Emotional States vs Artificial Intelligence - Dissertation Example

?How Do People Attribute Others’ Emotional s, And Could It Be Replaced Using Artificial Intelligence? How Do People Attribute Others’ Emotional States, And Could It Be Replaced Using Artificial Intelligence? Arguably, socializing is a very critical aspect in the society. Consequently, how people comprehend the emotions and feelings of another individual is significant. Such information is helpful because it helps us internalize and work on how to react to result these emotions and feelings (DeCharms, et al., 2005). Such form of emotional and feeling processing has to be fast, since it would allow one to gather enough information in an instant and immediately detect any change in emotion as a reaction to this fast changing world. As many experts have suggested, the application of such system, which are attached to the attribution of emotion, could be an essential technology towards the advancement of how humans interact with machines, and especially the computers. The emotional state Animals in general have a variety of emotional states. These emotional states are tasked with driving certain behaviors for the evolutionary purpose. Notably, they are connected to physiological and cognitive body changes (Damasio, 1994). Take the example of anger. Anger makes humans become more aggressive – there is little room for thought of what will happen after the actions that will ensue. Accordingly, it is possible to create certain models of emotional states with the application of general systems theory. This theory suggests that the universe de cf wq`1VCDS is based on vaarious systems. Some of these are open and can act in response to input from the surroundings while the rest are closed (there is no form of exchange with the surrounding). In itself, the brain is an open system since it processes input from the surrounding environment gathered from the different sense into numerous subsystems before it can be produced as a behavior – an output. Thereafter, the effect of the behavior on the environment is assess, the feedback then goes back to the system so as to diminish the discrepancy that exists between the goal state and the real state. The goal state refers to the homeostasis, where the system wants to end. In essence, it is important to look at such basic systems in order to augments our comprehension of more complex systems. Still with the emotion systems, infants have a basic structure that depicts the emotional components. They use signals like crying to give alerts to the parent of caregiver that they need changing, feeding and other attention. Emotional states are flexible and depend on the environment (Bouchard & McGue, 2003). For instance, the baby changes from being calm to crying then back to calmness when the demand has been settled. Minsky (2006), in his Emotional Machine essay, comes up with a certain model to explain a behavior he terms as a “Rule-Based Reaction-machine”. Herein, the brain functions are simplified into rules of if ‘x’, and do ‘y’, which goes in hand with certain states like bites of hunger to an action like crying, meant towards restoring a homeostasis. It is crucial to note that these rules and emotions become more complex as the brain develops over the years. The emotions end up overlapping as other things like culture enter the scene. As a result, more intricate emotional types are formed, which are separate from the normal instinctual emotions including disappointment and scheming. The advancement of the frontal cortex goes hand in hand with the development of other systems (Deryugina, 2010). It is often though that these emotional states are stage managed by more stable types of personalities. Gray (1981) proposes the Behavioral Inhibition/Activation Systems (BIS/BAS). Here, personality in itself depends with the construction of the brain in terms of neurology. The differences in the two systems will affect how a person will react to reward (BAS) or punishment (BIS). There is lots of evidence that show the linkage of personality to heritability, thus suggesting a biological connection. As the five-factor-model suggests, there are five factors that affect behaviors or emotions in an individual. A person with neuroticism, for instance, has more probability of showing affects of things like depression or anxiety compared to normal humans. Characteristic Emotions An interaction between two individuals ends in a circle of feedback between dyadic emotional states and systems. This way, when one person depicts angers, the other individual may show fear, which is a feedback in itself to the first angry individual. Probably, this maintains or reduces the response of anger if its suits their objectives (Bickmore, Gruber, & Picard, 2005). Consequently, it is crucial to have the ability to pinpoint and comprehend the emotions of another individual. This fact is important because it contributes to being a social apt individual being. Take the example of the Machiavellian intelligence. It suits this situation because it utilized the possibility of detecting a lie. It also misleads the other person via lying for their own good (Fridlund, 1997). It is also critical to be able to detect the emotions of another person because it enables one to come up with and uphold healthy links via conflict avoidance. All this needs the identification and attribution of these emotions. As experts have suggested, there are certain social benefits attached to being able to comprehend and communicate emotions, which suggests the reasons as to why such expression of external emotions is possible. In essence, expressing of emotions enables one to communicate the feelings that are intrinsic, thus producing certain action in other individuals. For instance, a baby cries when it is hungry; therefore it needs to be fed. Another possible use of anger would be to attract submission from another individual. One gets to show his emotional state in by producing certain noticeable expression like raising their voice and widening of the eyes. Consequently, it makes the people around behave in a certain way so as to avoid threat and submission (Gratch & Marsella, 2005). The available information for the formation of such emotional attribution can be drawn for the communication that takes place between two or more people, which includes features linked to facial expressions, behavioral actions and language such as body language. The attribution of these emotions ensures that it enables people comprehend why the other person is emanating these combined features. When a person avoid an eye gaze, for instance, it is expected that they do this because they are avoidant and uncomfortable in a present situation. Lots of information regarding the identification of emotions like anger or happiness can be obtained from the eyes. Any restriction from being able to comprehend this will be linked to the poor comprehension of emotions, as it is a characteristic of autism (Baumeister, Vohs, DeWall, & Zhang, 2007). Emotions can also be acquired from the expression of the voice as depicted by Scherer & Oshinksy (1977). Here, more than two-thirds of the emotional attribution variance in their research could be explained via the manipulation of aural characteristics such as contour, amplitude, and pitch. In the end, the use of body actions like clenched folding of arms or clenched fists can give extra clues to an individual’s underlying emotion. Individual can go for two ways to put to use attributions regarding their emotional states. It is possible to gain a person’s feelings from the surrounding cues are shown in attribution theory (Clarke, 1986). The second method would be imagining how a person would react or feel depending on how they would feel in the same situations – this is empathy. The concerns of attribution theory Attribution theory tells how individual explain the human behavior. It is also concerned with the path they choose to select what they do. The two attribution types possible include internal and external. External attribution associate external factors to the behavioral cause, for instance, other people and the environment. Internal attributions, on the other hand, assign behavioral causes to individual characteristics including attitudes, personality, and mood. This attribution type did add an extra dimension of stability to model put forward by Heider (1958) to explain the differences between invariable causes like personality factors and variable, irregular causes like effort and mood. The biasness in the information presented means that we cannot view the environmental things that pressure an individual, thus people appear to make what Jones & Harris (1967) refer to as fundamental attribution error. Here, the explanations to individual behavior in view of internal factors and not external factors are given. This way, we appear to make more judgment regarding an individual’s emotional stability – concerning their emotional status and personality. One advantage of this is because it avails information that may let a person to better predict future connections and interactions with the individual, which enables us to plan accordingly (Lazarus, 1991). As already explained above, there are only three ways for one to acquire information and evidence to make such attributions: basically facial expressions via body language, language, and actions. People often employ information obtained from other so as to pass judgment about a specific person. Kelley (1967) came up with a co-variation model regarding attribution that includes 3 dimensions that offer information regarding behavioral causes. For one to infer these behavioral causes, one has to link the cause to the specific behavior. If the cause is missing, the behavior should also miss. Such inferences help people to comprehend the emotional causes of such behaviors. The three dimensions include consensus, consistency, and distinctiveness. Consensus refers to how other individual react when facing the same circumstances. Consistency refers to how the person behaves in the circumstance during different times. Distinctiveness refers to whether the behavior is distinct to the specific situation or whether it is applicable to many others. Personality traits are workable using the above dimensions if one is given enough time to stay around a person (Clarke, 1987). For instance, one can discern whether a co-worker is generally reliable if they finish their work in time always. The same applies to other behaviors like never falling ill or going to work in time (Saxe & Baron-Cohen, 2007). Communication can be employed to pick up certain emotions of what other people have in two different ways. The first is from the ability to introspectively pinpoint the emotions in people as well as the ability to affirm and proclaim them. For instance one can proclaim that he or she is happy. It is possible to further explain the causes of such emotions as well. This function is possible so as to pinpoint and discern when emotions can deviate from the normal things, thus allowing for people to act in reaction to them and correct them in advance. However, it is not advisable to describe emotions in an explicit manner – descriptions help in the conveyance of a person’s emotional state (Baumeister, Vohs, DeWall, & Zhang, 2007). For instance if a person is always lively and talks with energy, and their present emotion is subdued or down, it is possible that the person is feeling sad or something sad has happened that is attached to his life. The ability to attain this via language does not necessary need individuals to be conversing face to face. The same can be conversed via computers. The use of emails and instance messaging can convey emotions through the use of things like emoticons or capitalization and grammatical structures. Simulation Theory The other likely model regarding how the emotions of people can be understood includes the capacity to empathise with the individual. Here, it is possible to undergo the emotions of another individual depending on the contextual surrounding of that individual. For instance, it is possible to feel the situation of a person with little time in his hands but with a lot to do. The explanation to this has a lot linked to the way the brain appears to be wired. According to simulation theory, it is possible to comprehend others first by coming up with such empathetic reaction. The reaction lets us gain access to the mental processes that relate to the specific emotion. This allows one to comprehend what sort of behaviors the person may likely show via comprehending what we would do when in the exact situation (Singer & Lamm, 2009). This theory is evidenced by the mirror neurons in the macaque monkeys. Pathways regarding performing and watching motor actions appear to be shared in this aspect. From this, one can discern that the monkeys are observing a motor action; they would have to execute the movements in their heads before they could actually comprehend it. Many other studies have also found out that new born babies can copy certain body actions as performed by adults. For instance, they learn to smile, open their mouths, move fingers, protrude the tongue, and other emotional expressions, as well. "This in itself is the start of a long streak of bonds present in empathy between the self and the other as well" (Bates, 1994). It can be advanced as age strikes in to comprehend the perceptions of intentions and dispositions in other people. Artificial Intelligence Emotional attribution application to machines would be very essential since it would provide numerous resources which can be employed where HCI – human computer interaction can be a concern. The original reason behind the creation of emotional AI was to augment its believability. The same would be helpful in certain tools like the use of anger management or psychotherapy, especially in places where there might be high demand for therapists but constrained time for interaction with the patients. In essence, the ability to find help by clicking on the computer would be a plus in times of need. This use in health care, as explored by Bickmore, uses emotional skills like social dialogue and empathy to uphold a connection with the user over a period to offer automated change in behavior to augment health (West, 1996). Such an application of emotional AI can again be instrumental in the creation of immersion with the frameworks since the characters appear to be more realistic. This could increase enjoyment in entertainment media like videos, which may be added with education to improve the tutoring of small children. This use of emotional AI in areas like gaming could be further employed to stress on essential goals, as well as success/failure to attaining the demands of such goals that can be depicted via emotional cues, thus reinforcing the user. Other appliance of emotion attribution may incorporate devices employed in biofeedback. Such instruments are employed in the measurement of physiological functions as well as feedback the same to the person, which exposes them to regulation and manipulation so as to improve performance and health. Other measures of emotion can be merged with such biological measure to incessantly measure the emotion of an individual (Baron-Cohen, Wheelwright, & Jolliffe, 1997). The same can be employed in anger management to pinpoint to the user that the anger is to treat with this and maintain calmness and offer immediate interventions together with other emotions. Another approach in which emotions can be regulated is via the use of subconscious feedback loops. This incorporates the recognition of the arousing state of the user and feed this back to the system which then reacts to the situation in trying to regulate the optimal levels. Limitations There are several issues and limitations that affect the appliance of human emotion attribution to AI machines. The first would be the level of believability that may end in the Ai falling off into the eerie valley. Though computer scientists try to shun this, the creation of an emotional AI which can read such emotions may be impractical to go beyond this since the application of expression may appear as humanlike and forceful. Moreover, a machine can easily comprehend all of the emotions and may as well adapt because this appears to be unnatural, thus there can be limitation to how far this technology can go. In the same manner, there appears to be an issue on whether this is just the construction of something that looks like what people can do yet it cannot in its entirety match these processes. Humans have come through millions and millions of evolutions years, therefore, it can be at times hard to achieve all this in an instance through AI (Bailenson, et al., 2007). Theoretically, systems are just systems and it does not matter the medium that they are actually on if the process are connection together in the same manner. Most people would share the exact basic modules to create emotional attribution. Each of these brains is distinct yet still shares similar underlying systems. Nevertheless, there are certain limitations as to how one can comprehend everything about the individual. Consequently, it is possible that some of these systems can be concealed from investigation because of their unconscious characteristic. There could be a possibility that the archaic systems have been replaced in essence. However, they are still embedded in the brain, just as the appendix is. Most of these issues and limitation often do with the creation of the same replica of the individual emotion attribution framework. It is easy to curve an exact replica of the human brain, but the creation of human emotional AI would somehow prove to be less valuable in its use. For instance, there are several biases regarding attribution. To comprehend the emotions of other people, it is imperative that we comprehend our own, evidenced by the simulation theory. For this to be a reality, information from the correct body may be required so as to incorporate the understanding of emotions. The application of emotion attribution is dependent on the function of what one wants to come up with. Summary and Conclusion In a summary, people gather many clues from the environment so as to attribute emotions to other people. They can attain this via inferring why a person executes such behaviors, or via empathy in which they envisage themselves as the person in context so as to comprehend and feel such emotions. It is possible in theory to come up with an AI that includes human emotional attribution – systems that are duplicated should be one and the same in spite of the medium they are dependent upon. In the present AI systems that apply the same processes to how people attribute emotions to the rest, none of the AI systems mirror real attribution in full. Thus, it may be possible theoretically but limited in practical terms, which prevents the achievement of this in full. References Bailenson, J., Pontikakis, E., Mauss, I., Gross, J., Jabon, M., Hutcherson, C., et al. (2007). Real-time classification of evoked emotion using facial feature tracking and physiological responses. International Journal of Human-Computer Studies, 66(5) , 303-317. Baron-Cohen, S., Wheelwright, S., & Jolliffe, T. (1997). Is There a “Language of the Eyes”? Evidence from Normal Adults, and Adults with Autism or Aspergers Syndrome. Visual Cognition, 4(3) , 311-331. Bates, J. (1994). The role of emotion in believable agents. Communications of the ACM, 37(7) , 122-125. Baumeister, R., Vohs, K., DeWall, C., & Zhang, L. (2007). How Emotion Shapes Behavior: Feedback, Anticipation, and Reflection, Rather Than Direct Causation. Personality and Social Psychology Review, 11(2), , 167-203. Bickmore, T., Gruber, A., & Picard, R. (2005). Establishing the computer-patient working alliance in automated health behavior change interventions. Patient Education and Counselling, 59(1), , 21-30. Bouchard, & McGue. (2003). Genetic and environmental influences on human psychological differences. Journal of Neurobiology, 54, , 4–45. Clarke, D. D. (1987). Emotion, decision and the long-term course of relationships. . In R. Burnett, P. McGhee, & D. D. Clarke, Accounting for relationships: Explanation, representation and knowledge. (pp. 3 - 21). London: Methuen. Clarke, D. D. (1986). The Heart of the Mind: A speculation on the Fundamentals of Human Psychology. In L. v. Langenhove, J. d. Waele, & R. HarrZ, Individual persons and their actions - Essays in honour of Prof. Dr. J.P. de Waele. . Brussels: Free University of Brussels, University Press. Damasio, A. (1994). Descartes' error: Emotion, reason and the human brain. New York: Grosset/Putnam. DeCharms, R., Maeda, F., Glover, G., Ludlow, D., Pauly, J., Soneji, D., et al. (2005). Control over brain activation and pain learned by using real-time functional MRI. Proc. Natl. Acad. Sci. U.S.A, 102(51), , 18626–31. Demenescu, L., Kortekaas, R., den Boer, J., & Aleman, A. (2010). Impaired Attribution of Emotion to Facial Expressions in Anxiety and Major Depression. PLoS One, 5(12), , e15058. Deryugina, O. (2010). Chatterbots. Scientific and Technical Information Processing, 37(2), , 143-147. Fridlund, A. (1997). The new ethology of human facial expressions. In J. Russell, & J. Fernandez-Dols, The psychology of facial expression (pp. 103-129). Cambridge: Cambridge University Press. Golarai, G., Grill-Spector, K., & Reiss, A. (2006). Autism and the development of face processing. Clinical Neuroscience Research, 6(3-4), , 145-160. Gratch, J., & Marsella, s. (2005). Lessons from Emotion Psychology for the Design of Lifelike Characters. Applied Artificial Intelligence 19(3-4), , 215-233. Issues in Brain and Cognition Research: 2011 Edition. (2012). ScholarlyEditions. Issues in Clinical Psychology, Psychiatry, and Counseling: 2011 Edition. (2012). ScholarlyEditions. Lazarus, R. (1991). Emotion and Adaptation. Oxford: Oxford University Press. Mendl, M., Burman, O., & Paul, E. (2010). An integrative and functional framework for the study of animal emotion and mood. Proceedings of the Royal Society B, 277, , 2895-2904. Minsky, M. (2006). The Emotion Machine. Simon & Schuster. Novaco, R. (2000). Anger. In A.E. Kazdin (Ed.), Encyclopedia of Psychology. Washington, D.C.: American Psychological Association and Oxford University Press. Prensky, M. (2003). Digital game-based learning. Computers in Entertainment, 1(1) , 21. Ritter, W. (2011). Benefits of Subliminal Feedback Loops in Human-Computer Interaction. Advances in Human-Computer Interaction, vol. 2011, Article ID 346492, 11 pages . Saxe, R., & Baron-Cohen, S. (2007). Theory of Mind. Psychology Press. Singer, T., & Lamm, C. (2009). The Social Neuroscience of Empathy. Annals of the New York Academy of Sciences, 1156 , 81-96. Wainwright, J., & Mulligan, D. M. (2004). Environmental modelling: finding simplicity in complexity. New York: Wiley. West, R. (1996). An application of prefrontal cortex function theory to cognitive ageing. Psychological Bulletin, 120(2), , 272-292. Read More