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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
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
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