Mental models, the basis of rationality

We live in a world that overloads us with information, stimuli, and challenges. We make decisions from the second we wake up until the moment we go to bed. To deal with this complexity, we look for unconscious and conscious patterns that help us understand and navigate our surroundings – small internal compasses that guide us through the experiences and information we absorb. These compasses we call “mental models.”

These models influence how we see and perceive the world and play a significant role in our cognitive processes and decision-making. 

However, variables (such as emotions, motivation, or a limited capacity to process information) can influence these internal representations of reality. The consequence? We develop cognitive biases that affect our attitudes and behaviors, preventing us from seeing the world objectively.

As researchers, we must identify and mitigate our cognitive biases to ensure accurate and objective data collection and analysis. 

Some examples of biases that often affect the quality of our decisions are:

When the way information is presented influences how it is perceived and evaluated, positive or negative framing can significantly alter the response of message recipients.

When we ask questions like “How did the new features improve your experience?” we dictate the participant’s focus. This framing directs the participant to concentrate on the improvements, potentially overshadowing other factors that may have negatively impacted their experience and perception of value.

It is the tendency to believe that most people expect and share our opinions and behaviors. Making this assumption could result in overestimating the degree of agreement others have with our views, contributing to erroneous assumptions about the target audience.

As researchers, when we consider ourselves users of the product we are working on, we assume that our difficulties or satisfactions when interacting with it are universal. This way, we discard opinions that differ from ours because we consider them outliers.

It is the tendency to seek, interpret, and remember information that confirms our pre-existing beliefs, ignoring contrary evidence. This could lead to a distorted interpretation of the data, compromising objectivity.

In the research process, confirmation bias often plays a significant role in presenting data. We seek information that validates our beliefs, emphasizing data that aligns with them.

These are just a few examples of biases that impact the quality of our decisions, but there are many more. It is essential, both in the professional and personal spheres, to be aware of them and recognize when they occur to ensure they do not interfere with the objective interpretation of data.

If mental models result from our need to understand the world more efficiently, how can we improve them for better effectiveness?

In addition to recognizing our biases, we can learn about new models that improve our ability to see situations from different perspectives.

Some examples of models that will help us think better are:

It consists of considering the consequences of our decisions. By doing so, we can anticipate the long-term impact and avoid unintended adverse effects.

Implementing a rewards program may initially increase interactions with the product. Still, second-order consideration reveals that it can lead to undesirable behaviors, such as users manipulating the system to earn rewards without meaningfully interacting with the product.

It consists of thinking in reverse. When we have a specific goal, instead of thinking about what we can do to achieve it, we think about what could stop us from achieving it. It is a powerful tool because it highlights points that we should avoid or mistakes that we may make and which, with a positive approach (“What do I need to do to achieve my goal?”), we can overlook.

When trying to improve an application’s sign-up process, inversion suggests thinking about the challenge of understanding and eliminating barriers that can frustrate users – “What can I do to make this process as frustrating as possible?”. This way, we can create a fluid and intuitive process that meets the objectives.

These are just a few examples that, when well applied, significantly improve our understanding of the world and contribute to more informed and objective decision-making.

We must move in this direction: strip ourselves of biases, empathize with the world, and know how to apply the theory.

The path to excellence is constant learning.