  Two general routes have been followed to develop artificial agents that are
sensitive to human values---a top-down approach to encode values into the
agents, and a bottom-up approach to learn from human actions, whether from
real-world interactions or stories. Although both approaches have made exciting
scientific progress, they may face challenges when applied to the current
development practices of AI systems, which require the under-standing of the
specific domains and specific stakeholders involved. In this work, we bring
together perspectives from the human-computer interaction (HCI) community,
where designing technologies sensitive to user values has been a longstanding
focus. We highlight several well-established areas focusing on developing
empirical methods for inquiring user values. Based on these methods, we propose
participatory design fictions to study user values involved in AI systems and
present preliminary results from a case study. With this paper, we invite the
consideration of user-centered value inquiry and value learning.
