Authors:
Jan Ehlers
1
;
Sebastian Alfonso
2
and
Arup Mazumder
3
Affiliations:
1
Department of Computer Science, Bauhaus-Universität Weimar, Schwanseestr. 143, Weimar, Germany
;
2
Unstructured.io, 7580 Horseshoe Bar Rd., Loomis, CA, U.S.A.
;
3
University of Rhode Island, 45 Upper College Rd, Kingston, RI, U.S.A.
Keyword(s):
Cognitive Pupillometry, Affective Processing, Arousal, Decision Making, Automation.
Abstract:
Decision making is a multi-stage process that involves a series of rational evaluations. Recently, bodily arousal has been identified as a factor that mediates individual decisions, particularly during partner selection. The current study investigates pupil size changes in response to facial images of the opposite sex from controlled eye-tracking data (Experiment 1) and by reading out signals from front-facing smartphone cameras in noisy environments (Experiment 2). The aim is to enable automated decision-making in dating apps using arousal-based information. The rating results showed a tendency towards moderate evaluations when coping with facial attractiveness, while pupil diameter did not clearly discriminate between all four rating categories. However, a ROCKET model was trained on the pupil data from Experiment 1 with a prediction accuracy of 77% for binary classification of clearly preferred and non-preferred images. Ambiguous responses will therefore continue to pose a problem
for cognition-aware systems. Capturing pupil diameter from mobile phone cameras resulted in a high proportion of inadequate recordings, probably due to a lack of experimental control. However, an overly systematic approach should run contrary to the intended scenario of lifelike mobile dating app usage.
(More)