Neutral Substrates: A Design Constraint for Shared Records Under Persistent Interpretive Disagreement
arXiv:2601.14271v2 Announce Type: replace Abstract: Shared accountability records are often used by parties who may never agree about causation, responsibility, or normative interpretation. For such records, neutrality cannot be achieved by omitting contested information, because accountability requires preserving the claims parties made, with their sources and provenance. Nor can neutrality be achieved by asserting one contested interpretation as the shared base. This paper defines a neutral substrate as a shared representational layer that provides stable reference while making no object-lev
This paper addresses a fundamental design challenge for shared records in complex environments, which is becoming increasingly critical with the rise of distributed ledger technologies and agentic systems.
A strategic reader should care about neutral substrates as they are foundational for trusted interoperability and dispute resolution in multiparty systems, crucial for future economic and governance infrastructures.
The definition and understanding of 'neutrality' in shared record-keeping are refined, moving beyond mere data omission to a robust representational layer that accommodates persistent interpretive disagreement.
- · Distributed Ledger Technology (DLT) architects
- · International legal frameworks
- · AI agent designers
- · Data governance specialists
- · Systems relying on single-source-of-truth models
- · Centralized arbitration systems
- · Frameworks assuming easy consensus
It establishes a new theoretical basis for designing shared digital infrastructures where full consensus is not achievable.
This could lead to more resilient and equitable data-sharing protocols across industries and national borders, particularly in regulatory and financial contexts.
The concept might influence the design of future 'constitutions' for autonomous AI systems and their interactions, enabling stable co-existence despite divergent objectives.
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Read at arXiv cs.AI