---
type: source
id: iproov-2025-consumer-study
title: iProov deepfake blindspot consumer study (industry report)
authors:
- iProov
year: 2025
venue: Industry report / press release
volume: null
pages: null
doi: null
peer_review: industry
evidence_tier: E
design: Online consumer test with mixed real and deepfake images and videos
modality:
- image-face
- video
stimuli: Vendor-selected
n_participants: 2000
n_note: UK and US consumers (approximate)
topics:
- human-detection
- overconfidence
summary: 'Vendor-reported: only ≈0.1% of participants classified every item correctly; older adults performed worse; confidence was high regardless of accuracy.'
results:
- metric: All items correct
  value: ≈0.1% of participants
  note: all-correct is a strict criterion, not mean accuracy
  source_location: null
moderators:
- Older adults performed worse
limitations:
- Not peer reviewed
- Vendor has commercial interest
- Methods not fully disclosed
verification:
  status: unverified
  confidence: medium
  checked: null
  via: compiler knowledge
url: null
pmid: null
pmcid: null
arxiv_id: null
openalex_id: null
oa_url: null
cited_in:
- MR-0001
updated: '2026-10-07'
---

# iProov deepfake blindspot consumer study (industry report)

> **Source record** `iproov-2025-consumer-study` · 2025 · Industry report / press release  
> **Evidence tier:** E (industry) · **Verification:** unverified (compiler confidence: medium)  
> **Bottom line:** Vendor-reported: only ≈0.1% of participants classified every item correctly; older adults performed worse; confidence was high regardless of accuracy.

## Citation {#citation}

iProov (2025). iProov deepfake blindspot consumer study (industry report). *Industry report / press release*.

Verification entry (identifiers, resolvers, claims with source locations): [/data/citations.json#iproov-2025-consumer-study](/data/citations.json#iproov-2025-consumer-study)

## Study design {#design}

| Field | Value |
|---|---|
| Design | Online consumer test with mixed real and deepfake images and videos |
| Modality | image-face, video |
| Stimuli | Vendor-selected |
| Participants (N) | 2000 |
| N detail | UK and US consumers (approximate) |
| Topics | human-detection, overconfidence |

## Results {#results}

| Metric | Value | Note |
|---|---|---|
| All items correct | ≈0.1% of participants | all-correct is a strict criterion, not mean accuracy |

## Moderators {#moderators}

- Older adults performed worse

## Limitations {#limitations}

- Not peer reviewed
- Vendor has commercial interest
- Methods not fully disclosed

## 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 | `unverified` |
| Compiler confidence | medium |
| Checked on | — |
| Via | compiler knowledge |

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