Factors to Consider

I tend to think about a lot of different things. It’s more than a bit annoying and it doesn’t mean that my observations and conclusions are accurate, just that I’m constantly making them (and sometimes changing them). I assume the world is in many ways knowable, and in a lot of ways not knowable, at least not by creatures of our limited intelligence. Whether an object of thought is somehow knowable or not, we can still attempt to reason about it. When thinking things through, I try to recall that all meaningful systems have certain traits, drivers, or properties that we should keep in mind.

Context – Everything that exists does so in relation to everything else. The universe is connected, the parts interacting weakly or strongly in various ways. Whatever the circumstance, a given piece is built on a lower order and embedded in a higher order. This is true at all levels of detail (or at least those that we usually operate within). It applies to ideas, molecules, organisms, fiction, side streets, beehives, corporations, French history, ecosystems, galaxies and everything else. The more you can understand the context, the better your decision-making can be. There’s no guarantee however because - beyond a certain threshold of complexity - you can never fully understand the context. You can make useful models but they will always be incomplete.

Feedback – Outcomes of the past are input to the present. Systems evolve and perpetuate when the results of previous decisions / events are advantageous to the continuation of the system. Feedback can be positive or negative. Negative feedback will inhibit or modify behavior. Positive feedback will encourage it. Most systems will tend toward an equilibrium that the feedback mechanisms maintain. Without equilibrium you can end up with vicious and virtuous cycles that destabilize the system. Resilient systems have (among other characteristics) multiple feedback loops that maintain equilibrium over long stretches of time.

Incentives – People make decisions and take action based on the avoidance of pain and/or an increase in pleasure (the former is often more important than the latter). This is a core of human motivation and any system that includes humans needs to take this into account. Perverse or simplistic incentives will distort or destroy a well-intentioned system. Incentives are themselves a form of feedback, but given how critical they are to understanding human action it might be that they deserve special consideration.

Trade-offs – There is always a down-side. No choice or course of action is without some negative aspect or sacrifice. If you can’t see the downside, you haven’t looked closely enough. If nothing else, there’s an opportunity cost, a sacrifice of time or other resources. Know which downsides are being selected for and perhaps how they can be mitigated. Understand that you may not know all the negative outcomes in a trade-off.

Bias – We all have conscious biases (preferences) and a myriad of unconscious ones. We incorporate these into our systems and into our attempt to understand systems. Your model is incomplete and so is your thinking process. The brain takes a number of shortcuts to conserve energy. Understanding your own biases and blind spots can make you a better thinker but only if you take action to offset them. Seek out disconfirming evidence. Take the opposite view point, understand it and argue against your choices.

Connectedness – You can never do one thing. Because within whatever context you are operating in, there are connections from the one to the many. There will be second and third-order effects from anything you do. In simple systems, these may be obvious and enumerable. That will not be the case with complex systems. Ecosystems and economies have levels of connectedness that are beyond comprehension. Which is why we use models. And why we can never know with certainty what cascade of effects our individual and collective actions will have.

Keep these things in mind when you’re thinking through a plan, making a decision, evaluating a system, wondering why something went wrong or otherwise dealing with the world. If humans are involved, these factors always matter. Most of them matter even if humans are not involved.