[email protected] – (314) 232-5042 On Chasing the Ether of Intelligent Systems Dr. James Guffey 25 Oct 2006 INCOSE Meeting – St. Louis MSG06-081332-001.ppt.

[email protected] – (314) 232-5042

On Chasing the Ether of Intelligent Systems

Dr. James Guffey

25 Oct 2006INCOSE Meeting – St. Louis

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Name: Dr. James A. GuffeySenior Principal EngineerKey Technical Field: Technology Integration; Autonomous TechnologiesPhone: (314) 232-5042E-mail: [email protected]

Dr. Guffey has been at Boeing/McDonnell Douglas for 2 dozen and 3 years and has been heavily involved in the definition, implementation and management of a large number of avionics research and development programs for the Army, Air Force, Navy and DARPA, covering a wide variety of technology areas. In the technology area of Autonomy and Intelligent Decision Aiding, Dr .Guffey initiated the first in-house investigations into the use and applicability of Artificial Intelligence Technology at then MCAIR in 1984 and lead the proposal team that won the DARPA Pilot’s Associate Program in the mid 80’s. He was the Technical/Deputy Program Manager of the PA program, which built an AI-based system to assist a fighter pilot in performing future advanced combat missions. The software architecture for PA was the basis for the Rotor Craft Pilot’s Associate system, which in turn was the genus of the Unmanned Combat Air Vehicle and some elements of the Future Combat System program for unmanned vehicles. He was a member of the Integration team for the Unmanned Systems organization when it was formed in 2001 and responsible for the development of a definition of potential future markets that could capitalize on advanced automation and autonomous applications for platforms and systems. In 2004 Jim acted as the Boeing management/technical liaison to the Carnegie Mellon University (CMU) RedTeam for the DARPA Grand Challenge autonomous vehicle race in the deserts of California and Nevada. Part of that role was to be the broker to reach back into Boeing for technical help requested by the onsite Boeing employees at CMU to make the vehicles successful.

Copyright © 2005 Boeing. All rights reserved.

Recent Introductions by a Colleague: “Jim’s Been at This for Decades!”Recent Introductions by a Colleague: “Jim’s Been at This for Decades!”

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I’ve Been at This a Long Time

AutonomyAutonomy

IntelligenceIntelligence

Common SenseCommon Sense

EtherEther


And……, I Guess It’s True!

Circa 1985

Artificial

IntelligenceAbsolutelyInsane

Acute

Indigestion

Abandoned Ideas

Advanced

Insanity

Action Item

Awe

Inspiring

AsinineIdeas

Almost

Incredible

Animal

Instincts


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A Few Definitions


• The Ability to Comprehend; to Understand and Profit From Experience• The Capacity to Acquire/Apply Knowledge, Especially Toward a Purposeful Goal • The Faculty of Thought and Reason • An Intelligent, Incorporeal Being, Especially an Angel

Intelligence:

• Showing Mental Alertness and Calculation and Resourcefulness • Of, Relating to, or Being a Highly Automated Device, Especially One That Imitates

Human Intelligence; Does the Right Thing in a Wide Variety of Complicated Circumstances

Smart:

• Not Controlled By Others or By Outside Forces; Independent• Independent in Mind or Judgment; Self-Directed

Autonomous:

• Without Volition or Conscious Control; Self-Regulating (i.e. Washing Machine) • Automatic, as Opposed to Human, Operation or Control of a Process, Equipment

or a System; or the Techniques and Equipment Used to Achieve This

Automation:


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Definition of Ether

Ether: “An All-Pervading, Infinitely Elastic,Massless Medium Formerly Postulatedas the Medium of Propagation ofElectromagnetic Waves;But Subsequently Foundto Be Nonexistent.”



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The Dawn of Artificial Intelligence


• Alan Turing’s Test; 1950– What He Claimed Was That With Intelligence, Imitation Is

as Good as the Real Thing

• The Quest for “Artificial Intelligence” Started in ~ 1955

• Alan Turing’s Test; 1950– What He Claimed Was That With Intelligence, Imitation Is

as Good as the Real Thing

• The Quest for “Artificial Intelligence” Started in ~ 1955

I propose to consider the question, "Can Machines Think?" - Alan Mathison Turing (1950)

I propose to consider the question, "Can Machines Think?" - Alan Mathison Turing (1950)


Johnny FiveJohnny Five

SonnySonny

Hard Artificial Intelligence-The Holy Grail


HAL 9000HAL 9000

Robby the RobotRobby the Robot

Knight Rider(Kitt)

Knight Rider(Kitt)

R2D2R2D2

Iron GiantIron Giant

The TerminatorThe Terminator

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The and of the Journey

• AI Expectations– Maybe Time for Another Up Swing?


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Ups Downs

• Over AmbitiousExpectations →

• Disillusion →

Icarus:The First AI Guy

• AI Winters in 70’s and 90’s


What We All Strive to Create

Johnny Five From Short CircuitJohnny Five From Short Circuit

Cold Reality

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It Doesn’t Help That the Definition Keeps Changing

At Every Step of the Way, on the Quest for Hard AI Systems, Whatever We Make Work, We Immediately Declare That It Is

Not Intelligent

Increasing Capabilities

NoIntelligent ??

System A

System D

System C

System B

NoIntelligent ??

NoIntelligent ??

NoIntelligent ??

Why? Because Once We See What We Did to Make It Work We Realize That It Is Only Doing What We Told It to Do!

Why? Because Once We See What We Did to Make It Work We Realize That It Is Only Doing What We Told It to Do!

The Creator Knows It Isn’t Smart, Even If the Audience Thinks It Is!

(So maybe We Should Get Rid of the Creators After They Create?)


Why Do Today’s SystemsLook “Smarter”?


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It’s All About Contingencies!It’s All About Contingencies!

+

•Brute Force Approach With Elegance– Storage + Throughput

• These Allow Much More Complicated Algorithms to BeImploded, But the Systems Aren’t Any Smarter inHuman Perspective Than Before

– We Ultimately Are Able toSignificantly Expand the Numberand Levels of Contingencies ThatWe Can Ask a System to Address

• (e.g. Deep Blue Chess Champion

60,000,000,000 moves in 180 seconds)


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INCOSE Mandatory Equation

E = mc2

Ether = man chasing conundrums*

*Conundrum: A paradoxical, insoluble, or difficult problem; a dilemma.



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A Working Definitionof an Intelligent System


Three Easy Steps

2. Locate a Time Machine

1. Take Any “Smart” System of Today

3. Go Back inTime and Askthe Locals ifThey Think It Is Intelligent?

If They Say Yes; It’s Because It Appears to Them to Be So Far Aheadof What They Could Do With the Systems of Their Day That it Must Be

“Intelligent”

If They Say Yes; It’s Because It Appears to Them to Be So Far Aheadof What They Could Do With the Systems of Their Day That it Must Be

“Intelligent”

-barian


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Who Needs Intelligence Anyway ?

It’s All About Capabilities,

Stupid!

It’s All About Capabilities,

Stupid!


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Be Careful of What You Ask For !

If We Make a System that Thinks Like a Human and is Truly Artificially Intelligent…….


….Then, Like Humans, it Could Also be Artificially Stupid ** !

Do We Really Want Them to Be Just Like Us ?Do We Really Want Them to Be Just Like Us ?

SonnySonny

HAL 9000HAL 9000

Whoops…, Sorry , Dave !

** Compliments to Jeff Erickson


I don’t need no stinking jack !

Why useCleats whenI’ve got this

cool bucket ?

Hmmmm Aluminum,

Electricity, andBare Feet.

Just Add Water !

Who says Ican’t reach

this lightbulb?

And the guy wondered Why he got Fired??And the guy wondered Why he got Fired??

If one lift won’t make it,

Just use two !

If one lift won’t make it,

Just use two !

Well, Gee it’s only a small chlorine gas leakWell, Gee it’s only a small chlorine gas leak

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It’s Not Like We Always Make Good Decisions!


Well, Gee it’s only a small chlorine gas leak


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Focused on the Wrong Thing

• Debates About Intelligence Are Interesting But TheyDon’t Get You Much

• We in an Engineering Company Look at It Fromthe Practical Perspective

• See If We Can Make Some Money Out of It Along the Way!

• We Still Have to Stay in Business While We Are Figuring It Out


I Think.I Think I am.

Therefore, I Am.I Think?

Moody Blues


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What Our Customers Really Want is…

• The Endstate Capability to Handle More and More Complicated, Dynamic Situations for Their Product or Service That Provide a Safe and Acceptable, Real Time Solution With Minimal Human Involvement

• Whether You Call It Smart, Robust, Multiple Layers of Contingency Management or Whatever Doesn’t Matter

– Increasing Capability with Increasing Autonomy Is What Most Customers Ultimately Want

DANTE IIDANTE II

Personal SatelliteAssistant

Personal SatelliteAssistant


The Line Between Automation,Autonomy, Smartness, and

Intelligence Doesn’t Really Matter!

The Line Between Automation,Autonomy, Smartness, and

Intelligence Doesn’t Really Matter!


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Autonomous Control Level (ACL) Chart


EXAMPLE OF INCREASING CAPABILITIES

RemotelyPiloted Vehicles

Group Accomplishment

of Strategic goal with No

Supervisory Assistance

Observe Orient Decide Act

10

9

8

7

6

5

4

3

2

1

0


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Autonomy AllocationProblem Decomposition


1. Complexity Defines the Total Problem Solving Requirements (TPSR)M

issi

on

Co

mp

lexi

ty (

Y)

Environment Complexity (X)

Examples: Program (X,Y)U2 (10, 10) (GTAS)

100

100

B2 (20, 20)F22 (50, 50)UUV (10,10)UCAR (70, 70)Orbital Express (40, 40)

PTS (10, 80)etc,..

The Combination of Mission and Environment Complexities

Determine the Magnitude of the “Total Problem Solving Requirements”

Problem Solving RequirementsProblem Solving Requirements


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Autonomy AllocationProblem Decomposition


2. Who Does What,…When?

Total Problem Solving Requirement

100

100

Platform/System

Network

Hu

man

Level of Autonomy to Platform or System Is BothDriven and Constrained by Customer Requirements…and Bounded by Technology

100

• Mission and environment

complexities determine the total problem

solving requirements

The Smaller the Arrow the Higher the Chance

of Automating the Solution and Increasing

the Autonomy of the Platform/System

eg. The Mars Rover BoysSpirit and Opportunity are

highly Autonomous


• But Who Cares??

We Can Still Make Them SMARTER !

So, Can We Ever Create aHard Artificially Intelligent System?


If It Looks Like a Duck and Walks Like a ….

Vaucanson’s Duck

It’s Still a Terrific Idea to Keep Striving for Real (?) Artificial

Intelligence

It’s Still a Terrific Idea to Keep Striving for Real (?) Artificial

Intelligence

• Answer:

Alas,……No

Make the World aLittle Better Along the Way!!

Make the World aLittle Better Along the Way!!

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My Niece, Lauren Says“I Love INCOSE This Much !!!”



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“THE COMPUTER IS CLAIMING ITS INTELLIGENCEIS REAL, AND OURS IS ARTIFICIAL”

I Think.I Think I am.

Therefore, I Am.I Think?

Moody Blues

[email protected] – (314) 232-5042 On Chasing the Ether of Intelligent Systems Dr. James Guffey 25 Oct 2006 INCOSE Meeting – St. Louis MSG06-081332-001.ppt.

Documents

definitions copyright

s slide

human intelligence

onsite boeing employees

angel intelligence

holy grail copyright

definition of ether

future combat system