PhD Document - Universidad de Las Palmas de Gran Canaria

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CHAPTER 2. THE CASE OF SOCIAL ROBOTICS contrary, autistic savants would be able to access raw information 1 . Figure 2.2: Children can not identify the couple sharing sexual intimacy (right) because they lack prior memory associated with such scenario. They can see nine dolphins (left). Representative of this theory is the case of the autistic savant child Nadia [Selfe, 1977]. At about three and a half years, Nadia could draw natural images with great detail, without training. She could draw a horse with amazing detail and perspective. Normal children aged four drew the horse with much less fidelity, usually side-on and with rough ellipses representing the main body parts. Normal children drew according to their mental schema, Nadia drew what she saw. Another astonishing example of this theory is represented in Tem- ple Grandin [Grandin, 1995, Grandin and Scariano, 1986], an autistic but highly functional person, who has an extraordinary visual intelligence. She herself points out that she stores information in his head as if it were a CD-ROM disk. Her thought patterns work with specific examples, while normal people move from the general concept to specific examples. Often, she struggles to comprehend things that people consider evident. The reason that leads us to associate autistic savants with computers/robots sheds light as to what makes a robot be observed as such. Typically, we tend to think in terms of what could make a machine more human-like. Here, the approach is to think in terms of what 1 Recently, a deficit in the activity of "mirror neurons" (MN) has been linked to autism (see [Williams et al., 2001] for example). MNs are active when monkeys perform certain tasks, but they also fire when the monkeys watch someone else perform the same specific task. A similar mechanism has been indirectly observed in healthy humans, but not at the same level in autistic people. Note that, essentially, the phenomenon involves two different perceptions that are "unified" at a neurological level. Such unification may be indicative of the formation or use of the concept ("hand-waving", for example). An explanation based on a difficulty in working with concepts at a conscious level (instead of the detailed perceptions) would also account for this phenomenon as a particular case. 14
CHAPTER 2. THE CASE OF SOCIAL ROBOTICS makes a human more machine-like 2 . This is not just unbalanced performance (i.e. abilities that are present in humans but not in the robot). The point is that autistic savants can easily accomplish tasks that require much effort for us (calculus, calendars, etc.) whereas they struggle to accomplish tasks that are trivial and almost automatic for us (like social tasks) 3 . We try to build robots that look and behave like (healthy) humans. Then why do non- autistic people build machines that turn out to be "autistic"? On the other hand, in Artificial Intelligence it is a well-known fact that certain tasks that are trivial for humans are hard for computers/robots and vice versa. But why is it so? The following sections propose an explanation for these two important questions. 2.2 Unconscious Mental Processes From the discussion in the previous section now it seems clear that if we try to somehow model human intelligence and behaviour we will do it from an unavoidable concept-driven point of view. Some details will remain hidden to our awareness, for it seems that, in healthy adults, an enormous amount of processing is done unconsciously. Nowadays, the existence of unconscious processes in our brain seems to be be- yond doubt [Wilson and Keil, 1999]. Freud’s work already acknowledged that unconscious ideas and processes are critical in explaining the behaviour of people in all circumstances. Helmholtz [H. von Helmholtz, 1924], studying vision, pointed out that even basic aspects of perception require deep processing by the nervous system. He argued that the brain con- structs perceptions by a process of unconscious inference, reasoning without awareness. Blindsight [Weiskrantz, 1998] refers to a set of residual visual functions, like the ability to locate a source of light, in cortically ("physically") blind patients. The cortical blindness is a result of the visual cortex’s destruction, caused by tumours or other causes. The fact is that patients have those abilities, though they consistently claim not to see the stimuli. Moreover, the abilities are present even in unconscious (comatose) patients. Face recognition, an ability which obviously falls within the ambit of social intelligence, is another example of unconscious processing. We do not know what features in a face tell us that the face belongs to individual X. Yet, we carry out that process fast and 2 An interesting aspect to explore is the "Confederate Effect": in the annual Loebner’s Contest (a version of the Turing test in which human judges try to distinguish chatbots from humans in a text conversation) some human interlocutors have been considered machine-like [Shah and Henry, 2005]. 3 Note that this confirms the two conditions for building a more "human" robot, already suggested in the previous chapter. That is, a) replication of a large number of human abilities and, b) that these abilities have similar performance levels. 15
Page 1: Departamento de Informática y Sist
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CHAPTER 5. PERCEPTION Figure 5.7: E
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CHAPTER 5. PERCEPTION Classify cues
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CHAPTER 5. PERCEPTION Figure 5.10:
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CHAPTER 5. PERCEPTION 5.3 Audio-Vis
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CHAPTER 5. PERCEPTION modules, inst
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CHAPTER 5. PERCEPTION each angle we
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CHAPTER 5. PERCEPTION hypothesis is
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CHAPTER 5. PERCEPTION M4.- Pattern
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CHAPTER 5. PERCEPTION nods and shak
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CHAPTER 5. PERCEPTION effect of thi
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CHAPTER 5. PERCEPTION effects of am
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CHAPTER 5. PERCEPTION image decreas
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CHAPTER 5. PERCEPTION with an incre
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CHAPTER 5. PERCEPTION However, we a
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CHAPTER 5. PERCEPTION where y0 is t
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CHAPTER 5. PERCEPTION be distinguis
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CHAPTER 5. PERCEPTION in the sense
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CHAPTER 5. PERCEPTION a) b) c) d) F
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CHAPTER 5. PERCEPTION the habituati
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Chapter 6 Action "CHRISTOF: We’ve
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CHAPTER 6. ACTION Expression: "Surp
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CHAPTER 6. ACTION 6.1.3 Implementat
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CHAPTER 6. ACTION Figure 6.3: Facia
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CHAPTER 6. ACTION c α error 0 o 0.
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CHAPTER 6. ACTION fear anger sorrow
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CHAPTER 6. ACTION However, we belie
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Chapter 7 Behaviour "A good name, l
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CHAPTER 7. BEHAVIOUR used defines t
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CHAPTER 7. BEHAVIOUR step environme
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CHAPTER 7. BEHAVIOUR Predicate Desc
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CHAPTER 7. BEHAVIOUR Action Descrip
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CHAPTER 7. BEHAVIOUR Name Action to
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CHAPTER 7. BEHAVIOUR ➔ Basic emot
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CHAPTER 7. BEHAVIOUR [Reilly, 1996]
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Chapter 8 Evaluation and Discussion
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CHAPTER 8. EVALUATION AND DISCUSSIO
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Chapter 9 Conclusions and Future Wo
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CHAPTER 9. CONCLUSIONS AND FUTURE W
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Appendix A CASIMIRO’s Phrase File
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APPENDIX A. CASIMIRO’S PHRASE FIL
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Bibliography [Adams et al., 2000] B
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BIBLIOGRAPHY [Bruce et al., 2001] A
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BIBLIOGRAPHY [Driscoll et al., 1998
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BIBLIOGRAPHY [Hernández et al., 20
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BIBLIOGRAPHY [Kjeldsen, 2001] R. Kj
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BIBLIOGRAPHY [Martin et al., 2000]
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BIBLIOGRAPHY [Oviatt, 2000] S. Ovia
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BIBLIOGRAPHY [Schulte et al., 1999]
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BIBLIOGRAPHY [Tyrrell, 1993] T. Tyr
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Index absolute pitch, 16 action sel
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INDEX proprioception, 39 prosopagno
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PhD Document - Universidad de Las Palmas de Gran Canaria

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