UDTR Global Rights of Nature Radar

Who is the 'I' in AI? Establishing Decentralized Identity and Accountability for Autonomous Agents

Identification

Public canonical key

doi:10.48550/arxiv.2610.17126

Authors

Ahammod Munim Ramil · Khalid Al Kafi · M. A. Abdullahis Sany · Muktadirul Islam Nibir · Md Yeasin Ali · Mohammad Zavid Parvez · Md Sadek Ferdous

Reported year

2026

Reported language

en

Source type

preprint

First detected

2026-11-09T19:04:47.727910+00:00

Last metadata observation

2026-11-09T19:04:47.727910+00:00

Last HTTP verification

Not checked

Institutions reported by the source

BRAC University · Charles Sturt University

Reported affiliation countries

AU · BD

Documentary abstract — original language

The rapid proliferation of autonomous AI agents in decentralized ecosystems challenges existing identity paradigms. While human identity is traditionally anchored in biological and/or self-asserted attributes and government credentials, AI agents lack a standardized definition of selfhood, creating critical gaps in trust and accountability. This paper introduces a novel framework for establishing Decentralized AI Identity rooted in Self-sovereign identity (SSI) principles. We propose a formal model that clearly distinguishes human users and AI agents, enabling distinct verification logic for each class while maintaining a unified identity calculus. The central to our contribution is the ABCD Framework, a multi-layered approach to agent identification and verification: (A) Algorithmic Fingerprint, which binds the identity to static model architectures and provenance; (B) Behavioural Fingerprint, which verifies dynamic performance metrics over time; (C) Cryptographic Identity, which anchors the agent via Decentralized Identifiers (DIDs) and (D) Delegation, which cryptographically binds agent actions to respective human accountability. By orthogonalizing these dimensions, we model how systems can enforce granular trust policies ranging from simple authentication to complex liability assignment, thereby solving the black box identity problem in the autonomous economic activities of AI agents.

Identifiers

OPENALEX

W7221748380

DOI

10.48550/arxiv.2610.17126

Documentary context

Documentary family

Working paper

Source-reported types

preprint

Natural entities mentioned

Ecosystem

Entity mentions are not evidence of legal recognition. Jurisdiction studied is separate from author affiliation country.

Sources

OpenAlex · Record 1 · Record 2

• DOI · https://doi.org/10.48550/arxiv.2610.17126
• OpenAlex · https://openalex.org/W7221748380

Documented bibliographic relations

Source-declared references and links; they do not establish legal support or UGLC qualification. Up to 20 outgoing references are displayed.

• openalex:w2066046989 · CITES
• openalex:w2070488416 · CITES
• openalex:w2120510885 · CITES
• openalex:w2151413173 · CITES
• openalex:w2990094262 · CITES
• openalex:w4245276699 · CITES
• openalex:w4404216613 · CITES
• openalex:w4414626354 · CITES
• openalex:w4416209823 · CITES
• openalex:w4416552339 · CITES
• openalex:w4416729942 · CITES
• openalex:w7103148403 · CITES

0 incoming references within the detected corpus

Documentary status

Relevance pending

Library

This identity is not yet included in the Legal Library.