  Prompt-based interfaces for Large Language Models (LLMs) have made
prototyping and building AI-powered applications easier than ever before.
However, identifying potential harms that may arise from AI applications
remains a challenge, particularly during prompt-based prototyping. To address
this, we present Farsight, a novel in situ interactive tool that helps people
identify potential harms from the AI applications they are prototyping. Based
on a user's prompt, Farsight highlights news articles about relevant AI
incidents and allows users to explore and edit LLM-generated use cases,
stakeholders, and harms. We report design insights from a co-design study with
10 AI prototypers and findings from a user study with 42 AI prototypers. After
using Farsight, AI prototypers in our user study are better able to
independently identify potential harms associated with a prompt and find our
tool more useful and usable than existing resources. Their qualitative feedback
also highlights that Farsight encourages them to focus on end-users and think
beyond immediate harms. We discuss these findings and reflect on their
implications for designing AI prototyping experiences that meaningfully engage
with AI harms. Farsight is publicly accessible at:
https://PAIR-code.github.io/farsight.
