Ethelo

Powered by collective intelligence

It’s a simple idea: decisions are complex

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Ethelo is a multi-party scenario analysis engine for solving complex, contentious problems.

Ethelo’s strength is the last stage of decision-making: convergence and closure.

Ethelo provides workflows for dozens of different decisions types

Inclusivity

Ethelo can work with a wide diversity of different opinions and objectives

Analysis

Ethelo is optimized to search billions of possible outcomes in moments

Fair Solutions

Ethelo finds outcomes that “optimize consensus,” maximizing
satisfaction while minimizing inequality

The decision on the right is a better plan than the one on the left. Why?

Polarization creates resistance
Fairness creates buy-in

People on the right are roughly equally happy. They will be united in moving forward together, which increases the chance of success. The plan on the left is divisive and polarizing, with winners and losers. This means there will be conflict and resistance to moving forward. Traditional democracy, with its “rule by majority,” can easily lead to these kinds of divisive outcomes eg. Brexit and the US elections

See Ethelo in action!

In the terminology of the international Association for Public Participation (IAP2), Ethelo focuses on Collaborative or Enpowering processes.

Recognized globally as one of the world´s top digital democracy platforms

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Engine deep dive

Ethelo uses combinatorics to search for fair decision outcomes

Ethelo considers a variety of parameters to evaluate potential decisions

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The Ethelo engine is open sourced under an Affero copy-left licence.

John Richardson

“The evolution of democracy; using collective intelligence and combinatorics to solve complex social problems”

Check out Video  > Ethelo inventor John Richardson’s presention to the Fields Mathematical Institute

White Paper

John Rawls and Ethelo

An Algorithm-Based
Approach for Resolving
Complex Group Decision Problems Fairly

“Justice is Fairness”

Ethelo was inspired by the philosophy of John Rawls

The Computer Science
University of Waterloo
optimized the Ethelo Engine

Ethelo learning guides

Training Tutorial

Ethelo’s Training Tutorial provides a step-by-step
guide on creating and managing participatory
decision-making projects. It covers key aspects such as structuring participant engagement, configuring project settings, utilizing platform features, and implementing best practices to ensure effective and inclusive decision-making.

Knowledge Base

Ethelo’s Knowledge Base Guide helps users understand
and navigate the platform through three key sections:
Understanding Ethelo, with insights and case studies;
Using the Platform, featuring tutorials and user guides;
and Help & Resources, offering FAQs and support. It’s a
go-to resource for users at any stage.

More Background Reading

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There has been growing speculation about the potential impact of artificial intelligence, in particular machine learning, on how society operates at the macro level.

Morphological Analysis (MA), which means “the study of forms” is well established as a method for modelling structural relationships between objects and phenomena in a number of scientific fields.

There has been growing speculation about the potential impact of artificial intelligence, in particular machine learning, on how society operates at the macro level.

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