Open innovation can be a good match for this:
A Promising Approach for Complex Challenges
Idea synergyThe long tail (marginalsMany hands
Complex societal problems inherently involve many stakeholders and areas of expertise, and require innovative out-of-the-box solutions
Many eyesWisdom of the crowdsVolunteer ethic
“No matter who you are, most of the smartest people work for someone else” (Joy’s Law)
Organization Contributions Contributors
Open for questions 70K 100K
Google 10^100 150K 100K
IBM Idea Jam 46K 150K
Dell Ideastorm 21K
Challenges with Open Innovation at Scale
“Upon this gifted age, in its dark hour,Rains from the sky a meteoric shower Of facts…they lie unquestioned, uncombined.Wisdom enough to leech us of our illIs daily spun; but there exists no loomTo weave it into fabric…”
Edna St Vincent Millay. Huntsman, What Quarry? (1939)
Challenges with Open Innovation at Scale• High harvesting costs:
• redundancy, due to ignorance or manipulation• signal-to-noise: only ~10% of ideas are worth consideration
• Rating dysfunctions• With large corpuses, users tend to rate only the highest-rated
ideas, creating feedback loops => rating lock
• Shallow ideas: lots of rudimentary ideas• solo ideas w/o collaborative refinement• tough to track and reward IP – “I didn’t see he had the same
idea”• Unsystematic
• No mechanism to ensure coverage of critical issues/ideas
• Shallow evaluations:• quick personal impressions, not customer criteria-based • little/no analysis and fact-checking
• Google project10tothe100 needed 3,000 volunteers & 9 months to filter/sort ideas
• Open for Questions was shut down due to overload
• IBM flew 100 executives to New York for a week to filter Web Jam ideas
• Process opaqueness• “It’s tough to steer when you can’t see where you’re going”
Planeta.com (5/1/08) had a 13-page discussion on carbon offsetting pros and cons
Argument Mapping Can Help!
No redundancy: can ensure each unique point appears just once
Better coverage: easier to find gaps that need to be filled Deeper ideas: crowd builds issue/idea trees instead of
standalones Credit tracking: non-redundancy makes idea precedence
clear
Argument Mapping Can Help!
Open Issues: Argument Mapping at Scale
• Structure• How do we keep large growing maps well-structured?
• Content• How do we foster good (creative, detailed) solution ideas?• How do we rapidly prune the top 10% of ideas?• How do we ensure good (well-founded, complete) evaluations?
• Process• How do authors know where they can best contribute, in large
maps?• How do managers know what process problems need
intervention?
• Outcome• How do customers know which content is ready to ‘harvest’?
High-Speed Idea Pruning: Bag of Stars
0 0.2 0.4 0.6 0.8 1 1.20
0.2
0.4
0.6
0.8
1
1.2
LikertBOSBOL
false positive rate
tru
e p
osit
ive
rate
A key trick: assign posts to users in a way that maximizes value e.g. • to posts whose value is uncertain• to calibrate ratings across multiple rater pools• ...
Unbundle – break your thoughts into points that each contain just one issue, idea, or argument.
Locate – search the argument map to see where your point(s) belongEnter – If it’s a new point, create a new post, else refine existing post.
The live-and-let-live rule: only edit a post to strengthen it
The honest broker rule: remain strictly content-neutral
Certify well-structured posts - a coaching role
Rate to highlight worthy posts
Only certified posts can be viewed by readers
Structure Moderators
Idea: reduce the energy-intensity of products and services
Pro: typically has positive ROI (addresses: low-cost)
Issue: what actions can help avoid global warming?
criterion: low-costcriterion: effectivecriterion: few negative side-effects
Extended IBIS to Support Design Problems
• Added criteria to IBIS so we can track evaluation completeness:• Augment issues with list of criteria successful solutions should
satisfy• Annotate arguments with the criteria they address
Recombinant Design•Map defines a multi-dimensional
design space – Issues = design dimensions – Complete solutions are packages
(combinations) of ideas
•Benefits– Enables systematic exploration of
design space– Fosters creativity by recombination
•Challenges– Creates very large search spaces due to
exponential combinatorics
Nonlinear Negotiation• How find pareto-optimal solution packages in very large search spaces with
self-interested stakeholders?• Standard (linear) negotiation protocols fare poorly in such contexts• New protocols, often counter-intuitive, are needed
U(A
2)
Contracts
U(A
1)
optimum
optimum
selected best
Metrics & Attention Mediation• A free open-source web service that deliberation platforms can call to
calculate metrics for their maps• A growing library of metrics, defined based on systematic analysis of
deliberation needs and challenges• A language for defining “alerts” that notify participants of metrics signal
that they need to know about
Implementing Metrics
A little semantics, in abundance, allows us to define metrics of unprecedented power compared to those for social media
Data mining (dimensionality reduction , hierarchical clustering ...)
Belief propagation (e.g. Bayesian)
Network topology (includes social network) analysis
Statistical analysis
Graph-based query languages (e.g. SPARQL)
Time series analysis
Balkanization Metric: SVD & Clustering
Apply dimensionality reduction to idea and argument ratings => ”bias space”
• each point represents a user• each axis represents a ”bias" (i.e. set of post with correlated ratings)
Balkanization = distinct clusters in bias space
Attention Mediation: A Keystone Capability
• Guide ideation towards gaps (maturity)• Guide ideation towards pareto front (negotiation)• Guide evaluation to where it is most needed (efficiency)• Guide managers to areas that need intervention• Guide customers to the good stuff
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