You will learn the precise criteria that separate AI-assisted, AI-generated, and human-made artworks in current critical use. By the end, you will be able to label a given piece correctly and explain why the label matters for context, not value.
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You will see how courts, museums, and artist collectives currently define authorship when a machine produces part or all of an image. You will leave able to identify who holds credit, and under what conditions that credit can be contested.
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You will get a concrete method for testing whether an AI tool is shaping your decisions or just executing them. By the end, you will have a short routine to run before and after each session with a generative tool.
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You will find a step-by-step list for deciding what to disclose about AI involvement before you submit, sell, or exhibit a piece. You will be able to match your disclosure to the specific venue's current requirements.
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You will learn seven concrete criteria for assessing an AI-generated piece beyond liking it or noting that a machine made it. You will be able to apply this checklist to any image regardless of the tool used to produce it.
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You will learn the specific visual and procedural markers that currently distinguish most human-painted portraits from AI-generated ones. You will also learn which of these markers are becoming unreliable as tools improve.
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You will understand the current copyright status of AI-assisted and AI-generated work in major jurisdictions, including what still lacks protection. You will be able to assess the copyright risk of a specific project before you publish or sell it.
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You will see the criteria curators currently apply when reviewing AI-involved submissions, drawn from published acquisition and exhibition policies. You will be able to anticipate which of your own work is more or less likely to clear institutional review.
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You will get a clear, non-sentimental account of what art does that image generation alone does not, based on how critics and historians define the function of art. You will be able to explain this distinction without relying on vague appeals to human creativity.
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You will learn how painters, critics, and institutions responded when photography was first accused of making painting obsolete, and how that debate actually resolved. You will be able to draw specific, sourced parallels to the current AI debate rather than loose analogies.
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