Welcome Ladies and Gentlemen.

My talk today is in two parts. First I want to talk about the challenges we face in

working at the evidence/policy interface.

Then I want to share with you some initiatives, we at the European Commission's

science and knowledge service - the JRC, are taking in addressing these

challenges.

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Those of us working at the evidence – policy interface are confronted with 3 types

of complexity:

• Complexity of knowledge

• Complexity of political problems – wicked problems

• Complexity of the relationship between evidence and policy

Complexity is the meta-problem of our age.

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Super-abundance of knowledge

There is a good news and bad news. The good news is that we have never

known so much about ourselves, our planet and our society.

According to the University of Ottawa, in 2009 we passed the 50 million

mark in terms of the total number of science papers published since 1665,

and approximately 2.5-3.0 million new scientific papers are published each

year. As of 2014 there were approximately 28,100 active scholarly peer-

reviewed journals.

This super abundance is also a curse. As William Davies said (2016): "The

problem is the oversupply of facts in the 21st century: There are too many

sources, too many methods, with varying levels of credibility, depending on

who funded a given study and how the eye-catching number was selected."

Note: William Davies - author of the "The Happiness Industry" and The New

York Times contributor.

https://www.nytimes.com/2016/08/24/opinion/campaign-stops/the-age-of-

post-truth-politics.html?_r=0

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Science complexity

We don’t just have a lot of science, it also is not well connected. This map of

science shows connections not in terms of citations but one billion clicks

between 2007-2008 on science web-sites.

There is some good news here – social sciences and humanities are more

closely linked to other sciences than previously thought based on citations.

But still we can see that there are not enough connections.

Policymakers need inter-disciplinary science. And without common

languages and strong connections this won't happen.

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Policymaking is becoming more complex as policy problems take on more wicked

characteristics.

Problems no longer arrive in neat department of ministry-shaped boxes. Almost any

given issue calls for coordination with policymakers from different fields and levels:

local, regional, national, international. More and more departments need to be

involved.

Hyper-complexity in science and policy is grwoing.

Is this the real source of post-fact politics and a return to simple heuristics based on

emotions?

Source of image: http://www.economplex.org/complexity-science/complex-vs-

complicated/, Jake David / 29 December 2010

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We may think governments want more information but this may not be the

case.

“There is nothing a government hates more than to be well-informed; for it

makes the process of arriving at decisions much more complicated and

difficult.” - John Maynard Keynes, The Times (March 11, 1937); Collected

Writings, vol. 21, p. 409

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Post-fact politics

The relationship between science and policymaking is also clearly not linear or is

one direction.

Political disagreements can blow back into the debate on the facts.

As this cartoon dates from 1977, there is no box for "alternative facts".

Filing cabinets labelled, "Our Facts" "Their Facts" "Neutral Facts" "Disput… - New

Yorker Cartoon, Dana Fradon, First published 7 March 1977

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So why is the relationship between evidence and policy so complex?

The last 40 years have now begun to give us a picture of human cognitive

biases .

This codex attempts to summarise the wikipedia page on cognitive biases.

It should not be a surprise to us to find that some biases are present among

all the actors at the evidence/policy interface.

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It's easy for scientists to see biases among policymakers. British politician,

Lord Molson (1903-1991), appears to capture the stereotype : "I will look at

any additional evidence to confirm the opinion to which I have already

come."

Note: No specific year of attribution of the quote found.

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But no one is immune as, as Francis Bacon, recognised in 1620.

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There are bias traps for those working at the science side of the evidence/policy

interface as well. So how do we deal with this?

Albert Einstein is often quoted as having said ‘not everything that can be counted

counts, and not everything that counts can be counted’.

The quote actually comes from sociologist William Cameron, who wrote in 1963: It

would be nice if all of the data which sociologists require could be enumerated

because then we could run them through IBM machines and draw charts as the

economists do.

However, not everything that can be counted counts, and not everything that

counts can be counted.

(Cameron 1963, “Informal Sociology: A Casual Introduction to Sociological

Thinking”, p. 13)

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So how do we tackle these three forms of complexity.

E.O. Wilson came closest to summarising how to do this.

Harvard biologist E.O. Wilson, in his 1998 book Consilience: The Unity of

Knowledge

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Theory of change // Beyond the deficit model

So, if we are to influence policymakers through science, we need to abandon the

linear, mechanical deficit model and move towards a model, which recognises the

emergent properties of the evidence interface with policy.

This is similar to Sheila Jasanoff's Two Models of Objectivity, where one moves

from isolated pure sciences model towards one of the interference.

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What does this mean in practice ?

We need "epistemic communities" built around policy problems that bring

together both science and policy actors, different scientific disciplines and

different policies that are open and transparent to stakeholders and the

public.

To make these communities work, we need knowledge brokers or managers

at the heart to convene the interested parties and organise discussion and

debate.

There is as much knowledge to be managed on the policy/demand side as

there is on the science/supply side.

Only through these communities can you synthesise all the available

knowledge to identify what is useful for policy. This means more than simple

quality control.

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The vision

So how are we in the JRC trying to make this work? Our new vision makes clear

that we are moving beyond knowledge production to include management and

sense-making.

We now have dedicated KM teams.

We are in the fortunate position of being a research institute inside the executive

arm of the EU, able to participate in policymaking discussions. We have +2000

scientists and we cover many scientific disciplines + support almost all EU policies.

This gives us the role to connect disciplines and policies and talk directly to

policymakers.

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And in specific policy areas we are building mere "epistemic communities" where

policymakers and scientists from different disciplines and policies can work

together to share knowledge and identify common issues.

The Disaster Risk Management Knowledge Centre (DRMKC) aims at enhancing

the EU and Member States resilience to disasters and their capacity to prevent,

prepare and respond to emergencies through a strengthened interface between

science and policy.

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The Knowledge Centre on Migration and Demography (KCMD) aims to be the point

of reference to support the work of Commission services and Member States on

migration and related issues.

Building upon the existing Migration Data Catalogue, we are developing a Dynamic

Data Hub, a web-based application that gives through interactive mapping direct

access to single datasets. As such, the hub helps to communicate knowledge to

the public at large on migration flows to Europe, related trends and impacts.

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The European Union consists of almost 300 diverse regions. The Knowledge

Centre for Territorial Policies aims to gather, manage and make sense of the

vast amount of socio-economic and bio-phusical data available on European cities

and regions.

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Our competence centres are similar epistemic communities organised

around specific evidence for policy tools rather than policies.

Competence Centre on Composite Indicators and Scoreboards

The JRC-COIN is renowned for its expertise on statistical methodologies

and technical guidelines on the development of sound composite indicators,

which can be used in making informed policy decisions.

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Competence Centre on Microeconomic Evaluation

This centre will be a network bringing together relevant policy and scientific

expertise from across the Commission, and external experts from around

the world, to perform impact evaluations. It aims to enhance the EU policy

process through ex-post causal evaluation and data-driven microeconomic

analysis.

Competence Centre on Text Mining and Analysis – TIM, launched 13

December 2016

Modelling and data mining – to be launched in 2017

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We have also realised that we need to re-think the policy conception process if we

are to help policy be both more innovative and better informed.

The EU Policy Lab is a collaborative and experimental space for innovative policy-

making. It is both a physical space and a way of working that combines

foresight, behavioural insights and design thinking to explore, connect and

find solutions for better policies.

Here you can see an example of one of our serious games. If you want to learn

more, you can learn about it at Stand 201.

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The policy process inside the Commission has also been designed to take

account of evidence. The OECD recently praised the Commission's

Integrated Impact Assessment process, which scrutinises the evidence

basis for EU law. It is underpinned by a Regulatory Scrutiny Board, which,

since 2016, has independent members from outside the Commission.

The Regulatory Scrutiny Board (RSB) is part of the Better Regulation eco-

system. It will assess all impact assessments and all major evaluations and

Fitness Checks. The Board issues opinions based on the requirements of

these guidelines. DGs are expected to modify their reports to reflect the

Board's opinion.

Chair: Anne Bucher(162 kB), Members: Nils Bjoerksten(207 kB), Didier

Herbert(239 kB) , Vassili Lelakis(117 kB) , Bernard Naudts(55 kB) , Isabelle

Schömann

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It is clear that this ambitious new agenda calls for Scientists and Policymakers to

have new skills: secondary research (research synthesis, quality control),

community management and facilitation, citizen/society/stakeholder engagement

(social media), advocacy skills (for evidence, not interests), visualisation,

communication of risks/uncertainty.

Last year we held a Summer School on evidence for policy for 100 Scientists

and policymakers from 45 countries.

As well as training our own scientists we will continue these events. If you are

interested in the practical skills and training, which scientists need to operate

effectively at this interface, we'd love to hear from you.

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Not everyone supports evidence-informed policy.

But there are quite a lot of people who do argue for it.

We've mapped this Community - and it's impressive!

Is your organisation here?

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JRC Community of practices

If you want to join this community, join our online Community of Practice. We have

an online presence with some resources and a place to share your news and

events.

Who: For those operating at the interface between evidence and policy

What: A dedicated community page on evidence for policy, bibliography of relevant

papers and useful links, events, concepts and practices on evidence for policy,

thematic twitter feed wall

Why: Connect with colleagues, share expertise, understand the politics of

evidence, comment on publications, read how to write a policy brief, announce your

event/training/activity

Where: Find our more and register here - QR code/mobile tag

Through this Community of Practice, JRC aims to gather thinkers and practitioners

focused on evidence-informed policymaking, in order to exchange our collective

expertise and experience in this complex field. We aim to link conceptual debates

on science, policy and their interconnections with practical approaches on how to

stimulate the demand for evidence and train people providing and receiving it for

the sake of better policies. By joining this community, you gain access to a one-

stop shop for everything related to evidence-informed policymaking. Explore – and

contribute to – our forum, news and events sections. Our library provides useful

resources to better prepare oneself for the challenges of this field.

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I wanted to finish with two slides setting out where we need to go next.

We desperately need to understand better how evidence is used in decisions taken

by policymakers on an empirical basis.

We are now beginning to see some interesting research on how the brain

processes facts, which contradict prior beliefs.

The study shows that it's easy to change certain beliefs but not the deepest political

convictions.

Other research suggests that there is a backfire effect that contradicting facts

actually entrench beliefs.

We need more research from the behavioural sciences applied in policy-making.

Does evidence change people’s behaviour? Figure shows the relationship between

belief change and brain activity.

From: Neural correlates of maintaining one’s political beliefs in the face of

counterevidence, Jonas T. Kaplan, Sarah I. Gimbel, Nature 2016

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We can't wait for this research to already change how we operate at the interface of

science-policy.

We need to explore the use of framing, mental models, narratives and emotions.

This is going to be hard, because we need to keep our commitment to the

objectivity of the evidence, but we can do both.

The Nobel Prize in Physics 1965 speech quote by Richard P. Feynman.

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Quote from The Objectivist Ethics, a paper delivered by Ayn Rand at the University

of Wisconsin Symposium on “Ethics in Our Time” in Madison, Wisconsin, on

February 9, 1961

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