Tootfinder

Programmable Governance for Group-Controlled Decentralized Identifiers
Carlo Segat, Sandro Rodriguez Garzo, Axel K\"upper
https://arxiv.org/abs/2507.06001

Programmable Governance for Group-Controlled Decentralized Identifiers
Self-Sovereign Identity (SSI) is a paradigm for digital identity management that offers unique privacy advantages. A key technology in SSI is Decentralized Identifiers (DIDs) and their associated metadata, DID Documents (DDOs). DDOs contain crucial verification material such as the public keys of the entity identified by the DID (i.e., the DID subject) and are often anchored on a distributed ledger to ensure security and availability. Long-lived DIDs need to support updates (e.g., key rotation)…

Several Issues Regarding Data Governance in AGI
Masayuki Hatta
https://arxiv.org/abs/2508.12168 https://arxiv.org/pdf/2508.12168

Several Issues Regarding Data Governance in AGI
The rapid advancement of artificial intelligence has positioned data governance as a critical concern for responsible AI development. While frameworks exist for conventional AI systems, the potential emergence of Artificial General Intelligence (AGI) presents unprecedented governance challenges. This paper examines data governance challenges specific to AGI, defined as systems capable of recursive self-improvement or self-replication. We identify seven key issues that differentiate AGI governan…

The 2025 OpenAI Preparedness Framework does not guarantee any AI risk mitigation practices: a proof-of-concept for affordance analyses of AI safety policies
Sam Coggins, Alex Saeri, Katherine A. Daniell, Lorenn P. Ruster, Jessie Liu, Jenny L. Davis
https://arxiv.org/abs/2509.24394

The 2025 OpenAI Preparedness Framework does not guarantee any AI risk mitigation practices: a proof-of-concept for affordance analyses of AI safety policies
Prominent AI companies are producing 'safety frameworks' as a type of voluntary self-governance. These statements purport to establish risk thresholds and safety procedures for the development and deployment of highly capable AI. Understanding which AI risks are covered and what actions are allowed, refused, demanded, encouraged, or discouraged by these statements is vital for assessing how these frameworks actually govern AI development and deployment. We draw on affordance theory to analyse t…