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Lecture 2: Theories of Emotion While We Wait Outline Lecture 2: Theories of Emotion While we wait Outline . Review why emotion theory useful – Give some positive and negative examples . Introduce some features that distinguish different theories – Emotions as discrete or continuious – Emotions as “atoms” or “molecules” – Emotions as a consequence or antecedent of emotin . Review some specific influential theories . Break . In-class “experiment” . Evidence for and against dual-process models of emotion . Appraisal Theory . Review a mental health application of affective computing Why should we care about emotion theory? What is a Theory . Theory explains how some aspect of human behavior or performance is organized. It thus enables us to make predictions about that behavior. – Provides a set of interrelated concepts, definitions, and propositions that explains or predicts aspects of human behavior by specifying relations among variables. – Allows us to explain what we see and to figure out how to bring about change. – Is a tool that enables us to identify a problem and to plan a means for altering the situation. – Create a basis for future research. Researchers use theories to form hypotheses that can then be tested. – Creates a basis for building software: suggests what variables are important to measure and how they relate to each other Example of dangers of atheoretical approaches (e.g., Data Mining) . We’ll learn about machine learning approaches – Collect bunch of data – Look at lots of features and try to predict some outcome Input Predicted features output . Enables us to make predictions about that behavior . Does not typically allows us to explain what we see and to figure out how to bring about change . This can easily lead us astray Famous example . In ‘80s, the Pentagon wanted to harness computer technology to make their tanks harder to attack. The research team went out and took 100 photographs of tanks hiding behind trees, and then took 100 photographs of trees - with no tanks. They trained a neural network. It reached near-perfect accuracy . Independent testing showed all “no tank” photos taken on sunny day and all “tank” photos taken on sunny day . Because neural network was “black box”, this not easy to discover Affective Computing Example . Last week, showed you system that tIn tries to recognize nonverbal signs of depression and PTSD . We collected data from two populations – Craigslist (and online job-recruiting service) – US Vets: organization that provides mental-health service for former soldiers . Tried machine learning approach . Discovered vocal pitch a strong predictor of depression – Lower pitch predicted depression severity – Not predicted by existing theory . Turns out there was big imbalance in our data – US Vets had highest rates of depression – US Vets also had highest rates of Males (most soldiers are male) – We actually “discovered” that men speak with a lower pitch Advantages of building on theory . Theory makes explicit the mechanisms that (are claimed to) underlie some behavior – Allows us to explain what we see and to figure out how to bring about change . Theories (typical) have good empirical support – The theories we will discuss are supported by dozens of empirical studies – They may still be incorrect of insufficient but are unlikely to suffer the sort of mistakes we just discussed Example: Appraisal Theory World Events Mental State (beliefs, goals) Argues for importance of three If we know two of these interrelated concepts variables, we can make • World events Body predictions about the third • Mental state (e.g. goals) Expression • Emotional Response Response= f(Env., Mind) Action Tendency Physiological Response 10 E.G.: Generating Emotional Response R=f(E,M) Environment Beliefs, Goals COMPUTER PREDICITONS: Emotional Response • Computer could predict what Expression emotion a person might hold Action Tendency • Computer could generate a Physiological Response believable emotion to user 11 E.G.: inferring emotional antecedents M=f-1(E,R) Reverse Appraisal Environment Beliefs, Goals COMPUTER PREDICITONS: Emotional Response • Computer could predict what Expression goal person has (i.e., what Action Tendency team are they rooting for Physiological Response 12 Another Example: Galen’s 4-process model of emotion Posits 4 “prototypical emotions”. Emotions organized in 2-dimensional space (valence, arousal) Argues emotions tend to transition along arrows. “Angry” “Happy” “Arousal” “Apa- “Sad” thetic” “Valence” Galen’s 4-process model of emotion Prototypical emotions associated with 4 specific physiological systems YB Bl “Angry” “Happy” “Arousal” BB Ph “Apa- “Sad” thetic” “Valence” Popular 2-dimensional model of emotion Each prototypical state associated with a characteristic expression YB Bl C S Angry Happy “Arousal” BB Ph M P Sad Apathetic “Valence” Again, this theory affords implementation and prediction . Recognition “language” YB Bl – 4 “prototypical” emotion labels but C S – 2 dimensions Angry Happy . Dimension 1 Dimension Predictions BB Ph – If we recognize Anger expect YB is active M P – If recognized Anger, don’t expect transition to Apathetic Apathy Sad – If BB active, expect sad expressions and self- Dimension 2 report of Sadness . Control – Can create Apathy by activating Ph system or suppressing other systems – Can’t control Ph by activating Apathy A Hippocratic physician would prescribe treatment to void the body of Theory of the imbalanced humor. if it was a fever -- a hot, dry disease -- the culprit was yellow bile. So, the doctor would try to increase its opposite, phlegm, by Four Humours prescribing cold baths. If there were obvious symptoms of excess phlegm by Galen of Pergamun (c. 180AD) production, the regimen would be to bundle up in bed and drink wine. Yellow Blood Hot Bile (Fire) Choleric Sanguine Black Phlegm Bile Temperature Melan- Phleg- choly matic Cold (Air) Dry Wetness Wet (Earth) A good theory is “falsifiable” (Water) Why should we care about emotion theory . Provides a definition of “emotion” and other related concepts that influence, or are influenced by emotion, and thus a starting point for affective “computing” . Unfortunately, psychology hasn’t sorted it all out yet – Different theories suggest different concepts and relationships between them . E.g., Say we want to recognize emotion – Give labeled data to machine learning algorithm – But what are the labels? . Discrete Emotion Theory: focus on discrete labels: Joy, Hope, Fear . Dimensional Emotion Theory: argues discrete emotions do not exist. Instead should focus on broad dimensions: valence and arousal . Affective computing researchers must make educated guess about which theory to use – But their success or failure can help inform research in the social sciences Scientific approach Theory Data • e.g.,Psychology Rapport (positive, Human • contingent,Linguistics nonverbal feedback) Behavior • facilitatesNeuroscience conflict • resolutionEconomics Embed capability within interactive Rapport virtual human Integrated testbed “Test bed” MRE SASO-ST Gunslinger RapportDCAPS 19 Scientific approach Inform theoretical Verify Implementation debate in social • Consistent with prior science Human findings? Behavior • Treated “as if” real Test theoretical predictions Human Integrated Studies “Test bed” MRE SASO-ST Gunslinger RapportDCAPS 20 For us, A theory should answer “What is emotion?” . Emotion is a feeling . Emotion is a state (of physiological arousal) . A brain process that computes the value of an experience --- Le Doux . A word we assign to certain configuration of bodily states, thoughts, and situational factors – Feldman Barrett. God’s punishment for disobedience -- St Augustine What is emotion NOT? From Scherer What is an emotion? What is an emotion? . Components of emotion Emphasizes that emotion potentially impacts several aspects – Cognitive: influences or influenced by thinking – Physiological: related to hormones, heart-rate, sweating… – Expressive: relates to facial expressions, posture, vocal features – Motivation: relates to goals and drives – Feeling: relates to conscious awareness being in an emotional state What is an emotion? . Phases of emotion: Emphasizes that emotions have “stages” – Low-level: automatic cognitive processes (e.g., reflexes) – Hi-level: deliberate, conscious cognitive processes – Goals/need setting – Examining action alternative: decision-making/action-selection – Behavior preparation – Behavior execution – Communication with other What is an emotion? . Different theories emphasize different aspects: – Appraisal theories emphasize cognitive antecedents of emotion – Discrete emotion theories emphasize physiological and expressive consequences of emotion . Affective computing researchers tend to draw on different theories depending on the aspects they focus on – E.g : emotion recognition techniques often draw upon discrete emotion theory and avoid appraisal models What is an emotion: theoretical disagreements . Different theories can be distinguished by how they chose to define emotion with respect to the previously-mentioned components and phases – Is emotion discrete or continuous? – Is emotion an “atom” or “molecule”? (Barrett) – Is emotion an antecedent or consequent of cognition? Emotions as discrete categories, Emotions are a combination of several biologically fixed, universal to all humans psychological dimensions and many animals Basic Emotions: Anger, disgust, fear, happiness, sadness, surprise Rene Decartes, Silvan Tomkins, Paul Wilhelm Wundt, James Russell, Lisa Ekman Feldman Barrett Some discrete models
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