Science vs Reason

philosophy

Tue Nov 24 19:07:33 -0800 2009

“Science” and “reason” are two words often spoken alongside each other - almost as if they were the same thing. Both are approaches to seeking truths about the world around us; they complement each other, but each is distinct.

Science is about the external world: measurement, controlled experiment, data collection, empiricism. It tests hypotheses against the hard reality of repeatable experiments with objectively measurable results. Those who practice it are called scientists or empiricists.

Reason, by contrast, is internally generated. It’s building mental models of the world, starting with your internal sense for what is right and pure, from which further truths can be deduced. Those who practice reason are called rationalists.

For most of history, reason was the only known or accepted way to arrive at truths about the world. My hunch is that this is because tools for objectively and accurately measuring distance and time - the two most basic features of the physical world - did not exist up until around four hundred years ago. Man had to look inside himself to discover truth.

When to Apply Reason

In some circumstances, reason excels where science fails. One example is our understanding of a triangle. (I’ve adapted the following from Kant’s example in Critique of Pure Reason.)

A equilateral triangle is a two-dimensional geometric shape with three sides of equal length and equal interior angles. If you wanted to seek this truth through empiricism, you’d need to go out and measure hundreds or thousands of three-sided objects. You might draw out on paper dozens of triangles, whose sides and angles you could then measure.

But no matter how many triangles you might measure, none would ever be exactly a perfect equilateral triangle. If your measuring tools are accurate enough, you’ll always see that there are slight variations between the length of the sides. Science, collecting data from the world around us, cannot tell us the nature of the equilateral triangle.

Reason wins out here because it happens in the purist and abstract realm of the mind. We can easily construct a mental model of a pure equilateral triangle, a geometric shape that has no depth, has three sides of exactly equal length, and three interior angles that exactly equal each other. We can create mathematical statements about this (and yes, that means math is not science). A single rationalist can discover in an evening of thought something that countless man-hours of science cannot.

When to Apply Science

Where does science excel, and reason fail? Reason’s downfall can be its disconnect from objective reality. One dramatic example of this comes from Aristotle, ancient master of reason-driven philosophy.

Aristotle presented one of the first physics models. He based his model on his own informal observation, and fed it through his deductive capabilities, Sherlock Holmes-style. One example: he argued that heavier objects fall at faster rates than lighter objects. This is easily disproved by dropping a heavy object and a light object of the same shape from a high place and seeing which hit the ground first. Yet it took over a thousand years before anyone thought to try this experiment.

Aristotle also held a theory that if you were riding a moving object, and you threw a ball straight up into the air, the ball would land on the ground behind you, rather than coming back to your hand. This seems intuitively correct. But a simple experiment - sitting in a moving vehicle and tossing a ball into the air and catching it - will disprove it. The forward momentum of the ball is identical to that of your hand, and it moves within that frame of reference as if you were standing on the ground. (It’s a good thing for this, because everything on earth is traveling at around 1000 miles per hour.)

Here, science can discover in a few minutes what eons of rationalist thinking could not.

Science and Reason in Business

In the end, both reason and science have their place. When making a decision in a situation where taking measurements is difficult or impossible, the only thing you can do is follow your intuition. The early days of most startups are such an environment. If you’re doing something truly revolutionary, there’s very little you can measure in the beginning to validate your theories. In fact, introducing measurement at this stage can be extremely harmful, because you make what you measure. The measurements you choose (which will necessarily be somewhat arbitrary) will shape what you make, and you will most likely end up making the wrong thing. This is why the intuition-driven entrepreneur thrives in the early stages of a startup.

In a more mature company, however, you can and should measure the hell out of everything. With a clearer path and a large enough pool of data for meaningful statistics to draw on, it’s possible to see trends and draw inferences. You know what you are trying to achieve, and most of those things can be quantified (number of users, quantity of web traffic, dollars of revenue, dollars of profit). Here, the intuition-driven entrepreneur starts to look more like a shoot-from-the-hip cowboy, a disruptive influence on a stable product. A mature company wants empiricists, careful and numbers-driven individuals who are making fine-tune adjustments based on hard data collected on a large scale and over long periods of time.