Daren Brabham Stakeholder Engagement Conference 2010

Integrating Previously Uninvolved Stakeholders in an Online Public Participation Program The Next Stop Design Case Daren C. Brabham with Thomas W. Sanchez Keith Bartholomew

Outline
The origins of crowdsourcing
Toward a typology of crowdsourcing
Crowdsourcing public participation in planning
A tour of Next Stop Design
Outcomes
Future Plans
Q & A
Me.

A Boy and His Shirts

A Struggle Over the Term
Challenges “in the form of an open call”
“ An online, distributed problem solving and production model”
Like anything in Wired , “crowdsourcing” was an instant buzzword
Old wine in new bottles?
A bloated concept makes for unclear research

Toward a Typology
Toward a typology of crowdsourcing approaches
Knowledge Discovery
Broadcast Search
Peer-Vetted Creative Production
Distributed Human Intelligence Tasking
And what about open source, commons-based peer production, distributed computing, etc.?

Knowledge Discovery
Online communities challenged to uncover existing knowledge in the network
Amplify discovery capabilities of an organization with limited resources
Example: Peer-to-Patent

Knowledge Discovery

Knowledge Discovery
Similar in spirit to what Yochai Benkler calls “commons-based peer production,” but not the same
Commons-based peer production (e.g., Wikipedia) lacks a centralized set of tasks
A knowledge management and coordination process

Broadcast Search
Online communities challenged to find solutions to difficult problems
Casting a wide net finds the “lone gunman” – the genius able to solve the problem
Examples: InnoCentive, Goldcorp Challenge

Broadcast Search

Online communities challenged to develop and choose solutions to ideation problems
Inviting a lot of input—diverse input—brings in many (different) ideas. And people “find the best stuff”
Best idea is the one the market will support
Examples: Threadless, user-generated ads

Online communities tasked to perform simple tasks that computers cannot do well
Decomposing a problem/task requiring human intelligence into smaller pieces and distributing it is faster, better
Examples: Amazon Mechanical Turk, Subvert & Profit

Similar to distributed computing projects like SETI@Home, Rosetta@Home, etc.
Distributed computing lacks human intelligence
Use of “spare cycles” is similar, though
Bored at work? Make $0.03 clicking on things
Complicates the idea of separate work, play, and “down” time

Why Does All of This Work?
Collective intelligence: we are smarter than me
Crowd wisdom
Aggregating individual input is sometimes better than averaging ideas
The Web coordinates effort
Speed, reach, asynchrony, anonymity, convergence
Crowds are motivated
money, reputation, portfolio building, enjoyment, friends

Review: 4 Types, 4 Features
4 types: knowledge discovery, broadcast search, peer-vetted creative production, distributed human intelligence tasking
4 core features:
Hierarchical task management by an organization (the “crowdsourcer”)
Crowdsourcer understands motivations of “crowds”
Crowdsourcing leverages human intelligence
Depends on the Web

Urban Planning & Public Participation
Urban planning central to many of today’s biggest social and environmental problems
Urban planning uses public participation programs
Traditional public participation methods have limitations
Interpersonal dynamics, special interest groups, logistics, skewed demographics, one-way comm.
Purpose is similar to peer-vetted creative production (ideation, market support)

Next Stop Design
Federal Transit Administration grant for “Innovations in Public Participation”
In cooperation with the Utah Transit Authority
Peer-vetted creative production approach
Bus stop design contest
Why bus stops? Common, complex, contained

Next Stop Design

Variety of Designs

Winners
1 st – “Folding Bus Stop” – 3.30
Thessaloniki, Greece
2 nd – “Stop to Move” – 3.05
Mumbai, India
3 rd – “Smart Stop” – 2.89
Sioux Falls, South Dakota

Final Breakdown
29,855 visits
316,141 page views (10.6 pages/visit)
3,187 registered users
260 bus stop designs
11,058 votes cast

Final Breakdown
Countries/territories visiting: 127
Top: US, UK, India, Greece, Canada
U.S. states visiting: 50, plus D.C.
Top: NY, CA, UT, TX, LA

Final Breakdown
Users were riders
48% rode bus “more than once a week” or “every day”
57% rode bus at least once a week
Users were new to the process
68.5% had never attended a public meeting
Diverse ages
13-85 years old
9% teens, 49% 20s, 21% 30s, 21% 40+

Outcomes
Crowdsourcing has potential for public participation in urban planning. Model needs refinement.
Replicated some of the limitations of traditional public participation methods
Cheaters – 20 cheaters, 27.6% of votes
Accountability
Keep current score unknown

Findings So Far
Building online community is challenging
Motivations are complex
Amateur – Professional Tension
Global – Local Tension

Future Plans
Continued interviews with participants
Motivations for participation
Perceptions of the project as effective for government
How they found out about the site
“ Expert” panel review of the winners
Code common themes in designs
Phase 2 – design a plan, not a structure
Publish source code, create toolkit

Thank You
Questions?

Daren Brabham Stakeholder Engagement Conference 2010

by University of North Carolina at Chapel Hill on Mar 03, 2010

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