Evaluating Chatbots to Promote Users' Trust -- Practices and Open Problems

TL;DR

This paper reviews current chatbot testing practices, highlights open problems affecting user trust, and suggests future directions to improve trustworthiness and societal impact of AI chatbots.

Contribution

It provides a comprehensive review of chatbot testing practices, identifies gaps, and outlines open problems to enhance user trust in AI chatbots.

Findings

Current testing practices are insufficient for ensuring trust.

Open problems include addressing societal and long-term impacts.

Recommendations for future research in chatbot trust enhancement.

Abstract

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.