  Nudging is a behavioral strategy aimed at influencing people's thoughts and
actions. Nudging techniques can be found in many situations in our daily lives,
and these nudging techniques can targeted at human fast and unconscious
thinking, e.g., by using images to generate fear or the more careful and
effortful slow thinking, e.g., by releasing information that makes us reflect
on our choices. In this paper, we propose and discuss a value-based AI-human
collaborative framework where AI systems nudge humans by proposing decision
recommendations. Three different nudging modalities, based on when
recommendations are presented to the human, are intended to stimulate human
fast thinking, slow thinking, or meta-cognition. Values that are relevant to a
specific decision scenario are used to decide when and how to use each of these
nudging modalities. Examples of values are decision quality, speed, human
upskilling and learning, human agency, and privacy. Several values can be
present at the same time, and their priorities can vary over time. The
framework treats values as parameters to be instantiated in a specific decision
environment.
