Causal Hypotheses

Causal Hypotheses

In The Book of Why Judea Pearl argues that humans have a unique superpower among animals and living creatures on earth. We are great at developing causal hypotheses. Animals are able to make observations about the world and some are even able to use tools to open fruit, find insects, and perform other tasks. However, humans alone seem to be able to take a tool, develop a hypothesis for why a tool works, and imagine what could be done to improve its functioning. This step requires that we develop causal hypotheses about the nature and reality of tools and how they interact with the objects we wish to manipulate. This is a hugely consequential mental ability, and one that humans have developed the ability to improve overtime, especially through cultural learning.
Our minds are imaginative and can think about potential future states. We can understand how our tools work and imagine ways in which our tools might be better in order for us to better achieve our goals. This is how we build causal hypotheses about the world, and how we go about exploring the world in search of evidence that confirms or overturns our imagined causal structures.
In the book, Pearl writes, “although we don’t need to know every causal relation between the variables of interest and might be able to draw some conclusions with only partial information, Wright makes one point with absolute clarity: you cannot draw causal conclusions without some causal hypothesis.”  (Sewall Wright is who Pearl references)
To answer causal questions we need to develop a causal hypothesis. We don’t need to have every bit of data possible, and we don’t need to perfectly intuit or know every causal structure, but we can still understand causality by investigating imagined causal pathways. Our brains are powerful enough to draw conclusions based on observed data and imagined causal pathways. While we might be wrong and have historically made huge errors in our causal attributions about the world, in many instances, we are great causal thinkers, to the point where causal structures that we identify are common sense. We might not know exactly what is happening at the molecular level, but we can understand the causal pathway between sharpening a piece of obsidian to form a point that could penetrate the flesh of an animal we are hunting. While some causal pathways are nearly invisible to us, a great deal are ready for us to view, and we should not forget that. We can get bogged down in statistics and become overly reliant on correlations and statistical relationships if we ignore the fact that our minds are adept at identifying and imagining causal structures.
Positive Test Strategies

Positive Test Strategies

A real danger for us, that I don’t know how to move beyond, is positive test strategy. It is the search for evidence that confirms what we want to believe or what we think is true. When we already have an intuition about something, we look for examples that support our intuition. Looking for examples that don’t support our thought, or situations where our idea seems to fall short, is uncomfortable, and not something we are very good at. Positive test strategies are a form of motivated rationality, where we find ways to justify what we want to believe, and find ways to align our beliefs with what happens to be best for us.


In Thinking Fast and Slow, Daniel Kahneman writes the following, “A deliberate search for confirming evidence, known as positive test strategy, is also how System 2 tests a hypothesis. Contrary  to the rules of philosophers of science, who advise testing hypothesis by trying to refute them, people (and scientists, quite often) seek data that are likely to be compatible with the beliefs they currently hold.” 


In science, the best way to conduct a study is to try to refute the null hypothesis, rather than to try to support the actual hypothesis. You take a condition about the world, try to make an informed guess about why you observe what you do, and then you formulate a null hypothesis before you begin any testing. Your null hypothesis says, actually nothing is happening here after all. So you might think that teenage drivers are more likely to get in car crashes at roundabouts than regular intersections, or that crickets are more likely to eat a certain type of grass. Your null hypothesis is that teenagers do not crash at roundabouts more than typical intersections and that crickets don’t display a preference for one type of grass over another.


In your experimental study, instead of seeking out confirmation to show that teenagers crash more at roundabouts or that crickets prefer a certain grass, you seek to prove that there is a difference in where teenagers crash and which grass crickets prefer. In other-words, you seek to disprove the null hypothesis (that there is no difference) rather than try to prove that something specific is happening. It is a subtle difference, but it is importance. Its also important to note that good science doesn’t seek to disprove the null hypothesis in a specific direction. Good science tries to avoid positive test strategies by showing that the nothing to see here hypothesis is wrong and that there is something to see, but it could be in any direction. If scientists do want to provide more evidence that it is in a given direction, they look for stronger evidence, and less chance of random sampling error.


In our minds however, we don’t often do this. We start to see a pattern of behavior or outcomes, and we start searching for explanations to what we see. We come up with a hypothesis, think of more things that would fit with our hypothesis, and we find ways to explain how things align with our hypothesis. In My Big Fat Greek Wedding, this is what the character Gus does when he tries to show that all words in the world are originally Greek.


Normally, we identify something that would be in our personal interest or would support our group identity in a way to help raise our social status. From there, we begin to adopt hypothesis about how the world should operate that support what is in our personal interest. We then look for ways to test our hypothesis that would support it, and we avoid situations where our hypothesis could be disproven. Finding things that support what we already want to believe is comforting and relatively easy compared to identifying a null hypothesis, testing it, and then examining the results without already having a pre-determined outcome that we want to see.