People often get attached to the idea of a single goal instead of truly appreciating how many different and sometimes conflicting things they care about. 

​

In order to support true decision-making, our models of those choices need to reflect that underlying complexity by making it visible. There are ways to systematically examine possible goals, including the simple model below.

​

• Begin by writing down what you consider as your goals.

• Take a model-based approach to identify other candidate goals. For example, corporations always want more profit and more revenue, but they also might like having more customers, more market share, and so on.

• Human preferences are an often overlooked aspect of goals. Taste, comfort, happiness, all can be part of the things you seek to improve through the meta-problem.

• Risk is also an important part of decisions. Generally we want lower negative risks and higher positive risks. 

• Unknowns are a final important category as sometimes our goal should be to learn more before we make a decision.

​

After creating a long list of candidate goals, we can identify the most important drivers and the ones that are most in conflict. This is inspired by the math of optimization since the most important or contradictory goals will drive the solution.

​

Understanding how to identify goals is just one part of the meta-problem cycle. You can also see illustrations of this idea in practice on the Examples page.