Activation Energy

Have you ever procrastinated doing something for days or weeks only to eventually get around to doing it, and realizing it wasn’t so bad after all? In fact, once you got started, perhaps it was pretty straight-forward, and not nearly as taxing as you’d anticipated. That’s because the act of starting required the most effort.

In chemistry, ‘activation energy’ refers to the minimum effort required to create a chemical reaction. For example, it takes a certain amount of energy to activate the molecules that make a chemical fizz in a test tube, but once that initial energy is exerted, it takes far less energy to sustain those same bubbles. Psychologists have adopted the term ‘activation energy’ to explain why starting is often half the battle when it comes to human decision-making and behavior.¹

The term activation energy was introduced in 1889 by the Swedish scientist Svante Arrhenius, although it is likely the underlying idea was developed long before then. Arrhenius developed what became known as the Arrhenius equation, an equation that provides a mathematical basis for the calculation of activation energies. This equation linked the activation energy of a process to its ‘rate constant’, also known as the reaction time. In basic terms, Arrhenius noticed a negative relationship between activation energy and rate constant, meaning the higher the activation energy, the slower the chemical reaction will be, and vice versa.²

While Arrhenius might have coined the term ‘activation energy’ scientifically, ancient philosophers like Plato had written about the more abstract concept as it relates to human thinking thousands of years prior. For that reason, we can’t give all the credit to chemists alone!

In the 20th century, psychologists started to use activation energy to explain why the level of effort required to start a task can determine how quickly we adapt to it. Activation energy is closely linked to learning and reinforcement, and experiments conducted by psychologists such as Iain Pavlov, John Dewey, and B.E Skinner showed how the required level of activation energy is reduced once learning and cognitive reinforcement takes place. These concepts dominated much of the behaviorist approach to psychology from the 1960s onwards.³ Around this time, behavioral economists started to combine psychological concepts with economic principles, such as the similarity between activation energy and marginal cost, which explains how the initial cost exerted is usually off-set by the marginal utility received over time.

More recently, activation energy is used to explain why some habits are easier to adopt than others, leading to applications in a broad range of fields including health and welfare, business psychology, and behavioral change interventions.

In psychology and decision science, the concept of activation energy was influential as a basis for explaining human behavior, specifically in relation to habit formation. As psychology started to develop as a science in the early 20th century, functionalist scholars began to look more closely at the underlying causes for human behavior. Activation energy was one of the terms psychologists adopted from traditional science, as it neatly describes why starting something is often half of the battle.

Activation energy has been particularly useful for understanding the motivations that drive behavior. If we understand that ‘starting’ is often the biggest barrier to action, we can actively target the starting phase of an activity or habit, with the understanding that it will  likely make it easier to sustain.⁴ At an individual level, we can do simple things to promote healthy habits, like keeping our running shoes in the same spot by the door so we don’t have to spend time looking for them before going for a run. We can buy frozen fruit that’s easy to toss into a blender for a healthy smoothie, knowing that the effort of peeling fresh fruit will likely discourage us from making one for breakfast. Anytime we do something that makes it easier for us to start a healthy habit, we reduce the activation energy it requires, and therefore increase the likelihood that we will sustain that habit.

On a broader level, activation energy is the main premise of the default, a tool that’s commonly used to encourage a specific type of behavior, both in business and public policy. Due to inertia and the status quo bias, we humans tend to opt for the easiest or most automatic option when making decisions. Examples of defaults include automatic subscription renewals (think of your Netflix or Amazon accounts), opt-out programmes (like automatic organ donations in some countries), and automatic enrollment in financial programmes (like pension funds in the UK). Through the use of defaults, policy makers slash the activation energy required to engage in a particular behavior to zero. Defaults are increasingly popular in a modern world that demands convenience, although we should pay attention when ‘easy’ doesn’t always align with what’s right for us

Read more: In order to increase the likelihood of certain choices, decision-makers will often employ nudges. Automatic subscription renewals or opt-out programmes are examples of just the opposite: sludges.

Since activation energy implies that starting an activity demands the most energy, most of its applied theories or interventions try to remove the starting phase from the process (like the default) or reduce the number of times a process has to be started and restarted. This can be challenging in the context of human behavior, since people get tired and require breaks to ensure they are operating at their best.

Take, for example, two different approaches to work that we’re all probably familiar with. On days when we don’t really feel like working, some people argue that gathering the motivation to sit at our desk and focus can be a greater struggle than the work itself. Therefore, once we’ve convinced ourselves to get going, and manage to get into a good working rhythm, the last thing we should do is stop, even if we’ve been working for hours. This is because once we stop, and perhaps grab a coffee from the kitchen, it will be much harder to return to the desk and get back to business. However, some people advocate that we are most productive when we organise our work into small time periods or ‘bursts’, and that the taking of short breaks is important to sustain our cognitive performance. Strategies such as the increasingly popular pomodoro technique are built with this type of thinking in mind, and would seem to contradict habit strategies that seek to reduce activation energy, since they advocate stopping and restarting every twenty five minutes. Similarly when it comes to learning, the spacing effect illustrates how learning is most effective when it is repeated in spaced-out sessions. This is because it takes time for our brains to process information and stimuli.

Furthermore, there isn’t much of a scientific basis for activation energy in human psychology. While learning and reinforcement theories demonstrate that we can improve  at things over time, thus reducing the amount of effort it takes to start them in the future, there is no real proof that ‘easy’ will always equate to ‘faster’. Human beings can’t be simplified like molecules or atoms, and what is easy to one person is incredibly taxing for another. Therefore, while activation energy is a nice metaphor and definitely has some useful applications when trying to implement new habits, we can’t say its application to psychology is scientifically concrete.

Dual Process Theory & Habit

In his famous book Thinking Fast and Slow, psychologist Daniel Kahneman outlines how our brains engage in two distinct processes when it comes to decision-making. System 1 thinking refers to our automatic behaviour, like recalling the answer to 2+2 or dialling a phone number you know by heart. This requires little to no activation energy, because it’s automatic. On the other hand, System 2 thinking refers to our more deliberate thinking, like when learning something new for the first time or solving a complex problem.⁵

Neuroscientists have shown how different parts of our brain are used when we engage in System 1 versus System 2 thinking. In fMRI scans, neuroscientists observe increased activity in the prefrontal cortex of the brain when engaging in deliberate, complex thinking. By contrast, more activity is detected in the basal ganglia when people perform automatic, ‘easy’ tasks which require less activation energy.⁴ These findings are important for a variety of reasons, but especially for research related to habit formulation and maintenance, More and more, research is showing that in order to make habits ‘stick,’ we need to make them automatic and easy. Therefore, by reducing the activation energy involved in a task, we allow this task to be part of our system 1 thinking, and it therefore requires much less energy to sustain it as a habit.

Defaults & Energy Consumption

As previously highlighted, the default is the option that requires zero activation energy from the decision-maker. Due to our human preference for inaction, illustrated by the status quo bias, defaults are commonly deployed to encourage us to behave in a particular way.

In 2006, McCalley⁶ conducted an experiment which tested various interventions aimed at encouraging people to reduce their household energy consumption. In one version of the study, two groups of participants were given a washing machine: one group of participants had the temperature on the machine set to  zero, while another had it set to 95 degrees, a common default temperature in North American washing machines. Those who had their washing machines set to zero, had to engage in some effort by switching the dial to their desired temperature, usually around 60-/70 degrees. It was hypothesized that because changing the given temperature setting involved effort on the part of the individual, most people would just run their laundry at the pre-set level of 95 degrees, therefore using more energy than necessary to heat the water.  The study’s hypothesis was confirmed, showing the influence that a non-desirable default can have on behavior. The group that received the high default temperature setting used an average of 89 kWh per wash, whereas the group receiving the zero setting averaged 68 kWh per wash. Setting the default to a high temperature meant that no activation energy was required to run a ‘hot’ wash, therefore this was the option most people absentmindedly chose, resulting in higher energy costs. Evidently, if we want people to run their washing machines at a lower temperature, therefore wasting less energy and costing less money, we should use lower temperatures as the default. However, that might not be in the best interests of our energy suppliers!

Status quo bias, explained.

The status quo bias describes our human preference for inertia, or simply doing nothing to change the current state of affairs. It explains why we tend to ‘go with the flow’ and can be reluctant to change or disrupt our regular behaviors and habits.

Defaults

This TDL Reference Guide article explains the concept of the default: the outcome of a decision when no decision is made. It’s the pre-set option that is made available when we do nothing, and requires no effort on our part. Defaults are commonly used by businesses and governments to encourage us to engage in behaviors that align with their goals.

1. Farnan Street (2021). Activation Energy: Why Getting Started Is the Hardest Part. (2021). Retrieved 2 April 2021, from https://fs.blog/2017/06/activation-energy/
2.  Britannica, E. (2021). Svante Arrhenius | Swedish chemist. Retrieved 3 April 2021, from https://www.britannica.com/biography/Svante-Arrhenius
3. Behaviorism (Stanford Encyclopedia of Philosophy). (2021). Retrieved 2 April 2021, from https://plato.stanford.edu/entries/behaviorism/
4. Hollingworth, C., & Barker, L. (2017). How to use behavioural science to build new habits.
5. Kahneman, D. (2011). Thinking, fast and slow. Macmillan.
6. L.T. McCalley (2006). From motivation and cognition theories to everyday applications and back again: the case of product-integrated information and feedback, Energy Policy, 34