Difference between revisions of "Emotion Recognition Algorithms (ERAs)"
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Emotion recognition algorithms (ERAs) are a form of emotion recognition technology and artificial intelligence that recognizes, infers, and harvests "emotions using data sources such as social media behavior, streaming service use, voice, facial expressions, and biometrics..." <ref>Andalibi, Nazanin and Buss, Justin. (2020). ''The Human in Emotion Recognition on Social Media: Attitudes, Outcomes, Risks;'. CHI 2020.</ref>. Emotion recognition algorithms are artificial intelligence technologies that are used in many different contexts including customer service (CITE), employment <ref>Robert, L. P., Pierce, C., Marquis, L., Kim, S., & Alahmad, R. (2020). Designing fair AI for managing employees in organizations: a review, critique, and design agenda. Human–Computer Interaction, 35(5-6), 545-575.</ref>, health and wellbeing (CITE), and law enforcement (CITE), and these algorithms can be useful in identifying information pertaining to the context, but they may also be invasive to individuals (CITE). | Emotion recognition algorithms (ERAs) are a form of emotion recognition technology and artificial intelligence that recognizes, infers, and harvests "emotions using data sources such as social media behavior, streaming service use, voice, facial expressions, and biometrics..." <ref>Andalibi, Nazanin and Buss, Justin. (2020). ''The Human in Emotion Recognition on Social Media: Attitudes, Outcomes, Risks;'. CHI 2020.</ref>. Emotion recognition algorithms are artificial intelligence technologies that are used in many different contexts including customer service (CITE), employment <ref>Robert, L. P., Pierce, C., Marquis, L., Kim, S., & Alahmad, R. (2020). Designing fair AI for managing employees in organizations: a review, critique, and design agenda. Human–Computer Interaction, 35(5-6), 545-575.</ref>, health and wellbeing (CITE), and law enforcement (CITE), and these algorithms can be useful in identifying information pertaining to the context, but they may also be invasive to individuals (CITE). |
Revision as of 21:39, 25 January 2022
Emotion recognition algorithms (ERAs) are a form of emotion recognition technology and artificial intelligence that recognizes, infers, and harvests "emotions using data sources such as social media behavior, streaming service use, voice, facial expressions, and biometrics..." [1]. Emotion recognition algorithms are artificial intelligence technologies that are used in many different contexts including customer service (CITE), employment [2], health and wellbeing (CITE), and law enforcement (CITE), and these algorithms can be useful in identifying information pertaining to the context, but they may also be invasive to individuals (CITE).
History
Emotion recognition roots can be traced back to Paul Ekman[3] who, in 1975, identified what he found to be "basic" and "universal" emotions: anger, disgust, fear, joy, sadness, and surprise.[4] As technology has advanced, emotion recognition technologies such as artificial intelligence algorithms have emerged using much of Ekman's work.
EAIs on Social Media
Many companies such as Google [5] have begun to use emotion recognition and have patents for them to analyze user data through emotions.
Benefits and Harms of EAIs
See also
References
- ↑ Andalibi, Nazanin and Buss, Justin. (2020). The Human in Emotion Recognition on Social Media: Attitudes, Outcomes, Risks;'. CHI 2020.
- ↑ Robert, L. P., Pierce, C., Marquis, L., Kim, S., & Alahmad, R. (2020). Designing fair AI for managing employees in organizations: a review, critique, and design agenda. Human–Computer Interaction, 35(5-6), 545-575.
- ↑ https://en.wikipedia.org/wiki/Paul_Ekman
- ↑ Paul Ekman and Wallace V Friesen. 1975. Unmasking the face: A guide to recognizing emotions from facial cues.
- ↑ Puneet Agrawal. 2017. Emotionally connected responses from a digital assistant. Retrieved June 26, 2019 from https://patents.google.com/patent/WO2017078960A1/en