Chatbots have been studied for more than half a century. With the rapid development of
natural language processing (NLP) technologies in recent years, chatbots using large …

We present the first English corpus study on abusive language towards three conversational
AI systems gathered" in the wild": an open-domain social bot, a rule-based chatbot, and a …

The popularity of pretrained language models in natural language processing systems calls
for a careful evaluation of such models in down-stream tasks, which have a higher potential …

Given significant concerns about fairness and bias in the use of artificial intelligence (AI) and
machine learning (ML) for psychological assessment, we provide a conceptual framework …

Data-driven algorithms are studied and deployed in diverse domains to support critical
decisions, directly impacting people's well-being. As a result, a growing community of …

Mitigating algorithmic bias is a critical task in the development and deployment of machine
learning models. While several toolkits exist to aid machine learning practitioners in …

Despite remarkable advances that large language models have achieved in chatbots,
maintaining a non-toxic user-AI interactive environment has become increasingly critical …

Oyeniran, Adewusi, Adeleke, Akwawa, & Azubuko, P. 115-126 Page 116 implementing
robust auditing processes. We also review existing ethical guidelines and frameworks, such …

In an effort to regulate Machine Learning-driven (ML) systems, current auditing processes
mostly focus on detecting harmful algorithmic biases. While these strategies have proven to …

The Human-Computer Interaction (HCI) community has consistently focused on the
experiences of users moderated by social media platforms. Recently, scholars have noticed …