TY - JOUR
T1 - Guest editorial
T2 - Ethics in affective computing
AU - Gratch, Jonathan
AU - Greene, Gretchen
AU - Picard, Rosalind
AU - Urquhart, Lachlan
AU - Valstar, Michel
N1 - We express our sincere thanks to all the authors and reviewers for extending their cooperation in revising and in preparing the final versions of the papers.
PY - 2024/2/29
Y1 - 2024/2/29
N2 - Stunning advances in machine learning are heralding a new era in sensing, interpreting, simulating and stimulating human emotion. In the human sciences, research is increasingly highlighting the explanatory power of emotions, feelings, and other affective processes to predict how we think and behave. This is beginning to translate into an explosion of applications that can improve human wellbeing including methods to reduce stress and improve emotion regulation skills, techniques to support healthier social media use, pain monitoring in neonates, and decision-support tools that recognize emotional bias.
AB - Stunning advances in machine learning are heralding a new era in sensing, interpreting, simulating and stimulating human emotion. In the human sciences, research is increasingly highlighting the explanatory power of emotions, feelings, and other affective processes to predict how we think and behave. This is beginning to translate into an explosion of applications that can improve human wellbeing including methods to reduce stress and improve emotion regulation skills, techniques to support healthier social media use, pain monitoring in neonates, and decision-support tools that recognize emotional bias.
UR - http://www.scopus.com/inward/record.url?scp=85187003842&partnerID=8YFLogxK
U2 - 10.1109/TAFFC.2023.3322918
DO - 10.1109/TAFFC.2023.3322918
M3 - Editorial
AN - SCOPUS:85187003842
SN - 1949-3045
VL - 15
SP - 1
EP - 3
JO - IEEE Transactions on Affective Computing
JF - IEEE Transactions on Affective Computing
IS - 1
ER -