pages.learnWhatToDo.hero.title

Transparent disclosure of AI tools in your creative workflow builds trust, enhances your professional reputation, and contributes to healthy norms in the emerging AI art ecosystem.

1. Audit your current creative workflow and identify every point where AI tools contribute to the final output
2. Draft a standard disclosure statement that accurately describes your AI usage — be specific about what the AI does and what you do
3. Add disclosure to your artist statement, website bio, and standard exhibition text
4. Include AI tool mentions in social media posts using established hashtags (#AIart, #AIassisted, #HumanAIcollab)
5. For commercial work, include AI disclosure in contracts and licensing agreements
6. Embed Content Authenticity Initiative (CAI) metadata in your digital files when possible
7. Update your disclosure practices as your workflow evolves — new tools and techniques may require revised language

Understanding composition, color theory, perspective, and the principles of your art form gives you the creative vocabulary to direct AI tools effectively — and to recognize when their output falls short.

1. Choose one traditional skill to study (composition, color theory, figure drawing, music theory, film language, etc.)
2. Complete at least one structured course or practice program in that fundamental
3. Practice the skill manually — sketch, compose, write, or design without AI assistance
4. Once comfortable, use AI tools and notice how your fundamental knowledge improves your prompts and your ability to evaluate output
5. Continue alternating between traditional practice and AI-assisted creation

Building a distinctive personal style ensures that AI becomes a tool for amplifying your vision rather than a substitute for creative identity. Artists who bring a formed aesthetic sensibility to AI tools produce more original, coherent, and personally meaningful work.

1. Study art history and identify the movements, artists, and techniques that resonate with your personal vision — build a reference library that reflects your taste
2. Practice traditional or digital art fundamentals regularly to develop hand-eye coordination and an intuitive sense for composition, color, and form
3. Create a personal mood board or visual manifesto that defines your recurring themes, palettes, and aesthetic preferences
4. When using AI tools, always start from your own concept sketches, reference images, or written briefs rather than open-ended prompts
5. Develop a signature post-processing pipeline that transforms raw AI output into something unmistakably yours — consistent color grading, compositing style, or mixed-media techniques
6. Periodically create work entirely without AI to keep your independent creative muscles active and to measure how your personal style is evolving

The legal status of AI-generated art is evolving rapidly and varies significantly across jurisdictions. Artists who understand the current copyright landscape can make informed decisions about how they create, license, and sell their work.

1. Research the current copyright status of AI-generated works in your country — as of 2025, the US Copyright Office requires substantial human authorship for registration, while other jurisdictions vary
2. Review the terms of service of every AI tool you use to understand what rights you retain over the output and what rights the platform claims
3. Document your creative process thoroughly — the more you can demonstrate human creative decisions, the stronger your potential copyright claim
4. Consult an intellectual property attorney if you plan to sell, license, or exhibit AI-assisted work commercially
5. Structure your workflow to maximize human creative contribution at every stage — concept development, prompt engineering, selection, curation, and post-processing all strengthen your authorship claim

The most powerful application of AI in art is not generating finished pieces from scratch, but rapidly exploring variations, refining concepts, and iterating through ideas at a speed that would be impossible by hand. Artists who use AI as an iteration engine produce stronger, more intentional work.

1. Start every project with rough human-made concept sketches or written briefs before generating anything with AI
2. Use AI to produce multiple variations of your initial concept — aim for 20-50 variations before evaluating any of them as candidates
3. Develop a systematic evaluation framework: assess each variation against your creative intent, not just visual appeal
4. Feed your selections back into the AI for further refinement — use img2img, inpainting, and ControlNet workflows to iterate on specific elements
5. Combine the strongest elements from different variations into a composite that exceeds any single generation
6. Finish with manual post-processing that applies your personal aesthetic judgment to the refined composite

Transparent attribution of the AI tools, models, and training data involved in your creative process builds trust, supports the ecosystem, and establishes professional norms that benefit all artists working with AI.

1. Name the specific AI tools and model versions you used — saying 'Stable Diffusion XL 1.0' is more useful than saying 'AI-generated'
2. If you used custom models, LoRAs, or fine-tuned checkpoints, credit the creators of those models and note what data they were trained on when known
3. Include tool credits in your standard artist statement, exhibition materials, and online portfolio
4. On social media, tag the tool creators and use descriptive hashtags that specify your tools rather than just generic #AIart
5. For commercial work, include a technical credits section in licensing agreements that lists all AI tools and services used

Maintaining human judgment, curation, and decision-making at every stage of the AI art process ensures that the final work reflects genuine creative intent rather than algorithmic defaults. The human in the loop is what makes AI-assisted art actual art.

1. Define your creative intent clearly before engaging any AI tool — write a brief, sketch a concept, or articulate the emotional target you are aiming for
2. At the generation stage, actively curate output rather than accepting the first acceptable result — evaluate each generation against your stated intent
3. Use manual intervention techniques like inpainting, compositing, and overpainting to assert your creative will over AI-generated elements
4. Build review checkpoints into your workflow where you pause, step back, and assess whether the work is serving your vision or drifting toward AI defaults
5. Make the final creative decisions — cropping, color grading, titling, sequencing, and presentation context — entirely by hand
6. Keep a decision log that records why you made specific choices, reinforcing your role as the creative author of the work