Algorithms: Turn Life Into A Simple Recipe

Mental models are tools for the mind. Professors are specialists in their disciplines and lack understanding in the disciplines of others. This creates what Charlie Munger calls the “man with a hammer” syndrome. To a man with only a hammer, every problem looks like a nail. The antidote is to give the man a set of tools. When he does not just have a hammer, but a full toolbox, he is bound to make use of them. Mental models are additive, and we need an algorithm to search through them and pick the ones fit for the context.

Search engines search. They are effectively organized using algorithms. Algorithms are like recipes. They are lists of steps that tell us how to get from point A to point B. Rather than being directions, algorithms are if-then machines that help us tune out the noise to zero in on the signal. Thinking in algorithms helps us repeatedly get desired outcomes. It is a step-by-step procedure by which a problem or specific task is solved or achieved. An algorithm can be as simple as the recipe to bake a cake and as complex as the machine learning models that power artificial intelligence systems. They are fundamental to computing, mathematics, and everyday activities where structured problem-solving is involved.

In essence, an algorithm transforms inputs into desired outputs by following a well-defined sequence of steps. Every algorithm has to have a defined end point or condition at which it terminates. For example, a sorting algorithm ends when all the elements are in the correct order, and a recipe algorithm ends when the cake is on our table. Each step must be precisely defined. With no ambiguity. Adding two cups of sugar to the batter is clear. Some sugar into the mix is not. Algorithms require both inputs and outputs. The mere existence of a recipe—the data, conditions—does not necessarily dictate that we will bake the cake—the solutions, processed data. Each step must be basic enough for execution. And the best algorithms are generalizable: they apply to a broad set of problems, not just one, like a cake batter that can be integrated into numerous different recipes.

Real life implications of algorithms:

• Day-to-day activities: algorithms guide daily activities, like navigation or shopping, such as by using Google Maps to find the shortest route between two points or a company’s standard operating procedure to onboard a new employee;

• Technology: algorithms underpin software development, data processing, and the functionality of most complex systems; like compression algorithms which reduce file sizes for storage and transmission;

• Business: automating tasks like stock trading, customer segmentation, and fraud detection is now the norm, with high-frequency trading algorithms analyzing and acting on market data in milliseconds;

• Artificial intelligence: models are trained to recognize systems, patterns, make predictions, or to automate tasks, such as the recommendation systems on Netflix or YouTube.

How you might apply algorithms as a thinking tool: (1) break down the problem, decomposing it into smaller, manageable, immediately actionable parts that can be formulated into a checklist-like algorithm; (2) iterate and refine, testing different steps, designs, or sequences of actions to come up with the most efficient workflow for yourself; (3) leverage pre-built algorithms the people already use, like tried and true morning routines or work environment optimizations; (4) optimize for efficiency, focusing on how fast you can get the algorithmic tasks done in an effective manner; (5) visualize the flow in your mind, mapping out the steps for better understanding and to see whether your algorithm will actually work and will work consistently when implemented into your life.

Thought-provoking insights. “Algorithms are opinions embedded in code.” came from Cathy O’Neil, highlighting the ethical implications algorithm designers have to handle. “The simplicity of an algorithm is often its greatest strength.” is a reminder to prioritize clarity and efficiency above complexity. “Data is the fuel, and algorithms are the engine of the modern world.” underscores the symbiosis between data and algorithmic processes seen in modern living. Algorithms are the backbone of modern technology. They enable efficient problem-solving in numerous fields. Harness their power to streamline your processes. Try checklists, recipes, and decision-making frameworks. Rely on algorithms.