Quotes About Decision

want to, you say it's not a good idea." She shook her head. Grown-

What makes a decision great is not that it has a great outcome. A great decision is the result of a good process, and that process must include an attempt to accurately represent our own state of knowledge. That state of knowledge, in turn, is some variation of "I'm not sure.

In most of our decisions, we are not betting against another person. Rather, we are betting against all the future versions of ourselves that we are not choosing.

Improving decision quality is about increasing our chances of good outcomes, not guaranteeing them.

Over time, those world-class poker players taught me to understand what a bet really is: a decision about an uncertain future. The implications of treating decisions as bets made it possible for me to find learning opportunities in uncertain environments. Treating decisions as bets, I discovered, helped me avoid common decision traps, learn from results in a more rational way, and keep emotions out of the process as much as possible.

If you feel like you've got a close call between quitting and persevering, it's likely that quitting is the better choice.

And this feeling that the result of the decision tells you something significant about the quality of the decision process is so powerful that even when the description of the decision is identical (you quit your job and take a new position), your view of that decision changes as the quality of the result changes.

When people result, they look at whether the result was good or bad to figure out if the decision was good or bad.

RESULTING A mental shortcut in which we use the quality of an outcome to figure out the quality of a decision.

Experience is supposed to be our best teacher, but sometimes we draw a connection between outcome quality and decision quality that is too tight.

For reasons that are going to become clear, a good decision tool seeks to reduce the role of cognitive bias (such as overconfidence, hindsight bias, or confirmation bias) and a pros and cons list tends to amplify the role of bias.

Determining whether a decision is good or bad means examining the quality of the beliefs informing the decision, the available options, and how the future might turn out given any choice you make.

When the outcome turns out poorly, it's easy to focus on the details that suggest the decision process was poor. We think we are seeing the decision quality rationally because the bad process is obvious.

The quality of the outcome casts a shadow over our ability to see the quality of the decision.

We want outcome quality to align with decision quality.

The decision you make determines which set of outcomes are possible and how likely each of those outcomes is. But it doesn't determine which of that set of outcomes will actually happen.

Luck is what intervenes between your decision (which has a range of possible outcomes) and the outcome that you actually get. Because any decision determines only the set of possible outcomes (some good, some bad, some in between), this means good outcomes can result from both good and bad

Most decisions have a mix of upside and downside potentials. When figuring out whether a decision is good or bad, you are essentially asking if the upside potential compensates for the risk of the downside.

The actual outcome casts a shadow over your ability to remember what you knew at the time of the decision.

As Nietzsche points out, regret can do nothing to change what has already happened. We just wallow in remorse about something over which we no longer have any control. But if regret happened before a decision instead of after, the experience of regret might get us to change a choice likely to result in a bad outcome.

Whenever we choose an alternative (whether it is taking a new job or moving to Des Moines for month), we are automatically rejecting every other possible choice. All those rejected alternatives are paths to possible futures where things could be better or worse than the path we chose. There is potential opportunity cost in any choice we forgo.

Kill criteria could consist of information you learn that tells you the monkey isn't trainable or that you're not sufficiently likely to reach your goal, or signs that luck has gone against you.

Do you want to just let it all out, or are you thinking of what to do about it next?

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