In a three-month randomized trial with 133 patent lawyers, AI assistance raised graded drafting quality by 0.38 standard deviations at 90 days; on a later task done without AI, treated seniors scored 0.45 standard deviations higher than control seniors, treated juniors no higher (−0.03), and the senior–junior difference was statistically significant.

SocioLens project,

Claim LD04-SL-C10 (v1.0)

Research opportunities this claim motivates

What this claim leaves open for research. Each is a hypothesis about a gap, not a finding.

Do professionals trained with AI lose the skill without it a year later?After three months of AI-assisted patent drafting, seniors improved on an unaided task and juniors did not; the study has no baseline skill test and stops at three months.
Does retained skill depend on how routine the task is and who is learning?In judgement-heavy patent drafting, three months of AI help improved unaided skill for seniors but not juniors: the expertise contrast within one task.

Provenance and status

Claim type: Estimate
Publication status: Eligible for publication, with qualifiers: institutional position
Verification state: Checked against the primary source. Who checked this claim is not recorded for it; claim checks so far were AI-led, and no person has checked claims against their sources.
Does not license: That AI erodes junior skill (juniors did not fall below controls); effects beyond three months; why the gap appears (the authors say the experiment does not answer why)
Limitations: Not peer reviewed; small junior subgroup; attrition of 21–32% across tasks, not differential by treatment; no baseline skill test; AI non-use during the unaided task not directly observed; conflict of interest: the study was conducted by Google, six of seven authors are Google employees, Google paid direct costs and all firms draft for Google; checked against the version dated 7 October 2026
Source (as cited): Autor, Rodchenko, Martin, Iscenko, Strand, Pearl & Ferere, “Does AI Assistance Enhance or Erode Expertise? Evidence from a Three-Month Field Experiment in Patent Drafting,” NBER Working Paper 35720, 2026
Source type: Working paper (recorded as “Academic working paper”)
Institutional position: Mixed
Maturity of the evidence: Emerging evidence
Recorded date: 14 October 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Autor, Rodchenko, Martin, Iscenko, Strand, Pearl & Ferere, “Does AI Assistance Enhance or Erode Expertise? Evidence from a Three-Month Field Experiment in Patent Drafting,” NBER Working Paper 35720, 2026 (Working paper)
Read the original

Version

This is the current version, v1.0. Earlier versions stay available, and their records never change.

Versions: v1.0 · current

Raw record: every recorded field, with its coded values

All 25 canonical Claim fields, verbatim, with the coded values derived from them. The plain-language labels above are read from these.

Claim type (coded): ESTIMATE (as printed: “ESTIMATE”)
Publication status (coded): ELIGIBLE (INSTITUTIONAL_POSITION) (as printed: “ELIGIBLE WITH INSTITUTIONAL-POSITION QUALIFIER”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY
Source type (coded): WORKING_PAPER
Maturity (coded): EMERGING

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD04-SL-C10	—
2	PUBLIC-FACING CLAIM	In a three-month randomized trial with 133 patent lawyers, AI assistance raised graded drafting quality by 0.38 standard deviations at 90 days; on a later task done without AI, treated seniors scored 0.45 standard deviations higher than control seniors, treated juniors no higher (−0.03), and the senior–junior difference was statistically significant.	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	B — Skill after the tool is removed	—
5	MATURITY	EMERGING	states: EMERGING
6	SOURCE	Autor, Rodchenko, Martin, Iscenko, Strand, Pearl & Ferere, “Does AI Assistance Enhance or Erode Expertise? Evidence from a Three-Month Field Experiment in Patent Drafting,” NBER Working Paper 35720, 2026	source_ids: SRC-SL-AUTOR-ET-AL-NBER-35720
7	SOURCE TYPE	Academic working paper	classes: WORKING_PAPER
8	INSTITUTIONAL POSITION	Mixed	—
9	SCOPE	133 patent lawyers at 11 US IP firms that all draft patents for Google; juniors have under seven years’ experience	—
10	DESIGN	Preregistered three-month randomized field experiment (2:1 treatment), stratified by firm and experience; blind grading by attorneys at an independent firm	—
11	SAMPLE / DATASET	133 lawyers; 91 completed the final unaided redlining task	—
12	MODEL / TOOL / VERSION	Generative-AI drafting assistance (tool details not reported here)	—
13	COMPARATOR	Lawyers randomized to draft without AI	—
14	MAIN RESULT	With AI, +0.34 SD at 10 days and +0.38 SD at 90 days, from less weak work rather than more excellent work; unaided redlining at 90 days: treated +0.32 SD overall, seniors +0.45 SD, juniors −0.03 SD (SE 0.20); the senior effect is significantly larger (p = 0.04); treated juniors became more dispersed	—
15	INFERENTIAL TARGET	Whether three months of AI-assisted drafting changes unaided professional judgement, by experience	—
16	DOES NOT LICENSE	That AI erodes junior skill (juniors did not fall below controls); effects beyond three months; why the gap appears (the authors say the experiment does not answer why)	—
17	VERIFICATION STATE	CONTENT VERIFIED	state: CONTENT_VERIFIED_PRIMARY · verified_by: UNKNOWN
18	LIMITATIONS	Not peer reviewed; small junior subgroup; attrition of 21–32% across tasks, not differential by treatment; no baseline skill test; AI non-use during the unaided task not directly observed; conflict of interest: the study was conducted by Google, six of seven authors are Google employees, Google paid direct costs and all firms draft for Google; checked against the version dated 7 October 2026	—
19	CONTRADICTORY / SUPPORTING SOURCES	Fits compression while assisted but widening in retained skill; contrasts with retained gains in routine customer support	—
20	GEOGRAPHY / LANGUAGE	US / English	—
21	DISTRIBUTIONAL LEDGER	Seniors convert assisted practice into unaided skill; juniors split between improving and falling behind	—
22	R01 / FIELD-MAP LINKS	LD-04, D2, D3	—
23	WHAT WOULD CHANGE THIS CLAIM?	Peer review, an independent replication, or a longer follow-up with a baseline skill test	—
24	PUBLICATION STATUS	ELIGIBLE WITH INSTITUTIONAL-POSITION QUALIFIER	state: ELIGIBLE · qualifiers: INSTITUTIONAL_POSITION
25	RECORDED DATE	2026-10-14	—

Field 22 references resolved against Field Map v0.2: LD-04 (LIVING_DEBATE); D2 (DOMAIN); D3 (DOMAIN)

The sources as recorded, with their record IDs and coded source types:

Pinned Sources (field 6, version-specific)

“Autor, Rodchenko, Martin, Iscenko, Strand, Pearl & Ferere, “Does AI Assistance Enhance or Erode Expertise? Evidence from a Three-Month Field Experiment in Patent Drafting,” NBER Working Paper 35720, 2026” → Autor et al. (2026), “Does AI Assistance Enhance or Erode…” (SRC-SL-AUTOR-ET-AL-NBER-35720--v1.0) — Autor, Rodchenko, Martin, Iscenko, Strand, Pearl & Ferere, “Does AI Assistance Enhance or Erode Expertise? Evidence from a Three-Month Field Experiment in Patent Drafting,” NBER Working Paper 35720, 2026; class WORKING_PAPER (explicit public provenance pin)

Cited by Living Debate versions

Cite this page

SocioLens project. (2026, October 14). In a three-month randomized trial with 133 patent lawyers, AI assistance raised graded drafting quality by 0.38 standard deviations at 90 days; on a later task done without AI, treated seniors scored 0.45 standard deviations higher than control seniors, treated juniors no higher (−0.03), and the senior–junior difference was statistically significant [Claim LD04-SL-C10, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld04-sl-c10/v1.0/

@misc{sociolens_ld04_sl_c10_v1_0,
  author = {{SocioLens project}},
  title = {In a three-month randomized trial with 133 patent lawyers, AI assistance raised graded drafting quality by 0.38 standard deviations at 90 days; on a later task done without AI, treated seniors scored 0.45 standard deviations higher than control seniors, treated juniors no higher (−0.03), and the senior–junior difference was statistically significant.},
  year = {2026},
  date = {2026-10-14},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld04-sl-c10/v1.0/}},
  note = {Claim LD04-SL-C10, version v1.0}
}

The link points to this version, whose record never changes. For a finding, cite the original study as well: SocioLens summarizes research and does not replace it.

Research-of-record provenance

Materialized by sociolens-materializer 0.6.0 at 2026-09-28T20:00:00.000Z; normalization contract SocioLens — Claim Value Vocabulary v1.0.2 — Pre-Spike Materialization Contract (v1.0.2). Content seal SHA-256 0f5223206c3657b2f2f9d041ac4f439e75cf49448a6033139f9eda30d8031214.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD04-SL-C10 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-14; no Drive identity exists. Authority: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 14 October 2026 to build the LD-04 debate; a new Claim, first version, written from the project's LD-04 source notes, checked against full texts or official abstracts. Block “ENTRY 10 — LD04-SL-C10” SHA-256 af46745035e29c81d81ef619570afc851173c6a6eca45e6100be2fb4c6660960; fixture fixtures/authored/claims/LD04-SL-C10--v1.0.

Builder decisions (not Drive data)

VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD04-SL-C10 v1.0); the first version of a new Claim of the LD-04 debate
CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD04-SL-C10 v1.0" (Project Lead (Claude, AI), 2026-10-14); basis: AGENTS.md "Authority" (the Project Lead decides research content within the research-integrity rules) and the Owner's choice in the SocioLens project chat on 14 October 2026 to build the LD-04 debate; a new Claim, first version, written from the project's LD-04 source notes, checked against full texts or official abstracts
FIELD_6_SOURCE_REFERENCE = SRC-SL-AUTOR-ET-AL-NBER-35720--v1.0 — basis: field 6 of ENTRY 10 — LD04-SL-C10 cites "Autor, Rodchenko, Martin, Iscenko, Strand, Pearl & Ferere, “Does AI Assistance Enhance or Erode Expertise? Evidence from a Three-Month Field Experiment in Patent Drafting,” NBER Working Paper 35720, 2026"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-AUTOR-ET-AL-NBER-35720--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Autor, Rodchenko, Martin, Iscenko, Strand, Pearl & Ferere, “Does AI Assistance Enhance or Erode Expertise? Evidence from a Three-Month Field Experiment in Patent Drafting,” NBER Working Paper 35720, 2026".