id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
spir-11039	Stark, Luke ; Hoey, Jesse	THE ETHICS OF EMOTION IN AI SYSTEMS	2019.0	4	.pdf	application/pdf	1276	87	44	Many such systems seek to model emotional interactions through “digital phenotyping,” the analysis of biosignals, including optical data (such as facial movement, gait, or infrared emanation); audio data (such as the vocal tone and cadence) (Jain et al., 2015); haptic and physiological data (such as skin conductivity, blood flow, and body velocity) (Picard, 2000); others examine semantic signifiers of emotional expression, including written words, graphic means such as emoji and emoticons, and other representations of human feeling) (Alashri et al., 2016). Yet contemporary, quotidian, narrow AI/ML technologies are most frequently used by social media platforms for modeling and predicting human emotional expression as signals of interpersonal interaction and personal preference (Bucher, 2016).	cache/spir-11039.pdf	txt/spir-11039.txt