordinate timing between its separate specialized modules (cortical regions). Similarly, the computer uses electrical oscillations in the form of a system clock to organize and coordinate its operations. The brain oscillates up to around 150 times per second (150 hz). A modern computer’s system clock oscillates at frequencies above 3 billion times per second. 

Human brains live 79 years on average. Desktop computers have a lifespan of 3 to 5 years.

The brain never shuts down until death. A computer is regularly turned off. Brains and computers both sleep. Computers have a hibernation setting and humans do not.

Brains don’t crash or hang like computers do. Both can get viruses. Both can malfunction and take damage from overheating.

When one operating system simulates another operating system within it, this is called virtualization. When one person simulates the thoughts of another in their mind, this is called empathy.

Two brand new computers of the same make and model will be identical, two members of the same species will be very different.

A new computer is much like a baby in that it has a basic input/output system (BIOS) that will determine how it will “instinctually” interact with its environment. Both new computers and babies will come to acquire a lot of disparate information over their lifetime, making each very unique.

In the case of trauma for instance, some human memories that are unwanted cannot be forgotten. However, information can be selectively and permanently erased from a computer.

Some things that we would like to remember (like an old phone number) cannot be recalled. Other things (like a new phone number) may be difficult to store at times. A computer doesn’t have this problem, if it is asked to recall, or store a memory on the hard drive, it does it with no problems and no mistakes.

Both brains and computers use instructions. In a sense these come in the form of “if, then” instructions. Both can be thought to have instruction sets made up of all the possible operations they can perform. A computer’s instruction set is its alphabet containing operations like add, divide, recall from RAM, and place in RAM.

Computers are often described as having a “memory hierarchy,” expressed as a pyramid with different levels of memory storage. This is also referred to as a caching hierarchy, because there are different levels of short-term memory with different associated speeds.

The levels at the top are faster, smaller, and more energetically expensive. The same could be said for human memory, because there are several levels, the levels at the top are faster, and more metabolically expensive. The following table is my attempt to compare the levels of these two hierarchies: 

Time Scale
CPU Register
Cortical Binding
Very short-term working memory (millis.)
CPU Cache (SRAM)
Sustained Firing
Short-term working memory (seconds)
Synaptic Potentiation
Short-term memory (seconds to hours)
Virtual Memory
Short-term Potentiation
Short-term memory (minutes to hours)
Commonly used LTM
Accessible Long-term Memory
Hard Drive
Long-term Memory
Long-term Storage (days to lifetime)

RAM and CPU cache memory, much like working memory, are volatile. This means that the information in them decays rapidly and require energy be maintained. RAM and cache, also like working memory, have a limited, and fixed capacity.

Long-term memory holds everything a person knows, just like the storage drive (HDD or SSD) holds everything the computer knows.

A person’s long-term memory takes longer to access than short-term memory, but has a much larger capacity. Similarly, the storage drive takes much longer to access than RAM or cache, but has a much larger capacity.

Human short-term memory is thought to be able to remember 3-7 items or concepts at a time. Computer short-term memory can hold millions of bytes, but cannot hold any true concepts. Nothing in a computer can hold concepts.

In order to feed more pertinent information into limited-capacity short-term memory the least pertinent information must be removed.

Both brains and computers get rid of the least recently used information to make room for new, incoming information in their short-term memory. This is an eviction policy known as LRU for “least recently used.”

We can take notes when there is too much information to hold in working memory. Similarly a computer can record information in a swap or paging file if there is not enough room in RAM.

Computers and humans use limited resources to perform tasks. They can both reach a processing limit where they are loaded by tasks so much that their performance decreases. In humans this is called cognitive load.

Computers can quantify their processing resources and tell you exactly how much of their resources are currently engaged by ongoing tasks. Humans cannot do this precisely.

Computers can give you detailed up-to-date information about the state of their components, the occupancy of their drives, heat of CPU, memory usage, and others. Humans can make similar reports, though in the form of unquantified sensations. Like people that can state their name and birthday, a computer can display its make, model and manufacture date.

Like us computers have basic needs. They need energy to run. They must be protected from the elements, and from physical harm.

Computers have no emotions, drive, curiosity, thought, interests, imagination, opinions, creativity, philosophies, beliefs, fears, wants, awareness, mental models, or sentience. A computer running AI software can be considered an agent, but not a subjective entity.

Human information processing is much more energy efficient. The largest supercomputers consume millions of watts of electricity, and yet do not have the processing capacity of the human brain. An average home desktop PC uses between 60 and 300 watts. The human brain uses merely 20 watts, less than most incandescent light bulbs.

Computers are inherently adept at logic and arithmetic, humans must learn it for years in school. Even the very first computers from the mid 20th century were much faster at computing than humans. This is how they got their name.

Most modern computers can multiply two 64 bit numbers more than 4 billion times in a second. Can you do this calculation once in an hour? Without a pen and paper humans cannot do this at all.

However, brains are inherently good at working associatively, using abstractions, finding matches, completing patterns, and using analogies. Computers struggle with this. Today even the most sophisticated personal assistants (Siri, Alexa, Google Assistant) cannot hold a conversation past one exchange. Every sentence you say to it is disconnected from every other sentence.

Brains and computers are both adept at “networking,” but only humans are good at socializing. AI chatbots are getting better, but without any comprehension or consciousness, can their chatting really be considered social?

Supercomputers are now approaching human brains in terms of processing speed, and amount of memory. However, they cannot think, even at the level of a two year old.

Even one year olds know things. A computer though does not know anything, just like a thermostat doesn’t know anything. All it can know is the locations of where bits are either 1s or 0s. In fact, any computer in the world, even the most complicated AIs, could be replaced by wooden parts and a hand crank (a mechanical Turing machine). It would amount to a tremendous contraption, but in theory it would work exactly the same.

Computers are now better than humans at checkers, chess, go, Jeopardy, object recognition, language translation, and much else.

Even the best computers and programs have trouble understanding natural spoken language. Today they can transcribe and translate language better than humans, but have zero comprehension. We have to admit though that most humans have trouble understanding programming languages, and very few people can read machine language (1s and 0s).

Computers appear to perform very complex tasks but they are really performing very simple tasks extremely quickly. Because they are exceptionally fast and accurate they can be made to chain together long series of operations to produce useful software and applications. However, each individual thing they do is very simple, the equivalent of elementary school math.

Computers learn new programs immediately after downloading and installing them. Humans can take years to learn new skills.

Computers can do things they were never programmed to do explicitly, but only if that thing is implicit in their design. Humans can do things that were never implicit in their design (like writing a poem).

Animal brains are embodied in the sense that they interact with and live in the world. Desktop computers, phones and tablets are disembodied.

Humans are made of carbon, oxygen and hydrogen. Computers are made from silicon, metal and plastic. But very soon computer semiconductors may be made from carbon nanotubes. This would make computers carbon-based, just like us.

Computers have short-term memory, but it works in a way that is fundamentally different from short-term memory in humans. Computers have no equivalent of working memory. This is probably the most important difference between humans and computers today. Until they are programmed to simulate working memory they probably cannot be conscious.