This is a summary of the book “Streetlights and shadows: searching for the keys to adaptive decision making” written by Gary Klein and published by MIT press in 2009. This book is in a series of books by the author on decision making in complex situations. He has spent decades interviewing people such as firefighters, soldiers and pilots and brings us to some common themes and the errors in judgement. People tend to simplify complex situations until their beliefs become dangerous. This book teaches ways to avoid that and make us more adaptive. Communication and feedback are helpful but often misunderstood. He suggests blending intuition with logical analysis and draws away from guidelines and procedures to tacit knowledge including intuition, pattern recognition and mental models.

The human eye uses different systems for daylight and darkness, with "cone cells" focusing on detail and "rod cells" being more sensitive to faint light. Decision making should be approached differently in well-known and clearly defined situations and in ambiguous ones. Most common beliefs about decision making work in "bright and clear conditions," but they can be limiting or dangerous.
Incorrect beliefs include teaching people specific procedures, which can distort thinking and hinder learning and expertise. Cognitive biases, such as framing and representativeness heuristics, can also distort decision-making. Using logic instead of intuition is essential for sound decision-making, as people may overthink and back away from strong initial decisions.
Blocking out several choices and comparing them is also a common belief, but it takes too long to be useful in most situations. Experts read situational cues and react when faced with different options, making it crucial to consider both intuition and logic when making decisions.

In ambiguous situations, reducing uncertainty by acquiring more information is true, but some problems are mysteries that require analysis and action. It is important to wait until all evidence is available before jumping to conclusions. Giving feedback on the consequences of actions helps employees learn better, but it is easier in well-ordered situations and more difficult in complex, shifting circumstances. Drawing inferences from data is the "assembly line" metaphor, where data and relevance are not self-evident. Create narratives early in a situation and revise them as new data arrives. To start a project, clearly describe your goal, but this rule can stall progress in complex and shifting situations. Instead, set qualitative goals and redefine them as needed, using "managing by discovery" to gather data and adapt to the situation. This approach helps in navigating complex situations and making informed decisions.

Identifying and eliminating the biggest risks is crucial for effective risk-mitigation plans. However, inexperienced organizations may struggle with accurate evaluations. Resilience engineering and an adaptive mindset are essential for quick and effective responses. Assigning roles and writing ground rules can help define common ground, but communication is difficult due to individual experiences. Recognize the fragility of common ground.

To make better decisions in complex situations, start by shifting your mindset from a "mental storehouse" to a "circle" of adapting, sense-making, and decision-making. This involves practicing "unlearning" and recognizing the importance of intuition and analysis. As you move through life, you develop, change, and shed your skin, allowing for continual growth and change.
Make a circle of expertise, with adapting, sense-making, and decision-making points along the outer edge. This approach allows you to make sense of a situation and adapt as you act on it.
Switch from explicit knowledge to tacit knowledge, which includes recognizing patterns, mental models, perceptions, skills, and judgment. Convert tacit knowledge to explicit knowledge by internalizing it with the deep well of tacit knowledge.
Become an expert in your field by drawing lessons from experience and developing sophisticated mental models about your capabilities. Expertise doesn't prevent mistakes but helps you recognize them more quickly.

Previous book summary: BookSummary61.docx

Summarizing Software: SummarizerCodeSnippets.docx. 

Get the Longest Increasing Subsequence:

For example, the LIS of [10, 9, 2, 5, 3, 7, 101, 18] is [2, 5, 7, 101] and its size() is 4.

public static int getLIS(List<Integer> A) {

if (A == null || A.size() == 0) return 0;

var best = new int[A.size() + 1];

for (int I = 0; I < A.size(); i++)

      best[i] = 1;

for (int I = 1; I < A.size(); i++)

 {

     for (int j = 0; j < I; j++) {

            if (A[i] > A[j]) {

                   best[i]  = Math.Max(best[i], best[j] + 1);

            }

     }

}

List<Integer> b = Arrays.asList(ArrayUtils.toObject(best));

return b.stream()

.max(Comparator.comparing(Integer::valueOf))

.get();

}