Assembl - bluenove

Massive collective intelligence platform

Massive collective intelligence is the capacity to mobilize communities on a large scale (hundreds and thousands of participants) around key stakes and challenges to co-create new solutions in a short space of time.

Zoom on Assembl analysis features

Our levers

Enable Conversations

Assembl is a platform that enables conversations, rather than ideas. It recreates, as realistically as possible, the conditions of a debate based on rich content and free expression. Visible to all participants, these conversations take place with maximum transparency.

Use a Modular Design

The consultative process framed by Assembl respects the evolution and life cycle of each idea. This is why the platform is modular and the interface created according to Design Thinking principles to conserve the evolutive nature of the debate.

Draw on Artificial Intelligence

Machine Learning helps categorize the content published on the platform, before it is analyzed and synthesized using human intelligence. A unique algorithm developed in partnership with Inria classifies messages automatically. However, humans have the final say, natural language recognition simply helps process the huge amounts of data.

A Hybrid Approach

The digital experience extends over several weeks and mobilizes as many people as possible. Face-to-face encounters reinforce and enhance this digital approach. They may take the form of co-construction workshops, design fiction sessions e.g. BrightMirror or flash debates led by mediators and ambassadors. All the ideas expressed during these encounters are used to further enrich the platform.

Methodology

Assembl is a collective intelligence method and technology

Assembl methodology is based on two key elements: establishing different phases to facilitate dialogue and continuously structuring information using digital tools.

Appropriate

Understand the needs of participants, establish the main concerns and create a common language

Deliberate

Debate the key stakes, develop co-constructed solutions and transform them into concrete proposals

Prioritize

Select the most relevant ideas using an adapted voting method

4 ROLES

Analyzing and facilitating an Assembl debate

Harvester

Identify and extract key ideas during conversations
Categorize content to make the information easier to synthesize

Synthesizer

Produce regular iterative summaries (visual and text) from the debate
Deliver a final overview

Knowledge manager

Provide data and information to stimulate conversations
Check facts to enrich contributions with objective data

Community Manager

Identify target populations
Motivate the community during the debate

Examples of debates

Vision 2030

This open consultation organized by Decathlon aims to collectively imagine Decathlon Vision 2030.

Artificial Intelligence governance

This debate on AI governance was an international public consultation run in 5 languages. In total, more than 2,200 people took part to help determine how to govern the current technological revolution.

Cancer prevention

This citizen consultation organized by La Ligue contre le cancer gave rise to numerous proposals that were added to a white paper presented during the first General Assembly for cancer prevention.

Tomorrow’s cities and regions

1,500 citizens debated their vision of the future challenges facing our cities and local regions resulting in 30 concrete, co-constructed proposals and 50 different utopia.