ORBIS: An AI-Enabled Architecture for Scaling Online Deliberation

Abstract The chapter presents the process behind the development of the ORBIS toolkit as a set of software components and services de-signed to facilitate large-scale online deliberation through the combination of human (collective intelligence) and artificial intelligence technologies. The platform is built on a modular and flexible architecture that combines different AI heterogeneous components. The main layers of the toolkit are: (i) Enabling layer: Provides core services such as authentication, authorisation, and resources management. (ii) Data Layer: Manages deliberation content, participant profiles, AI models, and connects to external knowledge bases, (iii) Service Layer: Contains the key AI-powered deliberation functionalities such as Argument Mining, Explanations Generator, Feedback Aggregation, Conflict Detection and Policy Recommendation, and (iv) User Interface Layer: Composed by existing well-adopted deliberation services designed to consume in a seamless to the end-user and orchestrated way, the external deliberation augmentation services. The chapter points out the key innovations of ORBIS toolkit, which include: (i) argument visualisation and clustering to organise lengthy discussions, (ii) AI-assisted explanation and interpretation of complex issues, (iii) summarisation of key ideas and points in long deliberations, and (iv) reporting mechanisms to assist policy-makers in their decision making procedures. By combining collective and artificial intelligence, the chapter ultimately describes how ORBIS aims to achieve scaling of online deliberations while maintaining discussion quality. Ultimately, it is discussed how the further promising research that this open architecture invites, and how it can inform future development and advances in the emerging field of AI-augmented collective intelligence.