  There has been upsurge in the number of people participating in challenges
made popular through social media channels. One of the examples of such a
challenge is the Kiki Challenge, in which people step out of their moving cars
and dance to the tunes of the song, 'Kiki, Do you love me?'. Such an action
makes the people taking the challenge prone to accidents and can also create
nuisance for the others traveling on the road. In this work, we introduce the
prevalence of such challenges in social media and show how the machine learning
community can aid in preventing dangerous situations triggered by them by
developing models that can distinguish between dangerous and non-dangerous
challenge videos. Towards this objective, we release a new dataset namely
MIDAS-KIKI dataset, consisting of manually annotated dangerous and
non-dangerous Kiki challenge videos. Further, we train a deep learning model to
identify dangerous and non-dangerous videos, and report our results.
