Visualizing Good Behavior

Does your behavior always align with your intention? I doubt it. Mine certainly doesn’t, so I’ve devised a way so quantify and visualize the gap in real time.

It’s pretty simple: when the gap between my actual choices and my intended choices is small, my behavior is good. When the gap is large, my behavior is bad.

How often I should act depends entirely on my intentions. When I intend to have a long and healthy life, I should exercise often, eat the healthiest food, and stay away from risky habits. Health involves many activities and it’s entirely up to me to make good choices as often as possible. Any help I can get is quite wonderful.

Having my behavior information at my fingertips helps keep me on the right track. It’s especially helpful when I’m under stress, when down, or when my memory or discipline isn’t as sharp as it should be. I need this information the most when I’m not thinking clearly, as a mirror that shows me where I am failing, what I’m neglecting, and just how bad has it gotten over the past couple of weeks. And, for the same reason, it’s critically important that the information is easy to accumulate and simple to consume.

A bonus of having all of this information in digital form is that it’s easy to share with family, friends, or professionals. That opens up many opportunities for them to help. Perfect for a person in a spot of trouble.

The Visual

Interpreting the visual is simple: how thick is the graph? How thick is it right now compared to this morning, or yesterday, or a week ago? What are the trends and patterns over the past month or year? This isn’t your typical mathematical, statistical, or metrics graph because it’s based on data you already know: your actions. It’s designed for quick but frequent consumption, like looking in a mirror or asking a friend for their perspective.

The following graph shows many dips in the quality of my behavior since a week ago:

The horizontal symmetry is an aesthetic preference.

In the above example, I’m behaving about half as well as I’d like to, and fairly consistently too. Dips in the graph indicate periods where my choices have become misaligned with my goals.

Repetition and Decay

I repeat my actions because the effect of each action dissipates and decays. Eating satiates me for a while, drinking slakes my thirst for a while, but soon enough I need to do it again.

It’s the same type of repetition for everyone: maintaining relationships, going to work, exercising, paying bills, having sex, buying groceries, personal hygiene, taking medication, listening to music, drinking alcohol, maintaining the car, and everything else we do.

Nothing lasts forever, especially not the effects of individual actions. The Second Law of Thermodynamics makes sure of that.

How It’s Done

The core visualization is based on timelines of activity. Each type of activity gets its own timeline, like this:

Such a timeline can be created by simply pressing a button. That’s easy enough for anyone. It also applies equally well to any type of activity, no matter how abstract, concrete, simple, or complex.

Each timeline is then assigned a target interval based on the target frequency for that activity. This interval might be 24 hours for flossing and showering, 12 hours for brushing teeth, 4 weeks for a haircut, and so on.

With a 12-hour interval, each time I brush my teeth my behavior is considered “good” for the next 12 hours. As long as I repeat after roughly 12 hours, I’m doing pretty well. Perfect behavior makes a boring visual:

Perfectly boring behavior

Teeth-brushing behavior during a vacation week might look more like this:

Patterns often break down absent external influence

And when we stack several activities, it begins to look like this:

Again, left to right.

Remember that “now” is on the left, meaning that each graphed action gradually shifts toward the right.

Per-action decay of effect

Next up is the decay of effect — the universal driver of repetition.

An action’s decay can either begin immediately after the action occurs or the decay can be delayed until after the action is expected to repeat. I find delayed decay to be more psychologically friendly. For simplicity, we’ll say that the rate of decay is linear even though it may often be an exponential curve.

Immediate linear decay looks like this:

Decay begins immediately after action.

Delayed linear decay looks like this:

Decay begins after recurrence is expected

And finally we combine the three-activity rectangular graph above with delayed linear decay to get this view.

Good and bad behavior made plainly obvious

It’s apparent that in the past week there’s been several neglectful days and a couple of better days. Each new good choice I make causes the graph to immediately thicken on the left and gradually move to the right.

As part of a complete system

I’ve integrated these visuals into a larger open-source project of mine named Benome. Although not part of the current release, there’s an interactive demo of this visualization on the project’s home page.

In the image below, you’ll notice a kind of hierarchy where the blue, yellow, and aquamarine circles each have their own behavior-quality graphs while the large red circle combines those three graphs into a single high-level view.

The hierarchy can be as deep or complex as necessary while still offering a real-time aggregate view of the quality of one’s recent past behavior. Drilling down into the details is as simple as tapping on any of the smaller circles.

The top-level view aggregates the behavior detailed in the lower-level views, leading to a natural ability to drill down into the details.

I designed Benome to enable anyone to capture timelines of activity with utmost efficiency, to any degree of detail. This visualization supports the project’s core objective of gradually aligning a person’s behavior with their goals.

Recently I laid out the project’s fundamentals in a three part series consisting of data structure, algorithm, and user interface:

There’s a lot more to it, but the basics come first. Let me know what you think!