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.
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.
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.
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
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.
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…
Why I don’t trust most human-AI interaction experimental research – Jason Collins blog
Behavioural economics, data science and artificial intelligence.
SimPolitics
For more than six decades, the public has been promised that computers will revolutionize politics, both nationally and internationally. In SimPolitics, Fenw...
Thoughts on narratives and the role of AI and validators going forward
I wanted to quickly share some reflections and connect some dots around ongoing work with Prashant on causal claims and language in Economics. We have extended
The Scaling Era: An Oral History of AI, 2019–2025
An inside view of the AI revolution, from the people an…
The Unaccountability Machine: Why Big Systems Make Terrible Decisions—and How the World Lost Its Mind
Longlisted for the 2024 Financial Times Book of the Year. How life and the economy became a black box—a collection of systems no one understands, producing outcomes no one likes. Passengers get bumped from flights. Phone menus disconnect. Automated financial trades produce market collapse. Of all the challenges in modern life, some of the most vexing come from our relationships with automation: a large system does us wrong, and there’s nothing we can do about it. The problem, economist Dan Davies shows, is accountability sinks: systems in which decisions are delegated to a complex rule book or set of standard procedures, making it impossible to identify the source of mistakes when they happen. In our increasingly unhuman world—lives dominated by algorithms, artificial intelligence, and large organizations—these accountability sinks produce more than just aggravation. They make life and economy unknowable—a black box for no reason. In The Unaccountability Machine, Davies lays bare how markets, institutions, and even governments systematically generate outcomes that no one—not even those involved in making them—seems to want. Since the earliest days of the computer age, theorists have foreseen the dangers of complex systems without personal accountability. In response, British business scholar Stafford Beer developed an accountability-first approach to management called “cybernetics,” which might have taken off had his biggest client (the Chilean government) not fallen to a bloody coup in 1973. With his signature blend of economic and journalistic rigor, Davies examines what’s gone wrong since Beer, including what might have been had the world embraced cybernetics when it had the chance. The Unaccountability Machine is a revelatory and resonant account of how modern life became predisposed to dysfunction.
WarmHub | WarmHub is more than a platform. It's a movement.
In a world of rapid information, trust is scarce. Innovation outpaces our ability to verify claims, leaving us with risk and uncertainty. WarmHub is building infrastructure to make trust scalable, verifiable, and composable, empowering progress everywhere
