Cited by 7,382Emotion and Mood RecognitionInnovative Human-Technology InteractionPsychiatry, Mental Health, Neuroscience

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Affective Computing

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Picard, Rosalind W.·1997·MIT Press

DOI 10.7551/mitpress/1140.001.0001

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Abstract

According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions. The latest scientific findings indicate that emotions play an essential role in decision making, perception, learning, and more—that is, they influence the very mechanisms of rational thinking. Not only too much, but too little emotion can impair decision making. According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions. Part 1 of this book provides the intellectual framework for affective computing. It includes background on human emotions, requirements for emotionally intelligent computers, applications of affective computing, and moral and social questions raised by the technology. Part 2 discusses the design and construction of affective computers. Although this material is more technical than that in Part 1, the author has kept it less technical than typical scientific publications in order to make it accessible to newcomers. Topics in Part 2 include signal-based representations of emotions, human affect recognition as a pattern recognition and learning problem, recent and ongoing efforts to build models of emotion for synthesizing emotions in computers, and the new application area of affective wearable computers.

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Authors: Picard, R. W.
Affiliations: MIT Media Lab (US)
Corresponding author: Picard, Rosalind W.
ORCID: Picard, Rosalind W.
Venue: MIT Press
Publisher: The MIT Press
Published: 1997-09-24
DOI: 10.7551/mitpress/1140.001.0001
OpenAlex: W2339343773
Cited by: 7,382
References: 0
Citations by year: 2026: 376 · 2025: 295 · 2024: 212 · 2023: 266 · 2022: 208 · 2021: 274 · 2020: 322 · 2019: 356 · 2018: 283 · 2017: 279 · 2016: 301 · 2015: 318 · 2014: 315 · 2013: 335 · 2012: 329
FWCI: 92.96
Type: book
Language: en
Open access: green
hdl.handle.net
Licence: cc-by-nc-sa
Locations: The MIT Press eBooks (publishedVersion)
PsycEXTRA Dataset (publishedVersion)
DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc)
Topics: Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
Physical Sciences › Computer Science › Artificial Intelligence › Psychiatry, Mental Health, Neuroscience
Keywords: affective computing, emotion recognition, emotion models, emotion synthesis, wearable computers, human-computer interaction, decision-making, pattern recognition

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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Affective Computing

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cited by

Related

Metadata

Record

About these checks