  Large Language Models (LLMs) have created opportunities for designing
chatbots that can support complex question-answering (QA) scenarios and improve
news audience engagement. However, we still lack an understanding of what roles
journalists and readers deem fit for such a chatbot in newsrooms. To address
this gap, we first interviewed six journalists to understand how they answer
questions from readers currently and how they want to use a QA chatbot for this
purpose. To understand how readers want to interact with a QA chatbot, we then
conducted an online experiment (N=124) where we asked each participant to read
three news articles and ask questions to either the author(s) of the articles
or a chatbot. By combining results from the studies, we present alignments and
discrepancies between how journalists and readers want to use QA chatbots and
propose a framework for designing effective QA chatbots in newsrooms.
