---
type: source
id: kramer-2024-crowds-synthetic-faces
title: Crowds Improve Human Detection of AI-Synthesised Faces
authors:
- Robin S. S. Kramer
- Charlotte Cartledge
year: 2024
venue: Applied Cognitive Psychology
volume: 38(5)
pages: null
doi: 10.1002/acp.4245
peer_review: peer-reviewed-journal
evidence_tier: B
design: 'Exp1: real-vs-synthetic ratings on a 1-7 scale, completed twice (inner and outer crowds). Exp2: single binary judgement with confidence and estimate of others'' agreement (majority vote, confidence-weighted and ''surprisingly popular'' aggregation)'
modality:
- image-face
stimuli: AI-synthesised and real faces (details not in abstract)
n_participants: null
n_note: not in abstract
topics:
- human-detection
- crowds
- aggregation
summary: Aggregating different people's judgements (outer crowds) improved synthetic-face detection as crowd size grew, with gains comparable to training; averaging one person's two attempts (inner crowd) added little.
results:
- metric: Inner crowd
  value: little benefit over individuals
  note: ''
  source_location: abstract
- metric: Outer crowd
  value: performance improved with crowd size
  note: ''
  source_location: abstract
- metric: Aggregation rule
  value: majority vote best for small crowds; 'surprisingly popular' best for larger crowds
  note: ''
  source_location: abstract
- metric: Personality
  value: no association with performance
  note: ''
  source_location: abstract
moderators:
- Crowd size
- Aggregation rule
limitations:
- Values not checked against full text
verification:
  status: verified-abstract
  confidence: medium
  checked: 2026-10-12
  via: OpenAlex abstract record for doi:10.1002/acp.4245
url: null
pmid: null
pmcid: null
arxiv_id: null
openalex_id: null
oa_url: null
cited_in:
- MR-0001
updated: '2026-10-12'
---

# Crowds Improve Human Detection of AI-Synthesised Faces

> **Source record** `kramer-2024-crowds-synthetic-faces` · 2024 · Applied Cognitive Psychology  
> **Evidence tier:** B (peer-reviewed-journal) · **Verification:** verified-abstract (compiler confidence: medium)  
> **Bottom line:** Aggregating different people's judgements (outer crowds) improved synthetic-face detection as crowd size grew, with gains comparable to training; averaging one person's two attempts (inner crowd) added little.

## Citation {#citation}

Robin S. S. Kramer, Charlotte Cartledge (2024). Crowds Improve Human Detection of AI-Synthesised Faces. *Applied Cognitive Psychology*, 38(5). https://doi.org/10.1002/acp.4245

Verification entry (identifiers, resolvers, claims with source locations): [/data/citations.json#kramer-2024-crowds-synthetic-faces](/data/citations.json#kramer-2024-crowds-synthetic-faces)

## Study design {#design}

| Field | Value |
|---|---|
| Design | Exp1: real-vs-synthetic ratings on a 1-7 scale, completed twice (inner and outer crowds). Exp2: single binary judgement with confidence and estimate of others' agreement (majority vote, confidence-weighted and 'surprisingly popular' aggregation) |
| Modality | image-face |
| Stimuli | AI-synthesised and real faces (details not in abstract) |
| Participants (N) | not recorded |
| N detail | not in abstract |
| Topics | human-detection, crowds, aggregation |

## Results {#results}

| Metric | Value | Note |
|---|---|---|
| Inner crowd | little benefit over individuals |  |
| Outer crowd | performance improved with crowd size |  |
| Aggregation rule | majority vote best for small crowds; 'surprisingly popular' best for larger crowds |  |
| Personality | no association with performance |  |

## Moderators {#moderators}

- Crowd size
- Aggregation rule

## Limitations {#limitations}

- Values not checked against full text

## Cited in {#cited-in}

- [MR-0001](/metareports/human-detection-accuracy.md): Human Detection of Deepfakes: Accuracy, Bias, Confidence, and Training

## Verification {#verification}

| Field | Value |
|---|---|
| Status | `verified-abstract` |
| Compiler confidence | medium |
| Checked on | 2026-10-12 |
| Via | OpenAlex abstract record for doi:10.1002/acp.4245 |

Values on this page have not all been checked against the full text. Confirm them against the primary source before high-stakes use.