  Digital systems for analyzing human communication data have become prevalent
in recent years. Intelligence analysis of communications data in investigative
journalism, criminal intelligence, and law present particularly interesting
cases, as they must take into account the often highly sensitive properties of
the underlying operations and data. At the same time, these are areas where
increasingly automated, sophisticated approaches systems can be particularly
relevant, especially in terms of Big Data manageability. However, by the
shifting of responsibilities, this also poses dangers. In addition to privacy
concerns, these dangers relate to uncertain or poor data quality, leading to
discrimination and potentially misleading insights. Visual analytics combines
machine learning methods with interactive visual interfaces to enable human
sense- and decision-making. This technique can be key for designing and
operating meaningful interactive communication analysis systems that consider
these ethical challenges. In this interdisciplinary work, a joint endeavor of
computer scientists, ethicists, and scholars in Science & Technology Studies,
we investigate and evaluate opportunities and risks involved in using Visual
analytics approaches for communication analysis in intelligence applications in
particular. We introduce, at first, the common technological systems used in
communication analysis, further discussing the domain-specific ethical
implications, tensions, and risks involved. We then make the case of how
tailored Visual Analytics approaches may reduce and mitigate the described
problems, both theoretically and through practical examples. We show that
finding Visual Analytics design solutions for ethical issues is not a mere
optimization task, but balancing out and negotiating these trade-offs has, as
we argue, to be an integral aspect of the system design process from the
outset.
