Your SlideShare is downloading. ×
0
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
The Perils & Pleasures of Interdisciplinarity
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Text the download link to your phone
Standard text messaging rates apply

The Perils & Pleasures of Interdisciplinarity

2,350

Published on

David E. Goldberg reflects on living an interdisciplinary life at a talk given at a Workshop on the Challenges in Top-Down, Bottom-Up and Computational Approaches in Synthetic Biology

David E. Goldberg reflects on living an interdisciplinary life at a talk given at a Workshop on the Challenges in Top-Down, Bottom-Up and Computational Approaches in Synthetic Biology

Published in: Education, Technology
0 Comments
2 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total Views
2,350
On Slideshare
0
From Embeds
0
Number of Embeds
32
Actions
Shares
0
Downloads
26
Comments
0
Likes
2
Embeds 0
No embeds

Report content
Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
No notes for slide
  • Honor
  • Photo from “wanted” poster in 1986. Of course this meeting changed my life profoundly and I’m so blessed that it did.
  • When I first showed this to John his reaction was characteristic. Concerned that I not limit models in this way.
  • Tie together three things. Story telling, moving from qual to quant, many types of models, and uses models from different fields. May need hybrids of qual-quant models for given problem.
  • Transcript

    • 1. The Perils and Pleasures of Interdisciplinarity:Practical & Philosophical Reflections on an Interdisciplinary Life
      David E. Goldberg
      Illinois Genetic Algorithms Laboratory & iFoundry
      University of Illinois at Urbana-Champaign
      Urbana, IL 61801 USA
      Email: deg@illinois.edu; Web: http://www.ifoundry.illinois.edu
      1
      © David E. Goldberg 2010
    • 2. Reflections on an Interdisciplinary Life
      30th year in GAs; 27th year since dissertation. 22th year since GASOML.
      Have been blessed to be part of growth of an interdisciplinary field.
      Could easily have been otherwise.
      Almost every central turning point was unlikely event.
      Want to reflect on those times personally, practically & philosophically.
      Not a moral exemplar. Just interesting stories.
      2
      © David E. Goldberg 2010
    • 3. Roadmap
      • What’s a nice civil engineer doing in a place like this?
      • 4. A cocktail party in Canterbury.
      • 5. One September in Ann Arbor.
      • 6. A professor named Holland.
      • 7. The education of a genetic algorithmist.
      • 8. My philosophical turn & starting a company.
      • 9. Reflections on existentialism, paradigms, and the education of engineering and computer scientists in an interdisciplinary age.
      • 10. Finding a life’s impedance match.
      3
      © David E. Goldberg 2010
    • 11. Once Upon a Time…
      Once upon a time…
      There was a civil engineer
      working for Stoner Associates
      doing hydraulics software for pipelines.
      Was starting to do real-time control &
      wondered how human operators
      controlled gas pipelines
      like you or I drive a car.
      Went to British Hydromechanics Research Association to represent company.
      4
      © David E. Goldberg 2010
    • 12. A Cocktail Party in Canterbury
      At the opening reception.
      My advisor walks in…
      Like the parting of the Red Sea.
      Another prof asks WHEN will I return for PhD.
      Not “cost effective.”
      A phone call & a big night.
      E. Benjamin Wylie (b. 1928)
      5
      © David E. Goldberg 2010
    • 13. One Fine September Day in A2
      First day of classes and was signed up for standard AI course.
      Expert systems were the rage, Prolog was hip, LISP was cool.
      Class was cancelled with little sign on the door.
      Hopes and dreams down the drain.
      Searched and searched for a replacement.
      Found CCS 524, Intro to Adaptive Systems, taught byJohn Holland.
      6
      © David E. Goldberg 2010
    • 14. A Professor Named Holland
      Youngish looking prof:
      Talking about biology & genetics.
      Samuel’s checker player.
      Schemas and building blocks.
      Classifier systems.
      What’s nice civil engineer doing in class like this?
      When was Prof Holland going to get to real AI I could use for pipelines?
      Or maybe this was the real AI.
      7
      © David E. Goldberg 2010
    • 15. Education of a Genetic Algorithmist
      1984 took position in Engineering Mechanics at Alabama, Tuscaloosa.
      Education began then, but there was a lot I needed to learn:
      Focus on 4 core lessons:
      Learning to ask
      Learning to label
      Learning to decompose
      Learning to model
      8
      © David E. Goldberg 2010
    • 16. Lesson 1: Learning to Ask
      • In 1984 had many questions about how GAs work, when they fail?
      • 17. Wasn’t experienced in asking good framing questions.
      • 18. Key problem: Using GAs to solve engineering problems, but GAs weren’t engineered well.
      • 19. Philosophical terms: Socrates 101.
      © David E. Goldberg 2010
      9
      Socrates (470-399 BCE)
    • 20. What’s a Good Question?
      Socrates asked variety of questions.
      What is truth? What is courage?
      More often the critic. Rarely gave answers.
      In creative enterprises, many good questions are framing questions:
      Get at heart of the issue.
      Help define the problem or elicit definition.
      Sometimes cause problem to be represented in novel way or from unusual or creative perspective.
      Fundamental importance of dialectic. Creative process of asking and answering questions.
      GA example from 1985: Alleles, Loci & Traveling Salesman Problem. How is inversion for orderings, similar to and different from mutation & crossover for alleles?
      10
      © David E. Goldberg 2010
    • 21. Lesson 2: Learning to Label
      • In the early days, language was nonexistent or unsettled.
      • 22. Challenge of being category creator vs. category enhancer.
      • 23. Tabula rasa or a green field.
      • 24. Some borrowed from biology, “fitness,” “linkage” & “landscape.”
      • 25. Others invented: “deception,” “niching,” “abeyance,”
      • 26. Philosophical terms: Aristotle 101.
      • 27. Underappreciated as means to understanding and solving problems.
      • 28. GA example: Use of term “linkage learning” leads to practical schemes such as mGA, fmGA, LLGAs, and adaptive EDAs.
      © David E. Goldberg 2010
      11
      Aristotle (384-322 BCE)
    • 29. Terms Really Do Matter
      Terms gather thoughts under consistent rubrics.
      Can be part of larger taxonomy.
      Defines attention areas.
      Can have influence on how others think.
      Catchy or sticky terms propagate virally.
      12
      © David E. Goldberg 2010
    • 30. Lesson 3: Learning to Decompose
      • Wasn’t experienced at decomposing big problem into little problems.
      • 31. Looked for magic bullets in equations of motion or transform methods.
      • 32. 1990 talk by Gary Bradshaw on the Wright Brothers and their explicit decomposition of powered flight.
      • 33. Philosophical terms: Descartes 101?
      © David E. Goldberg 2010
      13
      René Descartes (1596-1650)
    • 34. Design Decomposition for GA Design
      ICGA 1991: Shared “theory” tutorial with GunarLiepins.
      Need design theory that works:
      Understand building blocks (BBs), notions or subideas.
      Ensure BB supply.
      Ensure BB growth.
      Control BB speed.
      Ensure good BB decisions.
      Ensure good BB mixing (exchange).
      Know BB challengers.
      Read about it in DoI.
      14
      © David E. Goldberg 2010
    • 35. Lesson 4: Learning to Model
      • Knew quite a bit about modeling mathematically.
      • 36. Engineers as Pavlovian dogs when it comes to equations.
      • 37. Didn’t know how to model conceptually:
      • 38. Causal chain.
      • 39. Categorize according to list of types or kinds.
      • 40. Need to understand problem qualitatively in words and diagrams prior to quantitative modeling undertaken.
      • 41. Philosophical terms: Hume 101 or Aristotle 102.
      © David E. Goldberg 2010
      15
      David Hume (1711-1776)
    • 42. A Model of Models
      Engineer/Inventor
      Error, ε
      Scientist/Mathematician
      Cost of Modeling, C
      16
      © David E. Goldberg 2010
    • 43. What is a “Model?”
      High Cost/Low Error
      Low Cost/High Error
      Unarticulated Wisdom
      Articulated QualitativeModel
      DimensionalModels
      FacetwiseModels
      Equations of Motion
      The Modeling Spectrum
      17
      © David E. Goldberg 2010
    • 44. Marginal Analysis
      When should engineer/inventor adopt more expensive model?
      At the margins, when ΔB ≥ ΔC.
      Marginal benefit of model to technology under development must equal or exceed its marginal cost.
      To engineer/inventor, artifact is the object of study  models almost always instrumental.
      To scientist/mathematician building a model
      may be the object
      or instrumental to some other goal (then engineer’s calculus applies).
      18
      © David E. Goldberg 2010
    • 45. Objection: That’s Common Sense
      People see this list and say “That’s common sense,” “I do that,” or “I know that.”
      Perhaps, but common sense is notconscious sense and
      Power is in being explicit about these techniques as systematic method.
      Productivity and quality of results improved when I labeled these things and start using them consciously.
      © David E. Goldberg 2010
      19
    • 46. Demarcation of Engineering Knowledge
      Realized that I was on philosophical grounds, a demarcation argument.
      Realized that many practices in engineering and CS have proceeded without critical reflection.
      Engineering and CS studied without definition.
      Starts with misleading math-science death march.
      Gives impression that engineering = analysis or “the basics” (math, science, engineering science).
      Ontology, epistemology, reasoning ignored.
      “Design” as abused term & mysterious process.
      20
      © David E. Goldberg 2010
    • 47. My Philosophical Turn
      Have turned to philosophy for personal & professional reasons.
      Started Engineering and Technology Studies at Illinois or ETSI (with Michael Loui).
      Co-chaired 2007 and 2008 Workshop on Philosophy & Engineering (WPE) at TUDelft and Royal Academy of Engineering.
      Started engineering reflections track at Society for Philosophy & Engineering.
      Co-Founded Illinois Foundry for Innovation in Engineering Education (2007, 2008).
      Co-chaired Summit on the Engineer of the Future 2.0 at Olin College.
      Turn had its roots in starting a company.
      21
      © David E. Goldberg 2010
    • 48. Conceptual Modeling at ShareThis
      Was asked to join co-founding team of ShareThis (then Nextumi) in 2004.
      Create consumer chromosome inspired by GASOML.
      Did tech work, but also worried a lot about modeling “creepiness.”
      Models were conceptual.
      Ray Price, tech visionary research & a course.
      Design of Innovation, explored qual-quant divide.
      22
      © David E. Goldberg 2010
    • 49. Some Philosophical Reflections
      The existential pleasures of engineering.
      Kuhn, paradigms, and all that.
      Is GEC stuck in a paradigm or paradigms?
      Is education of engineers and computer scientists stuck in paradigm?
      With so many calls for educational change, how come we’re still stuck?
      23
      © David E. Goldberg 2010
    • 50. Existential Pleasures of Engineering
      Slide title taken from book by Samuel Florman.
      Making cool technology is fun.
      Existential philosophers: Life is lived. Dasein, beings in time in the process of being.
      We choose. Things happen. We choose again.
      Thought of careers as planned. Tracing my career path as example.
      Not unlike genetic algorithms: Interesting mix of randomness and choice resulting in the solutions that become.
      Martin Heidegger (1889-1976)
      24
      © David E. Goldberg 2010
    • 51. Kuhn, Paradigms & All That
      My cocktail party started with me stuck in a “cost effectiveness” mindset.
      “Paradigm” traces to The Structure of Scientific Revolutions in 1962.
      Kuhn argued that science proceeds in fits and starts, not gradually.
      Old paradigms, ways of thinking about the world, are overturned by revolutions, not gradually.
      What ways are we all stuck in paradigms?
      Thomas S. Kuhn (1922-1996)
      25
      © David E. Goldberg 2010
    • 52. Is Synthetic Biology Locked in a Paradigm?
      What habits of thought productive early in GEC are counterproductive now?
      Continued adherence to old religions (GA, ES, EP, GP).
      Loose metaphorical operator design without any analysis? A vs. B comparisons with little basis.
      Rigorous theory & no consideration of design implications?
      Lack of progress in examining or contributing to understanding biological mechanism.
      Oftentimes progress comes from new influences: What field or disciplines are we not collaborating with that would help make progress?
      Interested in neuroscience, philosophy, GAs & consciousness.
      26
      © David E. Goldberg 2010
    • 53. Are Engineering & CS Ed Stuck in Paradigm?
      Paradigm of tech academy is from the cold war.
      Following assumptions sacrosanct:
      Basic engineering science key to success.
      Government funds superior to industry $$$.
      Demonstrate mettle as individuals with peer-reviewed journal papers in specialty.
      Question any  stare, derision & ridicule.
      These beliefs are not scientific.
      Paradigm of 50s-present.
      Code words: “the basics,” “rigorous,” & “soft.”
      Invoking code words not an argument.
      27
      © David E. Goldberg 2010
    • 54. The Missing Basics
      Have taught 20 years in industrially sponsored senior design course.
      After 4 years students don’t know how to
      Question: Socrates 101.
      Label: Aristotle 101.
      Model conceptually: Hume 101 & Aristotle 102.
      Decompose: Descartes 101.
      Measure: Bacon-Locke 101.
      Visualize/draw: da Vinci-Monge 101.
      Communicate: Newman 101
      List starts as before in education of Gamist.
      Call these the missing basics (MBs) vs. “the basics” = math, sci, & eng sci.
      Missing basics are in some sense more basic than “the basics.”
      Why does engineering education backfill these skills in practice?
      Socrates (470-399 BC)
      28
      © David E. Goldberg 2010
    • 55. The Missing Basics as Rosetta Stone
      Missing basics key to
      Engineering and CS ed reform
      Liberal ed reform
      Interdisciplinary research
      Lifelong learning
      If math & science the center, how do humanists and scientists talk?
      Wrong turn at the Enlightenment.
      Toulmin’s argument that geometry is not a good general epistemological model.
      29
      © David E. Goldberg 2010
    • 56. An Academic NIMBY Problem
      • NIMBY = Not in my backyard.
      • 57. “Reform is fine…”
      • 58. “….as long as you don’t change my course.”
      • 59. Politics of logrolling: You support my not changing. I support your not changing.
      • 60. Even when agreement for change is acknowledged, almost all specific changes are resisted.
      30
      © David E. Goldberg 2010
    • 61. iFoundry: A Pilot Incubator for Change
      Less planning more dot connecting.
      iFoundry = Illinois Foundry for Innovation in Engineering Education:
      Separate pilot unit/incubator. Permit change.
      Collaboration. Large, key ugrad programs work together. Easier approval if shared.
      Connections. Hook to depts, NAE, ABET (?), industry.
      Volunteers. Enthusiasm for change among participants.
      Existing authority. Use signatory authority for modification of curricula for immediate pilot.
      Respect faculty governance. Get pilot permission from the dept. and go back to faculty for vote after pilot change
      Assessment. Built-in assessment to overcome objections back home.
      Scalability. Past attempts at change like Olin fail to scale at UIUC and other big schools.
      31
      © David E. Goldberg 2010
    • 62. Emotional Rescue: Ditch the Greek Ideal
      Live in interesting times.
      Still playing by rules of 5th century BC in Athens.
      Eschewed emotions in favor of rational.
      Not either/or.
      Elephant and the rider.
      What 73 freshmen taught me.
      Passion powers the elephant through hard times.
      © David E. Goldberg 2010
      32
    • 63. Things that Happened & Their Lessons
      Events
      Bumped into GAs by accident.
      Joined field at time of growth. Was urged to do something else.
      Fluids training as disciplinary grounding in complexity.
      Wrote a book I was told not to write.
      Became philosophical in a action-oriented field.
      Took on reform effort not admired by peers.
      Rational stance from 2.5kya isn’t working
      Lessons?
      Important things can be random.
      Opportunity is knocking? Will you answer the door?
      Being appropriately different can be beneficial.
      Authority figures are not necessarily right or wise.
      Exploring the unexplored can yield interesting insights.
      Sometimes important jobs are not valued by others.
      Need balance of emotions, rationality, and changing the path.
      33
      © David E. Goldberg 2010
    • 64. Finding Your Impedance Match
      Metaphor of circuit impedance: Matched speakers.
      Mismatch  distortion or Match  clear sound.
      Aristotle talked about virtues leading to happiness or eudaimonia.
      About fulfilling your potential.
      New positive psychology takes up these ancient themes.
      Been blessed to be able to do things I found to be interesting and important.
      Hope you are blessed, too.
      34
      © David E. Goldberg 2010
    • 65. 2 Meetings
      Forum on Philosophy, Engineering & Technology, 9-10 May 2010 (Sunday Eve – Monday), Colorado School of Mines.
      Steven Goldman keynotes.
      www.philengtech.org
      Engineer of the Future 3.0: Unleashing Student Engagement.
      14-15 November 2010, University of Ilinois at Urbana-Champaign, Student-run & student-centered meeting for transformation of engineering education.
      © David E. Goldberg 2010
      35
    • 66. More Information
      Goldberg, D. E. (2002). The design of innovation: Lessons from and for competent genetic algorithms. Boston, MA: Kluwer Academic Publishers.
      Lab:www.illigal.org
      iFoundry:www.ifoundry.illinois.edu
      Philosophical writing: http://philsci-archive.pitt.edu/ (search for “Goldberg”).
      Powerpoint: www.slideshare.net/deg511
      YouTube: www.youtube.com/illinoisfoundry
      36
      © David E. Goldberg 2010

    ×