Problem
Research questions and friction points this paper is trying to address.
AI Regulatory Sandboxes
Collaborative Sense-Making
Socio-Technical Interpretation
Boundary Negotiating Artifact
Designing a Boundary Negotiating Artifact for Collaborative Socio-Technical Sense-Making in AI Regulatory Sandboxes
🤖 AI Summary
This study addresses the absence of technical mediating tools that facilitate collaborative understanding among multiple stakeholders within AI regulatory sandboxes. To bridge the cognitive gap between legal frameworks and sociotechnical interpretations, this work proposes the concept of boundary negotiating artifacts. Methodologically, adopting a research-driven design paradigm, we iteratively developed an interactive collaborative evaluation interface as the technical backbone. This interface is embedded within existing regulatory frameworks to structurally guide multi-agent sociotechnical sensemaking processes. The project has completed tool prototype iterations and system integration planning, yielding preliminary design insights. These outcomes provide an innovative pathway for achieving cross-domain, multi-agent collaborative sensemaking, with qualitative evaluation reserved for future work.
📝 Abstract
The rapid, unpredictable advancements in AI system capabilities has seen regulators take adaptive and experimental approaches to policymaking. Established in other domains as instruments balancing regulation with innovation, regulatory sandboxes are seen as solutions for AI regulation. However, analyses mostly focus on the legal and institutional design of AI Regulatory Sandboxes (AIRSes). With the legal framework leaving the socio-technical interpretation to stakeholders, this creates a gap on the sense-making required to fulfill the AIRS purpose. In this paper, we approach this by designing a Boundary Negotiating Artifact as a way to mediate meaning in AIRSes. Through Research-through-Design we iteratively develop a tool, providing an interface for the different stakeholders to collaborate in AI assessment. We then position it as technical backbone in established AIRS frameworks, structuring the collaborative sense-making of the involved stakeholders. We further report the insights gained from our design process leaving the qualitative evaluation for future work.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Boundary Negotiating Artifact
AI Regulatory Sandboxes
Research-through-Design
Socio-Technical Sense-Making
Collaborative AI Assessment
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