About Nesta

Nesta is a research and innovation foundation. We apply our deep expertise in applied methods to design, test and scale solutions to some of the biggest challenges of our time, working across the innovation lifecycle.

What is collective intelligence design?

Collective intelligence design is the art and science of bringing together diverse groups of people, data (including information or ideas) and technology.

When should we use collective intelligence design?

You can use collective intelligence design at any stage in a typical innovation, product development, policy design or service design process. You might use collective intelligence at just one of the stages in your process, or across multiple stages.

Use the table below as a guide to how collective intelligence design can help you address your challenge. Your starting point - the reason you decide to use collective intelligence design - will lead to different results, and the projects you design will have different characteristics. A brief summary is provided in the table below.

Examples for how collective intelligence design should be used according to your issue.
Examples of common issues Purpose for using collective intelligence Common characteristics Example outputs

"I have poor/incomplete information about this issue, or it is changing rapidly."

"I want to anticipate how a problem or situation might change in the future."

Understand problems

Generate contextualised insights, facts and information on the dynamics of a situation.

  • Connects multiple types of data (for example, satellite data with crowdsourced mapping of a location).
  • Uses novel data sources or proxy data (for example, light source data to measure GDP).
  • Often involves crowdsourcing data (for example, experiences or information) from people.
  • May use machine intelligence to analyse combined datasets or create models.

Real-time data dashboard.

Open map of local level (granular) data.

Predictive model.

Early warning alerts.

"I understand the problem I’m working on, but I don’t know how to best tackle it."

"My existing approaches to tackling this problem aren’t working well enough."

Seek solutions

Find novel approaches or tested solutions from elsewhere. Or incentivise innovators to create new ways of tackling the problem.

  • Searches academic/scientific literature for proven approaches.
  • Connects with other organisations/individuals who might already be working on this issue.
  • Invites a wide range of potential innovators to find a new/better solution.
  • Sometimes using machine learning tools (including text analysis) to sift data more quickly and/or rank results.

A register or prioritised list of new or existing solutions to adopt, adapt or test.

Prototypes for scaling and/or further investment.

"I want to share ownership for the decision(s) I need to make."

"I need other people to act with me on this issue."

Decide and act

Make decisions with, or informed by, collaborative input from a wide range of people and/or relevant experts.

  • Brings together a diverse range of stakeholders who are affected and/or knowledgeable about an issue.
  • Often involves online or in-person group deliberation on an issue.
  • May include voting and ranking of peer ideas or organisational policies.
  • May be combined with collaborative group exploration to understand the problem and seek solutions.
  • Sometimes uses machine learning tools such as natural language processing to cluster or summarise information.

Participant-ranked list of proposed actions/ideas for implementation.

Clarity on majority or consensus view on a given topic or course of action.

Collective agreement on next steps.

"I want to track if this project/policy is working the way it is intended."

"I want to share what is known and what works with others so that they can act more quickly/smartly."

Learn and adapt

Gather data to monitor the implementation of initiatives, and share knowledge to improve the ability of others.

  • Mobilises data generated by citizens - either actively through crowdsourcing or passively (for example, through call detail records).
  • Combines multiple sets and types of data.
  • Creates open repositories of data and/or tools.
  • May use machine learning algorithms to identify patterns in data and automate adjustments.

Open source repository of tools, designs or software.

Experiment results made available to others.

Formalised hubs of knowledge on ‘what works’.

Online learning programmes/exchanges that are personaslised or enhanced based on others’ experiences.

You might have one primary purpose for collective intelligence that you focus on, or you might incorporate two or more purposes in your project. You can introduce it in a modular and flexible way.

An example of a project which combines multiple uses (or categories) of collective intelligence is Regen Network, which aims to reward positive changes to our ecosystems.

Understand problems: Regen Network uses satellite, sensors and on-the-ground observation data to understand current ecological conditions.

Seek solutions: A network of farmers around the world are incentivised to experiment with new approaches to improving things like carbon sequestration, cleaning waterways or increasing biodiversity. They are paid as ecosystems improve and conditions set out in ecological protocols are achieved.

Decide and act: Ecological protocols are crowdsourced from relevant experts which stipulate the improvements needed for any particular ecosystem.

Learn and adapt: The satellite, sensor and on-the-ground observation data help farmers to monitor progress in real-time and learn which experiments are working best.

How do we know if collective intelligence design is right for us?

Use the following flowchart to help you decide if collective intelligence is right for your challenge and if your team or organisation is ready to use it.

Authors

Kathy Peach

Kathy Peach

Kathy Peach

Director of the Centre for Collective Intelligence Design

The Centre for Collective Intelligence Design explores how human and machine intelligence can be combined to develop innovative solutions to social challenges

View profile
Aleks Berditchevskaia

Aleks Berditchevskaia

Aleks Berditchevskaia

Principal Researcher, Centre for Collective Intelligence Design

Aleks Berditchevskaia is the Principal Researcher at Nesta’s Centre for Collective Intelligence Design.

View profile
Theo Bass

Theo Bass

Theo Bass

Senior Researcher, Government Innovation

Theo was a Senior Researcher in Nesta's Research, Analysis and Policy Team

View profile