The Seeding, Evolutionary Growth, Reseeding (SER) Model

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The Seeding, Evolutionary Growth, Reseeding (SER) Model

Gerhard Fischer, Hal Eden, and Holger Dick — Fall Semester 2010

gerhard@colorado.edu; haleden@colorado.edu; holger.dick@gmail.com;  

September 29, 2010

paper: Fischer, G., & Ostwald, J. (2002) "Seeding, Evolutionary Growth, and Reseeding: Enriching Participatory Design with Informed Participation," Proceedings of the Participatory Design Conference, Malmö University, Sweden, pp. 135-143. http://l3d.cs.colorado.edu/~gerhard/papers/pdc2002-ser.pdf

Observations

• we live in a world characterized by evolution – that is, by ongoing processes of development, formation, and growth in both natural and human-created systems

• biology tells us that complex, natural systems are not created all at once but must instead evolve over time

• we are becoming increasingly aware that evolutionary processes are ubiquitous and critical for social and technological innovations as well

• this is particularly true for complex human centered computational environments because they do not exist in a technological context alone but are embedded within human organizations

Theory and Practice of Design—A Quest for Evolution

• Dawkins — “The Blind Watchmaker”: big-step reductionism cannot work as an explanation of mechanism; we can't explain a complex thing as originating in a single step

• Simon — “The Sciences of the Artificial”: complex systems evolve faster if they can build on stable subsystems

• Petroski — “To Engineer Is Human”: the role of failure in successful design

• Brooks — “No Silver Bullet”: successful software gets changed, because it offers the possibility to evolve

• Polanyi — “The Tacit Dimension”: knowledge is tacit ? we know more than we can say

Karl Popper: Conjectures and Refutations

• “Our whole problem is to make the mistakes as fast as possible.” (foreword to the book by John Archibald Wheeler) — breakdowns as opportunities

• criticism of our conjectures is of decisive importance and all of our knowledge grows only through the correcting of our mistake— critiquing systems

• there are all kinds of sources of our knowledge but none has authority — symmetry of ignorance and mutual competency

• the advance of knowledge consists in the modification of earlier knowledge — evolution

Complex Systems

• design processes often take place over many years, with initial design followed by extended periods of evolution and redesign

• in urban development:

• naturally grown cities: London, Paris
• designed cities: Brasilia, Canberra, Abudja

• in software design: importance of

• design rationale
• redesign and reuse (“complex systems evolve faster if they can build on stable subsystems” (Simon)

Principles Coping with Complex Systems

• software systems must evolve

• they cannot be completely designed prior to use
• design is a process that intertwines problem solving and problem framing
• software users and designers will not fully determine a system’s desired functionality until that system is put to use
• systems must be open enough to allow “emergent behavior”

• software systems must evolve at the hands of the users (? meta-design)

• end users experience a system’s deficiencies; subsequently, they have to play an important role in driving its evolution
• software systems need to contain mechanisms that allow end-user modification of system functionality

• software systems must be designed for evolution —

• systems need to be designed a priori for evolution
• systems must be underdesigned to support emergent new ideas
• software architectures need to be developed for software that is designed to evolve

The Seeding, Evolutionary Growth, Reseeding (SER) Model

• at design time:

• development of an initial system that can change over time (seed)
• underdesign: creating design options for users

• at use time:

• users will experience breakdowns at use time
• end-user modifications allow users to address limitations they experience
• evolutionary growth through incremental modifications

• reseeding:

• significant reconceptualization of the system
• lack at all incremental modifications, mitigate conflicts between changes, and establish an enhanced system

A Simplified Illustration of the SER Model

• SER model accounts for and facilitates the understanding of:

• differentiation between design time and use time
• relation to learning and contributing
• the way that these concepts/objectives depend on each other

Extended Illustration of the SER Model

Evolution at the Different Levels of the SER Model

• Evolution of Individual Artifacts (“Artifact”)

• ontogenic development of an individual artifact
• the computer networks within CU Boulder and the Computer Science Department specifically

• Evolution of the Domain (“DODE”)

• phylogenic development of a generic species
• Computer network design ? new network devices, new design guidelines, new simulation support, and new design rationale

• Evolution at the Conceptual Framework Level (“multifaceted architecture”)

• domain-oriented construction kits
• support for evaluating the quality of an artifact ? development of critics
• “reflection-in-action” by making argumentation serve design ? argumentation component and a specification component

Example: SER Model and Courses as Seeds

Courses As Finished Products

• instructionist approach: learners listen and answer problems given to them by the instructor

• the learners are recipients of knowledge ? the assumption is that the teacher/instructional designer has all the relevant knowledge)

• this model is

• adequate: for courses where the learners get into a new field and therefore might have little to contribute
• not adequate: it does not account for mutual competency and symmetry of ignorance

• quality is solely determined by the knowledge of the teachers and their ability to present the knowledge effectively

Courses as Seeds

• community of learners approach: learners are knowledgeable people in their own domain of expertise and they are not just passive recipients of knowledge, but act (at least from time to time) active contributors

• value adde:

• at the end of the course, the content of the course will be greatly enriched through a semester-long interaction of knowledgeable people and important and relevant information will be incorporated into the course before it is taught the next time
• a model for learning in a knowledge society which is built upon distributed cognition, peer-to-peer learning, articulated learners, long-tail knowledge distribution
• a necessity for many domains/aspects of lifelong learning where communities of learners engage in the incremental construction and evolution of knowledge facilitated by a teacher

Example: SER as a Foundation for Next Generation Wikis

http://l3dswiki.cs.colorado.edu:3232/CreativeIT/

Example: Google’s 3D Warehouse

http://sketchup.google.com/3dwarehouse/modelcycle?scoring=d

SER Model: Relationships and Emerging Themes

• Relationships:

• domain-oriented design environments
• meta-design
• participatory design
• design/use time
• tipping point

• Emerging Themes

• continuing design in use
• end-user programming and development
• open source software
• web 2.0 technologies

Seeding

• explore middle ground between empty frameworks/architectures and complete systems

• seeding by anticipation

• in domains with well-established practices seeding requires anticipating users’ most specific needs ? professionally-oriented design

• seeding by participation

• in domains with loosely defined practices seeding requires the participation of user representatives ? participatory design

• seeding by emergence

• in domains characterized by a high degree of freedom and unpredictability seeding requires users’ spontaneous and direct engagement ? meta-design

Evolutionary Growth

• what will motivate people to contribute? ? utility = value / effort

• addition:

• data and/or functionalities are added to the system
• new infrastructures are implemented and/or created
• new users join the community of participants

• composition:

• data, functionalities, and infrastructures are created by recombining, exchanging, and reusing existing ones
• users aggregate and re-aggregate on the basis of their interests and social relationships

• modification

• existing data, functionalities, and infrastructures are updated, changed, or even eliminated;
• users acquire new knowledge, interests, and skills

Reseeding: Why?

• People “cannot” participate

• technical infrastructures are no longer efficient
• they cannot satisfy new requirements and/or policies
• the seed is no longer usable

• People “do not” participate

• social and technical infrastructures are no longer adequate to support users’ practices and engagement
• the seed has decreased in value
• the seed is no longer useful

Reseeding: How?

• when people cannot participate:

• Generalization: additions, compositions, and modifications are generalized and integrated to “recompose” an artifact that has evolved into incompatible versions at the hands of different users

• Re-factoring: redundancies are thrown away to bring order into an artifact that has become too “messy”

• when people do not participate:

• Facilitation: data, functionalities, or motivational strategies are implemented ad hoc as an opportunity to stimulate participation

• Tuning: infrastructures for communication and interaction are adjusted in order to comply, for example, with new policies enforced by institutional authorities

Design Challenges Associated with the SER Model

<<source: Fogli, D. & Giaccardi, E.(2005): “Make It Flourish! Revising the Idea of Seed in Metadesign”>>

• build for engagement

• enable technical and social infrastructures to evolve
• encourage an active relationship between people and artifacts

• enable modifiability

• content & functionalities
• social interaction paths

• sustain reflexivity

• critiquing mechanisms
• annotation mechanisms

• encourage social practice

• social interaction
• community strategies
• institutional policies

Design Challenges Associated with the SER Model

• give users authority to create value

• ease of use
• shareability

• perform evaluative thinking

• continuous and iterative process

• allow reseeding

• complementary process
• generalization and re-factoring
• facilitation and tuning

• think multidimensionally

• balance anticipatory, participatory and emergence approaches

Example: the American Constitution

<<source: Simon, H. A. (1996) The Sciences of the Artificial, The MIT Press, Cambridge, MA>>

• society as the client — “the members of an organization or a society for whom plans are made are not passive instruments, but are themselves designers who are seeking to use the systems to further their own goals”

• how do we want to leave the world for the next generation? ? desiderata:

• a world offering as many alternatives as possible to future decision makers, avoiding irreversible commitments they cannot undo
• to leave the next generation of decision makers with a better body of knowledge and a greater capacity for experience
• essential task: to keep open the options for the future or perhaps even to broaden a bit by creating new variety and new niches

The United States Constitution

• amendment process (part of the seed) — the authors of the Constitution

• were clearly aware changes would be necessary from time to time if the Constitution was to endure and cope with the effects of the anticipated growth of the nation

• were conscious that such change should not be easy, lest it permit ill-conceived and hastily passed amendment

Evolution in Biology versus Evolution in the Human-Made World — a Word of Caution

• the evolutionary metaphor must be approached with caution because

- there are vast differences between the world of the made and the world of the born

- one is the result of purposeful human activity, the other the outcome of a random natural process

• does software develop according to the “punctuated equilibrium” theory?

- if yes, what causes the periods of increased change (subroutines, object-oriented programming, the World Wide Web (WWW), Web 2.0)?

The Theory of the "Punctuated Equilibrium"

• Stephen Jay Gould’s (Biologist) theory of the "punctuated equilibrium"

• the fossil record long periods of stasis followed by rapid bursts of evolution ? this view has replaced the earlier prevailing view of continuous evolutionary change
• the bursts of evolutionary change in the punctuated equilibrium view are brought about by changes in the environment: a meteor crashes to earth, two continents collide, someone invents penicillin, etc
• after such dramatic events there are rapid changes in biological organisms until a new equilibrium is reached.

• claim: the evolution of social-technical systems follows a similar pattern

Punctuated Equilibrium