This talk was presented at the FET 11 presentation. It was not recorded there, so it has been re-recorded to present it on the internet. Mass Online deliberation, how to make it happen. Alternative Title: Procedural And Algorithmic Aspects of Mass Online Deliberation Authors: Pietro Speroni di Fenizio, Alois, Paulin, Cyril Velikanov If a really topical and controversial problem is proposed for public deliberation, and there are solid expectations that the results of deliberation will be at least influential if not decisive - then we can expect that really many citizens (thousands, tens of thousands...) will consider it worthwhile to join an open online deliberation over that issue, and will actively participate in it. However, such a mass online deliberation (MOD) raises several problems, related to how a very large number of users' one-to-many interactions can be coordinated and aggregated. These problems can only be solved by using a carefully designed MOD support system (MOD-SS). We analyse those problems and propose our solution to them, based on the principles of fairness and self-moderation, and using a special kind of two-parameter evaluation of participants' proposals. This makes it possible for the support system to cluster proposals according to how similar they are perceived by other participants. Our system will be implemented as a server cloud application with an open API and several alternative client applications for different use-cases.

1. PROCEDURAL & ALGORITHMIC
ASPECTS
OF MASS ONLINE DELIBERATION
An R&D project by
Pietro Speroni di Fenizio
(Coimbra University, Portugal)
Alois Paulin
(Faculty of IS, Novo Mesto, Slovenia)
Cyril Velikanov
(Memorial Society, Moscow, Russia, &
Fondation Euractiv/Politech, Brussels)

2. Mass online deliberation: the context
Govern-
ment
Parliament Regional Council
Agenda-setting Citizens, or other
stakeholders
Solution(s)
Problem or
or answer
question
(s)
MASS ONLINE
DELIBERATION
SYSTEM
Probably, also
Experts Citizens other stakeholders

3. Deliberation system type will depend
on:
Number of Participants
<12 10-150 150-1000 >1000
One Answer
(How should
we do this?)
What
are we Multiple
looking Answers
for (What should
we do about
this?)

4. MOD: Citizens’ Actions
Many
MASS ONLINE
to
DELIBERATION Many
SYSTEM
Proposing
Commenting Voting
Modifying Appraising
Citizens

5. MOD Principles: Fairness
Every proposal should be appraised by
the deliberating community according to
its intrinsic value,
regardless of:
- author’s personality
- friends’ support
- submittal time
- etc

6. MOD Principles: Scalability
The deliberation process should be
able to host thousands of contributors
MOD Principles: Informed opinion
Uninformed opinion is of little
value.
Information should come from
independent sources.
Experts (academics?) should
provide data, but not opinions

7. MOD Principles: Economy of efforts
Participation should be possible to everyone
at leisure time – not as a full-time occupation.
MOD Principles: Robustness
We value deliberative actions
of well-intentioned citizens.
So we must protect them from
concerted disruptive actions
(“mob attacks”)

8. MOD Principles: No External Moderation
The system should be self-moderated by
participants’ own actions, with no need for
external agents that can bias the result.
Self-
moderated
Moderation Unmoderated

9. Problems related to self-moderation
• Endless ramification of the
discussions: as in an
ordinary online forum
• Trolling: Open discussion on a
topical issue is prone to all kinds of
concerted disruptive actions (“mob
attacks”)
• Claque voting: A proposal
can easily win if its author is
supported by his/her many
“online friends”

10. Main problem of MOD: Making sure all are
heard
• Attention limit: • Minority voices:
Out of a very large If the whole “heap” is
“heap” of proposals presented as one
or opinions, ranked list, only the
everybody will read most supported voices
just a few ones will be heard
OUR SOLUTION: Random
appraisal of proposals,
and then clustering them
according to whether they
are supported mainly by
the same participants 10

11. Our solution: random two-parameter appraisal
• Initial appraisal: Every participant’s
contribution is first sent to few randomly
selected participants (a “peer review”)
• Two-parameter appraisal:
“h
ow
w
”
qu t is
w t:
it?
el
ee en
al ex
li
ith
gr m
ity pl
I a ree
: ain
ag
ed
o
“d
?”

12. Aggregating Several Appraisals
Quality Agreement
Ranking
t
Closeness
en
between qu
em
proposals al between
ity proposals
re
ag
bird’s-eye view:
“best” contributions Clustering
for each cluster

13. Proposals Experts
?
Proposals
Proposals
Proposals
Proposals
Proposals Writin
g
Citizens
&
Stakehold
Appraising
ers
Clusters
Clusters
Clusters

14. MOD: authorship vs. confidentiality
• Rewarding participants: • Confidentiality:
Many participants would Though, many
like to be rewarded for participants would
their efforts and for their like not to disclose
time spent in deliberation; their real names.
authors would like to have
proofs of their authorship.
SOLUTION: Unique registration under user-
selected pseudonym with digital signature

15. Collaboration within online deliberation
Deliberation should comprise
collaboration, otherwise it
will remain fruitless.
This raises several issues:
• Authorship: Who should be considered
the author of a collaborative proposal?
• What incentives should be provided to
convince authors to collaborate?
SOLUTION: Several workgroups in parallel;
every workgroup is self-governed according
to one of a choice of policies

16. Collaborative Working Groups of two types:
1.Clarity seeking WG: 2.Integration seeking
Working Group with WG: WG with people
only people that agree from different
with the proposals clusters, trying to
inside a cluster, with integrate different
the aim to edit a single ideas from those
proposal that clusters, with the aim
represents the whole to elaborate a final
cluster proposal
3. Among the proposals written by each i-WG, a
ranking is established using Condorcet Voting

17. Clarity WG Clarity WG Clarity WG
Cluster Cluster Cluster
Integration Integration Integration
WG WG WG
Final Proposals
VOTING

18. Proposals Experts
?
Proposals
Proposals
Proposals
Proposals
Proposals
Writin
g
Citizens
&
Stake-
Evaluations
holders
Clarity WG
Clarity WG
Clusters
Clarity WG
Clusters ation
Clusters p artici
p
WG
ng
Voti
Final
Final Ranked
Integration WG
Integration WG
Integration WG Proposals
Proposals Results

19. Realisation: MOD Cloud
(engine + storage)
19

20. Realisation: Multiple Equivalent MOD Clients
MOD Cloud
(engine + storage)
API
http://…
20