Adapting to the Future:

imminentpoppedIA et Robotique

23 févr. 2014 (il y a 3 années et 1 mois)

105 vue(s)

Adapting to the Future:

Understanding and Guiding Accelerating
Change as a Law Enforcement Leader




POST Command College

March 2010


䙯汳潭Ⱐ䍁



John Smart, President, ASF

Slides:
accelerating.org/slides

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Acceleration Studies Foundation: Who We Are


ASF

(
Accelerating.org
) is a small nonprofit
community of scholars (est. 2003)
exploring

accelerating change in:

1.

Science, Technology, Business, and Society
(STBS), using

2.

Universal, Global, Societal, Organizational, and
Personal (UGSOP) scales of analysis
.

Accelerating Change 2005, Stanford University

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Acceleration Studies Foundation: What We Do



We practice
evolutionary

developmental

(“
evo

devo
”) foresight,
a model of change that proposes the
universe contains both:


1.
Contingent and unpredictable
evolutionary choices
that
we use to create unique,
informationally

valuable, and
creative paths (most of which will fail) and a small set of

2.
Convergent and predictable
developmental constraints
(initial conditions, constancies) which direct certain
aspects of our long
-
range future.



Some
developmental trends
that may be
intrinsic
to
the future of complex systems on Earth include:


Accelerating

intelligence
,
interdependence

and

immunity

in our global
sociotechnological

systems


Increasing technological
autonomy
, and


Increasing
intimacy

of the human
-
machine and physical
-
digital interface.

Acceleration Studies

An Important, Understudied,

Universal, Human Historical, and
Technological Process

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Acceleration Studies:

Something Curious Is Going On

An unexplained physical phenomenon.


(Don’t look for this in your current

physics or information theory texts…)


A ‘Developmental Spiral’

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Are You Accelaware?

Free energy rate density values in

hierarchically emergent

CAS.

Free Energy Rate Density
(
Φ
)


Substrate


(ergs/sec/gm)


Galaxies


0.5

Stars



2

Planets (Early)


75

Ecosystems, Plants

900

(10^2)

Animals (hum. body)

20,000 (
10^4
)

Brains (human)


150,000 (
10^5
)

Culture (human)

500,000 (10^5)

Modern Engines


10^5 to 10^8

Intel 8080 of the 1970's

10^10

Pentium II of the 1990's

10^11


Global AI of the 21st C

10^12+


Cosmic Evolution
, Eric Chaisson, 2001

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The Developmental Spiral


Homo Habilis
Age

2,000,000 yrs ago


Homo Sapiens
Age

100,000 yrs


Tribal/Cro
-
Magnon Age

40,000 yrs


Agricultural Age


7,000 yrs


Empires Age


2,500 yrs


Scientific

Age



380 yrs
(1500
-
1770)


Industrial
Age


180 yrs

(1770
-
1950)


Information
Age


70 yrs

(1950
-
2020)


Symbiotic Age


30 yrs (2020
-
2050)


Autonomy Age


10 yrs (2050
-
2060)


Tech Singularity



≈ 2060


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World Economic
Performance

GDP Per Capita in Western
Europe,

1000


1999 A.D.


The curve is quite smooth
on a macroscopic scale.

And superexponential.


Note the “knee of the curve”
occurs circa 1850, at the
Industrial Revolution.

Contours of the World Economy 1
-
2030 AD
,

Angus Maddison, 2007

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Classic Predictable Accelerations:

Moore’s Law

Moore’s Law derives from two predictions in 1965 and 1975 by Gordon
Moore, co
-
founder of Intel, (and named by Carver Mead) that
computer chips (processors, memory, etc.) double their complexity
every 12
-
24 months at near constant unit cost.

This means that
every 15 years
, on average, a large number of
technological capacities (memory, input, output, processing) grow by
1000X

(Ten doublings: 2,4,8…. 1024).
Emergence!

There are several abstractions of Moore’s Law, due to miniaturization
of transistor
density

in two dimensions, increasing
speed

(signals
have less distance to travel) computational
power

(speed
×

density).


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All Kinds of Exponential ‘Learning Curves’

in Human
-
Technology Systems


Computing (Moore’s law, 1.5
-
2 years)


Digital Storage


Hard and Flash Disks (Kryder’s law, 2 years)


Computer Graphics (polygon prod.) (Smith’s law, 2 years)


Wired Bandwidth (Gilder’s, Nielsen’s law, 2 years)


Wireless Bandwidth Growth (Cooper’s law, 2.5 years)


GPS
-

and Video
-
equipped Cellphone Growth (1.5 years)


Network Address Density (Poor’s law, 2 years)


Flat Panel Display Size (Nishimura’s law, 2 yrs)


Electronic Systems Miniaturization (5.4 years)


Algorithmic Efficiency (Ebrahimi’s law, 5
-
6 years)


Some learning curves are
flat

(battery density) all are
bottlenecks

to breakthroughs (solar PV efficiency, desalination, etc.).

Bruce Henderson, Boston Consulting, 1960’s. The
price/performance ratios of many productive processes get
exponentially cheaper with time and S&T progress:


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Data grows
even faster
than processing power and storage.

All these grow slightly superexponentially, believe it or not.

The Singularity is Near,
Ray Kurzweil, 2005

The Diverse and Exploding Digital Universe, John Gantz, IDC, 2008



Computer power and storage double
every 18
-
24 months.



Created, captured and replicated
data doubles every 14
-
18 months.



By 2011 we’ll be throwing away half
the digital data we generate.



A flood of underused capacity in
processing, even more in data.

Developing the algorithms to use all this power, storage, and data is the challenge.

For now, humans are by far the best algorithms we’ve got.

© 2010 Accelerating.org

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Many Tech Capacity Growth Rates Are
Almost
Independent

of Socioeconomic Cycles

There are many natural cycles:
Plutocracy
-
Democracy, Boom
-
Bust,
Conflict
-
Peace…

But
Ray Kurzweil

first noted that a
generalized, century
-
long Moore’s
Law was unaffected by the U.S. Great
Depression of the 1930’s.

Conclusion:

Human
-
discovered, not
human
-
created complexity is the main
dynamic here. Not many intellectual
or physical resources are required to
keep us on the accelerating
developmental trajectory.


The Age of Spiritual Machines
, 1999

“Acceleration is a rigged game.”

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Foresight

An Emerging Discipline

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UGSOP


Five Useful Scales of Analysis

We can conduct foresight on
five scales of analysis
,
starting “big picture” and moving increasingly “local”:

1.
Universal

systems (science, systems theory, and
spirituality)

2.
Global

systems (technology, environment, and global
problems)

3.
Societal

systems (socio
-
economic, socio
-
political,
and socio
-
cultural)

4.
Organizational

systems (entrepreneurship,
management, cooperation, activism, family)

5.
Personal

systems (aesthetics, self
-
development,
tools, health, wealth, other social impact)

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From UGSOP to STEEPCOP:

Creating a Good Set of Horizon Scanning Categories

It is helpful to consider
eight foresight scanning categories
:

1.
S
cience

issues (general science, general systems theory,
cognition science and systems theory)

2.
T
echnology

issues (computing, engineering, automation,
virtualization, transparency, biotech)

3.
E
nvironment

issues (resources, commodities, energy,
biodiversity, pollution, catastrophes, sustainability)

4.
E
conomics

issues (entrepreneurship, capitalism, globalization,
aid and development)

5.
P
olitical

issues (democracy, sustainability, rights, migration,
governance, law, defense, crime)

6.
Social


C
ultural
issues (education, media, religion,
demographics)

7.
Social


O
rganizational
issues (organizational, social
activism, subcultures)

8.
Social


P
ersonal
issues (personal, relationships, psychology,
family, aesthetics, health)

U

G

S

O

P

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From STEEPCOP to SEISCBEEPCOP:

An
Accelaware

Set of Horizon Scanning Categories

S
cience (Theoretical, Applied, Prof., Sci. Ed, Sci. Policy)

Tech


E
ngineeringtech

(Macro & Nanotech)

Tech


I
nfotech

Tech


S
ociotech

Tech


C
ognotech

Tech


B
iotech

E
nvironment (Sustainability, Resources, Impacts, etc.)

E
conomics (Capitalism, Biz
-
Law, 3BL Accounting, etc.)

P
olitics (Military, Security, Policy, Non
-
Biz Law, etc.)

C
ulture (Traditions, Media, Education, Religion, Art, etc.)

O
rganizational (Entrepreneurship, Mgmt, Org Dev, etc.)

P
ersonal (Relationship, Career, Family, Spirituality, etc.)

All twelve categories are important to foresight and change management. The
first three
,
Science
,
Engineeringtech
, and
Infotech
, seem to be
“universal pulls” toward accelerating complexification.


All the rest

are
enablers, shapers, or blocks

to that acceleration.

Scan with them all

to see the big picture!

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Foresight Development:

Twelve Types of Futures Thinking

Social Types


Preconventional Futurist


Personal Futurist


Imaginative Futurist


Agenda
-
driven Futurist


Consensus
-
driven Futurist


Professional Futurist


Methodological Types


Critical Futurist


Alternative Futurist


Predictive Futurist


Evo
-
devo Futurist


Validating Futurist


Epistemological Futurist

See:
accelerationwatch.com/futuristdef.html

\
Fu"tur*ist
\
, n.


One who looks to and provides analysis of the future.

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3P’s/CMP/Evo Devo Foresight Model:

Three Fundamental Foresight Skills

Foresight skills can be classified with the
3P’s Foresight
model,

depending on if they are about “
Possible
,
Preferable,
and Probable
” Futures. The model comes from
Roy Amara
,
President and CEO (1970
-
1990) of one of the first foresight
think tanks, the
Institute for the Future
, founded in 1968.

An alternative name, based on the primary
mental skills
involved, is the
CMP Foresight Skills model
, as it is about:


1.
C
reating & Imagining
a range of
Possible

futures

2.
M
anaging

& Benefiting
from
Preferable

futures.

3.
P
redicting & Surviving
the most
Probable

futures

It is also an
Evo

Devo

Foresight model
, when we consider the
physical processes
involved (
evolutionary
,
developmental
,
and a
mix

of the two).

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3P’s/CMP/Evo Devo Foresight Model:

Six Skills Foresight Professionals Use On the Job

Possible Futures (
C
reating & Imagining the Future)


Evolutionary Foresight

1.
Scenarios & Horizon Scanning

Alternative Futures, Cultural, Ethnographic, and Religious Foresight (Future Beliefs), Foresight Journalism, Horizon
Scanning, Images and Artifacts of the Future, Scenario Development and
Backcasting
, Science Fiction and
Speculation, Visioning and Creative Thinking, Weak Signals, Wildcards

2.
Innovation & Entrepreneurship

Comparative Analysis, Competitive Intelligence, Competitiveness, Entrepreneurship, Finance and Venture Capital,
Global Sourcing and Markets, Innovation Studies, Intellectual Property
, Leadership, Open
Innovation Networks,
Research and Development Studies

Preferable Futures (
M
anaging & Benefiting in the Future)


Evo

Devo

Fore
sight

3.
Strategy & Analysis

Critical and Evidence
-
Based Foresight, Cross
-
Impact Analysis, Decision Analysis & Support, Emerging Issues &
Technology Analysis, Foresight Frameworks, Operations Research, Real Options Analysis, Robust Strategies,
Scenario Planning and Learning, Strategy Games and Serious Games, Systems Thinking

4.
Policy & Planning

Collaboration and Facilitation Studies, Democracy Studies, Demographics and Sociology, Economics, Ethics of
Emerging Tech, Policy Studies, Political Science,
Roadmapping
, Strategic and Long
-
Range Planning, Urban
Planning, Values Studies

Probable Futures (
P
redicting & Surviving the Future)

-

Developmental Foresight

5.
Forecasting & Long Bets

Acceleration Studies (Learning Curves), Actuarial Science, Complexity, Forecasting, Foresight Metrics & Ratings,
Long Bets (Organizational and National), Long
-
Term Investing, Long
-
Wave Studies, Modeling & Simulation,
Neuroeconomics

and Game Theory, Personal Foresight, Prediction Markets, Predictive Surveys (Delphi),
Predictive Marketing and Consumer Profiling, Trend Extrapolation

6.
Sustainability & Security

Socioeconomic Development Studies, Defense and Intelligence Studies, Environmental Studies, International
Relations, Resilience Studies, Risk Assessment and Management, Peace/Conflict Studies, Socially Responsible
Management, Security and Defense Studies, Sustainability Studies, Triple Bottom Line Accounting,
Wargames


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CMP is an Integral Foresight Skills Framework

I

(
Individual
/Self)

Creativity
-
Driven Futures

It

(
Organizational
/Contractual)

Benefit
-
Driven Futures


Creating, Imagining

Tech, Culture, Art,
Philos



Benefiting, Analysis

Econ
-
Political

We

(
Social
/Kinship)

Values
-
Driven Futures

Its

(
Global
/Species)

Survival
-
Driven Futures


Planning, Policy

Social
-
Political


Predicting, Sustaining


Science, Systems

The CMP foresight skills map well to Wilber’s (1996) four quadrants of life
experience. They are a balanced and comprehensive foresight framework.

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Learn to be an Integral Foresight Professional

Creating & Imagining

"Seeing and making the
future things, images, and
ideals I want"


Benefiting & Analysis

"Objectifying and analyzing
my progress toward a
better future."


Planning & Policy

"Getting consensus and
forming policy and plans
for the future we want.
"

Predicting & Sustaining

"Predicting and sustaining
how the system is moving
toward the future."


Tips for Foresight Practice

Learning how and when to use
each

of these foresight skills will make you a well
-
balanced or 'integral' foresight
professional.
Neglect any of these and you will have an incomplete, underdeveloped foresight model and skillset.

For example, many self
-
proclaimed futurists lack an adequate knowledge of
science and systems
, and may even state
ignorantly that "the future cannot be predicted." But the survival of any living system
depends

on accurate prediction, and
science and history reveal extensive predictability that we discover both quantitatively and intuitively. As forecasting and

actuarial work show, many well
-
established and/or well
-
understood trends and cycles allow insights into complex aspects
of society.

As another example, there are also foresight advocates who love to
create/imagine

and even
plan
, but who never
measure the
benefit (or lack of benefit)

on execution

(or lack thereof)

of their plans, keeping them ungrounded.

Achieving competence in all four skill areas is necessary if one is to be an
‘integral‘ foresight professional
with broad
social and process effectiveness.

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Jim Dator’s Four Futures: Each Have Value

They Also Represent Four Classic Political Dialogs

Dator, Jim. 1979.

Perspectives in Cross
-
Cultural Psychology,
Academic Press.

Key Images/Stories/Policies With Respect to Change


Rig
ht

wing


Continuation

(Economic Issues)


Limits & Discipline


(Social Issues)


Le
ft

wing


Continuation

(Social Issues)


Limits & Discipline

(Economic Issues)


Up

wing


Transformation

(Selective Issues)


Down

wing


Decline & Collapse

(Selective Issues)

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Cognitive Diversity in Small Groups


Diversity and Optimality (1998). Lu Hong, Scott E. Page, Dept. of Econ,
Syracuse U, and Dept. of Econ., U. of Iowa, 27 p.


A general [computational] model of diverse problem solvers of limited
abilities. We use this model to derive two main results: (1) a collection of
diverse, bounded problem solvers can locate optimal solutions to difficult
problems and (2) a collection of problem solvers of diverse abilities tends
to jointly outperform a collection of high ability problem solvers, where a
problem solver's ability equals her expected individual performance.

See also:

Symbiotic Intelligence Project

Norman Johnson, LANL

http://ishi.lanl.gov/


Diversity

is as important as
ability

for:



Poorly defined problems (nonlinear


optimization, prediction, horiz. scanning…)



Innovation



What else?

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Psychological Foresight Tools:

StrengthsFinder (and other Psych Testing Rubrics)







Peter Drucker: Individuals should discover and






focus on building their best
strengths
, much more






than fixing their weaknesses, to make their best






and happiest contribution to the world.


Weaknesses in turn can be best managed by:

1. Being aware of strengths you don’t have

2. Joining strengths
-
complementary teams

3. Allowing others to lead from their different strengths

4. Building situational intelligence (routines, tools, brief courses,



etc.) to keep you from getting tripped up by your weaknesses.


Gallup’s
StrengthsFinder

(and other psych profiling assessments like
MBTI
,
DiSC
, etc.) are
predictive futures tools
.



How validated are they? (Gallup lists 34 strengths, large polling set)



How complete are they (strengths
and

weaknesses, integral)?



When will they be a required part of our educational, hiring (AMA:


only 39% of U.S. companies use psych testing in hiring, mostly still

minor, not yet open source), and assessment processes?



We are still very early in this process. Major opportunity ahead.

© 2010 Accelerating.org

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Prediction/Idea/Decision Markets

and the Wisdom of Crowds


Aggregation of opinions is the new frontier for prediction/ innovation/
decisionmaking. Google realized there was hidden opinion order in an
apparently chaotic net. PageRank captured that order, created much
more relevant search.


Avoids bias. Michael Jensen, HBS, “Forecasting is paying people to lie.”

Sample Internal Markets:

Eli Lilly. Drug efficacy and market size.

Siemens. Software project length.

Google. Over 200 markets (experimental)

Microsoft. Software development.

Hewlett
-
Packard. Sales projections.


Three Requirements:

1.
Cognitive Diversity (“The Difference”)

2.
Independence

3.
Aggregation Tools (still primitive)

Real Money Markets:

Play Money/Reputation Markets:

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Wikipedia breeds Intellipedia and Eventually,
Futurepedia: A Foresight Vision

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What Today Would Have
Surprised


Most Americans Living in 1950?

1.

Electronics Miniaturization, Digitization, and Virtualization


Transistor, IC, laser, fiber optics, cell phones, personal computers, internet, comm.
satellites, transparency technology, computer graphics, virtual worlds. Could we have
imagined the power and pervasiveness of digital life?

2.

Decline of U.S. Mfg.,
Rise and Resiliency of Services and Intangibles Sector


Economic resiliency (no major depression since 1930’s), intangible assets, microcredit.
Could we have imagined the U.S. with less than 15% employment in manufacturing (12%)
and agriculture (1.4%) and still the leading world power?

3.

Egalitarianism, Pluralism, and Globalization (
Network Society
)


Civil rights movement, women’s rights and work parity, contraception, reproductive rights,
sexual revolution, gay rights, youth rights, 100,000 Global NGOs, multiculturalism,
multireligiosity, undocumented immigration, global trade interdependence, EU, NAFTA

4.

Peaceful End of Communism
, Decline of Militarism and Violence


State capitalism (China, Singapore), nuclear disarmament, WMD nonproliferation, loss of
superpower influence, European postimilitarism, decline of wars, genocides, homicide,
crime, rise of asymmetric (non
-
state) conflict

5.

Limits to Growth
, Environmentalism and Health Movements


Global population explosion, MDC population decline, nuclear power limitations, no return
to Moon for almost 50 years (1972
-
2017), ocean overfishing, global CO2 spike, sustainable
business, fundamentalist backlash/Terrorism, smoking decline, health care cost burden

6.

Consequences

of Increased Personal Freedom and Affluence


Obesity/diet industry, drug addiction, prolonged adolescence/youth culture, decline of
marriage, celebrity/entertainment culture, public education standards erosion, ADD/ADHD,
consumer debt

Yet each of these
was

eloquently anticipated

by someone.

Today, we have wisdom
of the crowds/networks/early wikis, collab. intelligence, prediction markets, etc.

[Adapted from Mar 2007 APF Survey by Peter Bishop. Profuturists.com]

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What Would
Not

Have Surprised

1950’s Americans?


Age of Automation


Process automation, industrial robotics, mega
-
scale engineering, and
material abundance (“The American Way”)


Multinational Corporate Economy


More powerful than most governments, able to grow faster, employ
technology more aggressively, periodic economic bubbles (Internet),
fraud (S&L, Enron), DJIA over 12,000, GNP growing 3
-
10% year and
accelerating.


Growth in Size and Plutocracy of Government


Largest employer, special interest lobbies, campaign finance
dysfunction, national security industry, erosion of states rights


Urban Decline and Renewal Cycle


Suburbia, decline of urban core, gangs, gentrification, new urbanism
(Repeat of Manchester in 1800’s).


Is
evolutionary surprise

in the human social space decreasing?

Frank Fukuyama, John Horgan, myself would argue:

In Human Space, Yes.
But Not in Tech Space.

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A Century of Foresight Scholarship,

But Still No General Theory of Foresight

Fundamental Questions Remain:


What is predictable?


What is intrinsically unpredictable?


What long
-
range forces act on complex
systems, besides natural selection?


Does history have directionality?


Recent scientific ideas, such as

evo devo
theory,

provide the beginnings of a
framework for answers to such questions.


Evolution and Development

Two Fundamental Models of Change

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Evolution vs. Development:

Understand it in Life, Understand it in the Universe

Consider two ‘genetically identical’ twins:

Thumbprints, brain wiring,
learned ideas and behaviors,
many local
processes and ‘small things’ are
unpredictably

unique

in each twin.

Yet many processes and ‘large things’ are
predictably

the same
.


The Lesson:

(Predictable and conservative)
development
is always different from
but works with (unpredictable and creative)
evolutionary processes
.

Both are fundamental
to universal complexity.

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Evolutionary Development (Evo Devo):

The ‘Left and Right Hands’ of Universal Change

“Experimentation”

Main Actor:
Seed


(Mostly
Nonadapted
)

Stochastic Search

Strange Attractors

Radiation

Development

‘Right Hand’ of Change

Evolution

‘Left Hand’ of Change

Well
-
Explored Phase Space ‘Optimization’

New Phase Space ‘Opening’


Convergent Unification”

Main Actor:
Environment


(
Global Adaptation)


Environmental Optimization

Standard Attractors

Hierarchy

“Natural
Selection”

Main Actor:
Orga
nism


(Local Adaptation)

Requisite

Variety

Mixed Attractors

Adapt
ation


Evo

Devo

(Inter
section)

For more:
Evodevouniverse.com/wiki/project

Some change is:


Experimentation (
Evo
)


Adapt
ation
/
Selec
tion
(
Evo
Devo
)


Optimizing/Dominating (
Devo
)

Learn to tell the difference.

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The ‘95/5%’ Rule of Thumb:

Evolutionary and Developmental Contributions to Change

A few examples:



Almost all genes in an organism (eg, 97
-
8% of
Dicty

DNA)
change often

to create evolutionary variety vs. a special subset (
2
-
3%)

which form the
developmental toolkit and are
highly conserved
.



Almost all cells compete for their location in the organism. A very few are
fated to a particular location early in development.



Almost all ideas and actions in an organization will not persist. A special
few become stable strategies seen in all orgs of that type.



Almost all technology products and services are
evolutionary
experiments
. A special few are
destined

to become the
next big thing
.



The vast majority (perhaps
95%
) of the events and
computation to create or control a complex system
(organism, organization, technology, species, society)
involve bottom
-
up, local,
evolutionary processes
.



A minor yet critical subset (perhaps
5%
) comes from
top
-
down, hierarchical,
developmental processes
.

5% Devo

95% Evo

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Three functional processes

(telos) can be observed in:


Physical Systems


Chemical Systems


Biological Systems


Societal Systems


Technological Systems


Our Universe as a System

Using the ECD model, we can look at complex adaptive systems as
either
:

1.

Adaptive Systems

(making their evo and devo processes implicit),

2.

Evo Devo Systems

(making their info processing implicit), or

3.

Evo, Compu and Devo Systems

(keeping all three perspectives explicit).

Evo Compu Devo (ECD) Triad: Three Basic Processes

Can Be Seen in All Complex Systems

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Evo Compu Devo (ECD) Triad: Three Common
Quantitative Relationships in Complex Systems

Normal curve

Power law

S curve

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Evo Devo Theory in Politics:

Innovation vs. Sustainability (Both are Fundamental!)

Evo devo theory argues for
process balance
in political
dialogs on
Innovation

and
Sustainability





Developmental sustainability without continuous
change/creativity creates
sterility
, clonality,
overdetermination, and adaptive weakness (Maoism).

Evolutionary creativity (innovation) without sustainability
creates
chaos
, entropy, and volatility that is not naturally
stable/recycling (Unregulated Capitalism).

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Evo Devo Theory in Politics:

Republican vs. Democrat (Both Seem Fundamental)

Evo devo theory suggests that both
Conservative

and
Liberal

platforms bridge the evo devo political center in two
complementary ways. That would make each
integral,
fundamental dialogs (among other integral evo devo
mixes) likely to be long
-
term stable all cultures.





Republicans

are

Devo
/
Maintenance
/Tradition on
Social
-
Political

Issues

Evo
/
Innovation
/Freedom on
Economic

Issues


Democrats

are

Evo
/
Innovation
/Freedom on
Social
-
Political

Issues

Devo
/
Maintenance
/Tradition on
Economic

Issues

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Some Limits and Benefits of Models

Limits:


Biased. “These are the most important factors”.


Oversimplified. There are other important factors.


Abstract. They may include false elements.


Inaccurate. They may not reflect reality.


Benefits:


Consensual. They help us see what the group sees, not just
what we see.


Clarifying. They show categories, forces, interactions we may
have overlooked.


Balancing. They help us pay attention more across the spectrum
of “generally accepted importance.”


Focusing. They help us look better at the things we are seeing
(drill deep in any subject).

STEM Compression:

An Ever
-
Growing Efficiency and Density

of Sci
-
Tech
-
Intelligence Systems

“The Engine of Accelerating Change”

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S
pace,
T
ime,
E
nergy,
M
atter




I
nfo. &
C
omp.

Increasingly Understood




Poorly Known


STEM Efficiency/Compression/Density

is the

ever

decreasing
STEM resources

required

for
any

standard physical process or computation
.

STEM Efficiency is the “engine” of accelerating change.


“STEM Efficiency is Doing More, Better, with Less.”

We Live in a STEM+IC Universe

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A Saturation Lesson:

Biology vs. Technology

How S Curves Get Old

1.
STEM

Resource limits



in a niche



S
patial


T
emporal


E
nergy


M
aterial

2.
Competitive

limits

in a niche



I
ntelligence/
I
nfo
-
Processing


No Known or Historic Limits to Computation Acceleration


1.

Our special universal structure permits each new computational


substrate to

be far more
STEM resource
-
efficient

than the last

2.

The most complex local systems have no intellectual
competition

Result:

No Apparent Limits to the Acceleration of Local Intelligence,
Interdependence, and Immunity in New Substrates Over Time


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STEM Compression Creates a “Paradise of
Resources” for Leading Edge Computation


Our machines are stunningly more STEM efficient
with each new generation.


Our main candidates for future computational
technology (nanomolecular and quantum computing,
reversible logic, etc.) require little or no energy.


We are all moving to increasingly energy efficient,
sustainable, and virtual cities.


Weight of GDP per capita goes down in all developed
Service Economies.


Global energy intensity (energy consumption per
capita) has been flat for almost three decades in the
developed world.

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Seeing STEM Efficiency and Density Increasing
Everywhere in the World


Barter > Coins > Paper Money > Checks > PayPal


Cities (>50% of world population circa 2005)


Working in Offices (or telecommuting with coming
videophone virtual offices)


Wal
-
Marts, Mega
-
Stores, 99 Cent Stores (Retail
Endgame: Wal
-
Mart #1 on Fortune 500 since 2001)


Flat
-
Pack Furniture (Ikea)


Big Box Retail (Home Depot, Staples)


Supply
-
Chain & Market Aggregators (Dell, Amazon,
eBay)


Local Community Third Spaces (Starbucks, Hotels)

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STEM Compression Implication:

Three Hierarchical Systems of Social Change


Technological

(dominant since 1920
-
50)


“It’s all about the
technology
” (what it enables in society, in
itself, how easily it can be developed)


Economic

(dominant 1800
-
1950’s,
secondary

now)


“It’s all about the
money
” (who has it, control they gain with it)


Political/Cultural

(dominant pre
-
1800’s,
tertiary

now)


“It’s all about the
power
” (who has it, control they gain with it)

Developmental Trends:


1. The levels have reorganized, to
“fastest first.”

2. More
pluralism

(a network property) on each level.


Pluralism examples: 50,000 Internat’l NGO’s, rise of
the power of Media, Tort Law, Insurance, lobbies, etc.




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Recognizing the Levers of Nano and Infotech

“The good opinion of mankind, like the lever of
Archimedes, with the given fulcrum [representative
democracy], moves the world.” (Thomas Jefferson, 1814)


The lever of accelerating information and communications
technologies (in outer space) with the fulcrum of physics
(in inner space) increasingly moves the world.

(Carver Mead, Seth Lloyd, George Gilder…)

"Give me a lever, a fulcrum,
and place to stand and I
will move the world."


Archimedes of Syracuse
(287
-
212 BC), quoted by
Pappus of Alexandria,
Synagoge,
c. 340 AD

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Smart’s Laws of Technology

1. Tech learns
ten million times

faster than you do.

(Electronic vs. biological rates of evolutionary development).

2.

Humans are
selective catalysts, not controllers
, of
technological evolutionary development.


(Regulatory choices. Ex: WMD production or transparency,

P2P as a proprietary or open source development)


3. The
first generation of any technology is often
dehumanizing
, the second is indifferent to humanity,
and with luck the third becomes net humanizing.
(Cities, cars, cellphones, computers).



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As There is a Hype Cycle for Almost Any Technology:

Use “Other People’s Innovation” Wherever You Can.

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Cumulative Production/Experience (Not Time)

Capacity/Impact


95% of the time
, you want to be a
second mover
/
“fast follower”.
(
Evo
)


Jump in or buy companies at the trough (Big co. acquisition strategy).


5% of the time
, you want to be a
first mover
/
“pioneer”.
(
Devo
)

Go early correctly and you’ll get lock
-
in (Amazon, eBay, Google, Facebook…)

What immature
tech products or
services do you
want to bet on
next?

As a

fast follower

or a pioneer?

Are you

too early

or already

too late?

The Well
-
Timed Strategy
, Navarro, 2009;
Mastering the Hype Cycle
, Fenn & Raskino, 2008

Limits of Biology

Parts of Us Are Slower and

Harder to Change Than Others

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The Limits of Top
-
Down Control:

Engineering Smartness is Very Hard to Do


“Doogie Howser” Mouse. Extra copies of NMDA receptor 2B

(NR2B) improved long term potentiation (LTP). They had

better memories but were more neurotic (sensitive to pain).


Intelligence breeding in hunting dogs, horses, and other domestics has
had
very

little

effect vs. wildtype animals (“dumb” Pointer vs. Wild Dog).


All

neuropharmacology always has a strong dose response and
receptor downregulation, and it
all

causes long
-
term damage.

Some

of this damage is adaptive (anxiolytics, antidepressants, etc.)

Domestic Pointer

African Wild Dog

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The Limits of Top
-
Down Control:

Growth Genes and Antagonistic Plieotropy

Clip a promotor for a growth hormone gene into …

a frog

and you will get
a bigger frog

a mouse

and you get
a bigger mouse

with
growth
dysregulation
, including
cancer

a pig

and you get the
same
-
sized pig

with
acromegaly

(bone growth problems) and
arthritis
.






More complex organisms have
more evolutionary

but
fewer developmental

differentiation abilities.

A lot more legacy code, a lot less flexibility!

Xenopus laevis

Mus musculus

Sus domesticus

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Limits to Biocomplexity: Declining Marginal

Adaptation from Genetic Differentiation

Only so much complexity can develop “on top” of DNA!

Thesis: The further out one gets from the first living cell, the less
developmental freedom remains (legacy code/path dependency).

Are humans
near the end

of the genetic line? Consider:


We went developmentally “backward” (heterochrony) to emerge


We emerged not due to incremental changes in variety of genes,
but instead due to a rare punctuated change in a tiny number of
brain genes 4
-
6 million years ago (
HAR sequences
) that
improved our
nongenetic

(language) abilities.


Since then, brain
-
expressed genes in humans clearly follow a
terminal differentiation dynamic. As Wang et al. (2006) Bakewell
et al. (2007) and others report,
evolutionary change in human
brain
-
expressed genes has
slowed down

both in absolute terms
and relative to chimps
since our split six million years ago.

Smart, John 2001. Limits to Biology: Performance Limitations on Natural and Engineered Biological Systems.
http://www.accelerationwatch.com/biotech.html
Wang, Hurng
-
Yi et al. 2006. Rate of Evolution in Brain
-
Expressed
Genes in Humans and Other Primates,
PLoS Biology
5(2):e13 Bakewell, Margaret A. et al. 2007. More genes
underwent positive selection in chimp evol. than in human evol.
PNAS
4.17.2007.


Automation and Artificial Intelligence

Technology as a ‘Learning System’

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Understanding Process Automation


Perhaps

80%

of today's First World
paycheck is paid for by
automation
(“tech we tend, not the arms we bend”).


Robert Solow, 1987 Nobel in Economics
(Solow Productivity Paradox,

Theory of Economic Growth)

“7/8 comes from technical progress.”


Human contribution (
20%?
) to a First
World job is Social Value of Employment
+ Creativity + Education


Developing countries are next in line
(sooner or later).



Continual education

and
grants

(“taxing the machines”) are the final job
descriptions for all human beings.


Termite Mound

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Artificial Intelligence: Coming Of Age

• AI is growing, but not yet fastest growing industry



― $1B in ’93 (mostly defense), $12B in 2002


(mostly commercial). AGR of 12%


― U.S., Asia, Europe are equally strong in AI


― Belief nets, neural nets, expert systems growing


faster than decision support, agents, evo AI


― Mostly incremental enhancement of existing apps


(online catalogs, etc.), few new platforms

• Translation, Natural Language Processing, and


Computer telephony (CT) are improving rapidly


(Google, Directory Systems, Booking Systems)


Expect

dedicated DSPs on the desktop

soon.


Coming:

Conversational Interface (CI)


Persuasive Computing, and


Personality Capture/Valuecosm


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Human
-
Competitive Machine Intelligence:

Automated Trading Comes of Age


As of 2005, automated computer trading models
(algorithmic, black box, and program trading) now
execute more than half of all U.S. stock trades.


From 2003 to 2005, Banc of America Securities LLC
let go of half their human traders, while increasing
trading volume 160%.

BusinessWeek, 4.18.2005


All major brokers are spending
millions on this technology.
Minor brokers coming next.


We are now seeing the
beginning of the
AI Age

in the
financial community.

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Robo sapiens

AIST and Kawada’s HRP
-
2


(Can get up when he falls or
when you knock him down)

“Huey and Louey”

Aibo Soccer

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Biologically
-
Inspired Technology and

Evo Devo Computing: The Next Frontier

Today we have
weakly

biologically
-
inspired computing
technologies (neural nets, genetic algorithms,
developmental genetic programming, belief networks,
support vector machines, evolvable hardware, etc.)

When such systems become:


Strongly

biologically
-
inspired


Extensively self
-
improving

(semi
-
autonomous)


Leading strategies

for creating complex systems

Only then may the “technological singularity” be near.


For more,

attend:

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How do you get stability/safety in an evolutionary
system? Select for symbiosis.


Look at how we do it in
domesticated animals (10,000
years, 5,000 breeding cycles).


How many breeds of dogs and
cats can you trust with small
children?


Military will always have the
warbots (narrowly trustable)


Most breeds of robotic systems will
be generally trustable, all will be
trustable for their missions, or we
won’t build them using evolutionary
processes.


Boston Dynamics BigDog

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Kevin Kelly is Accelaware

1995

What

Technology

Wants

2010

Kevin’s Blog. Read it.

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Globalization, Networks, and Immunity

Opportunities and Issues of Accelerating Change

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Our Greatest Strategic Interest:

Managing Globalization


“America has had 200 years to
invent, regenerate, and calibrate
the balance that keeps markets free
without becoming monsters. We
have the tools to make a difference.
We have the responsibility to make
a difference. And we have a huge
interest in making a difference.
Managing globalization is… our
overarching national interest
today

and the political party that
understands that first… will own the
real bridge to the future.”




Thomas Friedman,
The Lexus and
the Olive Tree: Understanding
Globalization
(2000).

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Network Economy 1.0

Remittances

(From Guest Workers in
U.S. and Canada)

Foreign Direct
Investment

(Corporate)

NGO’s

(Nonprofit Contribs)

Government Aid


(IMF, WB, G8, USAID)

Q:

Which is a larger monetary flow in Latin America as of
2003, the bottom
-
up
green

or the top
-
down
purple

column?

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Network Economy 1.0

Remittances

(From Guest Workers in
U.S. and Canada)

Foreign Direct
Investment

(Corporate)

NGO’s

(Nonprofit Contribs)

Government Aid


(IMF, WB, G8, USAID)

Q: Which is a larger monetary flow in Latin America today,

the bottom
-
up
green

or the top
-
down
purple

column?

A: Remittances, since 2003. This may be a permanent
shift. Shows what could happen in Africa, Russia, and
other continually emigrating (“brain drain”) nations.

Future of Philanthropy, GBN, 2005

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U.S. Transcontinental Railroad:

Promontory Point Fervor

The Network of the 1880’s

Built mostly by hard
-
working immigrants

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IT Globalization (2000
-
2020):

Promontory Point Revisited

The more things change,

the more some things

stay the same.


The intercontinental internet will be built
primarily

by hungry young IT developers in India, Asia, third
-
world Europe, Latin America, and other developing
economic zones.



In coming decades, such individuals will outnumber the
First World technical support population between
five
-

and
ten
-
to
-
one
.

Consider what this means for the goals of U.S.
business and education:

Global management,
partnerships, and collaboration.

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Likely Network Society Developments:

Staggered Closing of Global Divides


Digital divide

is already closing fast. 77% of
the world now has access to a telephone*.
Innovation leader: Grameen Telecom


Education divide

may close next (post
-
Conversational Interface, post
-
2020)


Income divide

may close next. Developed
world plutocracy is still increasing, but slower
than before. We’ve been “rationalizing” global
workforce wages since 1990’s*.


Power divide

is likely to close last. Political
change is the slowest of all domains.


*World Bank, 2005

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Our Generation’s Theme


First World Saturating

Emerging Nations Gap
-
Closing

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Gapminder.org: The Global

Income Gap Is Closing


Global marginal income
distribution is normalizing.


Is this a technology trend?


1970: Isolated economies


2000: Connected, flattening

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China Inc: The Next Economic Frontier


Annual
average

GDP growth of 9.5%
(Some urban areas up to 20%!)


Largest global producer of toys,
clothing, consumer electronics.
Moving into cars, computers,
biotech, aerospace, telecom, etc.


1.5 billion hard workers “greatest
natural resource on the planet.”


High savings, factory wages start at
40 cents/hour


45,000 Taiwanese Contract
Factories


20,000 European Contract Factories


15,000 U.S. Contract Factories

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Online Economy: Growing Even Faster than China


From 1996 to 2006, total internet users have gone from 36
million to 1 billion, or from 1% to 16% of the world's
population. We've still got a lot of user growth ahead of us.


From 1996 to 2006, U.S. online retail e
-
commerce
(business to consumer), perhaps the most useful proxy for
the growth of virtual world economies, has grown from 5
million to a projected $95 Billion for 2006, with a current
projected marginal growth rate of 12% per year. GDP per
capita of online worlds like Norrath (Everquest) are 4X
higher than China’s.


In 2004, Internet penetration in China was still less than
6% of the urban population in 2004, yet by that time China
already had the single largest population of online gamers.


Key Point
: Think of the
Metaverse Economy

as the
future
, even more (much more!) than “China as the future.”

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Tomorrow’s Fastspace:

User
-
Modified 3D Persistent Worlds

Global Collaboration and

Coexperience Environments

Streaming audio for main speaker, chat for others

Streaming video coming 2008.





Future Salon in Second Life

Synthetic Worlds
, 2005

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The Metaverse, the Conversational
Interface, and the Valuecosm

Potential Major Next
-
Gen Developments

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Digital Transparency: Gmail, Lifelogs

Next, some of us will store everything we’ve ever
said
. Then
everything we’ve ever
seen
. All this storage, processing, and
bandwidth makes us
networkable

in ways we never dreamed.

Add
NLP
,
collaborative filtering
, and other early
AI

to this, and all this
data

begins turning into
intelligence
.

Gmail (2004) preserves every email we’ve ever typed.
Gmailers are all bloggers who don’t know it.


Nokia’s Lifeblog (2004) (photos,

movie clips, text messages, notes),
SenseCam, What Was I Thinking, and
MyLifeBits (2003) are early examples of
lifelogs, systems for auto
-
recording,
archiving indexing, searching all life
experience.


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From the Metaverse to Metahumanity:

Evolutionary Development of the Web

Web 1.0

Read Mainly

(Graphical UI)




Web 2.0

Read/Write/Play

(Participatory, Social UI)



Web 3.0

Video
(
iTV
,
Geosocial

Web, AR, VW, MW)

Web 4.0

Semantic

(CI, Cyber/
Lobbytwins
,
Valuecosm
)

Web 5.0

Intelligent

(
Planetization
, Global Brain, NUI





‘Tech and Social Singularity’)


We are climbing the hierarchies of the web, via design, use, feedback.

Edge platforms include
search

(Google, Bing, Wolfram Alpha),
telephony

(
iPhone
, Android, Google Voice), static and mobile
social networking

(
Facebook
, Foursquare),
microblogging

(Twitter),
conferencing

and
collaboration environments

(Skype, Wave, WebEx, Wikis),
video

(YouTube,
Boxee
, P2PTV),
games and virtual worlds

(
XBox

Live, Second
Life),
mirror worlds

(Google Earth),
avatars

(
Miis
,
MyCyberTwin
),
lifelogging

(
MyLifeBits
),
augmented reality

(QR codes,
Wikitude
).

Collectively, these are today more a story of
intelligence amplification (IA,

Sociotech
’)

than of
artificial intelligence (AI, ‘
Infotech
’)
.

This is, by far, the largest and most meaningful complexity construction
process society has ever engaged in.


Smart, John et. al. 2007.
Metaverse Roadmap (to 2025)
. Metaverseroadmap.org

Web


Metaverse



Metahumanity

Metaverseroadmap.org

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Wearable Web:

24/7 Augmented Reality, Collective Intelligence

Wearcam.org’s first
-
gen

‘sousveillance’ cams (2001)

‘Bracelet phone’ concept
(Vodafone 2006)

‘Carpal PC’ concept

(Metaverse Roadmap 2007)

Flip Ultra (2007, $130)

Top
-
selling camcorder.

Necklace phone

(Nokia 2004)

iPhone (Apple 2007)

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IA (Intelligence Amplification) and the Conversational
Interface (CI): Circa 2012
-
2019

Date

Avg. Query

Platform


1998


1.3 words

Altavista

2005


2.6 words

Google

2012


5.2 words

GoogleHelp

2019

10.4 words

GoogleBrain

Average spoken

human
-
to
-
human

complex query is

8
-
11 words.

Codebreaking


follows a logistic curve.

Collective NLP

may as well.

Smart, J. 2003.
The Conversational Interface: Our Next Great Leap Forward
.

Halevy et. al. 2009. The Unreasonable Effectiveness of Data,
Intell. Sys.
24(2):8
-
12.

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Siri.com
. Amazing NLP
for phones
today
.

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Why Will We Want to Talk to an Avatar/Agent

Interface (“CyberTwin”) in 2010? In 2020?

Ananova,
2000

“Working with Phil” in Apple’s

Knowledge Navigator Ad, 1987

Nonverbal and verbal language in
parallel is a much more efficient
communication modality.


Birdwhistell says 2/3 (but perhaps
only 1/3) of info in face
-
to
-
face
human conversation is nonverbal.

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Milo (and Milly): The Faces of Xbox Natal.

Conversational Avatars for Kids.



A permanently better new primary way of interacting with our machines.



Start with a game (limited domain) and kids (patience for avatars of
limited intelligence).



Once this conversational interface is server
-
based, it will get
smarter
every month
. Like Google’s does now. Then every week.



A time when serious games can get serious.


Milo and Kate
, Lionhead Studios, Peter Molyneux (Proposed Dec 2010)

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Tablet Form Factor as a Developmental Optimum:

What Uses Do You Predict? Which Will Emerge Next?

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What are the truly inevitable
developmental

uses for a tablet?

#1.
iTV Remote
, #2.
e
-
Reading
, #3
Video Viewing
, #4
Notepad/Clipboard
.


There are about 2.3 billion TVs in the world. 15,000+
streamable

TV channels. Thousands more
sit on the web, waiting for bandwidth. May be hundreds of thousands by 2015.


25% of US TVs sold in Jan 2010 were connected by consumers to the internet (internally or via
a set top box, game console, DVD player), 40% of these were internally
-
enabled.


Tablet TV Remote
: Voice enabled, collaborative filtering of thousands of channels, 2ndary
screen, social viewing (chat,
teamspeak
), P2PTV,
true internet television
.



Lenovo Ideapad U1: Best

multiuse design. June 2010

Will Google

get this done?

A perfect

YouTube front end
.

Apple iPad: No Apple TV.

Too little, too closed.

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Circa 2020: The Symbiotic Age

A Coevolution Between Saturating Humans

and Accelerating Technology.

A time when:




Complex things can “speak our language.”



Our technologies become very responsive to
our needs and desires.



Humans and machines are intimately
connected, and always improving each other.



We will begin to feel “naked” without our
computer “clothes.”

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Symbiont Networks: The Extended Digital Self

A Post 2015 Emergence?

When we have an
early

Web 3.0
,
lifelogs
, and
pervasive
broadband connectivity
, we can expect…


150
(Dunbar number)

of our kids most
cognitively diverse

(Page
2008) friends permissioned into their lifestreams, 24/7.


A
reputation and reciprocity collaboration system
that keeps
everyone contributing to the symbiont (no free riders).


Powerful new group learning and expert performance, with
symbionts seriously outperforming unconnected individuals
.
Always having 150 “lifelines” who know you, in any situation.


New cultural protocols, symbionts must be temporarily turned off
for job interviews, tests, private moments, etc.).


Serious behavioral modification (juveniles, criminals, mentally ill)
and performance enhancement era begins.


Fantastic new subcultural diversity (geek symbionts, futurist
symbionts, Quaker symbionts, Shoppers United symbionts, etc.)


Page, Scott. 2008.
The Difference: How the Power of Diversity Creates Better Groups, Firms,
Schools and Societies
, Princeton U. Press.

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Circa 2030: The Valuecosm

A More Pluralistic and Positive
-
Sum Future


Microcosm (Gilder), 1960’s


Telecosm (Gilder), 1990’s


Datacosm (Sterling), 2010’s


Valuecosm

(Smart),
2030’s


-

Recording & Publishing Cybertwin Prefs


-

Avatars that Act and Transact Better for Us


-

Mapping Positive
-
Sum Social Interactions


-

Much Early Abuse (Marketing, Fraud, Advise)


-

Next Level of Digital Democracy (Holding

Powerful Plutocratic Actors Accountable)


-

Today’s Leading Edge: Social Network Media

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Conversational interfaces lead to personality models.

In the long run, we become seamless with our machines.

No other credible long
-
term futures have been proposed.









“Technology is becoming organic. Nature is becoming
technologic.” (
Brian Arthur
, SFI)

Personality Capture: A Long
-
Term
Development of Intelligence Amplification


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Your Cybertwin


Your Digital Self:

Helping You Now, Helping Others Later

Greg Panos and his Digital Mom

PersonaFoundation.org

“I would never upload my consciousness

into a machine.”

“I enjoy leaving behind stories about my life for
my children.”


Prediction:




When your mother dies in 2040,

your digital mom will be “50% her.”



When your best friend dies in 2060,

your digital best friend will be “80% him.”

Successive approximation, seamless integration,
subtle transition… of you.

When you can shift your own conscious
perspective between your electronic and
biological components, the encapsulation and
transcendence of the biological should feel like
only growth, not death.

We wouldn’t have it any other way.


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The Digital Self:

Social, Economic, and Political Implications

Some Challenges
-

particularly early:


Data Security and Privacy


Predictive Marketing and Profiling


Debt Slavery and Overconsumption


New Forms of Crime and Fraud


Polarizing and Isolating Eco Chambers (collapse of community)


Parenting (How early can kids have CT’s?)


New Addictions and Dependencies (CT ‘relationships’?)


Some Opportunities
-

particularly later:


Indiv. Intell./Performance Enhancement (Complete your sentences?)


Group Intelligence/Perform. Enhancement (Symbiont networks)


Subculture Diversity and Victimless Variety


Global Communication & Collaboration (no language barrier)


Digital and Educational Divides (greatly reduced)


Indiv./Group/Culture Rights Representation (‘lobby twins’)


Transparency and Accountablity of Corps, Institutions, Govts.




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The Digital Self:

Biggest Single Catalyst We’ll See in Our Lifetimes

What Do You Want to Improve?


IT/Infrastructure Mgmt


Identity Management


Social Networks


Video Management


Marketing


Education


Knowledge Management


Performance Management


Talent Management


Innovation


Social Responsibility


Environmental Sustainability


Organizational Development


Collective Foresight

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Valuecosm Future:

Law Enforcement Implications?











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Growth Curves and Accelerating Change

Generic System Behaviors

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The S Curve
(Phases BG
-
MS)

Example: Logistic Population Growth

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World Population, 10,000 BC to 2000 AD:

Birth and Growth

Positive
feedback loop:

Agriculture,
Colonial Expansion,
Economics,

Scientific Method,
Industrialization,
Politics,

Education,
Healthcare,
Information
Technologies, etc.

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Global Population Saturation

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The B Curve
(Phases BGM
-
SDR)

Example: Environmental Impact of Individuals

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The J Curve


First
-
Order Components

are
Growth
-
Limited Hierarchical
Substrates (S and B Curves)


Second
-
Order

Hyperbolic Growth

Emergence Singularities

and a Limit Singularity


Examples:



Sagan’s Cosmic Calendar



Chaisson’s FERD (Complexity)



Global Economic Performance



Sci & Tech Performance Metrics



Cultural Adoption of Innovation

Accelerating Socio
-
Technological Evolution: From Ephemeralization and Stigmergy to the Global Brain
, Francis Heylighen, 2007.


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Four Alternative Growth Scenarios:

Jim Dator’s “Four Futures”

First cited in:
Perspectives in Cross
-
Cultural Psychology,
Jim Dator,

Academic Press, 1979


The Key Images/Stories/Components of Emergent Change

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Eldredge and Gould


(Biological Species)






Pareto’s Law (“The 80/20 Rule”)


(income distribution


瑥捨湯汯杹Ⱐ散e測⁰潬楴楣猩i


創汥l潦o周畭T:

㈰2
偵P捴畡瑩潮o⡅癯(潲o䑥癯v





㠰8
䕱E楬楢物畭u⡅癯爠䑥癯v


Suggested Reading:

For the
20%:

Clay Christiansen,
The Innovator's Dilemma

For the
80%:

Jason Jennings,
Less is More

Punctuated Equilibrium in Biology,

Economics, Politics, Technology…

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Lesson: Maintaining Equilibrium is

Our 80% Adaptive Strategy

While we try unpredictable evolutionary strategies to
improve our
intelligence, interdependence, and
resiliency,
these won’t always work. What is certain is
that successful solutions always increase
STEM
efficiency
,
they


do more, better, with less.”
Strategies
to capitalize on this:




Teach efficiency as a civic and business skill.



Look globally to find resource
-
efficient solutions.



Practice competitive intelligence for STEM
-
efficiency.



Build a national culture that rewards refinements.



Examples: Brazil's Urban Bus System. Open Source
Software. Last year’s mature technologies. Recycling.

30 million old cell phones in U.S. homes and businesses.


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Be an Innovator 20% of the Time…

Compstat, Broken Windows, Transparency Tech,
Performance Accountability, Community Policing...

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© 2007 Accelerating.org

Or Be an Efficiency Maven 80% of the Time…

(Quality Control, Standards, Knowledge Mgmt, etc.)

(Walter) Shewhart Cycle

(Bell Labs)

PDCA Improvement Cycle

Plan:

Design/revise business process for best ROI

Do:

Implement plan with measurement tools

Check:

Analyze results, report to decisionmakers

Act:

Decide on changes to improve process

W. Edwards Deming