  Active participation in a conversation is key to building common ground,
since understanding is jointly tailored by producers and recipients.
Overhearers are deprived of the privilege of performing grounding acts and can
only conjecture about intended meanings. Still, data generation and annotation,
modelling, training and evaluation of NLP dialogue models place reliance on the
overhearing paradigm. How much of the underlying grounding processes are
thereby forfeited? As we show, there is evidence pointing to the impossibility
of properly modelling human meta-communicative acts with data-driven learning
models. In this paper, we discuss this issue and provide a preliminary analysis
on the variability of human decisions for requesting clarification. Most
importantly, we wish to bring this topic back to the community's table,
encouraging discussion on the consequences of having models designed to only
"listen in".
