What do AI detection scores actually mean?

AI detection scores are probability estimates indicating how likely text contains AI-generated characteristics, not definitive proof. A score reflects statistical patterns the tool measured, expressed as a percentage. Higher percentages suggest more AI-like features, but scores should be interpreted with context, since accuracy varies by text length and style.

How should I interpret AI detection score ranges?

Score ranges generally map from 0-20% as likely human-written up through 80-100% as highly likely AI-generated, with a 40-60% band signaling uncertain or mixed content. These ranges are guides, not guarantees. Middle scores especially call for human review and additional context before drawing conclusions.

What factors affect AI detection score accuracy?

Accuracy is affected by text length, writing style, the author's language background, and how much the text was edited or revised. Short passages, formulaic writing, and non-native English can skew results. Because these factors influence scores, results are most reliable on longer, unedited samples and should be interpreted cautiously.

Does a high AI detection score mean the content is definitely AI?

No, a high score does not definitively mean content is AI-generated. This is a common misconception; scores are probabilistic, not precise, and false positives occur. Likewise, a low score does not guarantee human authorship. Scores should inform decisions alongside context and human judgment, never serve as sole proof.

How should I use AI detection scores in high-stakes situations?

In high-stakes situations, use detection scores as one piece of evidence among many, combine them with human review and context, and ensure due process. Avoid treating any score as conclusive, since false positives can unfairly implicate people. StealthWriter recommends dialogue and corroborating evidence before making consequential decisions.

AI Detection Scores Explained: How to Interpret Results

Data analytics dashboard — Understanding detection score metrics

What Are AI Detection Scores?

AI detection scores represent the probability that a piece of text was generated by artificial intelligence rather than written by a human. These scores are typically expressed as percentages, but understanding what they truly mean requires looking beyond the numbers.

How Scores Are Calculated

Key Metrics

Most AI detectors analyze several factors:

Perplexity

Perplexity measures how "surprised" a language model is by the text. AI-generated content typically has lower perplexity because it follows predictable patterns. Human writing, with its creativity and unpredictability, usually shows higher perplexity.

Burstiness

Burstiness refers to the variation in sentence complexity and length. Humans naturally write with "bursts" of complexity—mixing short, simple sentences with longer, more elaborate ones. AI tends to be more uniform.

Pattern Analysis

Detection algorithms identify patterns characteristic of AI writing, including:

Word choice distributions
Phrase repetition patterns
Structural consistency
Transition word usage

Interpreting Score Ranges

0-20%: Likely Human-Written

Text in this range shows strong indicators of human authorship:

High perplexity (unpredictable word choices)
Natural variation in sentence structure
Personal voice and style
Creative or unconventional expressions

Action: Generally safe to consider as human-written, though no score is absolute.

20-40%: Mostly Human with Some AI Characteristics

This range may indicate:

Formal or technical writing style
Heavily edited content
Non-native English writing patterns
Minor AI assistance in editing

Action: Consider context. Academic or formal writing often falls here naturally.

40-60%: Uncertain/Mixed

The "gray zone" where determination is difficult:

Could be human writing with AI-like patterns
Could be AI content that has been edited
May indicate mixed human-AI collaboration

Action: Seek additional evidence. Consider the source, context, and other factors.

60-80%: Likely AI-Generated

Strong indicators of AI involvement:

Low perplexity scores
Uniform sentence structures
Predictable patterns
Generic, safe language choices

Action: Warrants further investigation. Consider having a conversation with the author.

80-100%: Highly Likely AI-Generated

Very strong AI indicators across multiple metrics:

Matches known AI writing patterns closely
Consistent with unedited AI output
Multiple detection methods agree

Action: High confidence of AI generation, but still verify through other means.

Factors Affecting Score Accuracy

Text Length

Longer texts provide more data for analysis:

Under 100 words: Results are less reliable
100-500 words: Moderate reliability
500+ words: Most reliable results

Writing Style

Some styles naturally score higher or lower:

Technical writing may appear more AI-like
Creative writing usually scores lower
Formal academic prose can trigger false positives
Conversational writing typically reads as human

Language and Background

Non-native speakers may have different patterns
Translation can affect detection accuracy
Regional language variations matter

Editing and Revision

Heavily edited AI content may score lower
Human content with AI editing assistance varies
Multiple revision passes change patterns

Common Misconceptions

"High Score = Definitely AI"

Even 99% scores are not absolute proof. Some human writing naturally exhibits AI-like patterns, especially in formal or technical contexts.

"Low Score = Definitely Human"

Sophisticated AI use with heavy editing can produce low scores. A low score suggests human authorship but does not guarantee it.

"Scores Are Precise"

Detection scores are probabilistic estimates, not precise measurements. Treat them as indicators requiring interpretation, not verdicts.

Making Decisions Based on Scores

Best Practices

Never rely solely on scores for important decisions
Consider context: Who wrote it? What is the purpose?
Look at patterns: Does this match the author's usual writing?
Seek clarification: When in doubt, have a conversation
Document reasoning: Record why you made specific decisions

For High-Stakes Situations

Use multiple detection tools for comparison
Combine automated detection with manual review
Establish clear policies and procedures
Provide opportunities for explanation and appeal

Conclusion

AI detection scores are valuable tools, but they require thoughtful interpretation. Understanding what the numbers mean—and their limitations—enables you to make better decisions while treating all parties fairly.

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Understanding AI Detection Scores: What the Numbers Really Mean