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Perspective: is the mapping from reality to internal language such that each distinct object, situation, problem or event is mapped to a unique word

The so-called perspective means that everyone has different experiences due to different experiences, knowledge, and backgrounds.

Different perspectives: This can either mean that two people map reality onto the same internal language in different ways, or it can mean that they map reality onto different internal languages

Different ways of dealing with problems and different experiences

Perspective usually means imposing some structure, internal language that fails to create structure is not helpful in solving or understanding the problem

Experience needs to be related to the problem. For example, we know that apple is a fruit, but we don’t know how it is grown, so it is meaningless to deal with how to grow other fruits.

Different strategies are available

It can either simplify or complicate the problem

New perspectives don’t come out of nowhere; other perspectives often need to be used to build new perspectives.

When people see problems through the same lens, they can get stuck on the same solutions

A common perspective enables fast and error-free communication

Many common perspectives emerge due to the need for imitation and communication.

Reduces diversity of perspectives and stifles group ability to find better solutions

A clear perspective can make the chaotic and unclear become clear and transparent

A heuristic is a rule that applies to existing solutions in a perspective that generates a new and better solution or set of better solutions

Non-deterministic polynomial problem

Topological heuristics

gradient heuristic

Allow to make mistakes heuristic

group heuristic

A perspective is a way of looking at a solution, while a heuristic is a way of building a solution

Interpretation is a mapping from objects, situations, problems, and time to words. A word can be used to refer to many objects in an interpretation

Projective interpretation refers to an interpretation that ignores certain dimensions of perspective

For example, whether a big black dog or a small dog or a white big dog or a small dog can be taken on a plane, the size-based dimension should be used; if you are worried about whether it will cause heatstroke if left under the scorching sun, the color-based dimension should be used. explanation of

Clustering interpretation creates categories of similar objects, situations, problems, or events that are not simple attribute projections

For example, if you want to classify houses according to the principles of Feng Shui, and to meet the requirements of Feng Shui, you need to combine various attributes.

Causal relationships derived from direct mining of data may be spurious

A predictive model is an explanation and makes a prediction for each set or category created by the explanation

The difference between predictive models and heuristics

Make predictions based on what you learned from experience

Make predictions based on basic theory

Make predictions based on data

Multidimensional measurement methods

Three-dimensional measurement method

When there are multiple dimensions, there is no clear winner

combination of tools

playing card model

ladder model

tree model

Intelligence = Diversity of Cognitive Tools

Diversity over ability

complementary perspective

The more tools you have, the more opportunities you have to solve problems

Individually better problem solvers have better local optimal solutions

Better problem solvers use fewer local optimal solutions

Good problem solvers tend to have a greater probability of finding local optimal solutions

Diversity of perspectives and heuristics may cancel each other out

Diverse people may also solve problems in the same way

Homogeneous problem solvers have the same local optimal solution

Diversity problem solvers have different local optimal solutions

The optimal solution lies at the intersection of the local optimal solutions of all problem solvers

problem difficulty conditions

calculus conditions

diversity conditions

large group size conditions

Given the above 4 conditions, a team composed of randomly selected problem solvers can outperform a team composed of the best individually performing problem solvers.

arbitrary contribution theorem

Model 1: “Millions of Fragments” Model

Model 2: "Regional Sales" Model

Model 3: The “Truth Gravity” Model

Model 4: “Noise Average” model

If two people build prediction models based on different variables from the same perspective, their accuracy in making second-house predictions is negatively correlated.

If two people consider different attributes from the same perspective, and if the prediction task to be completed is to predict a binary outcome such as good or bad, then when one of the people's predictions is correct, the other person may be incorrect

squared error method

A group consisting of a set of prediction models must have group error = average individual error - prediction diversity

groups due to the mean theorem

Herd mentality

different parts of the same perspective

Completeness

transitivity

Preferences are rational if they are complete and transitive

If the current amount exceeds the ideal point amount, then less is preferred

If the current amount is less than the ideal point, then more is preferred

Group preferences need to meet four requirements

In general, in situations where more than one dimension exists, no single alternative can defeat all other alternatives in a one-to-one vote

If preferences are multi-dimensional, then generally speaking, given any alternative, it is possible to reach any other alternative through a series of voting

Any non-authoritarian rule that aggregates diverse preferences for more than two outcomes can be manipulated

agenda manipulation

Fundamental preference for diversity leads to undersupply of resources

Imagine two families of four, each with the same fixed budget to spend on building a house

What problems you can see and what opportunities you can discover all depend on your understanding of what is valuable.

Diversity preferences lead people to build predictive models of diversity

People with different training will acquire different cognitive tools

People with different experiences also have different toolboxes

People with different lifestyles will also construct different interpretations and perspectives

Data is noisy

Knowledge spillover occurs when one person shares some perspective, heuristic, explanatory or predictive model with others

Cultural diversity is positively correlated with development

When a group of people are trying to solve a problem, if one person makes improvements and comes up with a new solution, others can often improve upon it.

Continuous experimentation and trying can lead to better individual performance, and doing so can also lead to better group performance.

Leverage external differences to make improvements

For groups to be intelligent, they must both possess the required capabilities and explode enough diversity

To ensure the accuracy of a group's predictions, have everyone make moderately accurate but very diverse predictions

Create an internal prediction market so that a business or organization can tap into its own internal crowd wisdom

Many difficult problems are relevant to multiple traditional disciplines and areas of thought

Basic preferences are compatible, but tool preferences may be conflicting

Slight changes in basic preference diversity can lead to vastly different solutions

If people believe that interacting with people who are different from themselves will pay dividends, they are more likely to receive those dividends

The best groups contain individuals who are both diverse and capable

Go back to the starting point and never forget your original intention