  The bridging research between Human-Computer Interaction and Natural Language
Processing is developing quickly these years. However, there is still a lack of
formative guidelines to understand the human-machine interaction in the NLP
loop. When researchers crossing the two fields talk about humans, they may
imply a user or labor. Regarding a human as a user, the human is in control,
and the machine is used as a tool to achieve the human's goals. Considering a
human as a laborer, the machine is in control, and the human is used as a
resource to achieve the machine's goals. Through a systematic literature review
and thematic analysis, we present an interaction framework for understanding
human-machine relationships in NLP. In the framework, we propose four types of
human-machine interactions: Human-Teacher and Machine-Learner, Machine-Leading,
Human-Leading, and Human-Machine Collaborators. Our analysis shows that the
type of interaction is not fixed but can change across tasks as the
relationship between the human and the machine develops. We also discuss the
implications of this framework for the future of NLP and human-machine
relationships.
