Policy Compass at eChallenges 2014

Session 4d, 29 October 2014 eChallenges e-2014 Copyright 2014 - Policy Compass

Towards more factual, evidence-based, transparent and accountable policy evaluation and analysis:

The Policy Compass approach

Dr. Sotiris Koussouris

DSSlab – NTUA

Greece


The Problems1. Internet has evolved into a rich

source for information but also to an instrument of spreading misinformation and propaganda

2. Lack of consensus about a suitable metric for measuring progress

3. Difficulty of objectively assessing the impacts of government policies

The Proposed ApproachI. Open Public Data

II. Prosperity Indicators

III. Fuzzy Cognitive Maps

IV. Argumentation Technology

V. Deliberation Platforms and Social Media

Improve the quality and transparency of the policy

analysis and evaluation phases of the policy cycle for a variety of stakeholders, ranging from

citizens to policy makers

Policy cycle

Analysis

Implementation/Monitoring

Problem, Motivation and Approach


The Policy Compass Approach

• A research prototype of an easy-to-use, highly visual and intuitive tool for:– Constructing prosperity and other policy metrics with an easy-to-use

visual language for defining variables and functions over open data sources.

– Constructing graphs and charts visualizing metrics for selected geographical regions and time periods.

– Annotating graphs and charts with political or policy events.– Building causal models with an easy-to-use visual tool for Fuzzy Cognitive

Maps (FCM).– Sharing and debating prosperity graphs and FCM across popular social

media platforms.– Summarizing and visualizing the debates in argument maps and

conducting structured surveys about policy issues– Aggregating opinions on policy issues, to formulate a common position in a

party or interest group.


Pillar I: Prosperity Indexes

• Prosperity metrics capture the level of welfare and quality of life in a given region or society.

• Prosperity is a vague and subjective concept with essential psychological, social and economic aspects.

• There is no consensus about how to objectively measure prosperity• Indicators of economic growth:

– Gross Domestic Product (GDP)– Genuine Progress Index (GPI)

– Index of Sustainable Economic Welfare (ISEW)– GINI Index

• Alternatives:– Human Development Index (HDI)– Legatum Prosperity Index– “Healthy life years statistics” by Eurostat


Pillar II: Open Public Data

• Open and unrestricted access to large scale data sets is essential for political engagement and scientific research

• Available large scale data sets have nowadays their own self-contained existence rules.

• Micro-data can be used to construct new indicators of multifaceted nature.

• Sources of micro-data:– Eurobarometer surveys– European Union Statistics on Income and Living Conditions (EU-SILC) by

Eurostat

– Urban Audit (the European cities Eurostat)


Pillar III: Fuzzy Cognitive Maps

• A well-founded, general-purpose and intuitive method for modelling and simulating relationships between variables.

• Introduced by B. Kosko (1986) as a fuzzified version of Cognitive Maps, originally introduced by political scientist R. Axelrod (1976).

• A fuzzy directed graph of nodes and edges, where nodes represent fuzzy concepts, describing behavioral characteristics of a system that occur to some degree, and directed edges represent the causal relationships among these concepts.

• The graph edges are weighted by a real value from the interval [-1, 1], which expresses the strength of the relation between two concepts.

• FCMs have been widely used to model and simulate policies and their effects.


Pillar IV: Argumentation Technology

• Argumentation support systems are computer software for helping people participate in various kinds of goal-directed dialogues in which arguments are exchanged.

• The idea of using argumentation support systems for eParticipation can be traced back at least to Horst Rittel’s pioneering work in the early 1970s who used visual maps of arguments, to help people collaborate and find solutions to what he called “wicked problems”.

• “Wicked problems” have no algorithmic, scientific or objectively optimal solutions for a variety of reasons, including the lack of consensus among stakeholders about utilities and values.

• Typically, eParticipation projects make use of generic groupware systems (e.g. discussion fora, online surveys, etc.) not providing though specific technical support for argumentation.


Pillar V: Deliberation Platforms and Social Media

• Deliberation platforms incarnate the efforts taken by government agencies, to increase citizens’ engagement in their decision and policy making processes.

• The first wave of deliberation platforms has witnessed extensive information on government activities, decisions, plans and policies, the proliferation of e-voting and e-consultation spaces, along with various types of e-fora.

• Still, the first generation of deliberation platforms did not meet the original expectations.

• The advent of Web 2.0 tools has created a more vivid environment and the popularity of the social media has set a new battlefield for the concept of e-Participation.


Policy Compass Pillars’ Relations

Pillar I: Prosperity

Indexes



Pillar IV: Argumentation

Pillar V: Deliberation Platforms & Social Media

Pillar I: Prosperity

Indexes



Pillar IV: Argumentation

Pillar V: Deliberation Platforms & Social Media

Define higher level metrics

from lower level ones

Define higher level metrics

from lower level ones

Construct metrics by

operationalizing open data

sources

Use historical events to

annotate metric visualizations

Access open data sources,

Publish data sets & their metadata

Access open data sources,

Publish data sets & their metadata

Develop ideas on the correlations

among policies and prosperity

fluctuations

Simulate causal policy models based on open

data sets

Debate on prosperity

metrics

Reuse argumentation

outcomes as structured open

data

Share own developed prosperity

metrics

Predict the evolution of prosperity

indicators by applying causal policy models

Use historical data to validate

causal policy models

Use open public data to bolster one’s opinion

Develop and apply own causal

policy models

Develop and apply own causal

policy models

Define the strength of correlations

according to the opinions

expressed

Debate on causal models

underlying policies

Summarize and visualize debates

in argument maps

Summarize and visualize debates

in argument maps

Share own developed causal

policy models

Poll public opinion on policy

issues

Define prosperity metrics

collectively

Define policy impact models

collectively

Aggregate poll outcomes to formulate a

common position

Ensure citizens’ wide

participation

Ensure citizens’ wide

participation

Weigh prosperity aspects

according to the opinions

expressed


Use Case Walkthrough


Discussion and Conclusions

• A framework for empowering citizens and policy makers to better assess government policies.

• Benefits of the approach:

• Assessment and validation in real case pilots (UK and Russia).

• Are user-generated metrics trustworthy?• How is prosperity measured?• Can prosperity be measured in the same way for all?• …..?

Decision makers:• Visualize the effects of their politics• Stimulate public debate• Communicate policy outcomes to

citizens clearer• Build confidence in progress

towards societal goals

Citizens:• Engage in the development of

prosperity indices• Monitor and critically discuss the

quality of public policies• Learn about the multiple

dimensions and social and economic consequences of policies

• Improve the objectivity and evidential basis of their arguments


Thank you

Dr. Sotiris Koussouris

[email protected]

DSSLab - NTUA

Policy Compass received funding from the European Union’s Seventh Framework Programme for research, technological development and demonstration

Science

Policy Compass at eChallenges 2014