Unveiling Latent Learning: How Hidden Knowledge Shapes Our Actions

Subconsciously picking up information for use later in life is a process known as latent learning. This type of learning, also known as incidental learning, is a passive type of cognitive learning. Cognitive refers to mental processes and functions such as thinking, recalling information, and reasoning. It involves no immediate reward or punishment after you’re exposed to new information. Unlike operant conditioning, it doesn’t require punishment, reward, or a conditioned or unconditioned stimulus, which is characteristic of classical conditioning.

The Discovery of Latent Learning

The concept of latent learning was developed in 1929 by Hugh C. Blodgett, who described it in laboratory rodents as they gradually improved the way they navigated their way through mazes. However, psychologist Edward C. Tolman is more famously associated with latent learning, particularly through his experiments with rats.

Tolman was studying traditional trial-and-error learning when he realized that some of his research subjects (rats) actually knew more than their behavior initially indicated. Early behaviorists such as Watson and Skinner believed psychology should only study observable behavior-not thoughts, plans, or expectations. Skinner went so far as to describe the mind as a “black box”-something unknowable and irrelevant to scientific study. But psychologist Edward C. Tolman had a different opinion.

In their famous experiments Tolman and Honzik (1930) built a maze to investigate latent learning in rats. In the experiments, Tolman placed hungry rats in a maze with no reward for finding their way through it. He also studied a comparison group that was rewarded with food at the end of the maze. As the unreinforced rats explored the maze, they developed a cognitive map: a mental picture of the layout of the maze (Figure 1). After 10 sessions in the maze without reinforcement, food was placed in a goal box at the end of the maze. As soon as the rats became aware of the food, they were able to find their way through the maze quickly, just as quickly as the comparison group, which had been rewarded with food all along.

Figure 1. Psychologist Edward Tolman found that rats use cognitive maps to navigate through a maze.

Read also: ACT or SAT?

The rats were divided into three groups and the individuals in each group were put in a maze. The rats in Group 1 received a food reward when they reached the end of the maze. The rats in Group 2 never received food; they just were put in the maze and wandered freely for a certain amount of time for 10 days. The rats in Group 3 wandered the maze with no food for 10 days, then on the 11th day they started receiving a food reward for finishing the maze. It took them only one day to catch up to the Group 1 rate of running the maze. The first group always received a food reward at the end of the maze, so the payoff for learning the maze was real and immediate. The second group never received any food reward, so there was no incentive to learn to navigate the maze effectively. As you might expect when considering the principles of conditioning, the rats in the first group quickly learned to negotiate the maze, while the rats of the second group seemed to wander aimlessly through it. The rats in the third group, however, although they wandered aimlessly for the first 10 days, quickly learned to navigate to the end of the maze as soon as they received food on day 11. By the next day, the rats in the third group had caught up in their learning to the rats that had been rewarded from the beginning.

It was clear to Tolman that the rats that had been allowed to experience the maze, even without any reinforcement, had nevertheless learned something, and Tolman called this latent learning. Latent learning is to learning that is not reinforced and not demonstrated until there is motivation to do so.

Figure 1. The maze. As you can see from the map, the maze had lots of doors and curtains to make it difficult for the rats to master. The blue marks represent doors that swung in both directions, which prevented the rat from seeing most of the junctions as it approached. This forced the rat to go through the door to discover what was on the other side. The green forms show curtains. These hung down and prevented the rat from getting a long-distance perspective and it also meant that they could not see a wall at the end of a wrong turn until they had already made a choice and moved in that direction.

Tolman’s experiments challenged the behaviorist view that all learning is driven by reinforcement. His work demonstrated that organisms can learn even if they do not receive immediate reinforcement.

Cognitive Maps: The Mental Blueprints

As the unreinforced rats explored the maze, they developed a cognitive map: a mental picture of the layout of the maze. Have you ever worked your way through various levels on a video game? You learned when to turn left or right, move up or down. In that case you were relying on a cognitive map, just like the rats in a maze.

Read also: Musical Instruments for Beginners

Whenever we go someplace new, we build a mental representation-or cognitive map-of the location, as Tolman’s rats built a cognitive map of their maze. Psychologist Laura Carlson (2010) suggests that what we place in our cognitive map can impact our success in navigating through the environment.

Latent Learning in Everyday Life

Latent learning also occurs in humans. Children may learn by watching the actions of their parents but only demonstrate it at a later date, when the learned material is needed. For example, suppose that Ravi’s dad drives him to school every day. In this way, Ravi learns the route from his house to his school, but he’s never driven there himself, so he has not had a chance to demonstrate that he’s learned the way. One morning Ravi’s dad has to leave early for a meeting, so he can’t drive Ravi to school. Instead, Ravi follows the same route on his bike that his dad would have taken in the car. This demonstrates latent learning.

You may use latent learning in all areas of life.

Home

Putting away cleaning supplies in your new home you realize the water valve is in the way. Months later when a pipe breaks, you know the water valve is in the closet where the cleaning supplies are kept.

Work

Working in a multi-level office, the conference rooms are on the second floor. You always take the elevators but today, they’re not working. You take the stairs to the right of the hall because you know they lead to the room you need to go to.

School

During science class, you sit next to a wooden shelf full of textbooks. When your personal book gets damaged later in the year, you immediately check the shelf where you know there’s a row of science textbooks.

Memorizing routes

Let’s say a colleague drives you to work for a few weeks until you can buy a car. Once you have the car, you’re able to drive to work using the same route with no mistakes, even though you never tried to memorize it.

Becoming like your parents

You spend years telling your child to clean their room. Or, remember the last time you found yourself unintentionally doing something your parents did while you were growing up.

Recalling facts

You didn’t enjoy history and were always tuned out in class.

Remembering instructions

At a restaurant, you overhear a conversation where a mechanic tells a friend how to check their car’s oil level.

Soaking in song lyrics

Your partner repeatedly plays their favorite song while you do chores around the house.

Observing leadership styles

You might observe your manager’s leadership techniques for years without actively trying to learn them.

Let’s say you’re walking down a road for the first time. You notice tall bushes obscuring a busy intersection but think nothing of it. Next time you drive your car down the same road, you immediately slow down and become alert anticipating poor visibility at the intersection. This is thanks to latent learning.

A real-life version of latent learning could go like this. Say I have no interest in bicycles or cycling. None. Nobody in my life does that. And say there is a bicycle repair shop in a little strip mall that I pass sometimes. If I notice that, there’s nothing in it for me. However, let’s say I have a new friend who is into cycling. She cycles to my house one day, and just as she arrives something goes wrong with her bike. She needs a repair. If at that moment I remember the location of that bike repair shop, that is latent learning. Learning about the location of the bike shop was not valuable earlier. There was no reinforcement available for it.

Curiosity as a Driver of Latent Learning

In 2021, Maya Zhe Wang and Benjamin Hayden theorized that curiosity, or the desire to gather information, is the main motivation behind latent learning. This leads learners to build cognitive maps about their environments. Curiosity is a desire for information that is not motivated by strategic concerns. Latent learning is not driven by standard reinforcement processes. We propose that curiosity serves the purpose of motivating latent learning. While latent learning is often treated as a passive or incidental process, it normally reflects a strong evolved pressure to actively seek large amounts of information. That information in turn allows curious decision makers to represent the structure of their environment, that is, to form cognitive maps. These cognitive maps then drive adaptive flexible behavior.

For example, red knots (arctic shorebirds), feed on bivalves that are patchily distributed and buried in the mud. Notably, the locations of these prey cannot be guessed based on visual inspection, but can be inferred based on a rich knowledge of likely patch structure and distribution of other prey. When foraging, the birds reside in patches longer than predicted by simple foraging models; their overstaying can explained by modified models that include a bonus for the information that the extra residence time provides.

The natural environment offers a plethora of rewards to most foragers but acquiring these rewards requires knowledge. Any forager placed within a complex natural environment must naturally trade off between the costs and benefits of exploration. In addition to the metabolic costs of locomotion, sensory processing, and learning, active exploration carries opportunity costs: that time could be better spent searching for food, courting and reproducing, or avoiding predators. Even motivational processes driven by distal reward seeking must necessarily discount future rewards and uncertain rewards, and the benefits of exploration are unavoidably delayed beyond the temporal horizon and, individually, infinitesimally unlikely. So reward-maximizing calculation is unlikely to sufficiently motivate search.

Indeed, curiosity would seem to go hand in hand with the learning of cognitive maps. Cognitive maps refer to detailed mental representations of the relationship between various elements in the world and their sequelae. Having a cognitive map allows a decision maker to not just guess what will happen but also to deal with unexpected changes in our environment. The classic idea about cognitive maps - also attributable to Tolman - is that they allow us to respond flexibly when contingencies change (e.g. when the layout of a maze changes. That kind of flexibility is very difficult to implement with basic reinforcement learning processes. Critically, cognitive maps typically require a rich representation of the world- they require a level of detail that is not normally available from reinforcement learning processes. That detailed representation of the linkages between adjacent spaces allows for vicarious travel along those linkages. Because it is so much more detailed, it requires orders of magnitude more information than standard reward-motivated reinforcement learning can give. We propose, therefore, that latent learning is motivated and enabled by curiosity.

However, Tolman conceived of latent learning as a fundamentally passive process, one that took place during apparently purposeless exploration - almost as if by accident. We propose, instead, that latent learning in practice tends to be more actively driven. The problems faced by a naturalistic decision-maker or forager are similar in many ways to the problems faced by artificially intelligence (AI).

The AI domain provides a good illustration of how cognitive maps can be crucial for the success of curiosity. The optimal search strategy in sparse (natural) environments is typically to identify a locally promising region and then perform strategic explorations from that spot to identify subsequent ones. That exploration will not be random, but will take place along identified high-value destinations. AI agents suffer from the problem of detachment, that is, when they explore the environment, they leave the relatively high-reward areas of space to explore lower-reward ones. Most such areas are likely to be dead ends, and, when a dead end is detected, the agent ought to return to the high reward area and pursue other promising paths.

Neuroscience of Curiosity and Latent Learning

Based on recent data, we propose that orbitofrontal cortex (OFC) and dorsal anterior cingulate cortex (dACC) play complementary roles in curiosity-driven learning. The neuroanatomy of curiosity is more complex and includes other areas such as hippocampal areas and basal ganglia. We propose that OFC serves to (i) track the intrinsic value of information, (ii) maintain a cognitive map of state space, and (iii) update that map when new information is gained.

We propose that dACC plays a distinct and complementary role to OFC. Specifically, it appears to track both information delivery and level and task demands for use by OFC in updating the cognitive map and applying it to instrumental use.

How to Maximize Latent Learning

Because it’s a passive process, latent learning may seem like something you can’t control or influence. However, you can put yourself in situations where latent learning is more likely to occur.

Intentionally create cognitive maps

To help you learn your way around a specific area, try intentionally creating cognitive maps by paying attention to your surroundings. Notice what’s new in the environment, make geographic associations (like remembering the entrance to a park is near a large and unique rock), and study which paths lead where. You can do this with large environments, like your entire city, or smaller environments, such as a grocery store. For example, you might take note that the cereal aisle is right next to the cookie aisle or that the deli directly faces the front registers.

Create space for latent learning

Create space for latent learning by immersing yourself in a subject or environment you enjoy. It’s well established that people are more likely to remember information they like or view as positive than they are to remember neutral information. For example, if you love animals, take a walk through the zoo and spend time watching them.

Stimulate curiosity

It’s easier for humans to learn information they’re curious about. For example, a teacher could talk about a popular television show while their students work on an art project they find boring. Asking questions can help stimulate critical thinking and creative thinking, which promote comprehension and recall. After immersing yourself in a new environment, try asking yourself questions about it to see what information you retained.

Challenge your knowledge

It’s important to also be open to the idea that some of your existing perceptions could be wrong. This is when unlearning becomes a crucial part of learning. Be willing to challenge your knowledge with tough questions to make sure it’s sound.

Although latent learning is subconscious, you can support it in yourself and others by creating an environment and mindset conducive to learning. Latent learning is an important part of your professional and personal development.

Latent Learning vs. Observational Learning

One of the main differences between latent and observational learning is the presence of reinforcement in the latter one. The concept of observational learning is a part of social learning theory pioneered by Albert Bandura, who suggested one way you learn behaviors, attitudes, and thought processes is through observing and imitating others. How someone reacts to your behavior (the reinforcement they give you) is a part of observational learning and can dictate if you decide to repeat that behavior or try something else. If you observe your mom getting angry when you eat with your fingers, for example, you may learn eating that way is undesirable.

Latent learning, on the other hand, can occur in the absence of others and without reinforcement - positive or negative. With latent learning, you may not even realize you’ve acquired knowledge in the moment. You may observe something but don’t realize you could use that information later on. When you do, you may not realize when or where you learned it.

One of the main differences is:

How it occurs: Latent learning happens passively, while observational learning involves intentionally observing and imitating others.
When it’s demonstrated: Observational learning is demonstrated almost immediately as you try to mimic someone else. Latent learning is not readily apparent to the researcher because it is not shown behaviorally until there is sufficient motivation.

The easiest way to remember the difference is that latent learning is often referred to as incidental learning.

Challenging the Concept

There were later studies that countered the latent learning effect. There were researchers who argued strongly against it. They claimed that the rats in the maze without food were getting some type of reinforcement and that their behavior could be explained under standard principles of behaviorism.

tags: #latent #learning #examples