Data is a powerful tool to make informed decisions. They can be
used to design products, to segment the market, and to design policies. However,
trusting so much in data can have its drawbacks. Sometimes a set of
indicators can conceal the reality behind them, leading to biased decisions that
could be very harmful to underrepresented individuals, for example. It is challenging
to ensure unbiased decision-making processes because people have their
own beliefs and characteristics and be unaware of them. However, visual tools
can assist decision-making processes and raise awareness regarding potential
data issues. This work describes a proposal to fight biases related to aggregated
data by detecting issues during visual analysis and highlighting them, trying to
avoid drawing inaccurate conclusions.
