Blade Runner has set me thinking about the notion of a “critical consensus.” Why should we have such a thing at all, and why should it change over time?
Consensus Democracy | The Paper Pilot
The Paper Pilot's digital garden of thoughts on philosophy, politics, and sociology
On Consensus and Humming in the IETF
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.
The Battle for Blade Runner
Released to mixed reviews in 1982, director Ridley Scott’s neo-noir vision of a not-so-distant future where the line between man and machine has all but disappeared went on to cult status and influenced a generation of filmmakers. On the eve of a sequel no one could have predicted, its creative core—Scott, star Harrison Ford, screenwriter Hampton Fancher, and others—tell the story of the original film’s contentious journey to the screen.
Consensus: AI for Research
Consensus is an AI academic search engine for peer-reviewed literature—your research OS for finding, organizing, and analyzing science 10x faster.
Who and What comprise AI Skepticism?
An attempt to do justice to a diverse community
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.
Gaming Consensus: Coordinated Manipulation in Crowdsourced Fact-Checking
In this work, we develop the first rigorous analysis of the resistance of the core matrix factorization component of Community Notes to coordinated manipulation. Bridging-based algorithms (Ovadya & Thorburn, 2023; Small et al., 2021) offer some inherent resistance to manipulation: unlike traditional voting systems where adversaries can fabricate volume through fake upvotes, bridging requires diverse agreement across users with opposing viewpoints. Forging bridging consensus is harder as it requires an understanding of users and rating patterns on the platform. However, we demonstrate that it is possible to create synthetic consensus through a carefully designed voting strategy. Our approach does not rely on exploiting any software/security vulnerability or implementation bug, instead leveraging a fundamental property of the system’s core matrix factorization algorithm.
A New Paradigm for Scientific Publishing, Peer Review, and Impact Assessment
Scientific publishing and peer review have evolved little in three centuries, while the demands placed on them have grown profoundly. The growing role of artificial intelligence has underscored deep, systemic shortcomings of an aging system that has largely evaded innovation, a system whose origins are appallingly closer to the invention of the printing press than to the internet. We can do better – much better. This article is intended as the beginning of a communal experiment: a living document that critically reviews the modern academic publishing and peer-review system and presents a concrete framework to address what bibliometrics experts¹ have characterized as "the pervasive misapplication of indicators to the evaluation of scientific performance". Building on the Leiden Manifesto, DORA, and a body of scholarship spanning many disciplines and decades, we present a community-governed, non-profit platform organized around three trust-weighted impact factors, for articles, authors, and reviewers, with full algorithmic transparency, an open development log, and structural decoupling of credibility scoring from content moderation and from monetization. We invite the community to discuss, critique, and help shape it.
Palantir's social media manifesto is a blueprint for technofascism
The surveillance firm’s viral X post calls for hard power, conscription and the end of pluralism. AI expert and academic Mark Coeckelbergh on what happens when technology becomes the gateway to authoritarianism
supercritical | shishyko!
Supercritical is a newsletter about what happens when systems produce faster than they can coordinate. AI is making the generation of knowledge abundant, but generation was never the whole system. Validation, dissemination, credit, trust: these were bundled into institutions designed for scarcity, and this legacy architecture is now the primary bottleneck. If we fail to redesign it, progress will be sawtooth rather than smooth. Using the crisis in modern science as an early warning, this newsletter imagines the capabilities and infrastructure that come next, including provenance, trust-graded disclosure, and new protocols of coordination.
Extropia's Children, Chapter 5: Irrationalism
The driving force behind rationalism, and founder of the Machine Intelligence Research Institute, seems to think it's already too late for humanity; we are already doomed to a catastrophic AI apocalypse. How worried should we be?
The Irrational Decision: How We Gave Computers the Power to Choose for Us | Critical AI | Duke University Press
Jathan Sadowski is an associate professor in the Faculty of Information Technology at Monash University in Melbourne, Australia. He is the author of two books on technology and capitalism, Too Smart (2020) and The Mechanic and the Luddite (2025). He also cohosts the podcast This Machine Kills.
The Silent Majorities: six groups across society whose views point to systemic change
Expressing our shared concerns can drive public confidence in systems change.
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.