  The increasing reliance on digital information necessitates advancements in
conversational search systems, particularly in terms of information
transparency. While prior research in conversational information-seeking has
concentrated on improving retrieval techniques, the challenge remains in
generating responses useful from a user perspective. This study explores
different methods of explaining the responses, hypothesizing that transparency
about the source of the information, system confidence, and limitations can
enhance users' ability to objectively assess the response. By exploring
transparency across explanation type, quality, and presentation mode, this
research aims to bridge the gap between system-generated responses and
responses verifiable by the user. We design a user study to answer questions
concerning the impact of (1) the quality of explanations enhancing the response
on its usefulness and (2) ways of presenting explanations to users. The
analysis of the collected data reveals lower user ratings for noisy
explanations, although these scores seem insensitive to the quality of the
response. Inconclusive results on the explanations presentation format suggest
that it may not be a critical factor in this setting.
