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When commissioning visual art, clients and artists communicate to agree on what is to be created. This often requires bridging a language gap in how they conceive art. To arrive at a mutual understanding, they leverage boundary objects—organized language and artifact instances. However, building and working with such objects is hard due to their innate subjectivity and ambiguity. Moreover, acquiring artifact instances, such as references and sketches, requires effort. We introduce Artinter, an AI-powered commission-support system for sharing, concretizing, and expanding boundary objects. Artinter helps artists and clients develop a mutually understood ‘language’ by allowing them to define concepts with artifacts (e.g., what they mean by ‘happy’). The system provides two AI-powered approaches for expanding commission boundary objects: 1) guided search with user-defined concepts and 2) instance generation by mixing concepts and artifacts. Our studies identify how AI features can support commissions and reveal future directions for AI-powered collaborative art-making.
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Stored only when both papers are in the corpus — 33 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.