Human-technology integration with industrial conversational agents: A conceptual architecture and a taxonomy for manufacturing

Colabianchi, Silvia; Tedeschi, Andrea; Costantino, Francesco

doi:10.1016/j.jii.2023.100510

Cited by 10 publications

(1 citation statement)

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“…Some studies present the architecture of their agent [23,69]. However, these architectures often focuses only on certain components.…”

Section: Related Workmentioning

confidence: 99%

Responsible-AI-by-Design: A Pattern Collection for Designing Responsible Artificial Intelligence Systems

Zhu

et al. 2023

IEEE Softw.

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The release of ChatGPT, Bard, and other large language model (LLM)-based chatbots has drawn huge attention on foundations models worldwide. There is a growing trend that foundation models will serve as the fundamental building blocks for most of the future AI systems. However, incorporating foundation models in AI systems raises significant concerns about responsible AI due to their black box nature and rapidly advancing super-intelligence. Additionally, the foundation model's growing capabilities can eventually absorb the other components of AI systems, introducing the moving boundary and interface evolution challenges in architecture design. To address these challenges, this paper proposes a pattern-oriented responsible-AI-by-design reference architecture for designing foundation model-based AI systems. Specially, the paper first presents an architecture evolution of AI systems in the era of foundation models, from "foundation-model-as-a-connector" to "foundationmodel-as-a-monolithic architecture". The paper then identifies the key design decision points and proposes a pattern-oriented reference architecture to provide reusable responsible-AI-by-design architectural solutions to address the new architecture evolution and responsible AI challenges. The patterns can be embedded as product features of foundation model-based AI systems and can enable organisations to capitalise on the potential of foundation models while minimising associated risks.

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“…Some studies present the architecture of their agent [23,69]. However, these architectures often focuses only on certain components.…”

Section: Related Workmentioning

confidence: 99%