A short guide to solving problems
Introduction
If there is one universal aspect to human life; it is to solve problems. Our brains our computers which use the input from our five senses to generate an output (action: movement, speech) which helps us navigate the world. In simple words, humans are problem solving machines. We have been genetically programmed to solve problems in order to survive the harsh realities of nature.
Problems by Reasoning
Problems can be represented by the magnitude of difficulty and the period of time required to solve them. As the time frame of a problem increases so does its complexity. In to better understand any problem we need to know its underlying reasoning.
Autopilot Reasoning
Simple problems like cooking or driving to work are easy problems which are solved on autopilot. They do not require any abstract thinking.
Semi-autonomous Reasoning
Problems which are time constraint are solved by experience aggregated over a period of time. A differential equation solved by calculus goes further back to foundation of mathematics inculcated at a young age. These problems although do not require elaborate deliberation, tend to be solved from experience (in this example basic and intermediate math literacy) and research (the way we used to solve similar problem before). Solving a differential equation is not entirely an autopilot task so we shall put this in a semi-autonomous category.
Manual Reasoning
A problem like passing a statistics, linear algebra or calculus class (add your subject here) is a more complex problem compared to driving or solving a differential equation. It is more complicated because of a higher level of abstraction (it is made up of individual problems in a sequential order of difficulty) over a length of time. These problems cannot be solved by auto reasoning or semi-auto reasoning. These problems are solved with manual reasoning, meaning you need to use active cognition.
Hard and Soft Intelligence
Intelligence can be dived under two sub categories: IQ (Intelligence Quotient) derived from a standardized test measuring raw intelligence and EIQ (Emotional Intelligence Quotient) derived from a standardized test measuring emotional competency. Although highly controversial IQ and EIQ in this article are to be taken on ontological merit only.
We will address IQ as hard intelligence and EIQ as soft intelligence.
Most of the manual reasoning problems are solved by a concatenated degree of hard and soft intelligence. Humans are not literal computers, we can think logically but our logic is governed by motivation which is ruled by emotion. Hard intelligence is the ability to think in abstract terms and soft intelligence is the ability to motivate oneself to solve the problem. A math prodigy may not even pass a high school course if he or she lacks motivation.
Structured places of learning like schools and universities are a good at honing hard intelligence but avoid addressing soft intelligence. This is why a lot of intelligent people are unable to solve complex problems; not because they lack intelligence but because they lack emotional intelligence. To solve a complex problem you need two things; the ability to solve it (hard intelligence) and the belief in your ability to solve it (soft intelligence).
Stress Paradigms
Soft intelligence varies from person to person, to use it you first have to understand what motivates a person and to which mental model they perform best to; some perform well under immense pressure, some under adequate pressure and some need to alleviate all pressure in order to solve the problem. These are the three paradigms of stress: high, medium and low stress.
Stress: A Thought Experiment
Lets say there are three people Bob, Jane and Alice. All three share similar and equal hard intelligence but differ in soft intelligence.
Their task is to get a PhD in quantum physics within 5–10 years.
A PhD in quantum physics is stressful task for anyone but the stress experienced is relative to each observer (in our case Bob, Jane and Alice).
Bob’s motivation and quality of work is dependent on high stress, Jane’s on medium stress and Alice on low stress.
The Approach
Each individual will need to calibrate the level of stress in their environment to fine tune the right conditions for success. These calibrations can be intuitive or counter intuitive depending on the individual.
An intuitive approach has a linearity of outcome. Do A to get B.
While a counter intuitive approach has non-linearity of outcome. Don’t do A to get B.
Conclusion
To solve any problem you need to follow these steps:
Reasoning: autopilot, semi-autonomous, manual
Tools: hard and soft intelligence
Stress paradigm: high, medium and low
Approach: intuitive or counter intuitive
These principles can form a robust methodology in formulation of your own problem solving framework. Self-awareness is a superpower in solving problems because you can devise the best strategy for yourself. Most people try linear models for problem solving while non-linear models although counter intuitive are sometimes more useful.