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

arXiv 2301.05517 ↗First posted 3 Jan 2023cs.SE cs.AIcited by 1

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Abstract (arXiv)

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.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 6 of its 17 references that are in the map. First posted on arXiv 3 Jan 2023.

Builds on

6 of 17 references.

References · 6

  1. 2020Closing the AI Accountability Gap: Defining an End-to-End Framework for Internal Algorithmic Auditingcited by 384
  2. 2020Questioning the AI: Informing Design Practices for Explainable AI User Experiencescited by 253
  3. 2020Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructurecited by 138
  4. 2021AI and Ethics -- Operationalising Responsible AIcited by 11
  5. 2022Towards a Roadmap on Software Engineering for Responsible AIcited by 9
  6. 2022Responsible-AI-by-Design: a Pattern Collection for Designing Responsible AI Systemscited by 4

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