In November 2021 we established a Collective Intelligence Lab (CILab), with the aim of improving policy outcomes by tapping into collective intelligence (CI). We define CI as the diversity of thought and experience that is distributed across groups of people, from public servants and domain experts to members of the public.
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(highlight:: Building on our initial experiments in partnership with Demos, we have adapted our approach to using Pol.is in three ways by:

1. convening a panel to moderate submitted statements to avoid duplicative or inappropriate content (this could include members of the policy team we are partnering with)
2. collecting demographic data when participants register for a debate, if they consent. This allows us to further analyse the opinion groups generated by Pol.is to interrogate what people in a particular region, organisation or job role, for example, think about particular topics - whilst participants remain anonymous
3. using Pol.is data to derive detailed personas for the opinion groups, or to draw policy implications that emerge from the discussion, depending on the policy team’s research focus)
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CI could be used to gauge expert and public sentiment towards existing policy ideas by asking participants to discuss existing policies and current thinking on Pol.is. This is well suited to testing public and expert opinions on current policy proposals, especially where their success depends on securing buy-in and action from stakeholders. It can also help collate views and identify barriers to effective implementation of existing policy.
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(highlight:: Because tools such as Pol.is are well-suited to showing where groups of people agree, CI could be used to test where different policy options lie within the Overton Window - defined as the range of interventions that mainstream opinion considers politically acceptable. This could enable policymakers to:

1. understand the extent to which people support different potential policy approaches. By inviting policymakers, experts and members of the public to debate a range of future policies on complex problems, we could better understand which interventions enjoy the most support, and which are least supported. As an example, independent newspaper Scoop.nz took a similar approach to exploring possible ways to reduce obesity in New Zealand. This would be especially useful when using Polis as part of a competitive or crowdsourcing approach to solving public problems, as described by Nesta and the United Nations Development Programme here
2. discover how stakeholder groups such as local government, service providers and communities might respond to proposed new policies)
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In the face of emergent and complex challenges such as climate change, no individual or group can claim a monopoly on ideas for effective policy. By harnessing the ideas of a diverse group of people beyond those who traditionally contribute to policymaking, a CI exercise could help reveal new ideas to be tested. CI has already identified novel climate change solutions. For example, a teenage participant in the Climate CoLab, another CI initiative, won funding to scale up an innovative rainwater-powered sun-tracking solar panel through outreach in the developing world.
- View Highlight
-

In November 2021 we established a Collective Intelligence Lab (CILab), with the aim of improving policy outcomes by tapping into collective intelligence (CI). We define CI as the diversity of thought and experience that is distributed across groups of people, from public servants and domain experts to members of the public.
- View Highlight
-

(highlight:: Building on our initial experiments in partnership with Demos, we have adapted our approach to using Pol.is in three ways by:

1. convening a panel to moderate submitted statements to avoid duplicative or inappropriate content (this could include members of the policy team we are partnering with)
2. collecting demographic data when participants register for a debate, if they consent. This allows us to further analyse the opinion groups generated by Pol.is to interrogate what people in a particular region, organisation or job role, for example, think about particular topics - whilst participants remain anonymous
3. using Pol.is data to derive detailed personas for the opinion groups, or to draw policy implications that emerge from the discussion, depending on the policy team’s research focus)
   - View Highlight
   -

CI could be used to gauge expert and public sentiment towards existing policy ideas by asking participants to discuss existing policies and current thinking on Pol.is. This is well suited to testing public and expert opinions on current policy proposals, especially where their success depends on securing buy-in and action from stakeholders. It can also help collate views and identify barriers to effective implementation of existing policy.
- View Highlight
-

(highlight:: Because tools such as Pol.is are well-suited to showing where groups of people agree, CI could be used to test where different policy options lie within the Overton Window - defined as the range of interventions that mainstream opinion considers politically acceptable. This could enable policymakers to:

1. understand the extent to which people support different potential policy approaches. By inviting policymakers, experts and members of the public to debate a range of future policies on complex problems, we could better understand which interventions enjoy the most support, and which are least supported. As an example, independent newspaper Scoop.nz took a similar approach to exploring possible ways to reduce obesity in New Zealand. This would be especially useful when using Polis as part of a competitive or crowdsourcing approach to solving public problems, as described by Nesta and the United Nations Development Programme here
2. discover how stakeholder groups such as local government, service providers and communities might respond to proposed new policies)
   - View Highlight
   -

In the face of emergent and complex challenges such as climate change, no individual or group can claim a monopoly on ideas for effective policy. By harnessing the ideas of a diverse group of people beyond those who traditionally contribute to policymaking, a CI exercise could help reveal new ideas to be tested. CI has already identified novel climate change solutions. For example, a teenage participant in the Climate CoLab, another CI initiative, won funding to scale up an innovative rainwater-powered sun-tracking solar panel through outreach in the developing world.
- View Highlight
-