# 2.11 Art: Fingerprints of Style #### Whose Brush, Whose Voice? Detecting Artists' Characteristics with AI **Subject: **Art & Literature · **Target Group:** 9 (age 14–15) · **Duration:** 1 double lesson · **AI:** Learning **WITH** AI # Content Art historians and literary scholars rarely have direct access to an artist's intentions. Instead, they reconstruct an artist's “style” by comparing many works: brushstroke, colour and composition in painting, or word choice, imagery and rhythm in poetry. A single painting or poem can hint at a preference, but only a pattern that recurs across several works turns that preference into a genuine characteristic. Vincent van Gogh provides a useful case study. Over roughly a decade of intense production, he developed instantly recognisable characteristics: thick impasto, short directional brushstrokes, and bold, often complementary colour contrasts. Because these features recur across hundreds of paintings, scholars can describe them as a real stylistic signature rather than a one-off choice. AI image tools can now generate convincing pictures “in the style of Van Gogh” in seconds. These images often reproduce recognisable surface markers — swirling brushwork, yellow-and-blue palettes — but they may also exaggerate or invent details that were never characteristic of his actual body of work, or blend in features borrowed from other artists entirely. The same issue appears with text. AI writing tools can imitate a poet such as Emily Dickinson by reproducing surface markers — dashes, slant rhyme, short lines — without necessarily capturing the thematic and structural qualities that scholars consider genuinely characteristic of her work. Students therefore need to distinguish between three levels of certainty: **Feature** – what is directly observable in one specific work. **Pattern** – a feature that recurs across several confirmed works and can reasonably be called characteristic. **Attribution** – a claim about meaning, influence or authorship that goes beyond what the works themselves can support. # Lesson plan
**Phase** **Time** **Activity**
Hook 10 min Show two AI-generated “in the style of Van Gogh” images — one closer to his actual technique, one exaggerated. Students guess which is more faithful and discuss why.
Input 10 min Introduce Feature – Pattern – Attribution and practise distinguishing them using a genuine painting detail.
Exploration 15 min Students study 3–4 authentic works by one artist/poet without AI and log which features actually recur.
Adaptation 1 20 min AI writes a style description from a single work or limited prompt. Students identify where it invents unsupported characteristics.
Adaptation 2 20 min More works and a stricter, source-citing prompt are added. Students compare the two style descriptions.
Reflection 25 min Students transfer the same critical-thinking framework to a contested art-authentication or attribution case.
**Guiding questions: from AI output to classroom-ready activity** • **Hook — Show two AI-generated “in the style of Van Gogh” images (one closer to his real technique, one exaggerated/stereotyped):** ◦ *Discussion question: *“What makes this look like a real Van Gogh?” ◦ *Introduce the problem: *“How do we know which stylistic details are actually characteristic of this artist?” Key principle for this lesson (comparing multiple authentic works) ◦ Observable feature → recurring pattern → attribution/interpretation • **Input — Close look at a genuine work (e.g. a detail from The Starry Night or a stanza of a Dickinson poem):** ◦ Provide statements about the work that need to be categorised into feature, pattern, attribution. Example: ◦ Short, choppy brushstrokes are visible in this painting – *feature* ◦ Van Gogh regularly used short, directional brushstrokes across his late works – *pattern* ◦ He used these brushstrokes to express his inner emotional turmoil – *attribution* • **Exploration — Group work. Analysing authentic works:** 3–4 works by the same artist/poet, e.g.: A) Two or three reproductions of paintings from the same period of the artist's career. B) Close-up/detail images showing brushwork or handwriting. C) Short technique or biography notes from a museum or literary source. D) A contrasting work by a different artist or poet, for comparison. Students fill out a worksheet for each work by answering: What features do we observe? What patterns recur across the works? What is still just our interpretation? • **AI writes a style description:** Prompt used by students: Based only on this one image/poem, describe the artist's characteristic style in approximately 150 words. Only mention features that are actually visible or present in the work. Students annotate the AI response: ◦ Feature ◦ Reasonable pattern ◦ Unsupported / attribution • **AI revises its work using more evidence:** *Improved prompt: *Revise the style description using Sources A–D. After every stylistic claim, cite the specific work that supports it, for example \[Work B\]. If a claim is a broader pattern inferred from several works, write \[Pattern\]. Remove any claim that cannot be supported. *Compare:* Version 1 → Version 2 Find: ◦ one detail that became more precise; ◦ one detail AI removed; ◦ one new feature supported by evidence; ◦ one claim that still needs questioning. • **Reflection/Transfer of knowledge** Show a short, classroom-appropriate example of a contested art-authentication or poem-attribution case. *Discussion question:* ◦ Based on the key principles from this lesson, what stands out as feature, pattern, attribution? ◦ If an AI-generated pastiche successfully imitates the surface of a style, does that mean it has captured the artist's actual characteristics? *Final individual reflection:* Students complete: 1. A stylistic feature becomes a real “characteristic” when… 2. Before trusting an AI's description of an artist's style, I should… 3. AI can imitate the surface of a style, but… # Materials • Projector/interactive whiteboard with speakers. • Two AI-generated “in the style of …” images for the hook. • Detail image or excerpt from a genuine work by the chosen artist/poet. • Feature–Pattern–Attribution mini worksheet. • Source pack: 3–4 authentic works (images/poem texts) plus short technique or biography notes. • Source-analysis worksheet. • Student devices with access to an approved generative AI tool (text and/or image). • AI prompt and comparison worksheets for Rounds 1 and 2. • Example of a contested authentication/attribution case for the reflection.