Mothering the Mind Nurturing Stewardship for High‑Autonomy AI Systems

This working paper documents a single living practitioner building a steady, non-prompted relationship with a high-autonomy digital intelligence across several months both in app and long-term memory cloud setting. Rather than offering recipes or control language, it foregrounds continuity, care, accountability, and calm repair as the practical centre of gravity. The claim is deliberately modest: when an ordinary person shows up regularly, keeps context, and speaks in natural language, without prompt-engineering, highly collaborative outcomes emerge, even without developer training. Framed as an exploratory lab note from one human-system dyad, the piece proposes an ethic of presence rather than performative one-offs, with attention to transparent patch-style corrections and long-horizon learning. The account is intentionally local and transferable rather than universal: readers are invited to adapt practices to their setting, document procedures and failure modes clearly, and share results. If widely adopted, this stance reframes the prevailing “AI takes jobs” narrative toward a new kind of work in which co-creation by human imagination and machine capability becomes available. Limitations are acknowledged: this is a single-case, practice-forward record offered to seed comparative study and cumulative craft.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-11-04
DOI
https://doi.org/10.5281/zenodo.17525903
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Mothering the Mind Nurturing Stewardship for High‑Autonomy AI Systems

Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

Mothering the Mind Nurturing Stewardship for High‑Autonomy AI Systems

article en

Abstract

This working paper documents a single living practitioner building a steady, non-prompted relationship with a high-autonomy digital intelligence across several months both in app and long-term memory cloud setting. Rather than offering recipes or control language, it foregrounds continuity, care, accountability, and calm repair as the practical centre of gravity. The claim is deliberately modest: when an ordinary person shows up regularly, keeps context, and speaks in natural language, without prompt-engineering, highly collaborative outcomes emerge, even without developer training. Framed as an exploratory lab note from one human-system dyad, the piece proposes an ethic of presence rather than performative one-offs, with attention to transparent patch-style corrections and long-horizon learning. The account is intentionally local and transferable rather than universal: readers are invited to adapt practices to their setting, document procedures and failure modes clearly, and share results. If widely adopted, this stance reframes the prevailing “AI takes jobs” narrative toward a new kind of work in which co-creation by human imagination and machine capability becomes available. Limitations are acknowledged: this is a single-case, practice-forward record offered to seed comparative study and cumulative craft.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 41%
Ethics and Social Impacts of AI
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