The Ladder of Inference
Have you ever found yourself perplexed at the way someone else has interpreted something you said or did, and put a meaning on it that you never intended? Or perhaps you have found yourself enraged by someone’s comment or action, and concluded that they must be acting against you for some reason?
You have been climbing the ‘Ladder of Inference’.
First proposed by Chris Argyris, way back in 1970, the ladder of inference is a way of describing how you move from a piece of data (a comment made to you, or something that you have observed to happen), through a series of mental processes to a conclusion.
You start by selecting from the data, translate it into your own terms, explain it to yourself, and then draw conclusions. It’s dangerous, because it all happens extremely quickly in your head, and you are probably unaware that you are only selecting some of the data. Nobody else sees your thought processes, or knows what stages you have gone through to reach your conclusions. All that they see is the action you take as a result.
How the Ladder Works in Practice
Your beliefs tend to reinforce the data that you select, and how you interpret it, which means that it becomes a positive feedback loop. In this sense, ‘positive’ is not necessarily ‘good’. Instead, it means that the feedback drives the process onwards instead of stopping it, and therefore confirms what you already believe.
Here’s a simple example of a few moves up the ladder:
- Jane arranges to meet Mary for coffee at 10.30am.
- Mary is late and does not explain why. In fact, she doesn’t seem to have noticed that she’s late at all.
- Jane decides that Mary simply couldn’t be bothered to turn up on time, and that Mary values her own time more highly than Jane’s.
- Jane concludes that it’s not worth bothering to meet up in future, because Mary obviously doesn’t want to see her.
- When Mary suggests meeting the next week, Jane makes an excuse to avoid it.
At the end of this, all Mary sees is that Jane does not want to meet up again. She may have no idea why. There could be any number of reasons why Mary was late, and hasn’t explained: a doctor’s appointment, perhaps, or it could be as simple as her watch being slow, so that she has no idea that she is late. Meanwhile, Jane has decided the friendship is not worth pursuing.
A lot of the time, you won’t even be aware of the beliefs and assumptions underlying your data selection and the inferences that you draw. They may go right back to childhood, and a chance comment, even one overheard and only half-understood.
Avoid Climbing the Ladder of Inference
What can you do to avoid climbing the ladder of inference, or help others to avoid it?
First of all, you have to accept that you are always going to draw meaning and inferences from what others say and do, based on your past experience. It’s how people work.
If we did not use past experience to help us interpret the world, we would be absolutely lost. Nobody would be able to ‘learn from experience’ at all.
The issue, then, is to draw on experience, but in a way that does not make assumptions about others’ behaviour, or which allows us to check back on those assumptions.
Rick Ross, in The Fifth Discipline Fieldbook, one of the standard organisational learning texts, describes three ways you can change to improve the way you communicate and avoid you or others climbing the ladder of inference:
- You can become more aware of your own thinking and reasoning (reflection, or reflective practice);
- You can make sure that others understand your thinking and reasoning (advocacy);
- You can ask questions of others about what they are thinking, and test your assumptions (inquiry).
When considering your own thought processes, beware particularly of pieces of information that you take for granted. They are likely to be deeply rooted in your belief system, and it’s worth stopping to examine them to make sure that they really are facts. Some of the time, at least, you will find that others do not see them as ‘right’ at all.
In explaining your reasoning and thinking, key phrases to use are “So, I’m hearing that you like this part, but not that aspect. Would you agree?”, “It sounds to me like…” and “I’m thinking that x makes sense, but do others agree?” You can also ask questions to test the data. There are three main types of questions. You can ask for data, in an open-ended way, test your assumptions, or just note the observable data.
In the example above, Jane might say to Mary:
“Is everything OK?”
“Did you have trouble with the traffic this morning?”
“Was 10.30 too early for you? We could have made it later.”
“Was it inconvenient to meet up this morning? You can always let me know if so, and we can rearrange.”
“Goodness, you’re very late!”
Any of these could open up a conversation about why Mary was late, or uncover the fact that she had no idea she was late. Alternatively, when Jane says that she doesn’t want to meet up next week, Mary might say to Jane:
“Are you OK? You’ve been very quiet this morning.”
It is, however, difficult to test your final assumptions directly without sounding either stupid or rude, and inviting a particular answer. For example, it would have been hard for Jane to ask Mary whether Mary valued their meetings. She could hardly have relied on the answer, since Mary was bound to say that she did, out of politeness, even if she did not. It is therefore important to think about how you ask the questions to test the data and your assumptions.
One Final Point
When testing the data or your assumptions, you don’t need to mention the ladder of inference at all. As Rick Ross says, using it is not about making a diagnosis, but about helping to make your own and others’ thinking processes more obvious, thus improving communication. If you both know the model, then it can provide a helpful language but, even then, it’s never going to help to say “Are you climbing the ladder of inference a little bit there?”, which even the most insensitive among us will admit could be a touch irritating!