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
8Unique collaborators
2/2Semantic Scholar citation coverage
Publication span: 2026. Corpus fetch span: 2026.
Identity provenance
Provider IDs
- Semantic Scholar:
9700358
ORCID evidence
No valid ORCID is stored.
Observed aliases (1)
- Ben M. Tappin (semantic scholar, provider refresh)
Topics and outcomes in this view
Assessment themes
- Governance: 2 papers
- Human Ai Collab: 2 papers
Claim outcomes
- Other: 2 papers
- Decision Quality: 1 paper
- Firm Revenue: 1 paper
- Output Quality: 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 |
|---|---|---|---|
| Frontier conversational AI out-persuades expert humans and raises far more money: in large preregistered trials, AI beat world-class debaters and incentivized persuaders and produced nearly three times the real donations of professional canvassers; the edge appears driven mainly by AI's ability to deploy larger quantities of information rapidly.arxiv | Ben M. Tappin provider id |
2026-06-15 | 0 |
| AI chatbots can significantly spur real-world actions—raising petition signing by about 20 percentage points and increasing donations—yet shifts in attitudes do not correlate with who acts, warning that attitude-based studies may misstate AI's behavioural impact.arxiv | Ben M. Tappin provider id |
2026-04-10 | 1 |
Citation observation summary
Semantic Scholar supplied counts for 2 of 2 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.