Traditional Emotions & Methods; Emotions Research Themes

1. CIIC 5995-100 / ICOM 5995-100
Human Perspective in Artificial Intelligence
(HPAI)
Professor José Meléndez, PhD
“To understand the basic emotional operating systems of the
brain, we have to begin relating incomplete sets of neurological
facts to poorly understood psychological phenomena that
emerge from many interacting brain activities.”
- Jaak Panksepp (1942-2017)

2. Today
• Emotions IV
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3. Report
• Project Report & Software
• “Mini Mind Modules – Inner Robots & Bias”
• Subject to Due Dates Vote
• Due Friday May 15, 2020 by 11:59PM

4. Required Reading – Keep up the Pace
• Influence Tactics by Dr. George Simon Jr. (on Moodle)
• Excerpt of Chapter 6 of Character Disturbance: The
Phenomenon of Our Age
• The kinds of things we want AI to help us with.
• How Emotions are Made: The Secret Life of the Brain
• Chapter 6: How the Brain Makes Emotions
• Chapter 7: Emotions as Social Reality
• Chapter 8: A New View of Human Nature
• Chapter 9: Mastering Your Emotions
• Chapter 13: From Brain to Mind: The New Frontier
• The brain integrates, “so much information from multiple sources
so efficiently that it can support consciousness.”

5. Next Up
• Emotions
• A Traditional View
• In Decision Research
• In Artificial Intelligence Systems

6. Science of Emotion – Traditional View
• Emotions characterized by attributes:
• Something that “happens to” you
• “Flavors”: Positive, Negative, Neutral
• Eliciting or intentional object (aboutness)
• Enable pursuit of goals (serve function)
• Inhibit pursuit of goals
• Multi-component response
• Subjective (what it feels like)
• Body aspects (physiological including brain)
• Outward display of behavior

7. Emotion “Classification” – Traditional View
• Basic/Discrete
• Anger, Disgust, Fear, Happiness, Anger and Disgust
• Plus more “complex” emotion concept words
• Affective Circumplex
• Two Dimensional “State” (static - not time dependent)
• Valence (pleasant/unpleasant)
• Arousal (agitation/calmness)
• Primary classification systems limited to discrete or
steady-state responses.
• Akin to classifying your thoughts
• “Classification” of emotion is square peg in round hole

8. Affective Circumplex
How Emotions are Made, Figure 4-5

9. Affective Circumplex
• Flawed model of limited utility for Emotion Implementation
• Transforms diverse subjective concepts into subjective and
arbitrary dimensions (recall Feldman’s tribal studies)
• Requires to label emotions as good (pleasant) or bad
(unpleasant)
• Does not capture emotional space as continuous
• Creates false non-subjective, quantitative sense
• ”Low Arousal” is arbitrarily large negative quantity and not
approximately zero!!
How Emotions are Made, Figure 4-5

10. Emotion “Elicitation”
• Handbook of Emotion Elicitation and Assessment
• Tools & Methods to Elicit emotions
• Film clips (audio & visual) – reactivity, regulation,
understanding
• Static photos (visual) – Arousal and Valence “standard”
levels
• “Relived Emotions” – semi-structured of influence
• Autobiographical
• Shared memories (e.g. 9/11)
• Dyadic Interaction (“live”) – how you feel

11. Example: Elicitation – Static Photos
https://www.researchgate.net/figure/A-sample-of-standardized-images-classified-as-representing-each-basic-emotion-within-the_fig2_280312285

12. Example: Elicitation – Static Photos
https://www.researchgate.net/figure/A-sample-of-standardized-images-classified-as-representing-each-basic-emotion-within-the_fig2_280312285

13. Example: Elicitation – Static Photos
https://www.researchgate.net/figure/A-sample-of-standardized-images-classified-as-representing-each-basic-emotion-within-the_fig2_280312285

14. Example: Elicitation – Static Photos
https://www.researchgate.net/figure/A-sample-of-standardized-images-classified-as-representing-each-basic-emotion-within-the_fig2_280312285

15. Example: Elicitation – Static Photos
https://www.researchgate.net/figure/A-sample-of-standardized-images-classified-as-representing-each-basic-emotion-within-the_fig2_280312285

16. Example: Elicitation – Static Photos
https://www.researchgate.net/figure/A-sample-of-standardized-images-classified-as-representing-each-basic-emotion-within-the_fig2_280312285

17. Example: Elicitation – Static Photos
https://www.researchgate.net/figure/A-sample-of-standardized-images-classified-as-representing-each-basic-emotion-within-the_fig2_280312285

18. Example: Elicitation – Static Photos
https://www.researchgate.net/figure/A-sample-of-standardized-images-classified-as-representing-each-basic-emotion-within-the_fig2_280312285

19. Example: Elicitation – Static Photos
https://www.researchgate.net/figure/A-sample-of-standardized-images-classified-as-representing-each-basic-emotion-within-the_fig2_280312285

20. Example: Elicitation – Static Photos
https://www.researchgate.net/figure/A-sample-of-standardized-images-classified-as-representing-each-basic-emotion-within-the_fig2_280312285

21. Example: DEAP Data Set - Summary
• The DEAP dataset consists of two parts:
• The ratings from an online self-assessment where 120
one-minute extracts of music videos were each rated by
14-16 volunteers based on arousal, valence and
dominance.
• The participant ratings, physiological recordings and face
video of an experiment where 32 volunteers watched a
subset of 40 of the above music videos. EEG and
physiological signals were recorded and each participant
also rated the videos as above. For 22 participants
frontal face video was also recorded.
https://www.eecs.qmul.ac.uk/mmv/datasets/deap/readme.html

22. Example: DEAP Data Set - Files
https://www.eecs.qmul.ac.uk/mmv/datasets/deap/readme.html

23. DEAP Data Set – Online Ratings
https://www.eecs.qmul.ac.uk/mmv/datasets/deap/readme.html

24. DEAP Data Set – Elicitation Videos
https://www.eecs.qmul.ac.uk/mmv/datasets/deap/readme.html

25. DEAP Data Set – Participant Ratings
https://www.eecs.qmul.ac.uk/mmv/datasets/deap/readme.html

26. DEAP Data Set - Questionnaire
https://www.eecs.qmul.ac.uk/mmv/datasets/deap/readme.html

27. Example: DEAP Data Set - Files
https://www.eecs.qmul.ac.uk/mmv/datasets/deap/readme.html

28. Example: DEAP Data Set – File Details
https://www.researchgate.net/profile/Joseph_Erlichman/publication/230864997/figure/fig34/AS:341917163376655@1458530812418/Surface-map-of-EEG-electrode-locations.png

29. Example: DEAP Data Set - Files
https://www.eecs.qmul.ac.uk/mmv/datasets/deap/readme.html

30. Example: DEAP Data Set - Files
https://www.eecs.qmul.ac.uk/mmv/datasets/deap/readme.html

31. Example: DEAP Data Set – Data/Videos
https://www.eecs.qmul.ac.uk/mmv/datasets/deap/readme.html

32. Next Up
• Emotions in Decision Research
• Emotions for Artificial Intelligence Systems

33. Emotions – Decision Research
https://scholar.harvard.edu/files/jenniferlerner/files/emotion-and-decision-making.pdf?m=1450899163

34. Emotions – Decision Research Themes
• Globalization of communications
• Variances more important when not “local”
• More regular international / inter-cultural interactions
• Previously more structured / business communications
• Emotional influence in decision making
• Generational changes
• Increasing individuality in business and work

35. Emotions – Decision Research Themes
https://scholar.harvard.edu/files/jenniferlerner/files/emotion-and-decision-making.pdf?m=1450899163
• Integral Emotions Influence Decision Making
• A Beneficial Guide
• Bias
• Incidental Emotions Influence Decision Making
• Unrelated Bias
• Moderating Factors
• Valence is Only One of Many Dimensions
• Differences of Emotions of Same Valence
• Appraisal Tendencies (Implicit Goals)
• Emotions Shape Decisions via Content of Thought

36. Emotions – Decision Research Themes
https://scholar.harvard.edu/files/jenniferlerner/files/emotion-and-decision-making.pdf?m=1450899163
• Emotions Shape Decisions via Depth of Thought
• Systematic vs Automatic Processing
• Role of Certainty
• Emotions Shape Decisions via Goal Activation
• Action Tendencies
• Motivations
• Emotions Influence Interpersonal Decisions
• Navigation of Social Decisions
• Emotional Communication and Expectation
• How to Reduce Unwanted Effects of Emotion
• Time Delay
• Suppression
• Reappraisal
• “Dual-Emotion Solution”

37. How to Reduce Unwanted Effects of
Emotion “Urges” to Eat
• Carry a bottle of water around – use as urge “anti-
dote”
• Thinking about benefits of not eating it
• Deferring as reward

38. How to Reduce Unwanted Effects of
Emotion “Urges” to sleep in
• A quick 10 push-ups – blood/oxygen activity
• More alarms
• Alarm off with puzzle – thinking activity

39. Next Up
• Emotions for Artificial Intelligence Systems