Mass online deliberation 20x20 presentation for budapest

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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)

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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 DeliberationAuthors: Pietro Speroni di Fenizio, Alois, Paulin, Cyril VelikanovIf 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.

Transcript of Mass online deliberation 20x20 presentation for budapest

Page 1: Mass online deliberation 20x20 presentation for budapest

PROCEDURAL & ALGORITHMIC ASPECTS

OF MASS ONLINE DELIBERATIONAn 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)

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Mass online deliberation: the context

Agenda-setting

Problem or question

MASS ONLINE DELIBERATION

SYSTEM

Citizens

Govern-ment

Experts

Solution(s) or answer

(s)

Probably, also other stakeholders

Parliament Regional Council

Citizens, or other stakeholders

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Deliberation system type will depend on:Number of ParticipantsNumber of ParticipantsNumber of ParticipantsNumber of Participants

<12 10-150 150-1000 >1000

What are we looking

for

One Answer(How should we do this?)

What are we looking

for

Multiple Answers

(What should we do about

this?)

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MOD: Citizens’ Actions

MASS ONLINE DELIBERATION

SYSTEM

Citizens

ProposingCommenting Voting

Modifying Appraising

Manyto

Many

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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

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MOD Principles: Scalability

MOD Principles: Informed opinion

Uninformed opinion is of little value. Information should come from independent sources. Experts (academics?) should provide data, but not opinions

The deliberation process should be able to host thousands of contributors

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MOD Principles: Economy of efforts

MOD Principles: Robustness

We value deliberative actions of well-intentioned citizens.So we must protect them from concerted disruptive actions (“mob attacks”)

Participation should be possible to everyone at leisure time – not as a full-time occupation.

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

Moderation Unmoderated

Self- moderated

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• 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”

Problems related to self-moderation

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• Attention limit: Out of a very large “heap” of proposals or opinions, everybody will read just a few ones

• Minority voices:If the whole “heap” is presented as one ranked list, only the most supported voices will be heard

OUR SOLUTION: Random appraisal of proposals, and then clustering them according to whether they are supported mainly by the same participants

Main problem of MOD: Making sure all are heard

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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:

quality:

“how well it is explained?”ag

reemen

t:

“do I a

gree w

ith it?

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Quality

Rankingbetween proposals

Agreement

Clusteringbird’s-eye view:

“best” contributions for each cluster

quality

agree

ment

Aggregating Several Appraisals

Closenessbetweenproposals

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Citizens&

Stakeholders

Proposals

Clusters

?ProposalsProposalsProposalsProposalsProposals

Experts

Appraising

ClustersClusters

Writing

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MOD: authorship vs. confidentiality

SOLUTION: Unique registration under user-selected pseudonym with digital signature

• Confidentiality: Though, many participants would like not to disclose their real names.

• Rewarding participants: Many participants would like to be rewarded for their efforts and for their time spent in deliberation; authors would like to have proofs of their authorship.

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Collaboration within online deliberation

Deliberation should comprise collaboration, otherwise it will remain fruitless.

This raises several issues:

SOLUTION: Several workgroups in parallel; every workgroup is self-governed according to one of a choice of policies

• Authorship: Who should be considered the author of a collaborative proposal?

• What incentives should be provided to convince authors to collaborate?

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Collaborative Working Groups of two types:1.Clarity seeking WG:

Working Group with only people that agree with the proposals inside a cluster, with the aim to edit a single proposal that represents the whole cluster

2.Integration seeking WG: WG with people from different clusters, trying to integrate different ideas from those clusters, with the aim to elaborate a final proposal

3. Among the proposals written by each i-WG, a ranking is established using Condorcet Voting

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Cluster Cluster Cluster

IntegrationWG

IntegrationWG

IntegrationWG

Clarity WG Clarity WG Clarity WG

Final Proposals

VOTING

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Citizens&

Stake-holders

Proposals

Clusters

?ProposalsProposalsProposalsProposalsProposals

Experts

EvaluationsClarity WG

ClustersClarity WG

ClustersClarity WG

Integration WGIntegration WGIntegration WGFinal

ProposalsFinal

Proposals

WG participation

Votin

g

Writing

Ranked Results

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1919

Realisation: MOD Cloud(engine + storage)

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2020

MOD Cloud(engine + storage)

API

http://…

Realisation: Multiple Equivalent MOD Clients