  The impact of cognitive biases on decision-making in the digital world
remains under-explored despite its well-documented effects in physical
contexts. This study addresses this gap by investigating the attractiveness
halo effect using AI-based beauty filters. We conduct a large-scale online user
study involving 2,748 participants who rated facial images from a diverse set
of 462 distinct individuals in two conditions: original and attractive after
applying a beauty filter. Our study reveals that the same individuals receive
statistically significantly higher ratings of attractiveness and other traits,
such as intelligence and trustworthiness, in the attractive condition. We also
study the impact of age, gender, and ethnicity and identify a weakening of the
halo effect in the beautified condition, resolving conflicting findings from
the literature and suggesting that filters could mitigate this cognitive bias.
Finally, our findings raise ethical concerns regarding the use of beauty
filters.
