Verifick AI Detection Test and Research
AI detection should be evaluated with real documents and transparent testing, not only with marketing claims. Verifick publishes tests to examine how its detection system responds to different AI-generated, human-written, and mixed writing conditions.
Why we test AI detection
AI detection systems do not produce identical results for every document. Different detectors use different models, datasets, signals, thresholds, and methodologies.
Testing helps users understand what a detection system can identify, where it performs well, and where its results require additional human review.
How Verifick tests AI detection
Our testing approach can include documents generated by different AI systems, human-written material, and documents that combine human and AI-assisted writing.
We examine the resulting detection scores and compare them with the known conditions under which the text was produced.
Where appropriate, tests also consider document length, editing, rewriting, and other factors that may influence automated detection.
What our tests are designed to measure
- Whether clearly AI-generated writing is detected.
- How results vary between different AI systems.
- How mixed human and AI-assisted writing is classified.
- How document length and writing characteristics affect results.
- Whether different writing conditions produce different detection outcomes.
- Where automated detection requires additional human interpretation.
Why one test is not enough
A single document or a single AI model cannot establish that an AI detector is universally accurate. Detection performance can vary according to language, genre, document length, editing, prompting, model version, and other factors.
For that reason, Verifick treats testing as an ongoing research process rather than as a one-time accuracy claim.
Published Verifick AI detection tests
Verifick publishes individual AI detection experiments and research articles with their test conditions and observed results.
View Verifick research and test results →
Interpreting the results
An AI detection score is a probabilistic signal. It should not be interpreted as definitive proof that a particular person used artificial intelligence.
A responsible evaluation considers the detection result alongside writing history, drafts, revision records, previous samples, citations, oral assessment, and other relevant evidence where appropriate.
AI detection accuracy
No responsible AI detection system should promise 100% accuracy for every document. Human writing can sometimes resemble AI-generated writing, and AI-generated writing can sometimes resemble human writing.
Our objective is therefore not to present a score as an unquestionable verdict. The objective is to provide useful evidence that helps reviewers investigate a document more efficiently.
Our research principle
Test openly. Report honestly. Interpret carefully.
AI detection technology is useful when its capabilities and limitations are understood.