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MOSAAIC: Managing Optimization towards Shared Autonomy, Authority, and Initiative in Co-creation

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arxiv 2505.11481 v1 pith:DL4KBWUF submitted 2025-05-16 cs.AI

MOSAAIC: Managing Optimization towards Shared Autonomy, Authority, and Initiative in Co-creation

classification cs.AI
keywords controlco-creationmosaaicauthorityautonomyframeworkhumansinitiative
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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Striking the appropriate balance between humans and co-creative AI is an open research question in computational creativity. Co-creativity, a form of hybrid intelligence where both humans and AI take action proactively, is a process that leads to shared creative artifacts and ideas. Achieving a balanced dynamic in co-creativity requires characterizing control and identifying strategies to distribute control between humans and AI. We define control as the power to determine, initiate, and direct the process of co-creation. Informed by a systematic literature review of 172 full-length papers, we introduce MOSAAIC (Managing Optimization towards Shared Autonomy, Authority, and Initiative in Co-creation), a novel framework for characterizing and balancing control in co-creation. MOSAAIC identifies three key dimensions of control: autonomy, initiative, and authority. We supplement our framework with control optimization strategies in co-creation. To demonstrate MOSAAIC's applicability, we analyze the distribution of control in six existing co-creative AI case studies and present the implications of using this framework.

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