"One-Size-Fits-All"? Examining Expectations around What Constitute "Fair" or "Good" NLG System Behaviors
arxiv(2023)
摘要
Fairness-related assumptions about what constitute appropriate NLG system
behaviors range from invariance, where systems are expected to behave
identically for social groups, to adaptation, where behaviors should instead
vary across them. To illuminate tensions around invariance and adaptation, we
conduct five case studies, in which we perturb different types of
identity-related language features (names, roles, locations, dialect, and
style) in NLG system inputs. Through these cases studies, we examine people's
expectations of system behaviors, and surface potential caveats of these
contrasting yet commonly held assumptions. We find that motivations for
adaptation include social norms, cultural differences, feature-specific
information, and accommodation; in contrast, motivations for invariance include
perspectives that favor prescriptivism, view adaptation as unnecessary or too
difficult for NLG systems to do appropriately, and are wary of false
assumptions. Our findings highlight open challenges around what constitute
"fair" or "good" NLG system behaviors.
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