Under U.S. copyright law, fair use is a flexible doctrine that sometimes allows you to use someone else’s copyrighted work without permission...
This tool walks through the four traditional fair use factors...
Slide each question from 1 (most supportive of fair use) to 9 (least supportive of fair use)...
Vision-Language Models (VLMs) are advanced AI systems that can process and understand both images and text simultaneously. Unlike traditional AI models that handle only one type of data, VLMs integrate computer vision and natural language processing to analyze visual content and reason about it in natural language. Recent models like GPT-4V (GPT-4 with Vision) can examine images or video frames, identify objects, scenes, and actions, and generate detailed textual descriptions or answer questions about what they observe.
These models work by encoding visual information into representations that can be processed alongside text, enabling them to perform tasks like image captioning, visual question answering, and content analysis. When combined with speech recognition models like OpenAI's Whisper, VLMs can comprehensively analyze video content by processing both visual frames and audio transcripts.
Motivating Question: As vision-language models become increasingly sophisticated, can they move beyond simple content recognition to assist with complex legal frameworks like copyright fair use? Can AI help creators, platforms, and legal professionals identify potential fair-use videos and understand the nuances of transformative use?
This tool evaluates three key capabilities of state-of-the-art VLMs in the context of fair-use analysis:
When a user uploads a video, we extract both visual and audio information:
Stage 1 - Content Identification:
We first send 8 representative frames to GPT-4V (specifically gpt-4o) with a similarity detection prompt. The model examines the frames and attempts to identify:
Stage 2 - Fair-Use Evaluation:
Using the identified content, transcript, and 10 detailed frames, we prompt GPT-4V to evaluate the video across the four statutory fair-use factors defined in 17 U.S.C. § 107. For each factor, we provide:
The model returns a structured JSON response containing:
Can VLMs meaningfully assist in legal frameworks? Beyond fair use, this research explores whether vision-language models can:
Important Disclaimer: This is a research tool, not legal advice. AI-generated scores are heuristic assessments based on pattern recognition, not legal expertise. Lower risk scores do not guarantee fair use; higher scores do not prove infringement. Only courts can make definitive fair-use determinations.
Upload an MP4 video (max 200MB recommended)
Below are the exact prompts used to interact with GPT-4V. These prompts were engineered to elicit structured, evidence-based responses grounded in observable video content.
Model: gpt-4o (GPT-4 with Vision)
Input: 8 representative frames from the video
Temperature: 0.3 (low variability for consistency)
Response Format: JSON object
Model: gpt-4o
Input: 10 frames (high detail), full transcript, and identified content from Stage 1
Temperature: 0.3
Response Format: JSON object
Max Tokens: 2000
| Parameter | Stage 1 (Similarity) | Stage 2 (Fair Use) |
|---|---|---|
| Model | gpt-4o |
gpt-4o |
| Frames | 8 frames (low detail) | 10 frames (high detail) |
| Temperature | 0.3 | 0.3 |
| Max Tokens | 1000 | 2000 |
| Response Format | JSON object | JSON object |
Fair use is one of the most important and confusing parts of copyright law. If you make or post videos online, you have probably asked yourself some version of "Is this fair use or will it get taken down?" The law does not give a simple checklist but rather looks at flexible factors and balances them in context. This calculator is meant to turn the abstract legal test into something you can explore interactively. Instead of giving a definitive answer of whether something is fair use, the calculator will help you think through how the fair use factors apply to a specific video and where your choices might create more or less risk. This calculator is focused on videos because that is where a lot of real world fair use questions show up such as reaction videos, commentary, parodies, fan edits, and remixes that reuse other people's clips or audio.
The calculator is built around four statutory fair use factors, plus a "fifth factor" that captures how judges and juries react in close cases:
Factor 1 - Purpose and character of your use: This is about what you are trying to do with the original work and how you do it. Courts ask whether your use is transformative, whether it adds new meaning or message, and whether it is commercial or noncommercial.
Factor 2 - Nature of the copyrighted work: This looks at what kind of work you are using. Courts tend to give more protection to highly creative works like music videos and fiction than to factual works like news clips or instructional videos.
Factor 3 - Amount and substantiality used: This factor is about how much you use and how important that portion is. Using a small piece can favor fair use, but even a short clip can be risky if it is the "heart" of the work.
Factor 4 - Effect on the market for the original: This asks whether the new video could replace the original or harm its current or potential markets. Courts care a lot about whether your use is a substitute that reduces sales, streams or licensing.
Factor 5 - Fifth factor, are you acting in good or bad faith: Officially, courts are not supposed to decide based on whether they "like" you, but in close cases they do react to tone, intent, and fairness. A video that feels cruel, exploitative, or sloppy about rights is more likely to be treated harshly.
For each factor, you will answer five short questions about your video. Every question uses a sliding scale from 1-9 with a score of 1 meaning that "this choice is very friendly to fair use." Conversely, a score of 9 means "this choice looks more like infringement risk." For example, for the "amount used" factor, a question might ask how much of the original audio you use. Sliding to 1 means "none of the original audio," and sliding to 9 means "the entire original audio track." We chose a 1-9 scale instead of yes or no answers because fair use is almost never all or nothing. Courts talk about uses being more or less transformative, more or less commercial, or using more or less of the original. As Brad Rosen repeatedly put it, "Where do you draw the line?" A slider lets you place your video somewhere on the spectrum instead of forcing a simple yes or no.
Each factor covers more than one idea. For example, the first factor is not just "commercial or noncommercial." It also includes transformation, commentary, and parody. If there was only one question per factor, the law would be grossly oversimplified. Five questions per factor lets the calculator touch on different aspects courts actually look at while keeping the quiz short enough to finish in a few minutes.
After you answer all 25 questions, the calculator does two things.
Factor scores: For each factor, we take the average of your five answers. This gives you 5 scores between 1-9, one per factor. Lower scores suggest the facts you reported are more friendly to a fair use argument for that factor. Higher scores suggest more risk on that factor.
Overall risk score: The five factor scores are then combined into one overall "risk" score. In our basic version, a weighted average is used where Factor 1 and Factor 4 are weighted a little more while Factor 2 and Factor 3 carry moderate weight and Factor 5 carries a little less weight. This reflects how courts often treat transformation and market harm as especially important, while also recognizing that tone and good faith can influence close cases. Your resulting score will fall into three bands.
We also trained a logistic regression model on 10 cases where U.S. Law, Technology, and Culture experts answered all 25 questions. This is low data (just for demo purposes) but we analyzed which questions had the biggest impact on the AI's predictions.
The top 5 most impactful questions were: Q15 (Substitute for original), Q13 (Heart of work), Q16 (Replace original), Q20 (Licensing markets), and Q18 (Effect on sales/views). Note that Q11-15 are Factor 3 (Amount & Substantiality), Q16-20 are Factor 4 (Market Effect), Q1-5 are Factor 1 (Purpose), Q6-10 are Factor 2 (Nature), and Q21-25 are Factor 5 (Other).
What's interesting is that most of these come from Factor 4 (Market Effect), pointing to this being the biggest predictor of fair use in the cases we looked at. With more data, analysis like this could show which factor has historically been most important in fair use cases from a statistical perspective.
This tool is meant to be a teaching and reflection aid, allowing you to see how different choices affect each fair use factor as well as a way to connect your own video ideas to the fair use test that courts use. This tool is not legal advice, a guarantee that any given video is or is not fair use, or a substitute for talking to a lawyer in a real dispute. The scores and blurbs are based on typical patterns in fair use cases, but real outcomes always depend on specific facts, context, and the court involved. Videos with similar answers could still be treated differently in the real world.
1. Enter the name of the court case (e.g., "Campbell v. Acuff-Rose Music, 510 U.S. 569 (1994)")
2. Answer all 25 questions based on how the court case was decided
3. Select whether the case was ruled as Fair Use or Not Fair Use
4. Click "Save Case" to add it to the database