Growing and Destroying the Worth of Ideas
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Creativity and Cognition Conference. UC Berkeley October 2009
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Growing and Destroying the Worth of Ideas
- 1. Ricardo Sosa John Gero Kyle Jennings Tec de Monterrey George Mason Univ UC Berkeley Page 295
- 2. Ideas are important! Especially in the current crisis... creative ideas are really important!
- 3. A tough question... How do new ideas get to be considered as 'creative'? (how do people ascribe this value?)
- 4. Research approach Explore possibilities with computer models
- 5. Computational explorations Individualistic Interactionist Social simulations
- 6. Computational explorations Individualistic Algorithms that human experts judge as worthy Interactionist Person-program interaction
- 7. Computational explorations Social simulations Systems where worth grows from interacting generators and evaluators
- 9. Evaluation criteria of creativity Individualistic pre-programmed Interactionist externalised Social simulations emergent, socially-defined
- 10. soft modelling (curious, playful) hard modelling (ignore indexicality)
- 11. ”Creative autonomy” Ability to change without resorting to: directly parroting others purely random drift
- 12. Multiagent frameworks Swarm, NetLogo, RePast, Mason... Inadequate model for ideas Ideas are dynamic entities Ideas are human products but also produce values
- 13. Theories of (creative) change Thomas Kuhn Cumulative anomalies of dominant ideas Communities ascribe value to new ideas Joseph Schumpeter Stages of high competition followed by disturbances by entrepreneurs Economic upswings based on increased differentiation and profits
- 14. Theories of (creative) change Edgar Morin 'noosphere': system of ideas value of dominant ideas embedded in a social world Mihalyi Csikszentmihalyi domain transmits information, person produces a variation, field selects some variations
- 15. Theories of (creative) change Dean Simonton Critical predictor of recognition is total output Hi = pTi + ui Hi : high impact works by person i p : average hit rate for that domain Ti : total productivity of person i ui : random variable with a mean = 0
- 16. IAS framework Idea – Agent – Society (IAS) Method for empirical experimentation Interplay of cognitive, social and symbolic dimensions where creativity develops
- 17. IAS framework Author Level I Level A Level S Focus Kuhn Exemplar Proponent Community Validity Schumpeter Innovation Entrepreneur Market Profits Morin Noosphere Strong spirit Culture Domestication Csikszentmihalyi Domain Individual Field Cultural evolution Simonton Logic Genius Zeitgeist Recognition Level I Level S Level A
- 18. IAS framework Level I Is/Si Level S (Ii) (Ss) Ia/Ai Level A Sa/As (Aa) Ia Transmission, language, intellectual property Ai Mutation, displacement, reinterpretation As Dissent, promotion, acceptance seeking Sa Norms, recognition, social influence, conformity Si Selection, 'gatekeeping' Is Allegiance, dogmas, anomalies
- 19. IAS framework Idea – Agent – Society (IAS) What is defined algorithmically? What is expected to be 'grown'? Non-deterministic rules, bootstraping, threshold modelling... Capture non-creative equilibrium trend with exceptional disruption points
- 20. IAS framework Idea – Agent – Society (IAS) Simulation is not the aim: - improve our understanding - assess ideas to test in the lab /field
- 21. What is creativity? Where is creativity? Author How do people and societies Level I Level A Level S Focus Kuhn Exemplar Proponent Community Validity ascribe the creative value? Schumpeter Innovation Entrepreneur Market Profits Morin Noosphere Strong spirit Culture Domestication Csikszentmihalyi Domain Individual Field Cultural evolution Simonton Logic Genius Zeitgeist Chance Level I Level S (Ii) (Ss) Level A (Aa)
- 23. Questions Claudia Eckert: can you model systems that distinguish between the idea itself and the way it is presented? Interesting, would be a scenario where I and A are constant, and S-processes are changed to assess how the way an idea is presented changes its impact Mary Lou: What are the scales of these systems? Suitable for modelling small groups (as in classroom studies) and for very large systems of 100ks