AI-Assisted Legal Self-Representation: Epistemic Autonomy, Access to Justice, and the Limits of Procedural Delegation

Legal rights may be formally available yet difficult to exercise without reliable legal knowledge. AI-assisted self-representation raises a question of procedural authority as well as epistemic autonomy: when may technology help a person act, and when would its use change who is authorized to act? A tier-sensitive account distinguishes assistance with acts individuals may lawfully perform themselves, legislative enlargement of those acts, and delegation of reserved acts to an artificial representative. The distinction supports a conditional allocation of justificatory burdens. Where the citizen remains the authorized actor, restrictions imposed specifically because assistance is computational require reasons tied to the risks of that assistance, while existing rules on professional services, privacy and procedure remain applicable. Extending personal-action rights requires evidence that legal protection will not deteriorate; conferring authority on an artificial representative additionally requires a valid source of entitlement and a reason to prefer that status over feasible accountable alternatives. Concerns about legal-aid inequality, human control, accountability, legal agency and interoperability bear differently on each institutional boundary. It does not establish an existing general right to use AI in legal proceedings, validated safety, cost savings or the novelty of its constituent principles. Voluntary assistance is justified only where users retain meaningful control, sources can be checked, human support remains accessible and remedies are effective.

Authors

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-11-09
DOI
https://doi.org/10.5281/zenodo.24082064
Primary Topic
Artificial Intelligence in Law
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
preprint

AI-Assisted Legal Self-Representation: Epistemic Autonomy, Access to Justice, and the Limits of Procedural Delegation

Israel Huerta Castillo
Zenodo (CERN European Organization for Nuclear Research)
Artificial Intelligence in Law
preprint

AI-Assisted Legal Self-Representation: Epistemic Autonomy, Access to Justice, and the Limits of Procedural Delegation

Israel Huerta Castillo
preprint en

Abstract

Legal rights may be formally available yet difficult to exercise without reliable legal knowledge. AI-assisted self-representation raises a question of procedural authority as well as epistemic autonomy: when may technology help a person act, and when would its use change who is authorized to act? A tier-sensitive account distinguishes assistance with acts individuals may lawfully perform themselves, legislative enlargement of those acts, and delegation of reserved acts to an artificial representative. The distinction supports a conditional allocation of justificatory burdens. Where the citizen remains the authorized actor, restrictions imposed specifically because assistance is computational require reasons tied to the risks of that assistance, while existing rules on professional services, privacy and procedure remain applicable. Extending personal-action rights requires evidence that legal protection will not deteriorate; conferring authority on an artificial representative additionally requires a valid source of entitlement and a reason to prefer that status over feasible accountable alternatives. Concerns about legal-aid inequality, human control, accountability, legal agency and interoperability bear differently on each institutional boundary. It does not establish an existing general right to use AI in legal proceedings, validated safety, cost savings or the novelty of its constituent principles. Voluntary assistance is justified only where users retain meaningful control, sources can be checked, human support remains accessible and remedies are effective.

Zenodo (CERN European Organization for Nuclear Research)
Universidade de Santiago de Compostela (ES)
Artificial Intelligence in Law
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon
AI-Assisted Legal Self-Representation: Epistemic Autonomy, Access to Justice, and the Limits of Procedural Delegation — Israel Huerta Castillo · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS