Direction, evidence grade, and study type are AI-generated labels (gpt-5-mini), not human-verified. Syntheses are LLM-written. "Tensions" are machine-detected candidates, not confirmed contradictions. A research-acceleration tool, not peer review.
How this is built →
1Distinct papers
4Unique collaborators
1/1Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2398905612
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Tom Deckenbrunnen (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Adoption: 1 paper
- Governance: 1 paper
Claim outcomes
- Governance And Regulation: 1 paper
- Regulatory Compliance: 1 paper
Papers in the Semantic Scholar view
Latest stored Semantic Scholar author observations only. Citation counts below are from the same provider and are not combined with other services.
Scroll the table horizontally to see every column.
| Paper | Author evidence | Date | Provider citations |
|---|---|---|---|
| Some legal uncertainty is a feature, not a flaw: the paper argues that leaving room for interpretation in high-level AI laws enables the boundary negotiations needed for adaptive governance. Well-designed technical sandboxes and boundary artifacts translate abstract legal requirements into operational checks, but enforcing premature legal closure risks stifling the learning that makes regulation effective.openalex | Tom Deckenbrunnen provider id |
2026-01-07 | 1 |
Citation observation summary
Semantic Scholar supplied counts for 1 of 1 papers in this view; 0 are missing. The observed paper counts sum to 1 cumulative citations. This is a coverage summary, not an author score or h-index.