Engineering as Argumentation and Vice Versa

David E. Goldberg ThreeJoy Associates & the University of Illinois Champaign, Illinois 61821 USA deg@threejoy.com

A Di!erent Path to Philosophy

•  Resigned my tenure 31 December 2010 as engineering professor.

•  Known as engineer & computer scientist for work in genetic algorithms.

•  Road to early retirement goes through philosophy and transformation of engineering education –  Was interested in history & economics in

mid-80s and 90s. –  Did Teaching Company courses as runner

in the mid-90s. –  Saw John Searle give talk in 1996. –  Some of my GA work took philosophical

turn. –  Returned to philosophical coursework

and reading in 2005-2006. •  Key fork in the road:The Blogpost.

24 May 06, www.entrepreneurialengineer.blogspot.com: Philosophy of Engineering Not a Contradiction in Terms

“I've been on a philosophy reading/learning jag for a number of months, and one of the questions I've had is why isn't there a well defined literature on the philosophy of engineering. Science has a longstanding literature on the philosophy of science. Other fields of practice, for example law and medicine seem more philosophically inclined. Engineering (and business for that matter) seem less inclined toward philosophical reflection and speculation.

On the one hand, this dearth of philosophizing can be

attributed to the practical nature of the engineering enterprise. Engineers are busy doing, and reflection on that activity detracts from getting the job done, but this argument does not answer why engineering scholars in the academy and elsewhere don't spend more time reflecting on the place of engineering in the world, the ontology and epistomology of engineering artifacts and knowledge, engineering method, ethics, and other philosophical topics.”

After The Blogpost

•  Nosed around and found NAE committee.

•  MIT meeting in 2006. •  Decision to have Workshop on

Philosophy & Engineering at Delft in 2007.

•  Ibo & Dave as Co-Chairs. •  3 meetings: 2007, 2008 & 2010. •  Let inside UIUC to Engineering &

Technology Studies at Illinois, Workshops on the Engineer of the Future, iFoundry, Olin-Illinois Partnership, early retirement & ThreeJoy Associates.

•  2 parts of talk: connect then combat.

Motivation for 1/2 This Talk

•  Presented paper at fPET-2010.

•  Developed economy of models argument as part of Design of Innovation.

•  Found Toulmin’s model useful as theoretical way to connect formal and informal engineering modeling.

•  Started teaching this in senior design and it proved helpful.

Roadmap

•  What Engineers Know & How They Know It. •  Engineering modeling lesson from a life in genetic

algorithms. •  A demarcation problem. •  An economy of models & a modeling spectrum. •  Lessons from senior design & the missing basics. •  Qualitative modeling as missing skill. •  Toulmin as a way to articulate & unify engineering

modeling. •  Tales from the trenches: Toulmin & tortillas. •  Argumentation as engineering: Homo habilis & Gary Klein.

Engineering vs. Scientific Knowledge •  Vincenti distinguishes engineering

knowledge from science with examples from aeronautical engineering history.

•  Suggests engineering is not merely applied science.

•  Two Vincenti cases: – Control volume models. –  Flush riveting.

•  Quantitative & qualitative models that are di!erent because of their usage.

•  Can we go beyond distinctive historical exemplars?

A Life in Genetic Algorithms

•  Met John Holland in 1980 upon return to Michigan for PhD.

•  Did dissertation applying GAs to gas pipeline optimization and rule learning.

•  Needed better understanding to improve GAs.

•  Received criticism for my “engineering style” of modeling.

•  Models not “proper” or “rigorous” but they were helping me design faster, more e!ective GAs.

•  Could I make rigorous defense of my method?

Science-Engineering Demarcation Problem

•  Engineers & scientists think in terms of models. •  Scientist is in business of model making. •  Engineer is in business of artifact making. Model making

& usage is instrumental to that aim. •  In era of technoscience, models themselves not

necessarily distinct. •  Make distinction in use. •  Engineers explicitly, necessarily & systematically use &

develop range of models with di!erent precision-accuracy and costs: an economy of models.

•  This economy of models fairly reliable demarcation of engineering modeling practice from science.

An Economy of Modeling

ε, Error

C, Cost of Modeling

Engineer/Inventor

Scientist/Mathematician

Modeling Costs and Benefits

•  Engineer is economic modeler when marginal costs do not exceed marginal benefits of modeing: ΔC ≤ ΔB.

•  Benefit to what: To designed artifact. •  3 points:

–  Calculation usually not explicit. –  But modeling economy taught in pedagogy: e.g. Statics

before Dynamics. –  Uneconomic model use common engineering manager’s

complaint: Modeling for modeling’s sake. •  Scientist studies at error frontier: New model pushes out error

frontier. •  Engineers often work at cost or benefit frontier (better C for

given error or better error for given C): e.g. FEM vs. analytical elasticity solutions.

Spectrum of Models

Qual-Quant Divide

Approach of Design of Innovation

•  First part of DoI methodological. •  Applied modeling methodology to

selectorecombinative GA design problem.

•  Constructed little models, quantitative models of di!erent facets, integrating them to design and tune GAs that scaled to large hard problems.

•  Quantitative analysis was prime concern.

•  Concern for modeling left (qualitative models) came with engineering education reform e!orts.

Qualita've   Quan'ta've  

People  

Things  

Sociotechnical Modeling Styles

Hard  Ignored  

So,   Dismissed  

Lessons from Senior Design

•  Coached 20 years of senior design. •  Students

–  expect clean problems with well-defined data & –  are Pavlovian dogs when it comes to Newton’s laws or

Maxwell’s equations. •  Real-world problems & data

–  are ill-defined; –  come in form of narrative; –  vary in feasibility & quality

•  Students have trouble making sense of problem & data. •  Misled by their classroom experience of clean problems, with

easy, single solution, and spend first half of course unlearning. •  What don’t they know how to do?

Missing Basics of Engineering

•  Question: Socrates 101. •  Label: Aristotle 101. •  Model conceptually: Hume 101 &

Aristotle 102. •  Decompose: Descartes 101. •  Experiment/Measure: Bacon-Locke

101. •  Visualize/draw: da Vinci-Monge 101. •  Communicate: Newman 101

©  David  E.  Goldberg  2010  16  

Socrates (470-399 BC)

How It Works: Key to Engineering

•  A key qualitative model in engineering is representation of causal chain of the way things work (or not): –  As narrative. –  Or diagram. –  Or working prototype.

•  “This led to this led to this.” •  Critical model, but students

think “if no equation, no model.”

•  Field example.

The Tortilla Problem

•  Interesting example in tortilla factory.

•  Company was using too much dusting flour relative to historical recollection.

•  Flour cost was rising. •  Wanted students to study

process and reduce dusting flour usage.

©  David  E.  Goldberg  2009  

Burnt-Flour-as-Mold Problem

•  Students heard story. •  Too much flour gets in air

flour burns falls on tortilla customer mistakes for mold complaint.

•  Causal chain a model. •  Students don’t recognize as

model. •  How can we help them?

19  

Help from Argumentation Theory

•  1958 book by philosopher Stephen Toulmin formed basis of argumentation theory.

•  How do people really make arguments?

•  How do people give reasons for what they think or do?

•  Form of reasoning ties together formal and informal engineering reasoning.

Formal Reasoning: Logic

•  Modus ponens (modus ponendo ponens: mode that a"rms by a"rming): –  if p then q –  p is true –  therefore q is true

•  Method of mathematical logic & formal reasoning.

•  Note: Once premises and rules in place, formal logic derives conclusions mechanistically. Aristotle (384-322 BCE)

Toulmin: Elements of a Human Argument

•  Like modus ponens: –  Claim. A single statement advanced for the

adherence of others. –  Grounds. A statement about persons, conditions,

events, or things that says support is available to provide a reason for a claim.

–  Warrant. A general statement that justifies using the grounds as a basis for the claim

–  Backing. Any support (specific instance, statistics, testimony, values, or credibility) that provides more specific data for the grounds or warrant.

–  Qualifier. A statement that indicates the force of the argument (words such as certainly, possibly, probably, usually, or somewhat).

•  Warrants can be generalizations, cause, sign, analogy, authority.

•  Backing can be anecdote, stats, testimony, credibility, and values.

Rieke, R. D & Sillars, M. O. (1997). Argumentation and critical decision making. New York: Longman.

€

G → C↑

B↑

W↑

Q↑

B

Back to the Tortillas: Burnt Flour Model

Grounds. Dusting flour is spread onto the moving dough on a continuous tortilla line.

Warrant. Excess flour becomes airborne & burn in the oven, deposits (authority).

Claim. Burnt black flour deposits is mistaken for mold, resulting in quality complaints

Qualifier. Sometimes

Backing. Client story & increased flour results in increased spot problem.

Tradeo!: Improve Backing or Solve Problem

•  In resource limited environment, often face decision: – Should you improve warrant

and backing? – Or should you work on solving the problem?

•  Can be di"cult choice. •  Key query: If assume correctness of warrant/

backing & wrong, will you fail to solve problem? •  Tortilla problem: Students took explanation as true

because it didn’t a!ect investigation (reducing dusting flour usage reduces this side e!ect).

iLaunch  

iCheckpoint  iExpo  

iCommunity  

ENG100++  Missing  Basics  

ENG100++  2  Hands-­‐on  Projects  

Illinois  Engineering  Freshman  Experience  

(iEFX)  

©  2011  David  E.  Goldberg  

www.missingbasics.org

Motivation for Other 1/2 of Talk

•  Sometimes hard to listen to what other tribes say about your tribe.

•  Engineers speak about engineering in triumphant way.

•  Philosophers speak about engineers in ways that contain.

•  Turnabout as fair play, but with serious point about historical perspective.

Example: Defining Engineers Institutionally

•  M. Davis, Thinking Like an Engineer, Oxford, 1999.

•  Uses institutional definition of engineer.

•  Close reading definitions are shifty.

•  Depends upon (a) advanced knowledge, (b) professional standing & (c) contrast to other occupations/professionals.

•  He insists upon use of term “protoengineer” for those who come before “engineers” in Davis’s sense.

•  What if I did immediate turnabout is fair play?

Michael Davis (b. 1943)

Davis’s Method of Defining

•  3 elements: – Rejects going back to origins of technology: “We will

understand the professions better if we start their history with the rise of modern markets…” (Davis, 1999, p.9).

– Compares and contrasts di!erent occupations/professions to elicit significant features: architect v. engineer, scientist v. engineer, lawyer v. engineer.

– Does not study precursors (“protoengineers”) in depth: e.g., Refusal to consider Vitruvius’s engineering work as engineering, for example.

•  How does this work for philosophy/philosophers?

Davis’s Method Applied to Philosophy

•  3 elements: –  Division of labor: Must reject study of

philosophy/philosophers until there is clear academic division of labor: Birth of the modern university (University of Bologna, 1088).

–  Compare & contrast: Philosophy was a catchall phrase. Probably need to wait for division of labor in 18-19th century.

–  Ignore precursors: Cannot study guild-like apprenticeships conferred by Plato in the Academy or Aristotle in Lyceum.

•  Conclusion: Socrates, Plato & Aristotle were not philosophers.

•  Must call them protophilosophers. Sorcrates (469 BC – 399 BC)

Early Protophilosopher

Vice Versa: Argumentation as Engineering

•  Outline of argument: 1.  Argument is an externalization of human thought

processes believed to be correct. 2.  Artifacts are first fully expressive externalization of

human thought processes. 3.  Research on naturalistic decision making suggest that

mental simulation processes similar to those of argumentation.

4.  Therefore, first tech artifacts may be thought of as first expressive evidence of argument-like processes in human ancestors.

5.  OK to think oral or written arguments as o!spring of first engineering e!orts.

•  Go back 2.5mya.

Tech Histories Don’t Go Back Far Enough

•  Let’s start 2.5mya. •  Homo habilis: First tool

maker, 4’-3” tall, 88 pounds, bipedal hominid.

•  Lived on open savanna (Lake Turkana)

•  Social. •  Made and used stone flakes. •  Did not speak (de Boer,

2005). de  Boer,  B.  (2005)  The  EvoluUon  of  Speech,  in:  Brown,  K  (Ed.)  Encyclopedia  of  Language  and  LinguisUcs  2nd  ediUon,  Elsevier.  

Oldowan Tools

•  First discovered by Louis Leakey.

•  Used 2.5mya to 0.5 mya. •  Know they were used by

scavengers. •  Scrape carcass clean of

meat following kill by another animal.

•  First known fully expressive externalization of human thought.

Homo Ergaster

•  Better tools around 1.6-1.7 mya.

•  Hand axes and cleaving tools with sharp edges.

•  Butchering of large animals.

•  Tamed fire. •  Still not talking.

Naturalistic Decision Making

•  Gary Klein has studied how those under pressure make decisions.

•  Naturalistic decision making. •  Rational decision making used

infrequently & not under pressure.

•  Cannot know Homo habilis mind. •  Assumption: Homo habilis mind

was likely similar to our minds under pressure.

The Role of Mental Simulation

•  Klein identifies di!erent modes, recognition primed decision & constructive decision, for example.

•  Mental simulation is key to all. •  Many decisions made with single

simulation that shows adequacy. •  Satisficing: First adequate

solution chosen. •  Imagined artifact simulated step

by step. •  Key point: No need for language

here. Mental pictures all that is required.

Object Then Made & Used

•  Steps: –  Artifact imagined in context of

use. –  Simulated step by step. –  Device created. –  Used for simulated purpose.

•  Step by step imaging of adequacy a causal chain played out in mind.

•  Thus, creation of first tech artifacts are first, external fully expressive evidence of human step-by-step mental simulation.

•  argument-like reasoning. •  Thus argumentation may be viewed

as o!spring of engineering.

Speech Invented Later

•  Once speech & language around, mental simulations can be augmented with language.

•  Use longstanding processes with speech. •  Chaining together speech in this way ultimately

leads to the notion of an argument. •  Precursor in mentally simulating and then creating

external physical artifacts key step on road to argumentation.

•  Argumentation as refinement of engineering of artifacts: Argumentation may be viewed as a form of engineering applied to linguistic constructs.

Bottom Line

Engineering as Argumentation •  Engineers are broad-spectrum

modelers. •  Qual is part of the canon. •  Toulmin’s model provides

unifying framework for math, science, & qualitative modeling.

•  Introduction to students helpful in aligning behavior with needs of practice.

•  Makes “soft skills” part of engineering not something apart.

Argumentation as Engineering •  Notion of argument as

external representation of mental reasoning traces back to engineered artifacts.

•  Tech as first shared representation of output of mental simulation.

•  Packaging of mental constructs.

•  Sometimes forget ancient prehistory of engineered artifacts.

For More Information

•  ThreeJoy Associates, Inc: www.threejoy.com

•  Illinois Foundry for Innovation in Engineering Education (iFoundry): www.ifoundry.illinois.edu

•  Philosophical writings on PhilSci archive: http://philsci-archive.pitt.edu/perl/search (author search for Goldberg).

•  www.philengtech.org •  This and related powerpoints:

www.slideshare.net/deg511