AI Detection
What Is AI Detection? How It Works for Text, Images and Video
By AIDetector365 Editorial Team · 11 min read · Published · Updated
AI detection is the practice of estimating whether content — text, an image, audio or video — was created by an artificial intelligence system rather than a person. It became a mainstream topic after ChatGPT's release in late 2022 and the spread of realistic image and voice generators.
This guide explains the main approaches, how they differ by type of content, where AI detection is used and why no method is perfect. Our own AI detector focuses on English text and runs in your browser.
Key takeaways
- AI detection estimates likelihood; it rarely proves origin.
- There are three main approaches: classifiers, watermarks and provenance records.
- Text detection relies on style and predictability; image and video detection on visual artifacts.
- Watermarks and provenance are more reliable but only work when the creator adds them.
- Results should support human judgment, never replace it.
Try it now: free AI Detector
Check whether text was likely written by AI. Runs in your browser, no sign-up.
The three approaches to AI detection
| Approach | How it works | Strength | Weakness |
|---|---|---|---|
| Classifiers (detectors) | A model or set of rules scores content for patterns typical of AI. | Works on any content, after the fact. | Probabilistic; false positives and negatives. |
| Watermarking | The generator hides a statistical or invisible signal in its output. | Strong evidence when present. | Only works for generators that add it; can be weakened by editing. |
| Provenance (content credentials) | Signed metadata records how content was created and edited (C2PA standard). | Verifiable history. | Metadata can be stripped; requires adoption. |
How AI text detection works
Text detectors look for statistical and stylistic signals that separate typical language-model output from human writing:
- Predictability (perplexity) — how expected each word is to a language model.
- Variation (burstiness) — how much sentence length and structure vary.
- Stock wording — phrases like “delve into” or “it's important to note.”
- Specificity — names, numbers, dates and first-hand detail.
- Voice — first person, contractions, questions and informal words.
AIDetector365 scores the last four in your browser, highlights the sentences that drove the estimate and explains why. For a deeper explanation, read Perplexity and burstiness explained.
How AI image, audio and video detection works
Detecting synthetic media relies on different clues. Image detectors look for artifacts such as inconsistent lighting, malformed hands or text, unnatural textures and statistical traces left by the generator. Audio deepfake detectors analyze voice characteristics and spectral patterns. Video detectors check facial movement, lip sync and frame-to-frame consistency.
These tools face the same arms race as text detection: each new generation of models removes the artifacts the previous detectors relied on. That is why watermarking and provenance are getting more attention. Google's SynthID embeds invisible watermarks in content from its own models, and the C2PA “Content Credentials” standard is supported by camera makers, Adobe, Microsoft and others.
Where AI detection is used
- Education — reviewing essays and assignments, ideally as a conversation starter.
- Publishing and SEO — finding generic, low-value passages before publication; see Does Google penalize AI content?.
- Hiring — reviewing cover letters and writing samples.
- Trust and safety — spotting fake reviews, spam and coordinated inauthentic posts.
- Journalism and fact-checking — verifying images, audio and video.
- Writers themselves — checking whether their own text sounds robotic.
The limits of AI detection
OpenAI retired its own AI text classifier in 2023 because of low accuracy, and independent research has repeatedly found that text detectors misclassify some human writing — especially by non-native English speakers — and miss AI text that has been edited or paraphrased. Short texts, formal genres and translated content are hard for every tool.
Responsible use means reading the explanation behind a score, checking confidence, combining it with other evidence and never basing a serious decision on detection alone. Our guide How accurate are AI detectors? covers this in depth.
How to run an AI text detection check
- Paste at least 80 words (ideally 300+) into the AI detector.
- Pick the closest variant: essays, web content, short text or paraphrased text.
- Read the verdict and confidence level.
- Open the highlighted sentences and check the reasons.
- Use the result as one signal among drafts, sources and context.
Frequently asked questions
What is AI detection in simple terms?
Using software or embedded signals to estimate whether content was made by an AI system instead of a person.
How accurate is AI detection?
It varies. Detectors work best on long, unedited AI text and struggle with short, edited, formal or translated text. Watermarks are more reliable but only when present.
Can AI detection identify images and videos?
Specialized tools can, using visual artifacts, watermarks and provenance data, but newer generators keep reducing detectable artifacts.
What is AI watermarking?
A hidden signal added by the generator to its output, which a matching detector can recognize. Examples include Google's SynthID.
Is AIDetector365's AI detection free?
Yes. The text detector is free, needs no account and analyzes your text in the browser without uploading it.
Put this into practice with the free AI Detector
Check whether text was likely written by AI. Runs in your browser, no sign-up.