







The IETF has had a long tradition of doing its technical work through a consensus process, taking into account the different views among IETF participants and coming to (at least rough) consensus on technical matters. In particular, the IETF is supposed not to be run by a "majority rule" philosophy. This is why we engage in rituals like "humming" instead of voting. However, more and more of our actions are now indistinguishable from voting, and quite often we are letting the majority win the day without consideration of minority concerns. This document explains some features of rough consensus, what is not rough consensus, how we have gotten away from it, how we might think about it differently, and the things we can do in order to really achieve rough consensus. Note: This document is quite consciously being put forward as Informational. It does not propose to change any IETF processes and is therefore not a BCP. It is simply a collection of principles, hopefully around which the IETF can come to (at least rough) consensus.
Taking AT to the IETF - AT Protocol
We recently posted two drafts to the IETF Data Tracker. This is the first major step towards standardizing parts of AT in an effort to establish long-term governance for the protocol.

The Internet is for End Users
This document explains why the IAB believes that, when there is a conflict between the interests of end users of the Internet and other parties, IETF decisions should favor end users. It also explores how the IETF can more effectively achieve this.
'Generative CI' through Collective Response Systems
How can many people (who may disagree) come together to answer a question or make a decision? "Collective response systems" are a type of generative collective intelligence (CI) facilitation...

Against Modesty’s Bailey
Modesty arguments often say that you should mostly or entirely bow to ‘expert consensus’ or the views of particular others, and who are you to disagree.

The emergence of consensus: a primer
The origin of population-scale coordination has puzzled philosophers and scientists for centuries. Recently, game theory, evolutionary approaches and complex systems science have provided quantitative insights on the mechanisms of social consensus. However, the literature is vast and widely scattered across fields, making it hard for the single researcher to navigate it. This short review aims to provide a compact overview of the main dimensions over which the debate has unfolded and to discuss some representative examples. It focuses on those situations in which consensus emerges ‘spontaneously’ in the absence of centralized institutions and covers topics that include the macroscopic consequences of the different microscopic rules of behavioural contagion, the role of social networks and the mechanisms that prevent the formation of a consensus or alter it after it has emerged. Special attention is devoted to the recent wave of experiments on the emergence of consensus in social systems.

'Generative CI' through Collective Response Systems
How can many people (who may disagree) come together to answer a question or make a decision? "Collective response systems" are a type of generative collective intelligence (CI) facilitation process meant to address this challenge. They enable a form of "generative voting", where both the votes, and the choices of what to vote on, are provided by the group. Such systems overcome the traditional limitations of polling, town halls, standard voting, referendums, etc. The generative CI outputs of collective response systems can also be chained together into iterative "collective dialogues", analogously to some kinds of generative AI. Technical advances across domains including recommender systems, language models, and human-computer interaction have led to the development of innovative and scalable collective response systems. For example, Polis has been used around the world to support policy-making at different levels of government, and Remesh has been used by the UN to understand the challenges and needs of ordinary people across war-torn countries. This paper aims to develop a shared language by defining the structure, processes, properties, and principles of such systems. Collective response systems allow non-confrontational exploration of divisive issues, help identify common ground, and elicit insights from those closest to the issues. As a result, they can help overcome gridlock around conflict and governance challenges, increase trust, and develop mandates. Continued progress toward their development and adoption could help revitalize democracies, reimagine corporate governance, transform conflict, and govern powerful AI systems -- both as a complement to deeper deliberative democratic processes and as an option where deeper processes are not applicable or possible.

fenc.es — be wrong on the internet, productively
Trace the map of reasonable disagreement. Break arguments into statements, rate confidence and importance, and find the crux.

Debate Maps — The Society Library
While The Society Library is dedicated to enabling access to information through our libraries, we recognize the difficult and tricky work of organizing that content into formal deliberation. There are hundreds of cognitive biases and logical pitfalls that can get in our way as human beings. Therefore, as a part of our service, The Society Library endeavors to map the knowledge we collect into “debate maps,” which essentially means we are organizing the arguments, claims, evidence, and opinions from all points of view into a formal debate - and effectively enabling “societal-scale debate.” A feat which may be otherwise impossible to organize in comparable levels of comprehensiveness with the existing limits of media, language, and human bandwidth to which we are confined.

AI and the knowledge commons
Commoning as a Transformative Social Paradigm | David Bollier
Every so often I am invited to write a piece that in effect answers the question, “Why the commons?” I invariably find new answers to that question each time that I re-engage with it. My latest attempt is an essay, “Commoning as a Transformative Social Paradigm,” which I wrote for the Next System Project as part of its series of proposals for systemic alternatives.
Verification, Deliberation, Accountability: A new framework for tackling epistemic collapse and renewing democracy
Demos is Britain’s leading cross-party think-tank. We produce original research, publish innovative thinkers and host thought-provoking events.
Something I keep thinking about is whether/how it would be possible to construct something like "trusted reviewing circles" without (1) destroying peer review's egalitarian goals, (2) accidentally enabling collusion rings, (3) recreating the same system with same issues over time.
Maria Antoniak
We are caught in such a trap. Asking good-faith community members to volunteer more when we can plainly see so much bad-faith behavior without consequences... IDK where it ends. Probably not central source of the problem, but NO ONE should be listed as an "author" on 20, let alone 40, submissions.
The first post for WTF is here: "Decentralization: Huh?" In this article I discuss what 'decentralization' means as a concept as well as how it can be used to protect us from corporate overreach wtf.samclemente.me/decentralization-huh-t22nqge
Decentralization: Huh? - What The Function!?
wtf.samclemente.me"The Internet isn't value-neutral, and neither is the IETF. We want the Internet to be useful for communities that share our commitment to openness and fairness. We embrace technical concepts such as decentralized control, edge-user empowerment, and sharing of resources." (2004)
RFC 3935: A Mission Statement for the IETF
datatracker.ietf.org
Conflict Systems
Spaces as Layers - Nick's Blog
web.archive.org
Axioms for Organizers by Fred Ross, Sr. | Fred Ross, Sr.
The Tyranny of Stuctureless
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