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basics
Our knowledge base
On humans, machines, decisions, and complexity
Humans knowledge base
Appreciating that humans are two minds in one
Getting humans to work together
Humans tell stories
Going beyond human norms
Humans are meaning-seeker and meaning-makers
Humans long to belong
Humans are wired to look for intentionality
Humans create worlds from concepts
Human thinking follows feeling
Human imagination is unique
Intuition is fast and mostly good enough
Human desires are layered and emergent
Humans knowledge is group knowledge
Humans are cause and effect thinkers
When the non-obvious becomes obvious - Aha!
Humans are creative because we’re curious about the world
Variability is both good and bad
Thinking as spatial and based on movement
How humans construct reality
Know when to explore versus exploit
The downside of uncertainty
Cognitive biases as the price of energy efficient cognition
We are our choices
Machines knowledge base
Four types of machine learning
How humans experience AI
How machines learn, a primer on machine learning
The basics of artificial intelligence
Decisions knowledge base
How to responsibly use the framing effect to influence people
How to tell stories with data
How to convince others of your decision
How to protect against the sunk cost fallacy
How to protect against the framing effect
How to protect against hindsight bias
How to protect against overconfidence
How to protect against availability bias
How to protect against anchoring bias
How to protect against loss aversion
How to protect against confirmation bias
How to understand your biased thinking
How to understand fast and slow thinking
How to make a group decision
How to prioritize solutions
How to generate solutions
How to know your current solution is not the best solution
How to know you have enough data to make a decision
How to synthesize information for decision making
How to triangulate analysis
How to use a decision tree
How to use a decision matrix to make a decision
How to use logic trees to analyze a decision
How to use technology adoptions curves in forecasting
How to analyze maximum market size
How to use the MECE principle to analyze a decision
How to use Occam’s razor to make a decision
How to use the 80:20 rule to make decisions
How to make predictions from data
How to conduct a statistical test
How to understand the different ways you might be wrong
How to spot confounding factors
How to determine causation from correlation
How to understand statistical significance
How to design an experiment to test an hypothesis
How to use statistical tests in decision making with data
How to spot patterns in data
How to understand randomness
How to define a hypothesis
How to use statistical and data mining techniques to find patterns, trends, and insights in data
How to understand errors
How to use dispersion statistics to understand data
How to use descriptive statistics to understand data
How to balance data and intuition when making decisions
How to collect and analyze data
How to prepare your data for analysis
How to structure data analysis by asking questions
How to break a problem into knowns, unknowns, and unknowable parts
How to define a problem or decision
How to think like an analyst
How to make decisions that take emotions into account
How to reduce the negative impacts of emotions in decision-making
How to understand the impact of your emotions
How to make data-driven decisions
Complexity knowledge base
How to design learning rules in complex systems
How to avoid unintended consequences when designing incentives in a complex human system
How to design incentives in a complex system
How to find the point of leverage in a problem system
How to use design abduction to respond to complex business problems
How to define the levels in system that represents a complex business problem
How to draw a systems map to represent a complex business problem
How to design a solution to a complex problem
How to apply principles from complexity science to complex business problems
How to recognize a complex problem
How to recognize a complicated problem
How to recognize a simple problem
How to recognize adaptation in business systems
How to recognize heterogeneity in business systems
How to recognize feedback loops in business systems
How to recognize non-linear relationships in business systems
How to recognize emergent properties in business systems
How to recognize interconnected business systems
How humans make problems more complex
How machine learning makes problems more complex
How digitization makes problems more complex
How to recognize a complex system
Human choice and our right to a future tense