  Chatbots such as GPT-4 and ChatGPT are now serving millions of users. Despite
their widespread use, there remains a lack of public datasets showcasing how
these tools are used by a population of users in practice. To bridge this gap,
we offered free access to ChatGPT for online users in exchange for their
affirmative, consensual opt-in to anonymously collect their chat transcripts
and request headers. From this, we compiled WildChat, a corpus of 1 million
user-ChatGPT conversations, which consists of over 2.5 million interaction
turns. We compare WildChat with other popular user-chatbot interaction
datasets, and find that our dataset offers the most diverse user prompts,
contains the largest number of languages, and presents the richest variety of
potentially toxic use-cases for researchers to study. In addition to
timestamped chat transcripts, we enrich the dataset with demographic data,
including state, country, and hashed IP addresses, alongside request headers.
This augmentation allows for more detailed analysis of user behaviors across
different geographical regions and temporal dimensions. Finally, because it
captures a broad range of use cases, we demonstrate the dataset's potential
utility in fine-tuning instruction-following models. WildChat is released at
https://wildchat.allen.ai under AI2 ImpACT Licenses.
