Final Paper: Nature of Success
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CAMSNatureofSuccessClassMidtermreviewREVIEWFall181.pptx1
The Nature of Success
Class Seventeen
REVIEW!!!!
Midterm Exam
1. 55 multiple choice questions
2. Testing your fund of knowledge
3. Mainly from lectures, readings that are directly relevant
4. An ‘A’ means an ‘A’
5. Understand the concepts
November 6
3
The Nature of Success
Class One
Introduction and Course Overview
4
Reality is Amorphous
Draw a line around the system boundary
Indicate the most important challenges the system must face
Indicate how the system interacts to face these challenges
What it means to draw that boundary line
You have defined the domain of success/failure that you want to understand.
You have identified the entities inside the boundary that are needed to achieve success (through their interactions). Thus, you have defined your system.
You have identified the entities outside the boundary that will pose the challenges/opportunities that must be managed by the system for the achievement of success.
You understand that it is the information that comes in from the outside entities and is processed by the inside entities – according to an established set of rules – that defines the functioning of the system.
The systems use of this established set of rules is based on the system’s working model of reality.
Core Ideas
Once a system’s purpose/aims and boundaries are known, then we have to understand the system’s structure and function.
A system’s structure describes the entities contained by the system and the particular way they are organized.
A system’s function describes how the entities interact with each other and how these interactions form the emergent properties of the system.
Emergent properties: The whole is greater than the sum of its parts.
Remarkably, a great variety of different systems have similar structural and functional characteristics.
Understanding these commonalities will make our work much easier.
Once we get all this we will see that Complex Systems – no matter how complex – usually follow a small number of simple rules.
If we can understand the rules of the Complex System containing a domain of success we care about, then we understand the rules that lead to the domain of success we care about.
6
7
The Nature of Success
Class Two
System Observations
8
The Nature of Success
Class Three
What is a System?
Our Basic System Model
Pattern of Emergent
Behavior
Observed Regularities
Behavior of System Elements
Positive
Feedback
Negative
Feedback
Responding to Ever-Changing
Environment
Key Points re Systems
System Boundaries: what’s in and what’s out
System components: what are the entities that comprise the inside of the system?
System interactions: what governs the behavior about how the systems entities interact with each other?
System purpose: What is the system ‘trying’ to accomplish? What does success and failure mean related to this definition of purpose?
System information processing: How does the system use information to accomplish its purpose?
System dynamics: How does the system change over time and why?
Regarding success: Always start by ‘planting your flag’.
Responding to Ever-Changing Environment
Adaptation concerns how a system maintains continuity over time (survives) within the environment in which it is situated
To be successful (in surviving) a system needs to adjust to changing circumstances and –especially - to changing competitive landscape.
As we will see, the way the system takes in information from the environment, transmits it across the system, and responds to it, will be critical.
Success requires adaptation but is often more than survival. In a way it means growing in the environment in a way that is desired.
Behavior of System Elements
What are the entities that comprise the system?
How are they organized related to each other?
What is the structure of the system?
What is the structure of a Complex Adaptive System?
System Boundaries
What’s in/What’s out
Sometimes the answer is not so clear (because systems are embedded within each other/hierarchically organized)
Knowing the correct boundary many require knowing the correct question (and visa versa)
Observed Regularities
How we observe the behavior of entities within the system
How do they interact. What patterns/regularities do we observe?
Are entities behaving randomly or interacting in a way that would not be expected by chance.
Once regularities are observed: What do they mean?
Important: The behavior of an entity may appear completely random, until the system is brought into the picture.
Pattern of Emergent Behavior
With our observations of regularities/patterns of entities, we can ask what does it mean for the system?
What is the system trying to accomplish? What is its purpose?
Such questions cannot be answered only at the level of individual entities.
How does this work for the bird flock, the ant colony, the slime mold, the Hanoi traffic community?
What are these systems trying to accomplish within their defined environment?
System Regulation
Systems use information to increase or decrease activity across the system
This is called regulation and is based on feedback to members of the system who respond according to predefined rules.
Positive feedback concerns response to information (feedback) that increases activity. It leads to system change.
Negative feedback concerns response to information (feedback) that decreases activity. It leads to system stability.
This regulation best defined within causal loops of activity.
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The Nature of Success
Class Four
Failure!!
18
Challenger System
Challenger System
Pattern of Emergent
Behavior
Observed Regularities
Behavior of System Elements
Positive
Feedback
Negative
Feedback
Responding to Ever-Changing
Environment
How Complex Systems Fail
Richard I. Cook, MD Cognitive technologies Laboratory University of Chicago
Complex systems are intrinsically hazardous systems.
Complex Systems are heavily and successfully defended against failure.
3) Catastrophe requires multiple failures – single point failures are not enough.
4) Complex systems contain changing mixtures of failures latent within them.
5)
The Virtue of Failure
Risk is embedded in human (and non human) existence. Efforts to eliminate risk (even if possible) limit possibilities to achieve success
Most important – perhaps – is these efforts limit possibilities to learn.
There is an important risk/reward tradeoff we must all grapple with:
Too much focus on gaining reward through taking risks creates instability and even the possibility of extinction
To much focus on avoiding risk limits opportunity for reward and for learning (about own capabilities and about what the environment can offer).
Saxe Interview
22
The Nature of Success
Class Five
The Individual within the System
First Principles
A system needs to survive and succeed in its environment
Environments pose multiple possible sources of challenge at any one time, and changing sources of challenge over the life of the system.
The specific challenge a system will be exposed to at a given time – and over time – is often unpredictable.
Therefore – to survive and succeed - systems need to contain a great variety of ways of addressing the challenges they might encounter.
This is the foundation of diversity
It is also the foundation of the individual
Start with an Open Field
Risk/Reward
Tradeoff
Focus on reward, gets you things of value
(often related to survival)
Focus on risk, keeps you
from being eaten
At center: High chance of harm,
but high chance of reward
At periphery: Low chance of harm
but low chance of reward
In between: Moderate chance of harm,
and moderate chance of reward
Nesters
Explorers
Communicators
An Ordinary Day
Risk/Reward
Tradeoff
Focus on reward, gets you things of value
(often related to survival)
Focus on risk, keeps you
from being eaten
A High Reward Day
Risk/Reward
Tradeoff
Focus on reward, gets you things of value
(often related to survival)
Focus on risk, keeps you
from being eaten
A High Reward Day
Risk/Reward
Tradeoff
Focus on reward, gets you things of value
(often related to survival)
Focus on risk, keeps you
from being eaten
An Ordinary Day
Risk/Reward
Tradeoff
Focus on reward, gets you things of value
(often related to survival)
Focus on risk, keeps you
from being eaten
A High Risk Day
Risk/Reward
Tradeoff
Focus on reward, gets you things of value
(often related to survival)
Focus on risk, keeps you
from being eaten
A High Risk Day
Risk/Reward
Tradeoff
Focus on reward, gets you things of value
(often related to survival)
Focus on risk, keeps you
from being eaten
What’s the point??
A system’s capacity to succeed is based on diversity
Explorers have less fear and more need for reward
Nesters have more fear and are more sensitive to signals of threat. More focused on security of system.
Communicators pick up and transmit signals and assist with reward and security.
Versions of this are found in all human groups (families, organizations, societies)
Human Diversity
Multiple intelligences
Temperament/Personality
Sex
Gender
Race
Culture
Religion
Geography
Class
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The Nature of Success
Class Six
How Systems Use Information
Basic Definitions
Information:
A change in a physical process (e.g. sensation) received by a Knowledge System that the Knowledge System uses to reduce uncertainty about its environment (external and internal).
Examples:
A change in the patterns of photons received by a birds’ retina that indicates the presence of an obstacle (a tree) 25 feet ahead.
A change in water pressure received by the scales of 100 sardines indicating the location and speed of an approaching object (a shark) and causing the 100 sardines to move in a specific pattern.
A change in revenue of a technology company received by 100 investors who believe such change is important enough to withdraw a proportion of their investment in the company, leading to a reduction in stock price of the technology company.
A change in the pattern of photons received by your retina that indicates the presence of a cigar in a wall.
Uncertainty:
The state of a Knowledge System regarding the possibilities contained in its environment. The function (and definition) of information enables a knowledge system to reduce these possibilities.
Entropy:
The number of possible configurations accessible to a physical system. Information is NegEntropy (i.e. it reduces uncertainty).
Basic Definitions
Knowledge System:
A collection of interacting entities (a system) that is configured (structured) in such a way that information can be used to reduce uncertainty about the systems’ environment. The specific configuration, and pattern of interactions, of the system form a working model of the systems’ environment.
Examples:
How the birds’ brain (i.e. knowledge system) uses the change in the patterns of photons (i.e. information) received by a birds’ retina to determine the presence of an obstacle (a tree) 25 feet ahead.
How the school of sardines (i.e. knowledge system) uses a change in water pressure felt by the scales of 100 sardines (i.e. information) to determine the location and speed of an approaching object (a shark).
How a community of investors (i.e. knowledge system) uses a change in investment patterns of 100 investors (i.e. information) to reduce the price of the technology stock.
How a human’s brain (i.e. knowledge system) uses a change in the pattern of photons (i.e. information) received by a human’s retina to determine the presence of a cigar in a wall.
Important: Knowledge Systems can be seen at multiple scales
The bird’s brain vs. the flock of birds
The brain of a sardine vs. the sardine school
The investors brain vs. the community of investors
Your brain vs. the classroom of students
Basic Definitions
Learning:
How a Knowledge System updates the way it is configured – based on new information – to change the way it can reduce uncertainty about its environment. This leads to the system possessing an adjusted working model of its environment.
Examples:
How a birds’ brain produces a greater shift in the direction of the bird when it receives a similar pattern of information, after the bird grazes the tree with its wing.
How a school of sardines produces greater ability to avoid predators when a gene mutation that leads to greater sensitivity to changes in water pressure, spreads through the population.
How a community of investors begin to use information on the investment behavior of more than 100 investors, after losing a lot of money based on their disinvestment in the technology stock.
How your brain now sees a cigar in every wall (presented to it in a lecture by Dr. Saxe).
Important: A change in a working model is not necessarily an improvement in a working model (but over many trials over a long period of time, change usually means improvement).
Basic Definitions
Memory:
How a Knowledge System stores adjustments to its configurations in the form of updated working models of its environment, such that these updates can be used to process new information.
Expertise:
The capacity of a Knowledge System to form, update, store, and access working models of its environment such that these working models can provide the means to effectively use information to reduce uncertainty of the environment.
Success always involves the application of expertise in this way (for any area of success you may care about).
What is Information?
Information reduces uncertainty by reducing the number of possibilities.
Think of the last time you received ‘news’ about anything. The moment just after you received the news, the number of possibilities was far less than just before.
At its foundation: Information is transmitted in bits. Bits are- in essence- answers to yes/no questions.
All information is reducible to answers to yes/no questions. This is how computers work and it is probably how the brain works.
In this way, everything is reducible to games of Twenty Questions.
Think of that game as a process of reducing uncertainty (about anything).
Two related questions when we consider the use of information by any system:
How does the system itself use information?
How does an observer of the system determine how the system is using information?
Risk/Reward
Tradeoff
Focus on reward, gets you things of value
(often related to survival)
Focus on risk, keeps you
from being eaten
When the data does not fit your model
Q1
Q4
Q3
Q2
Memory: Two Forms
Contemporary Memory: Stored and accessible configurations within a Knowledge System that were obtained via learning processes from the direct experience of members of the system
Historic Memory: Stored and accessible configurations within a Knowledge System that were obtained via learning processes that predate the lifespan of current members of the system
Genomic
Cultural
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The Nature of Success
Class Eight
How Systems Change
Core Ideas
Complex Systems change in specific ways
This change is based on risk/reward information received and guided by the systems’ working model of its environment
The process of change in complex systems tend to follow patterns of non-linear dynamics
Changes in such systems - towards both success and failure - follow patterns of non-linear dynamics
Understanding how a system succeeds or fails requires knowledge of these non-linear dynamic patterns
Important to distinguish two types of change:
Changes in system behavior – based on information received – according to the systems working model (i.e. its characteristic behavior)
Changes to the working model itself (i.e. learning)
Linear Dynamics
time
amount
Non-linear Dynamics
time
amount
Phase Transition
Non-linear Dynamics
time
amount
Phase Transition
T 1
T 3
T 2
T 5
T 4
When food is finished
time
amount
Phase
Transition
T6
T8
T7
T5
Systems Oscillate
time
amount
Growth Phase
Transition
Decline Phase
Transition
Feedback for Dynamic Systems
Pattern of Emergent
Behavior
Observed Regularities
Behavior of System Elements
Positive
Feedback
Negative
Feedback
Responding to Ever-Changing
Environment
Growth phase
(amplification/
‘Up’ Regulation)
Decline phase
(dampening/
‘Down’ Regulation)
Decline Dynamics
time
Population
1. Type 2 Mice
enter the
Open field
2. Some Type 1 Mice
Starve, less
reproduction
3. Type 1 Mouse
Pop declines
at critical point
4. Type 1 Mouse
pop at lower,
but stable level
3. Type 1 Mouse
Discover new chirp
4. Type 1 Mouse
pop manages threat
50
The Nature of Success
Class Six
What is an Expert?
A New Basic Definition
Success:
Success is problem-solving and requires the application of appropriate expertise to find and achieve solutions to the given problem.
A Problem: A meaningful challenge to a system from its environment
Problem-solving: The process of reducing the number of possible solutions to the problem to the one(s) that will address the challenge (achieve the solution)
Finding the solution: The Knowledge Systems’ ability to effectively reduce the possibilities (i.e. reduce uncertainty)
Achieving the solution: The Knowledge Systems’ ability to execute interventions to the environment that results in sufficient diminution of the challenge.
Some Problems
The Mice:
How to know the location and valiance of food and predators such that we can maintain the size of our population over time?
You (re a Quiz):
How to know what Saxe is talking about such that his questions make any sense to me and I can put down the correct answer?
The Candy Bar Company:
How to set the right price for our Candy Bar that maximizes our profits?
A Dance Company:
How to launch our next show that maintains our artistic integrity and sells enough tickets so that we can pay our bills?
A Football Team:
How to win todays game, even though our Quarterback is injured and we have not defeated our opponents in the last 2 seasons?
Solving These Problems Require:
A Knowledge System that defines the problem accurately
A Knowledge System that attends to the right information from the environment related to the problem definition
A Knowledge System that understands how to use the right information to reduce possibilities
A Knowledge System equipped to enact interventions that are effective for addressing the problem
A Knowledge System that is able to detect the impact of its interventions and to use this information to update its relevant working model
Was the problem defined accurately?
Was the right information used to reduce possibilities?
Were possibilities reduced sufficient to arrive at the right solution?
Was the intervention executed according to the determined solution?
Is there anything else that was missed?
A Knowledge System that is able to store the updates to its working model for a more effective intervention towards the problem, the next time the problem is encountered.
And that is Expertise
Leave right after class
Don’t stop to talk with friends
Don’t stop to go to the bathroom
Get to class on time, 90%
Working Model: If I start walking right when class ends and I don’t stop to talk with friends on the way, and I don’t go to the bathroom on my way, I will get to my next class on time.
Success Definition: Get to your next class on time, more than 90%
Working Models, Reducing Uncertainty, and Causal Diagrams
Funds for Star
Choice of Star
Interpretation of role
Choice of costume
100K Revenue
Success Definition: Gain $100,000 in revenue for the $100,000 spent
Working Model: We need to spend at least ¾ of the budget on the actress who will star in this show because a strong performance and will lead to good reviews and good ‘word of mouth’ buzz. This, more than anything else, will drive ticket sales: our main source of revenue. Additionally, the actress and
director must make sure that the role is interpreted in a compelling way for our likely audience and –
given the nature of this role – the right costume will be very important.
Working Models, Reducing Uncertainty, and Causal Diagrams
Producer
Business Manager
Casting Director
Director
Costume Designer
Marketing Director
Ushers
Lights
Sound
Star
Cashiers
Pool of Possible Ticket Holders
Other Theaters
Pool of Actors
Pool of Employees
Investors
Theater Company System
The Expert
Accountant
Spouse
Best
Friend
Advisor
Boss
Partner1
Partner4
Partner3
Partner2
The Expert
Present
Future
Past
Building Expertise
Member Training
System Historic
Knowledge
Applying Expertise
Anticipating Expertise
Present
Future
Past
Deliberate Practice
Automatic Practice
Automatic Practice
Deliberate Practice
Deliberate Practice
60
Once the expert working model is set, its automatic. That is why expertise can look (and feel) so easy
Deliberate practice is targeted at new possibilities, where the expert is unfamiliar. This serves to expand the Knowledge Systems capacity to find solutions to a very wide range of problems
Experts challenge their working models, throughout their lives, this is why they become experts
Experts avoid the usual bias to interpret information and prepare for what may come from within their working models
Deliberate Practice
61
The Nature of Success
Class Ten
Where does expertise come from?
Core Ideas
A Knowledge System expresses expertise through the quality of its working models of its environment.
A working model expresses a domain of ‘knowledge’ and the domain of knowledge is useful for a specific purpose: to solve a specific problem
Success is problem-solving and requires the application of appropriate expertise to find and achieve solutions to the given problem.
Where does a Knowledge Systems’ knowledge (working models) come from?
What is knowledge?
Knowledge is a defined process for using information
This defined process specifies a set of rules for how relevant information should be used to solve a specific problem (i.e. knowledge is algorithmic)
Its value to a Knowledge System is based on its capacity to solve specific problems related to challenges to the system from its environment
Knowledge gains in value over time through improvements, based on experience with versions of the problem that needs to be solved
Knowledge improved over generations can be extremely valuable, given the amount of experience that has gone into its refinement.
Knowledge can be biological (genes) or organizational/cultural (memes).
The Test of Time
Most forms of knowledge (biological and organizational/cultural) have been abandoned because the specific knowledge did not impart sufficient value for solving problems. Knowledge that is now ‘here’ has ‘passed’ the test-of-time.
This does not mean that all such forms of knowledge are good and that none should be abandoned. Its simply to say that we need to have a lot of humility in abandoning knowledge transmitted across generations (due to the vastly limited perspective of all individuals).
This is one reason that the art-of-life is subtle, complex, and difficult.
Two common mistakes in understanding the causes of success
The Expert
Accountant
Spouse
Best
Friend
Advisor
Boss
Partner1
Partner4
Partner3
Partner2
Narrow Spatial Frame
Present
Future
Past
Knowledge over past generations
Knowledge over
present lifespan
Narrow Time Frame
Knowledge passed
to future generations
Knowledge: Two Forms
Contemporary Knowledge: Stored and accessible configurations within a Knowledge System that were obtained via learning processes from the direct experience of members of the system
Historic Knowledge: Stored and accessible configurations within a Knowledge System that were obtained via learning processes that predate the lifespan of current members of the system
Genomic
Cultural/Organizational
69
The Nature of Success
Class 11
Changing the game: Innovation
Core Ideas
Given a perpetually changing environmental landscape, the capacity for a biological system or social/organizational system to succeed is based on the system’s capacity to generate and use new knowledge to face challenge.
This is the innovation process. We will call such new knowledge needed by the system to face challenges: ‘ideas’
Ultimately, all ideas have a physical form and this physical form is transmitted as ideas across systems
Ideas that contains survival value and value for a system achieving its purpose is more likely to spread broadly (and rapidly) across the system: and even jump between similar systems.
Some systems are better than others for spreading ideas. This is a question about the system infrastructure for innovation.
What is innovation?
A change to the rules!!!!
Present
Future
Past
Building Expertise
Member Training
System Historic
Knowledge
Applying Expertise
Anticipating Expertise
Why change the rules??
A Systems Perspective on Innovation
What is the idea?
What is the system that will use the idea?
What system challenge does the idea address?
How does idea relate to system survival and/or system purpose?
How much does system survival and/or system purpose depend on the spread of the idea?
How will the system spread the idea?
How equipped is the system to spread the idea?
How dangerous is the idea?