Evaluating Chatbots To Promote Users' Trust -- Practices And Open Problems · The Large Language Model Bible Contribute to LLM-Bible

Evaluating Chatbots To Promote Users' Trust -- Practices And Open Problems

Srivastava Biplav, Lakkaraju Kausik, Koppel Tarmo, Narayanan Vignesh, Kundu Ashish, Joshi Sachindra. Arxiv 2023

[Paper]    
GPT Model Architecture Reinforcement Learning

Chatbots, the common moniker for collaborative assistants, are Artificial Intelligence (AI) software that enables people to naturally interact with them to get tasks done. Although chatbots have been studied since the dawn of AI, they have particularly caught the imagination of the public and businesses since the launch of easy-to-use and general-purpose Large Language Model-based chatbots like ChatGPT. As businesses look towards chatbots as a potential technology to engage users, who may be end customers, suppliers, or even their own employees, proper testing of chatbots is important to address and mitigate issues of trust related to service or product performance, user satisfaction and long-term unintended consequences for society. This paper reviews current practices for chatbot testing, identifies gaps as open problems in pursuit of user trust, and outlines a path forward.

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