It isn’t too much of a stretch to say that feedback loops make the world go round. Among other things, feedback loops keep machinery—both digital and analog—running smoothly, moderate our weather, and maintain homeostasis in our bodies. Feedback loops also function to either maintain or disrupt the status quo within businesses and other organizations, in politics, in the economy, in interpersonal relationships, and even in regard to our own behavior.

David DiSalvo calls feedback loops “the engines of your adaptive brain.” He says research across multiple disciplines—psychology, sociology, economics, engineering, epidemiology, and business strategy, for example—has validated feedback loops as a solid governing principle.

Day in and day out, we make decisions based on the results of feedback loops that run in our minds without our noticing. None of us stops to think through each stage of the loop—how the data we’ve gathered is being processed to lead us to our next action. And yet, even without our conscious monitoring, the loops just keep moving.

Decision-making requires conscious thought. So it may be more accurate to say we react based on feedback loops rather than that we make decisions. In the same way that our brain has criteria for evaluating the data provided by physiological feedback loops (in order to, say, maintain our body temperature and signal when we need to eat or drink—or stop eating or drinking), it also has criteria for evaluating the data provided by our mental, emotional, and behavioral feedback loops. The problem is that these criteria are part of our mental model of the world, much of which is unconscious, which means we’re not aware of it.

If we don’t stop to think through “how the data we’ve gathered is being processed,” we’re more likely to maintain the very habits of thinking and behaving we’re trying to change.

What Exactly Is a Feedback Loop?

The four stages of a feedback loop as described by science writer Thomas Goetz in Wired Magazine are:

• Evidence
• Relevance
• Consequence
• Action

A feedback loop involves four distinct stages. First comes the data: A behavior must be measured, captured, and stored. This is the evidence stage.

Second, the information must be relayed to the individual, not in the raw-data form in which it was captured but in a context that makes it emotionally resonant. This is the relevance stage.

But even compelling information is useless if we don’t know what to make of it, so we need a third stage: consequence. The information must illuminate one or more paths ahead.

And finally, the fourth stage: action. There must be a clear moment when the individual can recalibrate a behavior, make a choice, and act. Then that action is measured, and the feedback loop can run once more, every action stimulating new behaviors that inch us closer to our goals.

When it comes to behavior-related feedback loops, such as changing an old habit or starting a new one, the sequence looks more like this:

• Action
• Evidence
• Relevance
• Consequence
• New Action (or Reaction)

Just about any activity generates feedback of some sort. The result of an action can be large or infinitesimal, desirable or undesirable. Ideally, you notice what happens and use the feedback to determine what to do next. If you’re driving your car along a snowy road and it begins to skid, the skid is evidence that road conditions require you to make some type of adjustment to your driving. The evidence is relevant to you because you want to avoid an accident, which is a potential consequence of not paying attention to the evidence. Your reaction might be to slow down.

That’s a fairly straightforward example. Another driving-related example, one you may have encountered and which Goetz wrote about in Wired, involves “dynamic speed displays,” also called driver feedback signs. These speed limit signs include radar sensors attached to digital readouts that flash your vehicle’s speed once you get in range. Driver feedback signs have been so successful in decreasing speeding they’re springing up in more and more locations.

The basic premise is simple. Provide people with information about their actions in real time (or something close to it), then give them an opportunity to change those actions, pushing them toward better behaviors. Action, information, reaction. 

The Premise May Be Simple, But the Process Isn’t.

The apparent result of an action we’ve taken—the evidence—must first be interpreted before we can proceed through the steps of the feedback loop to determine how to react. A roadside sign that tells you both the speed limit and your current speed provides you with straightforward, unambiguous evidence. If all the evidence we were faced with was similarly unambiguous, our lives would be much less complex and our decisions would be much easier to make. Alas, such is not the case.

As stated above, DiSalvo says we make decisions based on the results of feedback loops, but even in cases where we’re making decisions rather than simply reacting, it would be more accurate to say we make decisions based on our interpretation of the results of feedback loops.

Because we perceive the world through our particular mental model, we’re predisposed to interpret the results of our actions in certain ways. This can be problematic in general, but it’s especially so when we’re presented with negative evidence. Things didn’t work out the way we planned; we did something other than what we intended or wanted to do; or we’re faced with unexpected obstacles. The most useful way to respond to such information is to look at it objectively. We tried something and it didn’t work. We can then try to figure out why it didn’t work and decide whether to try it again or to try something else.

Instead of viewing the negative results of our actions objectively, however, we’re prone to interpreting them as evidence of failure. Once we interpret the results as evidence of failure, we’re much less likely to try to figure out what didn’t work and what to do next, and we’re much more likely to give up. At that point, the habit or behavior we were trying to change becomes even more entrenched than it was before we attempted to do something about it. And the goal we were trying to achieve seems even more distant.

A student in one of my classes reported struggling for several years with a particular issue of having to document, in detail, time spent caretaking a family member. Every time she tried and failed to find a system that worked, she interpreted it as evidence of personal failure. One day in class, she outlined something new to try. When she returned the following week, she was very excited, but not because the new system had worked. It hadn’t. What she was excited about was that when she realized that particular system didn’t work, rather than viewing it as more evidence of failure she was able to view it objectively. Because she was able to view it objectively, she didn’t waste time beating herself up over it. Instead, she immediately decided to try something else and that new system did work.

Confirmation bias is very powerful. If we believe we’re lazy or incapable or don’t follow through on anything, we’re likely to view the negative results of our actions as confirmation of our preexisting belief and then behave as though that belief is reality. So it’s important to remember that our automatic interpretations can’t always be trusted; sometimes we need to slow down long enough to question them.

Not everything you try is going to go smoothly or work out the way you hoped it would. Sometimes the road is slippery, under construction, or takes a detour. Noticing that what you tried simply didn’t work will allow you to use the information as feedback to help you determine the best way to correct your course—or to chart a brand new one.