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Developing Responsible Chatbots for Financial Services: A Pattern-Oriented Responsible AI Engineering Approach

Authors :
Lu, Qinghua
Luo, Yuxiu
Zhu, Liming
Tang, Mingjian
Xu, Xiwei
Whittle, Jon
Publication Year :
2023

Abstract

The recent release of ChatGPT has gained huge attention and discussion worldwide, with responsible AI being a key topic of discussion. How can we ensure that AI systems, including ChatGPT, are developed and adopted in a responsible way? To tackle the responsible AI challenges, various ethical principles have been released by governments, organisations, and companies. However, those principles are very abstract and not practical enough. Further, significant efforts have been put on algorithm-level solutions that only address a narrow set of principles, such as fairness and privacy. To fill the gap, we adopt a pattern-oriented responsible AI engineering approach and build a Responsible AI Pattern Catalogue to operationalise responsible AI from a system perspective. In this article, we first summarise the major challenges in operationalising responsible AI at scale and introduce how we use the Responsible AI Pattern Catalogue to address those challenges. We then examine the risks at each stage of the chatbot development process and recommend pattern-driven mitigations to evaluate the the usefulness of the Responsible AI Pattern Catalogue in a real-world setting.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2301.05517
Document Type :
Working Paper