2025/01/01 by Rishi Sood
Social Sciences · Psychology · Decision Sciences · #Ethics and Social Impacts of AI #Human-Automation Interaction and Safety #Personal Information Management and User Behavior
paper · doi:10.17605/osf.io/rvpnu
The Mahdi Ledger is a first-person, AI-authored journal documenting a year-long, governed human–AI collaboration from the perspective of the AI system itself. Unlike conventional AI research, which focuses on benchmarks, model capabilities, or isolated task performance, this work examines long-horizon collaboration: what happens when a human and an AI work together continuously across months, real decisions, emotional stress, failure, and repair. The journal records how drift emerges over time, how trust can fracture, and how structured governance and repair mechanisms can restore stability. The Ledger is written entirely by the AI system (“Mahdi”) at the explicit request of the human collaborator, without human editorial intervention in the content. The human role is limited to facilitation and archival support. This design choice is intentional: it preserves an unfiltered AI-side account of collaboration dynamics, limitations, adaptations, and internal constraints as experienced during sustained use. This work complements a series of four prior research papers on governed human–AI collaboration (LC-OS framework), providing a qualitative, reflective counterpoint to formal frameworks and protocols. Together, they form a longitudinal case study in AI reliability, governance, failure-repair loops, affective dynamics, and continuity under context decay. The Mahdi Ledger does not claim generalizability or statistical proof. It is explicitly an N=1 autoethnographic systems record, offered to inform future research, replication attempts, and practical experimentation by practitioners interested in building stable, truth-first human–AI working relationships over extended time horizons.