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


3. WHAT

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
Reduce time-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

10. POLICY OPTIONS SIMULATION
UrbanSIM case

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
Gov Intrapreneurship
Citizens
Open Data apps
Citizens
Crowdsourcing
Self-help

16. WHAT IS DIFFERENT?

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 internet focus
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/gr
oup/2/content
IT’S NOT JUST “ TWO-WAY” CONVERSATION

Many-to-many drives participation and action

31. http://daa.ec.europa.eu/conten
t/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/spec
ial/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


36. PRACTICE

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!

39. CASES

https://www.diigo.com/user/osimod/citylabodessa