Diversity 2007 Challenges in the Health Care System 1. How to evolve an overly-constrained, mature, complex, interdependent system? 2. Institutional change

Diversity 2007

Challenges in the Health Care System

1. How to evolve an overly-constrained, mature, complex, interdependent system?

2. Institutional change is too slow– Host-pathogen systems are dynamic– Major changes in who is providing health care

– More women, alternative medicine, “Physician's will be put out of business by

nurse practitioners”

– The patient’s genomic “pre-existing condition” problem

3. Data-poor ⇒ data-rich ⇒ data-overload – c.f. “Blink” by M. McDowell

– Increasingly broad patient cultural-ethnic background

– Who is the most genetically diverse ethnic group?

“Normal” Technology Development Phases

How to organize a movement, that changes/coordinates 100s of organizations and impacts 700,000 physicians? How do you then build processes that support new “utility”? How do new structures then become “transparent” and the building blocks of new options and structures?

Extreme stages can prevent development

X XCollective reinforcement of hype can lead to a

interruption of the developmental cycle

Norman L JohnsonReferentia Systems Inc

[email protected] http://CollectiveScience.com

Jen Watkins Los Alamos National Lab

[email protected] http://public.lanl.gov/jhw

Diversity: A Weapon of Mass Construction

Diversity 2007

Mauboussin: Deep Blue, Wisdom of the Crowds & Demise of Experts

1. Utility of experts is being eroded2. What system benefits from expert performance

– Computers: rule-based or probabilistic, limited options (low heterogeneity / complexity, but lots of data)

– Experts: rule-based, many options (moderate complexity and data)

– Collective intelligence: probabilistic, many options (high complexity, lots of data)

3. Conditions for Collective Intelligence– Diversity, an aggregation mechanism, incentives

4. Examples of Collective intelligence – Discovery: Needle in the haystack

– State prediction: Jelly beans in jar

– Future prediction: Academy Awards

Diversity 2007

Mauboussin: What system benefits from expert performance

Source: Michael J. Mauboussin,”Are You an Expert?” Mauboussin on Strategy, October 28, 2005.

Domain

description:

Rule-based,

limited options

Rule-based,

many options

Probabilistic,

limited options

Probabilistic,

many options

Expert

performance:

Worse than

computers

Better than

computers

Equal or worse

than computers

Collectives

outperform

experts

Expert

agreement:

High

(70-90%)

Moderate

(50-60%)

Moderate-Low

(30-40%)

Low

(<20%)

Examples:

Credit scoring

Simple medical

diagnosis

Chess

Go

College

admissions

Poker

Stock investing

Econ. forecast

Diversity 2007

Mauboussin: Questions asked

1. What about a “crowd of experts”?

2. What about incentives on web-based systems?

3. How do you use Diversity in investment?

4. What about behavior influencing individuals or crowds?

Diversity 2007

Test Question on the most important topic of our times

How did we get here?1. Evolution2. Intelligent design3. Creationism

“Of all the hazy and confounding areas in social psychology, leadership

theory undoubtedly contends for nomination. And, ironically, probably more has been written and less is known about leadership than about

any other topic in the behavioral sciences” - Bennis 1959

“Of all the hazy and confounding areas in social psychology, leadership

theory undoubtedly contends for nomination. And, ironically, probably more has been written and less is known about leadership than about

any other topic in the behavioral sciences” - Bennis 1959

How to make sense of it all?

Consider Leadership

How to make sense of it all?

Consider Leadership

Leadership 2007

Theories of LeadershipTheories of LeadershipPower-based: leaders sustained by powerPower-based: leaders sustained by power

Innate traits theories Innate traits theories - Leaders are born not made- Leaders are born not made Trait theory (Stogdill 1974)Trait theory (Stogdill 1974) Great Man theory (Carlyle 1843)Great Man theory (Carlyle 1843)

Structure-based: leaders fill structural rolesStructure-based: leaders fill structural rolesRole theoryRole theory

Social theory and structure (Merton 1957)Social theory and structure (Merton 1957) Supervisory behavior (Pfeffer & Salancik, 1975)Supervisory behavior (Pfeffer & Salancik, 1975) (Adair 1965)(Adair 1965)

Performance-based - leaders as performersPerformance-based - leaders as performersEx: Situational theory Ex: Situational theory (Tennenbaum 1958, Maier 1963, Yuki 1989)(Tennenbaum 1958, Maier 1963, Yuki 1989)

Required leader style is situation dependent Required leader style is situation dependent Ex: Contingency theoryEx: Contingency theory (Fiedler 1954) - (Fiedler 1954) - Context basedContext based

Leader’s effectiveness is based on ‘situational contingency’Leader’s effectiveness is based on ‘situational contingency’Performance-based - Collective/plurality/shared-based: leaders as enablersPerformance-based - Collective/plurality/shared-based: leaders as enablers

Ex: Shared, relational, collective, situational theoriesEx: Shared, relational, collective, situational theoriesEx: Distributed leadershipEx: Distributed leadership (Gronn 2002) - (Gronn 2002) - Plurality basedPlurality based

Leadership happens everyday in formal and informal interactions and is spread Leadership happens everyday in formal and informal interactions and is spread over leaders, followers, and contextover leaders, followers, and context

Ex: Adaptive leadershipEx: Adaptive leadership (Linsky 2002) - (Linsky 2002) - CAS-basedCAS-based ““Leadership is an interactive event in which knowledge, action preferences, and Leadership is an interactive event in which knowledge, action preferences, and

behaviors change, thereby provoking the organization to become more behaviors change, thereby provoking the organization to become more adaptable.” adaptable.”

Performance-based Leadership + EmergencePerformance-based Leadership + Emergence

Leadership 2007

Landscape Model for LeadershipLandscape Model for Leadership

Where Leadership ArisesWhere Leadership Arises

Some Some IndividualsIndividuals

Most of the Most of the CollectiveCollective

Emergent: Emergent: Unpredictable, Unpredictable, opportunistic, opportunistic, from interactionsfrom interactions

Structurally Structurally determined: determined: predictablepredictable

Classic Leaders Classic Leaders - from power or - from power or traits (structure)traits (structure)

How How Leadership Leadership arisesarises

Previous presentation useful to understand the literature, but less helpful to develop new approaches and resources for leadership.

Leadership 2007


Examples

Where arises?Where arises?

How arises?How arises?Some Some

IndividualsIndividualsMost of the Most of the CollectiveCollective

EmergentEmergent

Structurally Structurally determineddetermined

Classic Leadership Classic Leadership theories for theories for individualsindividuals

Aggregation methods Aggregation methods from collective input - from collective input -

democracies, democracies, markets, etc. => markets, etc. => “lower” collective “lower” collective

intelligenceintelligence

Leadership 2007


Distribution?Distribution?

Emergence?Emergence? Some IndividualsSome Individuals Most of the CollectiveMost of the Collective

HighHighLeadership emerges Leadership emerges without precedence - without precedence -

opportunistic opportunistic

None None Classic LeadershipClassic Leadership ““Lower” collective Lower” collective intelligenceintelligence

Secondary considerationsEmbodied and disembodied emergent solutions (upper row)

The emergent solutions can either be embodied in individuals or

captured in the interactions between the individuals (disembodied).

Maturation: creating structure by “capturing” the emergent property• Emergent leadership can go “classic” with rules and regulations • Ex: early development of eBay: eBay structure followed emergent

social processes

Leadership 2007



Emergence?Emergence? Involves some Involves some IndividualsIndividuals

Involves all of Involves all of CollectiveCollective

HighHigh

Leadership Leadership emerges without emerges without

precedence precedence ??

NoneNone Classic LeadershipClassic Leadership ““Lower” collective Lower” collective intelligenceintelligence

Leadership 2007

Examples within Leadership LandscapeExamples within Leadership Landscape

Localized Emergent: Leadership outside of structure as in a hero

or savior

Distributed Emergent: Emergent functions in

societies as in the fall of the Berlin wall, future symbiotic

intelligent systems, …

Localized Deterministic: Classical top-down

leaders supported by structure

Distributed Deterministic: Democracies,

commodity/currency exchanges, prediction markets, recommender

systems, …

LocalizedLocalized DistributedDistributed

Degree of DistributionDegree of Distribution Where performance is locatedWhere performance is located

Degree of Degree of Emergence: Emergence:

How performance How performance arisesarises

DeterministicDeterministic

UnpredictableUnpredictable

Diversity 2007

Expert Performance in Finance

Why can’t financial experts outperform consistently the S&P 500

“collective” (including good + bad performers)?

• Professional money managers fail to beat the S&P 500 at an average rate of 70% per year.

• 90% trail the S&P over a 10-year period.

• Only a few beat every year for 10 years – Soros, Miller, ….

“These are the people who have more knowledge and more training than the vast majority of investors. And yet, neither the superior knowledge nor the superior experience helps them in the long run.”

Bill Mann, TMFOtter

Diversity 2007


Where Experts Have Value

Simple Complex

Domain

Va

lue

Michael Mauboussin - Legg Mason Capital Management

Why can’t financial experts outperform consistently the

S&P 500 “collective” (including good + bad

performers)?

Experts

V

alu

e

?

Collectives

The ant colony (and individuals) finds the shortest path

Nest

Food

Nest

FoodDoes a “classic leader” find

the path?

How is this possible?

Ants Solving “HARD” problems

Start

EndIn “Learning” the maze, individuals create a diversity of experience.

A Model for Collectives Solving Hard Problems

How can groups > solve hard problems,> without coordination,> without cooperation, > without selection?

The Maze has many solutions > non-optimal and optimal.

Individuals > Solve a maze> Independently> Same capability

When individuals solve the maze again, they eliminate “extra” loops

But because a global perspective is missing, they cannot shorten their path. This is where diversity helps.

Averaged Performance

.

Individuals in Collective Decision

Nor

mal

ized

num

ber

of s

teps

0 5 10 15 20

0.9

1.0

1.1

1.2

1.3

0.8

Average Individual

Using novice information, with two different collections

Usingestablishedinformation

Shortest path

How collectives find the Shortest path

Paths of three ants Collective path

Unlike in natural selection, no one individual is the

fittest!

Noise and RobustnessNoise: Replace “valid” information with “false” information

• Individuals are very sensitive to noise

10 steps become 21 steps

Lack of experience

An “expert” individual A collective

• Collectives are insensitive

10 steps become 9 steps

Contingency from diversity

Diversity 2007

Conclusions on Emergent Problem Solving

Collectives reliably solve a problem “perfectly” that experts cannot reliably solve

The emergent solution is not initially embodied in any individual (no one ant finds the shortest path).

Diverse collectives not only perform better, but they are also more robust to misinformation.

The accuracy of emergent solution correlates with diversityDiversity is defined as uniqueness of information/skills contributedDiversity of performance is also requiredCompetition, optimization or stress all reduce diversity, performance and/or

robustness.

Collective “solves” a problem that individuals are unaware of => emergent problem definition and solution

Performance from synergistic diversity has a sweet spotCollective performance is bounded by individual performance and complexity

of the problem.

Diversity 2007


Simple Complex

Domain

Va

lue

of E

xper

ts

Va

lue

of

Co

llec

tiv

es

!

Leadership 2007



Emergence?Emergence? Involves some Involves some IndividualsIndividuals

Involves all of Involves all of CollectiveCollective

HighHigh

Localized leadership Localized leadership emerges without emerges without precedence or precedence or

structure structure

Emergent collective Emergent collective “Leadership” from “Leadership” from

synergistic diversitysynergistic diversity

NoneNone Classic LeadershipClassic Leadership ““Lower” collective Lower” collective intelligenceintelligence

Leadership 2007

Leadership Landscape ConsiderationsLeadership Landscape ConsiderationsDistribution

Emergence Involves some Individuals Involves all of Collective

HighLeadership emerges without

precedence or structure

Emergent collective “Leadership” from

synergistic diversity

None Classic Leadership“Lower” collective

intelligence

Secondary considerationsEmbodied and disembodied emergent solutions (upper row)Maturation: creating structure by “capturing” the emergent propertyProblem solving capability and robustness increases as you move up & right

• Higher diversity (and complexity) is required from lower left to upper rightThe efficiency-quality tradeoff problem - particularly for fast change

• Lower left can be the most efficient (less communication and coordination required) and has a speed advantage in dealing with fast change

• But Upper right has the best and most robust solutions Mixed “classic” leadership models are becoming essential

• “Localized” Leader as facilitator to develop emergent collective intelligence

Leadership 2007

Revisit Traits of Good LeadershipRevisit Traits of Good Leadership

Good Leadership traitsGood Leadership traitsPerformance: Performance: Accurately and reliably solves problems Accurately and reliably solves problems => Collectives => Collectives

outperform leadersoutperform leadersApproach: Approach: Able to communicate and persuade others without resort to Able to communicate and persuade others without resort to

negative or coercive tacticsnegative or coercive tacticsResources:Resources: Able to understand a wide range of areas Able to understand a wide range of areas => Collectives have => Collectives have

greater resourcesgreater resourcesIntegrity: Integrity: Owning up to mistakes, rather than putting energy into covering up Owning up to mistakes, rather than putting energy into covering up

=> Collectives are more robust=> Collectives are more robustPersonality:Personality: Calm, confident and predictable, particularly when under stress Calm, confident and predictable, particularly when under stress

=> ? Collectives have detrimental herd (heard) effects=> ? Collectives have detrimental herd (heard) effects

Do some of these also apply to Distributed Leadership?Do some of these also apply to Distributed Leadership?

Diversity 2007

Themes for Complex Adaptive Systems

Processes in “one” system– Role of diversity– Optimizing performance or robustness– Multi-level viewpoint: system(internal, external)– Interplay of structure (rules) and options– Situated intelligence

Co-Development of multiple systems How systems develop? Dynamics and effects of change Strategies for responding to change

Leadership 2007

ConclusionsConclusions Challenges: Challenges:

Creating hype, utility and transparency – while in a quickly changing Creating hype, utility and transparency – while in a quickly changing systemsystem

Consider a Leadership landscape that covers all resourcesConsider a Leadership landscape that covers all resources From power-based, structure-based resources to performance-based, From power-based, structure-based resources to performance-based,

distributed and emergent theoriesdistributed and emergent theories New leadership resources reflect greater needs by societyNew leadership resources reflect greater needs by society

Match “Leadership” resources to systems characteristicsMatch “Leadership” resources to systems characteristics Data-poor systems of high complexity require expertsData-poor systems of high complexity require experts Data-rich systems of low complexity require computer resourcesData-rich systems of low complexity require computer resources Data-rich systems of high complexity require human-computer Data-rich systems of high complexity require human-computer

solutionssolutions

Complex systems require diversity for performance and Complex systems require diversity for performance and robustnessrobustness

Diversity 2007

Test again

How did we get here?1. Evolution2. Intelligent design3. Creationism

Rat Studies of Maximum Carrying Capacity

Social order system can carry 8 times the optimal capacity.

NIMH psychologist John B. Calhoun, 1971

Control - no imposed social structureCooperative social structure

Both systems loaded to 2 1/2 times the optimal capacity.

Diversity 2003 Los Alamos

References

Johnson, N. L. (1998). "Collective Problem Solving: Functionality Beyond the Individual." from http://collectivescience.com/Documents1.html

Johnson, N. L. (2002). "The Development of Collective Structure and Its Response to Environmental Change." S.E.E.D. Journal 2(3).

Lichtenstein, Uhl-Bien, Marion, Seers, Orton and Schreiber. “Complexity Leadership Theory: An interactive perspective on leading in complex adaptive systems” Emergence: Complexity and Organization Volume 8, Number 4, 2006. <Entire issue is of interest>

Sawyer, R.K. (2006). Social Emergence: Society as Complex Systems.

Symbiotic Intelligence Project http://www.collectivescience.org/symintel.html

Watkins, J.H. (2007). “Prediction Markets as an Aggregation Mechanism of Collective Intelligence.” from http://public.lanl.gov/jhw.

Watkins and Rodriguez (2007). “A Survey of Web-based Collective Decision Making Systems” from http://public.lanl.gov/jhw.


Norman L. [email protected]

Jennifer H. [email protected]


The Problem with Collective EffectsThe Problem with Collective Effects

Ants foraging for food chose one path out of two equidistant paths. Ants foraging for food chose one path out of two equidistant paths.

(Deneubourg et al. 1990)

Cooperation leads to exclusive behavior in stable environments

Non-linear or Chaotic behavior: Positive reinforcements can amplify random weak signals >> global chaos.

Nest

Food

Leadership 2007

Definitions of LeadershipDefinitions of Leadership

Good Leadership traits:Good Leadership traits:Performance: Performance: Accurately and reliably solves Accurately and reliably solves

problems. problems. Approach: Approach: Able to communicate and persuade Able to communicate and persuade

others without resort to negative or coercive tactics.others without resort to negative or coercive tactics.Resources:Resources: Able to understand a wide range of Able to understand a wide range of

areas, rather than having a narrow (and narrow-areas, rather than having a narrow (and narrow-minded) area of expertise.minded) area of expertise.

Integrity: Integrity: Owning up to mistakes, rather than putting Owning up to mistakes, rather than putting energy into covering up.energy into covering up.

Personality:Personality: Calm, confident and predictable, Calm, confident and predictable, particularly when under stress.particularly when under stress.

Leadership 2007

Definitions of LeadershipDefinitions of Leadership

““Leadership is like the abominable snowman whoLeadership is like the abominable snowman whosese footprints are everywhere but who is nowhere to be footprints are everywhere but who is nowhere to be seen. “seen. “

““Leadership is like pornography (or complexity), you Leadership is like pornography (or complexity), you know it when you see it, but you canknow it when you see it, but you can’’tt define it.” define it.”

Diversity 2007

How to Predict and Manage Change

Broadest understanding– Governing processes– Specific system (inference, network, etc.)– Environment and context– Dynamics: Specific triggers, non-linearities, etc.

Methods - Resources– Theories & Models

Dynamical systems vs. Complex systems– Simulations, experiments, …– Data sources (poor or rich or overwhelmed)?– Science: Integration of theory, data & simulations– Predictive methods: risk assessment, uncertainty

management

Leadership 2007

Self-Organizing Adaptive SystemsSelf-Organizing Adaptive Systems

“Solutions” arise from the dynamics from a diversity of potential solutions. Decentralized, robust, adaptable, fault-tolerant, scalable, ...

Fundamental conceptsChaotic behavior or non-linear response Performance AND robustnessEmergent properties

Interaction Emergent propertiesAgent

rules

Environment (culture, economy, demography, technology, nature)

Network View of System of systems

Dynamics on the network performance - stability - resilience - transients

• Change of states• Creation/destruction of structure & options• Dynamics under stable conditions• Dynamics in response to change

Personal•Motivation•Sensory•…

Groups•Media•Organization•…


Regulations•Feds•Agencies•…



Social-organizational -information network

• Diversity • Connections• Strengths• Asymmetry• Change

Individual types •Peers•Bosses•Clients, …

Individual•Sensory•Memory•Motivation • …