Euro Agora

How could we accelerate the debate of the EU reforms within the confines of the Conference on the Future of Europe (COFE) and make the results quickly presented to the Conference Panel in a succinct and coherent way? We already have over 500 events planned with tens of thousands of participants, and over 1,500 ideas. How can you sort out all this massive information into coherent proposals quickly but in such a way that everybody’s voice can be heard?

Thankfully we apply a very advanced AI tool called POLIS, used now in various countries such as the USA, Canada, Australia, New Zealand, Taiwan, etc. in similar debates on creating a new legislation. It does not only streamline debates on each of the ideas but also enable the participants in the debate to come to an agreement very quickly. Sustensis ( has used this open-source system and created such a support for COFE, so that you can use it straightaway. But you must first learn how it works (the text below is quoted from the POLIS website:

Polis is a an open source technology for survey research that leverages data science. It is described on the website as:
a real-time system for gathering, analysing and understanding what large groups of people think in their own words, enabled by advanced statistics and machine learning.
More specifically, Polis is a platform for a conversation, in which participants submit short text statements, or comments, (<140 characters) which are then sent out semi-randomly to other participants to vote on by clicking agree, disagree or pass. Polis allows conversation owners to create conversations which can seamlessly engage (currently) up to hundreds of thousands or (conceivably) millions of participants.

It starts with an assumption that people need time to understand the implications of a proposed idea, which concerns a certain policy. To enable that understanding, POLIS uses a customised version of Facebook. It enables potential signatories to see the initial wording of the petition (max. 140 characters), its all modified versions, comments left by users, and how many people have signed up for each of these versions. A potential signatory can sign one of the existing versions of the proposed legislation or propose his own. He can also leave comments or suggestions for all others to read.

Leaving comments is a crucial part of the Polis system, which is an AI-powered conversation platform. Comments left by signatories on a petition create an indirect “conversation”. The AI machine learning methods uncover patterns in real-time, mapping out the entire conversation by visualizing correlations between opinions and participants, sorting participants into opinion groups, and surfacing areas of consensus and divisiveness. Therefore, a signatory, can after some time, assess the changes in an on-line visual representation of various groups’ support for each of the variants of the legislation. He can then switch his support for another version of the petition. In this way, the most preferred version of the petition will be chosen through a consensus and compromise.