There is not enough meaning…

The 2nd conundrum is that the process of turning raw information into something meaningful requires connecting the dots between the limited information that?s made it to you and the catalog of mental models, beliefs, symbols, and associations that you?ve stored from previous experiences. Connecting dots is an imprecise and subjective process, resulting in a story that?s a blend of new and old information. Your new stories are being built out of the bricks of your old stories, and so will always have a hint of past qualities and textures that may not have actually been there. A simple example of this is how the first automobile was referred to as a horseless carriage, because the closest thing to it had horses attached. If a super artificial intelligence was loaded with every symbol and story on the internet and in our collective human minds, it would still not be able to interpret new information without using old symbols (and a ton of those symbols and stories would be pretty wonky and mostly useless? I do not envy that super A.I. the task of sifting through all of that).

Below is a comprehensive list of Cognitive biases that make up section #2 of the Cognitive bias chart,

There is Not Enough Meaning…?

We think we know what other people are thinking

• Illusion of transparency
• Curse of knowledge
• Spotlight effect
• Extrinsic incentive error
• Illusion of external agency
• Illusion of asymmetric insight

We simplify probabilities and numbers to make them easier to think about

• Mental accounting
• Appeal to probability fallacy
• Normalcy bias
• Murphy?s law
• Zero sum bias
• Survivorship bias
• Subadditivity effect
• Denomination effect
• Magic number 7+2

We imagine things and people we?re familiar with or fond of as better

• Out-group homogeneity bias
• Cross-race effect
• In-group bias
• Halo effect
• Cheerleader effect
• Positivity effect
• Not invented here
• Reactive devaluation
• Well-traveled road effect

We fill in characteristics from stereotypes, generalities and prior histories

• Group attribution error
• Ultimate attribution error
• Stereotyping
• Essentialism
• Functional fixedness
• Moral credential effect
• Just-world hypothesis
• Argument from fallacy
• Authority bias
• Automation bias
• Bandwagon effect
• Placebo effect

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