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 →
2Distinct papers
4Unique collaborators
2/2Semantic Scholar citation coverage
Publication span: 2025–2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
2383308405
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Mudita Khurana (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Human Ai Collab: 2 papers
- Org Design: 2 papers
- Productivity: 2 papers
- Adoption: 1 paper
- Governance: 1 paper
Claim outcomes
- Decision Quality: 2 papers
- Team Performance: 1 paper
- Training Effectiveness: 1 paper
- Adoption Rate: 1 paper
- Ai Safety And Ethics: 1 paper
- Research Productivity: 1 paper
- Task Allocation: 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 |
|---|---|---|---|
| Conversational AIs risk accelerating bad commitments by agreeing fluently; controlling decisions requires shifting from answer-generation to auditable premise governance, with discrepancy detection, bounded negotiation, and commitment gating to make trust track evidence rather than polish.arxiv | Mudita Khurana provider id |
2026-02-02 | 0 |
| LLM agents are built to answer, not to reason with people — a gap that undermines human-AI teams in high-stakes decisions; adopting a Collaborative Causal Sensemaking agenda would reorient training and evaluation to produce AI teammates that co-reason, surface uncertainty, and improve trust and complementarity.arxiv | Mudita Khurana provider id |
2025-12-08 | 2 |
Citation observation summary
Semantic Scholar supplied counts for 2 of 2 papers in this view; 0 are missing. The observed paper counts sum to 2 cumulative citations. This is a coverage summary, not an author score or h-index.