The multiple, capitalist information fiduciaries of the Balkin proposal and the regulatory regime that Khan and Pozen appear to imagine seem to have little in common. But they are responses to the same problem: that of governing data-driven algorithmic processes that operate in real time, immanently, automatically, and at scale.
Digital Socialism?
What opportunities does the new feedback infrastructure of data capitalism offer for non-market forms of social coordination? Hayek and the Calculation Debate revisited in the age of big data.
Collective action strategies in the age of AI w/ Nick Vincent from Data Leverage - The Blockchain Socialist
I spoke to Nick Vincent, assistant professor of computing science at Simon Fraser University and author of the Data Leverage substack, about what it actually means that AI systems are built on the collective output of humanity’s digital labor and what we can do about it. Nick has spent years researching how data functions as a bargaining tool, […]
Our Spreadsheet Overlords
Weatherby argues that the current discourse around AI, especially the buzz around “artificial general intelligence,” is a distraction from its actual impact: the expansion of bureaucracy through massive data systems…
Trust Revolution
Unfiltered conversations with builders, thinkers, and operators in Bitcoin and beyond. Exploring systems we trust, why they work (or don't), and what's next.
Radical Skepticism About Information Fiduciaries
Khan and Pozen are right to note the fundamental conflict between “information fiduciary” duties and shareholder interests. I only wish to add two further points in service of a radical skepticism towards the information fiduciary concept.
ĐApps: What Web 3.0 Looks Like
As we move into the future, we find increasing need for a zero-trust interaction system. Even pre-Snowden, we had realised that entrusting our information to arbitrary entities on the internet was fraught with danger. However, post-Snowden the argument plainly falls in the hand of those who believe that large organisations and governments routinely attempt to stretch and overstep their authority. Thus we realise that entrusting our information to organisations in general is a fundamentally broken model. The chance of an organisation not meddling with our data is merely the effort required minus their expected gains. Given they tend to have an income model that requires they know as much about people as possible the realist will realise that the potential for convert misuse is difficult to overestimate.
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.
Funded projects | Scaling Trust
Explore the projects we're funding in the Scaling Trust opportunity space.
The Fourth Theory of Agent Trust: Emergence - Astral's Blog
Coordination Tech in Science: Letters, Journals, and Whatever Comes Next | shishyko!
To modernize our scientific infrastructure, we need new contextualization and coordination technologies that decouple trust from legacy branding — shifting from gatekeeping on write to algorithmic contextualization on read.
Trump and Musk's history obsession
The frenemies' strange obsession with historical "accuracy" has disturbing connections to big AI
Collective Bargaining in the Information Economy Can Address AI-Driven Power Concentration
This position paper argues that there is an urgent need to restructure markets for the information that goes into AI systems. Specifically, producers of information goods (such as journalists, researchers, and creative professionals) need to be able to collectively bargain with AI product builders in order to receive reasonable terms and a sustainable return on the informational value they contribute. We argue that without increased market coordination or collective bargaining on the side of these primary information producers, AI will exacerbate a large-scale "information market failure" that will lead not only to undesirable concentration of capital, but also to a potential "ecological collapse" in the informational commons. On the other hand, collective bargaining in the information economy can create market frictions and aligned incentives necessary for a pro-social, sustainable AI future. We provide concrete actions that can be taken to support a coalition-based approach to achieve this goal. For example, researchers and developers can establish technical mechanisms such as federated data management tools and explainable data value estimations, to inform and facilitate collective bargaining in the information economy. Additionally, regulatory and policy interventions may be introduced to support trusted data intermediary organizations representing guilds or syndicates of information producers.
The Scaling Era: An Oral History of AI, 2019–2025
An inside view of the AI revolution, from the people and companies making it happen.
Role differentiation as ignition of a collective information...
Informational active matter shows how measurement-informed decisions produce collective order, so far in systems that reach consensus. We design collective information engines structured by...
Inverting the physics of trust
Common Fabric is a social computing lab building a medium for software that revolves around people, not apps.
On Trust Infrastructure Trust underpins civilisation. It expands the scope and complexity of the pursuits within our collective reach by allowing us to act as a…