Introduction
Art has always evolved with the tools of its time — from oil paints to digital brushes, from film photography to generative AI. Today, we have a powerful new tool at our disposal: LoRAs (Low-Rank Adaptations). These lightweight models allow artists to explore identity, beauty, and emotion in ways never before possible.
This article explores why training and using custom LoRAs of public figures, such as actors or artists, is not only an act of creative expression, but also falls firmly within the boundaries of "fair use" under copyright law and ethical creation principles.
I. Understanding the LoRA: Generalization over Repetition
A LoRA does not memorize or reproduce images. It learns patterns from a dataset and uses them to generate new outputs — ones that are inspired by the data, but not identical to it.
The operation of a LoRA is closer to nonlinear regression than interpolation. Unlike a Lagrange polynomial, which passes exactly through each point in a dataset, a LoRA learns generalized visual relationships between the inputs.
It doesn’t store or replicate specific pixels. It generates synthetic outputs based on learned structures. It transforms, rather than copies.
Therefore, even if trained on real-world images, the final output is not a reproduction of any single image, but a new interpretation guided by style, lighting, and emotional cues.
This distinction is key: we're not cloning people. We're creating representations — artistic interpretations made with matrices and light.
II. Ethical Use: Artistic Intent vs. Misuse
I do not aim to deceive or exploit. My goal is to capture essence — facial expressions, cinematic lighting, emotional depth — and reinterpret them in a stylized form. Just like makeup artists discover beauty where it’s not seen, I guide AI to highlight aesthetics using datasets of carefully selected public images.
This process is:
- Not commercial
- Not invasive
- Not misleading
- Focused on personal, artistic, and educational purposes
III. Legal Grounding: Fair Use and Creative Expression
There are two main legal questions when training a LoRA:
1. Are the training images protected by copyright?
2. Does generating outputs violate a person's right to their own image?
Both can be addressed within the framework of "Fair Use" (U.S.) or similar doctrines (e.g., "Fair Dealing" in U.K./Canada), and the right to free creative expression.
Fair Use – The Four Factors
- Purpose and character of the use: Non-commercial, artistic, and transformative → favors fair use
- Nature of the copyrighted work: Public promotional material → favors fair use
- Amount and substantiality: Only patterns and visual features used → favors fair use
- Effect upon potential market: No competition with original → favors fair use
When training a LoRA:
- We use publicly available promotional and cinematographic images
- We extract high-level visual features, not exact reproductions
- We produce synthetic outputs, not duplicates
- We don’t compete with the source material or its market
Thus, this activity falls within reasonable interpretations of fair use.
Right of Publicity / Right to Image
Public figures, especially those in entertainment, are inherently exposed to media visibility. Their presence in cinema, TV, and promotional events makes them part of cultural discourse.
It is common to find promotional photos from events, premieres, and studio sessions, often required by studios so the public can see them.
These images are not private — they are official content, produced specifically for public exposure as part of the artist's professional visibility contract.
- They accept a diminished expectation of privacy.
- Representations of them for artistic, critical, or parodic purposes are often protected under free speech laws.
- In many jurisdictions, public figures must prove actual malice or intent to harm to claim violation of image rights.
Since:
- Outputs are transformed, interpreted, and stylized
- There is no attempt to mislead or defame
- The purpose is artistic exploration, not exploitation
…there is no infringement of the right of publicity.
IV. The Creator's Signature: Parameters Define Style
Even when multiple creators train LoRAs on the same dataset, the final results will not be the same — because each model reflects the decisions and vision of its creator.
Parameters such as:
- Number of epochs
- Learning rate
- Rank size
- Prompt engineering
- Resolution filtering
…all influence how the model interprets and reconstructs facial features and expressions. This means that the LoRA is not just a technical artifact — it's a reflection of the creator's artistic intent.
Each choice shapes the final output, making every LoRA a unique blend of algorithm and aesthetic preference. Therefore, these models should be understood not as mechanical reproductions, but as creative transformations guided by human intention.
V. Philosophical Perspective: Art Through Code
To me, AI is not a mirror reflecting reality — it’s a canvas. Every prompt is a brushstroke; every parameter tweak is a decision about composition. I am not hiding behind algorithms — I am guiding them.
I train LoRAs not to replicate, but to reveal. To interpret. To imagine versions of beauty that may not exist in the raw photos, but feel emotionally true.
That’s what art has always done.
VI. Conclusion
Training and using custom LoRAs of public figures is not copying — it's interpretation.
It's not plagiarism — it's transformation.
And most importantly, it's not illegal — it's art.
From a technical standpoint, LoRAs generalize patterns, not replicate images.
From a legal perspective, these models fall within the scope of fair use and free expression.
From an ethical viewpoint, they respect both the integrity of the subject and the responsibility of the creator.
With awareness, transparency, and creativity, we can continue exploring new frontiers in digital art — responsibly, beautifully, and legally.
cbrescia
