  Large language models can be prompted to produce text. They can also be
prompted to produce "explanations" of their output. But these are not really
explanations, because they do not accurately reflect the mechanical process
underlying the prediction. The illusion that they reflect the reasoning process
can result in significant harms. These "explanations" can be valuable, but for
promoting critical thinking rather than for understanding the model. I propose
a recontextualisation of these "explanations", using the term "exoplanations"
to draw attention to their exogenous nature. I discuss some implications for
design and technology, such as the inclusion of appropriate guardrails and
responses when models are prompted to generate explanations.
