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“Critical Mass of Ideas”
     A Model of Incubation in Brainstorming




Ricardo Sosa and John S Gero
Incubation




                               www.dilbert.com




Ricardo Sosa and John S Gero
This talk                           www.icdc2012.org.uk




     Context and big picture
     Definitions and issues
     Insights
     Computational Social Science
     Modelling principles, hypotheses and results*


Ricardo Sosa and John S Gero
www.sutd.edu.sg/idc.aspx




Ricardo Sosa and John S Gero
Brainstorming groups


     Interactive – Nominal Groups
     Facilitation Strategies – Unstructured
     Ideational Productivity – Quality
     Individual – Team Conditions
     Laboratory – Field – Computational
     Practice – Analysis
Ricardo Sosa and John S Gero
Incubation


  “A stage of creative problem solving in
 which a problem is temporarily put aside
       after a period of initial work”



Ricardo Sosa and John S Gero
Incubation


     Differentially advantageous: Moderators?
     Why and when interrupt/resume ideation?
     A better characterization, expected effects,
     appropriate conditions, best timing and
     management strategies
     Comp Soc Sci: exploratory but explicit
Ricardo Sosa and John S Gero
“Critical Mass of Ideas”


     Ideation is significantly more productive once
     initial stages have produced a sufficiently large
     mass of base ideas

     Incubation amplifies and accelerates ideation
          A small mass is insufficient, a large mass unproductive

Ricardo Sosa and John S Gero
“Critical Mass of Ideas”


     CMI principle: a sufficiently rich body of initial
     ideas is a pre-condition for combinatory
     processes to generate a high number and variety
     of creative ideas

     With CMI, marginal amounts of incubation are
     sufficient to produce peak results
Ricardo Sosa and John S Gero
Computational Social Model


     IAS: Ideas, Agents, Society (Sosa, Gero and Jennings 2009)
     shapeStorming –a thinking tool:
          A computational model of brainstorming using 2D shape
          emergence
          Design agents (A) explore, exploit and incubate solutions
          and design concepts (I) organised in teams (S)
          Experimental variables: exploration length and incubation
          rate
Ricardo Sosa and John S Gero
Ricardo Sosa and John S Gero
Questions and Comments


                                      Ricardo Sosa
                               ricardo_sosa@sutd.edu.sg

                                     John S. Gero
                                 john@johngero.com


Ricardo Sosa and John S Gero
Exploration – Exploitation - Incubation


     Explore: random arrangement of connected lines
     from which polygons of n-sides are built
     Exploit: variations to geometries guided by
     topological relations (design concepts) derived
     from previous solutions
     Incubate: variations to design concepts with no
     direct changes in geometries
Ricardo Sosa and John S Gero
Hypotheses


     (H1) a combination of exploration and
     exploitation is likely to produce a significant
     increase in ideational productivity

     (H2) incubation will produce a significant increase
     in ideational productivity

Ricardo Sosa and John S Gero
Ricardo Sosa and John S Gero
Emergent Shape Semantics
                               Number of emergent polygons, number of sides




Ricardo Sosa and John S Gero
Ideation in Exploration Mode

                         shapeStorming conditions            Ideational productivity

       A: 1,000 steps, 4 agents, 2 initial shapes, 3 sides            7.23

     B: 10,000 steps, 4 agents, 2 initial shapes, 3 sides             9.38

      C: 10,000 steps, 4 agents, 3 initial shapes, 3 sides           134.22

    D: 100,000 steps, 4 agents, 2 initial shapes, 3 sides             15.35



Ricardo Sosa and John S Gero
Experiment 1


     Effects of exploitation mode in ideational
     productivity at different stages in conditions A
     and B

     Exploration length φ: from 0.0 to 1.0 in 0.05
     increments

Ricardo Sosa and John S Gero
Experiment 2


     Effects of varying incubation stage against length
     of preparation stage in conditions A and B

     Incubation rate μ: from 0.0 to 0.50



Ricardo Sosa and John S Gero
Results: Exploitation


     Condition A: peak ideational productivity +6% with φ
     = 0.75 (short runs). Condition B: +93% with φ = 0.75
     (long runs)
     In B, exploitation-driven concepts show a significant
     increase as exploration is extended
     Exploitation has positive but differentiated effects on
     ideational productivity depending on the ability to
     build on a sufficiently large mass of ideas
Ricardo Sosa and John S Gero
“Critical Mass of Ideas”


     A significant gain in ideational productivity due to
     positive feedback effects between exploitation
     and a sufficiently large body of ideas from
     exploration




Ricardo Sosa and John S Gero
Results: Incubation


     Condition A: peak ideational productivity +220%
     with a low incubation rate μ = 0.05 and φ = 0.20
     Condition B: ideational productivity +160% when
     μ = 0.05 and φ = 0.10

     Effects of incubation dependent on the size of the
     problem space addressed in ideation
Ricardo Sosa and John S Gero
Discussion


     Incubation: put aside a problem for a time period
     t, once n ideas of m categories are generated

     CMI: used to manage interactive/nominal groups



Ricardo Sosa and John S Gero
Questions and Comments


                                      Ricardo Sosa
                               ricardo_sosa@sutd.edu.sg

                                     John S. Gero
                                 john@johngero.com


Ricardo Sosa and John S Gero

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Critical mass of ideas

  • 1. “Critical Mass of Ideas” A Model of Incubation in Brainstorming Ricardo Sosa and John S Gero
  • 2. Incubation www.dilbert.com Ricardo Sosa and John S Gero
  • 3. This talk www.icdc2012.org.uk Context and big picture Definitions and issues Insights Computational Social Science Modelling principles, hypotheses and results* Ricardo Sosa and John S Gero
  • 5. Brainstorming groups Interactive – Nominal Groups Facilitation Strategies – Unstructured Ideational Productivity – Quality Individual – Team Conditions Laboratory – Field – Computational Practice – Analysis Ricardo Sosa and John S Gero
  • 6. Incubation “A stage of creative problem solving in which a problem is temporarily put aside after a period of initial work” Ricardo Sosa and John S Gero
  • 7. Incubation Differentially advantageous: Moderators? Why and when interrupt/resume ideation? A better characterization, expected effects, appropriate conditions, best timing and management strategies Comp Soc Sci: exploratory but explicit Ricardo Sosa and John S Gero
  • 8. “Critical Mass of Ideas” Ideation is significantly more productive once initial stages have produced a sufficiently large mass of base ideas Incubation amplifies and accelerates ideation A small mass is insufficient, a large mass unproductive Ricardo Sosa and John S Gero
  • 9. “Critical Mass of Ideas” CMI principle: a sufficiently rich body of initial ideas is a pre-condition for combinatory processes to generate a high number and variety of creative ideas With CMI, marginal amounts of incubation are sufficient to produce peak results Ricardo Sosa and John S Gero
  • 10. Computational Social Model IAS: Ideas, Agents, Society (Sosa, Gero and Jennings 2009) shapeStorming –a thinking tool: A computational model of brainstorming using 2D shape emergence Design agents (A) explore, exploit and incubate solutions and design concepts (I) organised in teams (S) Experimental variables: exploration length and incubation rate Ricardo Sosa and John S Gero
  • 11. Ricardo Sosa and John S Gero
  • 12. Questions and Comments Ricardo Sosa ricardo_sosa@sutd.edu.sg John S. Gero john@johngero.com Ricardo Sosa and John S Gero
  • 13. Exploration – Exploitation - Incubation Explore: random arrangement of connected lines from which polygons of n-sides are built Exploit: variations to geometries guided by topological relations (design concepts) derived from previous solutions Incubate: variations to design concepts with no direct changes in geometries Ricardo Sosa and John S Gero
  • 14. Hypotheses (H1) a combination of exploration and exploitation is likely to produce a significant increase in ideational productivity (H2) incubation will produce a significant increase in ideational productivity Ricardo Sosa and John S Gero
  • 15. Ricardo Sosa and John S Gero
  • 16. Emergent Shape Semantics Number of emergent polygons, number of sides Ricardo Sosa and John S Gero
  • 17. Ideation in Exploration Mode shapeStorming conditions Ideational productivity A: 1,000 steps, 4 agents, 2 initial shapes, 3 sides 7.23 B: 10,000 steps, 4 agents, 2 initial shapes, 3 sides 9.38 C: 10,000 steps, 4 agents, 3 initial shapes, 3 sides 134.22 D: 100,000 steps, 4 agents, 2 initial shapes, 3 sides 15.35 Ricardo Sosa and John S Gero
  • 18. Experiment 1 Effects of exploitation mode in ideational productivity at different stages in conditions A and B Exploration length φ: from 0.0 to 1.0 in 0.05 increments Ricardo Sosa and John S Gero
  • 19. Experiment 2 Effects of varying incubation stage against length of preparation stage in conditions A and B Incubation rate μ: from 0.0 to 0.50 Ricardo Sosa and John S Gero
  • 20. Results: Exploitation Condition A: peak ideational productivity +6% with φ = 0.75 (short runs). Condition B: +93% with φ = 0.75 (long runs) In B, exploitation-driven concepts show a significant increase as exploration is extended Exploitation has positive but differentiated effects on ideational productivity depending on the ability to build on a sufficiently large mass of ideas Ricardo Sosa and John S Gero
  • 21. “Critical Mass of Ideas” A significant gain in ideational productivity due to positive feedback effects between exploitation and a sufficiently large body of ideas from exploration Ricardo Sosa and John S Gero
  • 22. Results: Incubation Condition A: peak ideational productivity +220% with a low incubation rate μ = 0.05 and φ = 0.20 Condition B: ideational productivity +160% when μ = 0.05 and φ = 0.10 Effects of incubation dependent on the size of the problem space addressed in ideation Ricardo Sosa and John S Gero
  • 23. Discussion Incubation: put aside a problem for a time period t, once n ideas of m categories are generated CMI: used to manage interactive/nominal groups Ricardo Sosa and John S Gero
  • 24. Questions and Comments Ricardo Sosa ricardo_sosa@sutd.edu.sg John S. Gero john@johngero.com Ricardo Sosa and John S Gero