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Policy 2.0: theory and practice

MUNICIPAL INNOVATION LAB
David Osimo
Director – Open Evidence
#citylabodessa 16/10/2013
TODAY’S TALK


Theory of policy 2.0
What
 Why
 How




Practices of policy 2.0
Technologies
 Design
 Examples

WHAT
THE CHALLENGES OF GOVERNANCE






Detect and understand problems before they become
unsolvable”
Involve open intelligence in policy-making, and extract “good
ideas” from it
From words to action: ensure implementation and actual
behavioural change
Reducetime-to-impact evaluation


All this, dealing with a distributed governance
model. The traditional division of “market” and
“state” no longer fits a reality where public decision
and action is effectively carried out by a plurality of
actors.
A VISION: A THIRD WAY OF POLICY MAKING?

+ Emergent
+ Open
+ Peer2peer
+ Unexpected

+ Expert based
decisions
+ Robust
+ Relevant

Direct Democracy

Technocracy

- Social media
- Populism
- Unstructured discussion
- Loudest voice

- Black box
- Closed models
- Reductionism
A VISION: A THIRD WAY OF POLICY MAKING?
Policy-making 2.0:
Open and evidence based
+ Emergent
+ Open
+ Peer2peer
+ Unexpected

+ Expert based
decisions
+ Robust
+ Relevant

Direct Democracy

Technocracy

- Social media
- Populism
- Unstructured discussion
- Loudest voice

- Black box
- Closed models
- Reductionism
COVERING THE FULL POLICY CYCLE: IT’S NOT ABOUT
CROWDSOURCING DECISIONS
ANTICIPATING THE UNEXPECTED: BIG AND OPEN DATA
POLICY DESIGN: SMART CROWDSOURCING
POLICY OPTIONS SIMULATION

UrbanSIM case
TURNING POLICY IN IMPACT: APPS FOR
BEHAVIOURAL CHANGE
SENSE MAKING IN EVALUATION THROUGH OPEN
DATA
WEB 2.0 IS ABOUT VALUES, NOT TECHNOLOGY
User as producer, Collective intelligence,
Long tail, Perpetual beta, Extreme ease of
use

Values

Blog, Wiki, Podcast, RSS, Tagging, Social
Applications
networks, Search engine, MPOGames

Technologies

Ajax, XML, Open API, Microformats,
REST, Flash/Flex, Peer-to-Peer

Source: Author’s elaboration based on Forrester
13
A NEW WAY TO DO
PUBLIC INNOVATION
Innovation without
permission
 Fast development (weekend)
 Perpetual beta
 Planning for emergence
 Government not only a
player but a platform

DIFFERENT TYPES OF CITIZEN/GOV
COLLABORATION
Data
Services

Gov

Citizens

Gov

Intrapreneurship

Crowdsourcing

Citizens

Open Data apps

Self-help
WHAT IS DIFFERENT?
BEYOND ARTIFICIAL OPPOSITIONS
Planning,
Top down

Kublai, Rewired State, The Hub,
Social Innovation Camp,
Appsfordemocracy,
…. #CitylabOdessa

Emergent, bottom-up

1
WHY
6 THINGS CITIZENS CAN OFFER
Software development skills (OpenCamera)
 Specific technical knowledge (PeerToPatent)
 Experience of using public services (PatientOpinion)
 Trust of other citizens (ActiveMobs)
 Capillar coverage of the territory (Fixmystreet)
 “Many eyes” (openspending)

REMINDER: CITIZENS AND EMPLOYEES DO IT
ANYWAY

2
POLICY TOOLS RELEVANT FOR POLICY CHALLENGES
LET’S TAKE A LOOK AT THE DARK SIDE
DESIGN FOR BART NOT FOR LISA!

Hat tip: Carter and Dance, Nytimes.com

2
NON-TECH BARRIERS
Learning lessons from 20 years of technology adoption
in government: bottlenecks are cultural and
organisational, not technological
 Technology will not suddenly free policy-making from
politicking, corruption, personal interests, short term
thinking, low interest from citizens…
 But it changes the power relationships, the incentives
and the barriers to entry

SPAM, CONFLICTS AND TROLLING

High relevance

Recommended for
short term

Recommended for
long term

Low relevance

Typical gov initiative

Typical internetfocus

Low conflict

High conflict
HOW
LESSONS LEARNT








“There are more smart people outside government than
within it” (Bill Joy)
“A problem shared is a problem halved ...and a pressure
group created” (Paul Hodgkin – PatientOpinion.com)
“it’s about pressure points, chinks in the armour where
improvements might be possible, whether with the
consent of government or not” (Tom
Steinberg, Mysociety.org)
“many participants in the process dilute the effect of bad
apples or unconstructive participants” (Beth
Noveck, Peertopatent.org)
2
THE 7 STEPS TO SUCCESS!
http://daeimplementation.eu/

THE GAMIFICATION OF POLICY MAKING


Feedback + Friends + Fun
http://daa.ec.europa.eu/gro
up/2/content

IT’S NOT JUST “ TWO-WAY” CONVERSATION


Many-to-many drives participation and action
http://daa.ec.europa.eu/content/
special/crowdsourcing

IT’S NOT ABOUT DIRECT DEMOCRACY


It’s about letting good ideas emerge and bad ideas be
revealed
http://daa.ec.europa.eu/content/speci
al/towards-european-strategy-webentrepreneurs

IT’S NOT ABOUT “ TOTAL OPENNESS NOW”


A continuous trend: opening up earlier, and at more granular level
IT’S NOT ABOUT “ TOTAL CITIZENS”


Not representative but insightful
A REALITY CHECK: EVALUATING THE IMPACT OF
POLICY 2.0
CRITERIA
 Number of participants
 Involvement of decision makers
 Actual usage of the output in policy-making
 Media impact
 Feedback by policy-makers
 Actual improvement of policy quality
FINAL RECOMMENDATIONS
Do no harm
 Enable
 Experiment
 Manage expectations
 Track and evaluate

PRACTICE
TOOLS
Sentiment analysis (sentiment viz)
 Commentable documents (commentneelie.eu)
 Ideastorms (uservoice)
 Crowdsourcing (challenge.gov)
 Visualisation (openspending)
 Mapping (ushahidi)
 Open data (FP7 recipients)




Delivery model: custom vs off the shelf, installed vs as a
service; open source vs proprietary
DESIGN TOOLS
Friend (using social networks and peer pressure)
 Feedback (seeing the impact of your action immediately):
daa.ec.europa.eu
 Competition (light but deep): challenge.gov
 Moderation (ex-post vs ex-ante): patientopinion
 Identity (anonimity?) : evasori.info
 Reputation : DAA “interesting” daa.ec.europa.eu
 Rules (transparency about what is accepted and what is
not; how will the outcome be used) : Italy Digital Agenda
 Reach-out to the community : sicamp.org




For both government and citizens!
CASES


https://www.diigo.com/user/osimod/citylabodessa

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SmartCity David Osimo

  • 1. Policy 2.0: theory and practice MUNICIPAL INNOVATION LAB David Osimo Director – Open Evidence #citylabodessa 16/10/2013
  • 2. TODAY’S TALK  Theory of policy 2.0 What  Why  How   Practices of policy 2.0 Technologies  Design  Examples 
  • 4. THE CHALLENGES OF GOVERNANCE     Detect and understand problems before they become unsolvable” Involve open intelligence in policy-making, and extract “good ideas” from it From words to action: ensure implementation and actual behavioural change Reducetime-to-impact evaluation  All this, dealing with a distributed governance model. The traditional division of “market” and “state” no longer fits a reality where public decision and action is effectively carried out by a plurality of actors.
  • 5. A VISION: A THIRD WAY OF POLICY MAKING? + Emergent + Open + Peer2peer + Unexpected + Expert based decisions + Robust + Relevant Direct Democracy Technocracy - Social media - Populism - Unstructured discussion - Loudest voice - Black box - Closed models - Reductionism
  • 6. A VISION: A THIRD WAY OF POLICY MAKING? Policy-making 2.0: Open and evidence based + Emergent + Open + Peer2peer + Unexpected + Expert based decisions + Robust + Relevant Direct Democracy Technocracy - Social media - Populism - Unstructured discussion - Loudest voice - Black box - Closed models - Reductionism
  • 7. COVERING THE FULL POLICY CYCLE: IT’S NOT ABOUT CROWDSOURCING DECISIONS
  • 8. ANTICIPATING THE UNEXPECTED: BIG AND OPEN DATA
  • 9. POLICY DESIGN: SMART CROWDSOURCING
  • 11. TURNING POLICY IN IMPACT: APPS FOR BEHAVIOURAL CHANGE
  • 12. SENSE MAKING IN EVALUATION THROUGH OPEN DATA
  • 13. WEB 2.0 IS ABOUT VALUES, NOT TECHNOLOGY User as producer, Collective intelligence, Long tail, Perpetual beta, Extreme ease of use Values Blog, Wiki, Podcast, RSS, Tagging, Social Applications networks, Search engine, MPOGames Technologies Ajax, XML, Open API, Microformats, REST, Flash/Flex, Peer-to-Peer Source: Author’s elaboration based on Forrester 13
  • 14. A NEW WAY TO DO PUBLIC INNOVATION Innovation without permission  Fast development (weekend)  Perpetual beta  Planning for emergence  Government not only a player but a platform 
  • 15. DIFFERENT TYPES OF CITIZEN/GOV COLLABORATION Data Services Gov Citizens Gov Intrapreneurship Crowdsourcing Citizens Open Data apps Self-help
  • 17. BEYOND ARTIFICIAL OPPOSITIONS Planning, Top down Kublai, Rewired State, The Hub, Social Innovation Camp, Appsfordemocracy, …. #CitylabOdessa Emergent, bottom-up 1
  • 18. WHY
  • 19. 6 THINGS CITIZENS CAN OFFER Software development skills (OpenCamera)  Specific technical knowledge (PeerToPatent)  Experience of using public services (PatientOpinion)  Trust of other citizens (ActiveMobs)  Capillar coverage of the territory (Fixmystreet)  “Many eyes” (openspending) 
  • 20. REMINDER: CITIZENS AND EMPLOYEES DO IT ANYWAY 2
  • 21. POLICY TOOLS RELEVANT FOR POLICY CHALLENGES
  • 22. LET’S TAKE A LOOK AT THE DARK SIDE
  • 23. DESIGN FOR BART NOT FOR LISA! Hat tip: Carter and Dance, Nytimes.com 2
  • 24. NON-TECH BARRIERS Learning lessons from 20 years of technology adoption in government: bottlenecks are cultural and organisational, not technological  Technology will not suddenly free policy-making from politicking, corruption, personal interests, short term thinking, low interest from citizens…  But it changes the power relationships, the incentives and the barriers to entry 
  • 25. SPAM, CONFLICTS AND TROLLING High relevance Recommended for short term Recommended for long term Low relevance Typical gov initiative Typical internetfocus Low conflict High conflict
  • 26. HOW
  • 27. LESSONS LEARNT     “There are more smart people outside government than within it” (Bill Joy) “A problem shared is a problem halved ...and a pressure group created” (Paul Hodgkin – PatientOpinion.com) “it’s about pressure points, chinks in the armour where improvements might be possible, whether with the consent of government or not” (Tom Steinberg, Mysociety.org) “many participants in the process dilute the effect of bad apples or unconstructive participants” (Beth Noveck, Peertopatent.org) 2
  • 28. THE 7 STEPS TO SUCCESS!
  • 29. http://daeimplementation.eu/ THE GAMIFICATION OF POLICY MAKING  Feedback + Friends + Fun
  • 30. http://daa.ec.europa.eu/gro up/2/content IT’S NOT JUST “ TWO-WAY” CONVERSATION  Many-to-many drives participation and action
  • 31. http://daa.ec.europa.eu/content/ special/crowdsourcing IT’S NOT ABOUT DIRECT DEMOCRACY  It’s about letting good ideas emerge and bad ideas be revealed
  • 32. http://daa.ec.europa.eu/content/speci al/towards-european-strategy-webentrepreneurs IT’S NOT ABOUT “ TOTAL OPENNESS NOW”  A continuous trend: opening up earlier, and at more granular level
  • 33. IT’S NOT ABOUT “ TOTAL CITIZENS”  Not representative but insightful
  • 34. A REALITY CHECK: EVALUATING THE IMPACT OF POLICY 2.0 CRITERIA  Number of participants  Involvement of decision makers  Actual usage of the output in policy-making  Media impact  Feedback by policy-makers  Actual improvement of policy quality
  • 35. FINAL RECOMMENDATIONS Do no harm  Enable  Experiment  Manage expectations  Track and evaluate 
  • 37. TOOLS Sentiment analysis (sentiment viz)  Commentable documents (commentneelie.eu)  Ideastorms (uservoice)  Crowdsourcing (challenge.gov)  Visualisation (openspending)  Mapping (ushahidi)  Open data (FP7 recipients)   Delivery model: custom vs off the shelf, installed vs as a service; open source vs proprietary
  • 38. DESIGN TOOLS Friend (using social networks and peer pressure)  Feedback (seeing the impact of your action immediately): daa.ec.europa.eu  Competition (light but deep): challenge.gov  Moderation (ex-post vs ex-ante): patientopinion  Identity (anonimity?) : evasori.info  Reputation : DAA “interesting” daa.ec.europa.eu  Rules (transparency about what is accepted and what is not; how will the outcome be used) : Italy Digital Agenda  Reach-out to the community : sicamp.org   For both government and citizens!

Editor's Notes

  1. More dataVisual simulationIterative process with policy-makers