Ideas generated by language models for a new product had higher average purchase intent than human ideas and were 7 times more likely to rank in the top 10%, but were less diverse; pooling ideas across vendors, chain-of-thought prompting and varied personas or constraints raised their diversity “almost to the level of human idea generation”.

SocioLens project,

Claim LD09-SL-C17 (v1.0)

Provenance and status

Claim type: Estimate
Publication status: Eligible for publication, with qualifiers: preprint
Verification state: Checked against the primary source; the source is a preprint. 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: Effects on people working with AI, as opposed to AI working alone
Limitations: Read in the arXiv version, which records acceptance in July 2026 by named editors (the journal, Production and Operations Management, is inferred, not confirmed); one product domain; AI pools compared with human pools; the style check rewrote ideas with an Anthropic model (Claude Sonnet 4.5) and measured meaning with the same sentence-embedding model, so it reduces but does not remove the doubt that embeddings track wording rather than ideas
Source (as cited): Terwiesch, Meincke, Girotra, Mollick, Nave & Ulrich, “AI and Its Impact on Creativity and Diversity: An Empirical Study of LLM-Generated Product Ideas,” arXiv:2607.27553, 2026
Source type: Preprint (recorded as “Preprint (accepted journal article)”)
Institutional position: Independent academic (The Wharton School-led)
Maturity of the evidence: Emerging evidence
Recorded date: 15 October 2026
Currentness / correction: This is the current version. No correction or concern is recorded on its sources.

Sources this version cites

Terwiesch, Meincke, Girotra, Mollick, Nave & Ulrich, “AI and Its Impact on Creativity and Diversity: An Empirical Study of LLM-Generated Product Ideas,” arXiv:2607.27553, 2026 (Preprint)
Read the original

Version

This page shows version v1.0. Its record never changes, even when newer evidence arrives; the site may add a note to the page or withhold a figure not cleared for public use.

This pinned version is also the current version.

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 (PREPRINT) (as printed: “ELIGIBLE WITH PREPRINT QUALIFIER”)
Verification state (coded): CONTENT_VERIFIED_PRIMARY (PREPRINT)
Source type (coded): PREPRINT
Maturity (coded): EMERGING

#	Canonical field	Canonical value (verbatim)	Normalized (Claim Value Vocabulary v1.0.2)
1	CLAIM ID	LD09-SL-C17	—
2	PUBLIC-FACING CLAIM	Ideas generated by language models for a new product had higher average purchase intent than human ideas and were 7 times more likely to rank in the top 10%, but were less diverse; pooling ideas across vendors, chain-of-thought prompting and varied personas or constraints raised their diversity “almost to the level of human idea generation”.	—
3	CLAIM TYPE	ESTIMATE	base_types: ESTIMATE
4	RESEARCH STRAND	B — Creative work, writing and ideas	—
5	MATURITY	EMERGING	states: EMERGING
6	SOURCE	Terwiesch, Meincke, Girotra, Mollick, Nave & Ulrich, “AI and Its Impact on Creativity and Diversity: An Empirical Study of LLM-Generated Product Ideas,” arXiv:2607.27553, 2026	source_ids: SRC-SL-TERWIESCH-ET-AL-ARXIV-2607-27553
7	SOURCE TYPE	Preprint (accepted journal article)	classes: PREPRINT
8	INSTITUTIONAL POSITION	Independent academic (The Wharton School-led)	—
9	SCOPE	Consumer product ideas	—
10	DESIGN	Comparison of AI-generated and human-generated idea pools, with a re-analysis of five datasets and tests of mitigation techniques	—
11	SAMPLE / DATASET	Idea pools from several studies, including the authors’ own	—
12	MODEL / TOOL / VERSION	GPT-4 and other models from several vendors	—
13	COMPARATOR	Pools of ideas from people	—
14	MAIN RESULT	Higher average quality and 7 times the chance of a top-10% idea; lower diversity in every comparison of the re-analysis; mitigation raises diversity almost to human levels; in a separate study scaling to 1,000 ideas, “some human-explored regions remain difficult for AI to reach”; in Study 2a, after every idea was rewritten into one neutral style, 80% (zero-shot) and 90% (few-shot) of the human–AI diversity gap remained	—
15	INFERENTIAL TARGET	Whether the diversity deficit of AI-generated ideas can be designed away	—
16	DOES NOT LICENSE	Effects on people working with AI, as opposed to AI working alone	—
17	VERIFICATION STATE	CONTENT VERIFIED PREPRINT	state: CONTENT_VERIFIED_PRIMARY · qualifiers: PREPRINT · verified_by: UNKNOWN
18	LIMITATIONS	Read in the arXiv version, which records acceptance in July 2026 by named editors (the journal, Production and Operations Management, is inferred, not confirmed); one product domain; AI pools compared with human pools; the style check rewrote ideas with an Anthropic model (Claude Sonnet 4.5) and measured meaning with the same sentence-embedding model, so it reduces but does not remove the doubt that embeddings track wording rather than ideas	—
19	CONTRADICTORY / SUPPORTING SOURCES	Cross-model homogeneity of errors: LD09-SL-C25	—
20	GEOGRAPHY / LANGUAGE	Not checked / English	—
21	DISTRIBUTIONAL LEDGER	Not recorded	—
22	R01 / FIELD-MAP LINKS	LD-09, D3	—
23	WHAT WOULD CHANGE THIS CLAIM?	Evidence that the mitigations work when people, not models, produce the final ideas	—
24	PUBLICATION STATUS	ELIGIBLE WITH PREPRINT QUALIFIER	state: ELIGIBLE · qualifiers: PREPRINT
25	RECORDED DATE	2026-10-15	—

Field 22 references resolved against Field Map v0.2: LD-09 (LIVING_DEBATE); D3 (DOMAIN)

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

Pinned Sources (field 6, version-specific)

“Terwiesch, Meincke, Girotra, Mollick, Nave & Ulrich, “AI and Its Impact on Creativity and Diversity: An Empirical Study of LLM-Generated Product Ideas,” arXiv:2607.27553, 2026” → Terwiesch et al. (2026), “AI and Its Impact on Creativity…” (SRC-SL-TERWIESCH-ET-AL-ARXIV-2607-27553--v1.0) — Terwiesch, Meincke, Girotra, Mollick, Nave & Ulrich, “AI and Its Impact on Creativity and Diversity: An Empirical Study of LLM-Generated Product Ideas,” arXiv:2607.27553, 2026; class PREPRINT (explicit public provenance pin)

Cited by Living Debate versions

Individual gain, collective narrowing? Does AI make science, creative work and shared knowledge more alike? (v0.1) LD-09

Cite this page

SocioLens project. (2026, October 15). Ideas generated by language models for a new product had higher average purchase intent than human ideas and were 7 times more likely to rank in the top 10%, but were less diverse; pooling ideas across vendors, chain-of-thought prompting and varied personas or constraints raised their diversity “almost to the level of human idea generation” [Claim LD09-SL-C17, version v1.0]. SocioLens. https://sociolens-web.pages.dev/claims/ld09-sl-c17/v1.0/

@misc{sociolens_ld09_sl_c17_v1_0,
  author = {{SocioLens project}},
  title = {Ideas generated by language models for a new product had higher average purchase intent than human ideas and were 7 times more likely to rank in the top 10\%, but were less diverse; pooling ideas across vendors, chain-of-thought prompting and varied personas or constraints raised their diversity “almost to the level of human idea generation”.},
  year = {2026},
  date = {2026-10-15},
  howpublished = {\url{https://sociolens-web.pages.dev/claims/ld09-sl-c17/v1.0/}},
  note = {Claim LD09-SL-C17, 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 db03b58396974ad00a028421c987d14cae518bf2200ec5de78e566a4f867a6b3.

Repository-authored inputs (not Drive exports)

SocioLens claim — LD09-SL-C17 v1.0 (v1.0) — written in the SocioLens repository by Project Lead (Claude, AI) on 2026-10-15; 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 15 October 2026 to build the LD-09 debate; a new Claim, first version, written from the project's LD-09 source notes, checked against full texts or official abstracts. Block “ENTRY 17 — LD09-SL-C17” SHA-256 fb5c921d38fe43ae34be9fcea025dcaca253e95d6c1adb19240a82d9406a6afe; fixture fixtures/authored/claims/LD09-SL-C17--v1.0.

Builder decisions (not Drive data)

VERSION = v1.0 — basis: Claim version taken from the repository-authored claim fixture version (SocioLens claim — LD09-SL-C17 v1.0); the first version of a new Claim of the LD-09 debate
CURRENT_POINTER = true — basis: repository-authored claim "SocioLens claim — LD09-SL-C17 v1.0" (Project Lead (Claude, AI), 2026-10-15); 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 15 October 2026 to build the LD-09 debate; a new Claim, first version, written from the project's LD-09 source notes, checked against full texts or official abstracts
FIELD_6_SOURCE_REFERENCE = SRC-SL-TERWIESCH-ET-AL-ARXIV-2607-27553--v1.0 — basis: field 6 of ENTRY 17 — LD09-SL-C17 cites "Terwiesch, Meincke, Girotra, Mollick, Nave & Ulrich, “AI and Its Impact on Creativity and Diversity: An Empirical Study of LLM-Generated Product Ideas,” arXiv:2607.27553, 2026"; the only field-6 segment of this ClaimVersion's repository-authored ledger block.
SOURCE_PROVENANCE_PIN = SRC-SL-TERWIESCH-ET-AL-ARXIV-2607-27553--v1.0 — basis: explicit version-pinned public provenance of this ClaimVersion (Amendment v1.2 §6): the pinned field-6 Source record "Terwiesch, Meincke, Girotra, Mollick, Nave & Ulrich, “AI and Its Impact on Creativity and Diversity: An Empirical Study of LLM-Generated Product Ideas,” arXiv:2607.27553, 2026".