Robots React, but Can They Feel?

Robots React, but Can They Feel?

Bruce J. MacLennan (University of Tennessee, USA)
DOI: 10.4018/978-1-60566-354-8.ch008
OnDemand PDF Download:


This chapter addresses the “Hard Problem” of consciousness in the context of robot emotions. The Hard Problem, as defined by Chalmers, refers to the task of explaining the relation between conscious experience and the physical processes associated with it. For example, a robot can act afraid, but could it feel fear? Using protophenomenal analysis, which reduces conscious experience to its smallest units and investigates their physical correlates, we consider whether robots could feel their emotions, and the conditions under which they might do so. We find that the conclusion depends on unanswered but empirical questions in the neuropsychology of human consciousness. However, we do conclude that conscious emotional experience will require a robot to have a rich representation of its body and the physical state of its internal processes, which is important even in the absence of conscious experience.
Chapter Preview


Recent decades have seen a renaissance in the scientific investigation of consciousness, but a fundamental issue has been neglected, which is to integrate the facts of subjective experience with our understanding of physical processes in the nervous system. David Chalmers (1995, 1996) has called this the Hard Problem of consciousness because it poses unique epistemological challenges that make it resistant to straight-forward scientific investigation (see also MacLennan, 1995, 1996). The fundamental problem is that it would seem possible for there to be “zombies” in which all the usual neurophysiological processes take place in the brain, leading to normal behavior, brain scans, etc., but without any accompanying subjective experience (Campbell, 1970; Kirk, 1974; Kripke, 1980). Therefore, it is necessary to distinguish between functional (or access) consciousness, which refers to cognitive and behavioral functions fulfilled by consciousness in an organism, and phenomenal consciousness, which refers to the experience of subjective awareness (e.g., Block, 1995).

The Hard Problem is especially interesting when we consider robot emotions. Emotion is essential to the competent functioning of many animals (arguably, all animals: Panksepp, 2004, pp. 34–7; Plutchik, 2003, pp. 223–6), and synthetic emotion can fulfill similar functions in autonomous robots (as discussed briefly in Background, below). Just as the emotion fear can galvanize an organism and reorganize its cognition and behavior in order to protect itself, so synthetic fear can function for a robot’s self-protection. But will the robot feel afraid? Or, more carefully, what, if any, are the conditions under which a robot would feel fear (as opposed to acting afraid, in both its behavior and cognitive processes)? Thus, my goal in this chapter is to address the Hard Problem of robot emotions.

It bears repeating that the other problems of consciousness are not easy! If they are less hard, it is only because they are amenable to the usual methods of scientific investigation, and don’t pose any unusual epistemological challenges. Certainly, functional consciousness is relevant to robot emotions, but this chapter will focus on phenomenal consciousness and robot emotions. (For a general discussion of robot consciousness, both functional and phenomenal, see MacLennan, 2008a.)

Key Terms in this Chapter

Phenomenology (Phenomenological): Phenomenology, especially as developed by Husserl, Heidegger, and Merleau-Ponty, is the systematic investigation of the invariant structure of experience by empirical, but first-person (q.v.) methods. Accurate phenomenology requires systematic training, which distinguishes it from naive introspection.

Soma: The soma is the cell body of a neuron. Inputs to a neuron causes fluctuations in the electrical potential across the neuron membrane, which are integrated into the somatic membrane potential. In a typical neuron, and to a first approximation, a sufficiently large depolarization of the membrane at the axon hillock (q.v.) will trigger the generation of an action potential (q.v.).

Subjective: There are two distinct but overlapping senses in which something may be termed subjective and contrasted with the objective (q.v.). In the context of this chapter, subjective refers to first-person (q.v.) observation, which is essential to the protophenomenological analysis (q.v.) of emotion. Colloquially, subjective may connote observations and opinions that are biased or distorted, but that is not the intent here, since the purpose of phenomenology (q.v.) is to produce unbiased and factual first-person (subjective) observations.

Protophenomenological Analysis: Protophenomenological analysis seeks to explain the structure of conscious experience in terms of the interdependencies among protophenomena (q.v.) as determined by neurophenomenology (q.v.).

Objective: Objective and subjective (q.v.) are used to make two different distinctions, which overlap, but confusion between the distinctions muddies the mind-body problem. In the context of this chapter, objective refers to a third-person (q.v.) perspective, as opposed to a subjective or first-person perspective (q.vv.). Colloquially, objective connotes the unbiased, factual, and scientific, but that is not the meaning here, since phenomenology (q.v.) seeks unbiased, factual, and scientific knowledge based on subjective observation.

Action Potential: An action potential, also called a neural impulse or spike, is a stereotypical excursion in the membrane potential caused by the opening and closing of ion channels in a cycle of positive feedback and recovery. An action potential is triggered when a membrane is sufficiently depolarized from its normal negative resting potential; positive feedback causes a rapid repolarization in the positive direction, after which there is a relatively slow return to a potential slightly more negative than the resting potential, followed by a gradual return to resting potential. Action potentials propagate down axons without attenuation to convey information to other neurons.

Hard Problem: The “Hard Problem” is the term introduced by Chalmers (1995) to refer to the principal problem of the scientific investigation of consciousness, namely, the integration of the primary fact of conscious experience with contemporary scientific understanding of the material universe.

First-Person: In the context of consciousness studies, first-person refers to the experience of one’s own consciousness. In contrast to third-person observation (q.v.), the observer is not separable from the observed. Such observation is inherently private, but the techniques of neurophenomenology (q.v.) permit the establishment of an observer-independent body of public fact on which scientific theories can be built.

Protophenomenon: Protophenomena are the smallest units of conscious experience, which are hypothesized and investigated on the basis of neurophenomenological research (q.v.), that is, on the basis of coordinated phenomenology (q.v.) and neuroscience.

Axon Hillock: The axon hillock is the base of an axon, that is, the region of a neuron’s soma (q.v.) from which the axon projects. In many neurons it is the place where action potentials (q.v.) are generated.

Third-Person: In the context of consciousness studies, third-person is used to refer to ordinary scientific observation of some object separate from the observer. For example, we may make third-person observations of some physical system, of the brain, or of some person’s behavior (including verbal report). Third-person observation can be a public process grounded in shared observational practices leading to a provisional consensus about observed facts. Often taken to be synonymous with objective (q.v.) and contrasted with first-person and subjective (q.vv.).

Qualia: Qualia (singular: quale) are the felt qualities of phenomena, as aspects of first-person (q.v.) or subjective (q.v.) experience. Examples of qualia are the feeling of warmth of a warm thing, the auditory experience of a C-major chord, the feeling in the gut of anger or fear, and so forth.

Neurophenomenology: Neurophenomenology combines the phenomenological (q.v.) investigation of the structure of experience with the neuroscientific investigation of the neural correlates of that experience. Thus it promises a coherent account of experience from both first-person (q.v.) and third-person (q.v.) perspectives.

Complete Chapter List

Search this Book:
Editorial Advisory Board
Table of Contents
Craig DeLancey
Jordi Vallverdú, David Casacuberta
Chapter 1
Oscar Deniz, Javier Lorenzo, Mario Hernández, Modesto Castrillón
Social intelligence seems to obviously require emotions. People have emotions, recognize them in others and also express them. A wealth of... Sample PDF
Emotional Modeling in an Interactive Robotic Head
Chapter 2
Cyril Laurier, Perfecto Herrera
Creating emotionally sensitive machines will significantly enhance the interaction between humans and machines. In this chapter we focus on enabling... Sample PDF
Automatic Detection of Emotion in Music: Interaction with Emotionally Sensitive Machines
Chapter 3
Christoph Bartneck, Michael J. Lyons
The human face plays a central role in most forms of natural human interaction so we may expect that computational methods for analysis of facial... Sample PDF
Facial Expression Analysis, Modeling and Synthesis: Overcoming the Limitations of Artificial Intelligence with the Art of the Soluble
Chapter 4
Sajal Chandra Banik, Keigo Watanabe, Maki K. Habib, Kiyotaka Izumi
Multi-robot team work is necessary for complex tasks which cannot be performed by a single robot. To get the required performance and reliability... Sample PDF
Multirobot Team Work with Benevolent Characters: The Roles of Emotions
Chapter 5
Matthias Scheutz, Paul Schermerhorn
Effective decision-making under real-world conditions can be very difficult as purely rational methods of decision-making are often not feasible or... Sample PDF
Affective Goal and Task Selection for Social Robots
Chapter 6
Christopher P. Lee-Johnson, Dale A. Carnegie
The hypothesis that artificial emotion-like mechanisms can improve the adaptive performance of robots and intelligent systems has gained... Sample PDF
Robotic Emotions: Navigation with Feeling
Chapter 7
C. Gros
All self-active living beings need to solve the motivational problem—the question of what to do at any moment of their life. For humans and... Sample PDF
Emotions, Diffusive Emotional Control and the Motivational Problem for Autonomous Cognitive Systems
Chapter 8
Bruce J. MacLennan
This chapter addresses the “Hard Problem” of consciousness in the context of robot emotions. The Hard Problem, as defined by Chalmers, refers to the... Sample PDF
Robots React, but Can They Feel?
Chapter 9
Mercedes García-Ordaz, Rocío Carrasco-Carrasco, Francisco José Martínez-López
It is contended here that the emotional elements and features of human reasoning should be taken into account when designing the personality of... Sample PDF
Personality and Emotions in Robotics from the Gender Perspective
Chapter 10
Antoni Gomila, Alberto Amengual
In this chapter we raise some of the moral issues involved in the current development of robotic autonomous agents. Starting from the connection... Sample PDF
Moral Emotions for Autonomous Agents
Chapter 11
Pietro Cipresso, Jean-Marie Dembele, Marco Villamira
In this work, we present an analytical model of hyper-inflated economies and develop a computational model that permits us to consider expectations... Sample PDF
An Emotional Perspective for Agent-Based Computational Economics
Chapter 12
Michel Aubé
The Commitment Theory of Emotions is issued from a careful scrutiny of emotional behavior in humans and animals, as reported in the literature on... Sample PDF
Unfolding Commitments Management: A Systemic View of Emotions
Chapter 13
Sigerist J. Rodríguez, Pilar Herrero, Olinto J. Rodríguez
Today, realism and coherence are highly searched qualities in agent’s behavior; but these qualities cannot be achieved completely without... Sample PDF
A Cognitive Appraisal Based Approach for Emotional Representation
Chapter 14
Clément Raïevsky, François Michaud
Emotion plays several important roles in the cognition of human beings and other life forms, and is therefore a legitimate inspiration for providing... Sample PDF
Emotion Generation Based on a Mismatch Theory of Emotions for Situated Agents
Chapter 15
Artificial Surprise  (pages 267-291)
Luis Macedo, Amilcar Cardoso, Rainer Reisenzein, Emiliano Lorini
This chapter reviews research on computational models of surprise. Part 1 begins with a description of the phenomenon of surprise in humans, reviews... Sample PDF
Artificial Surprise
Chapter 16
Tom Adi
A new theory of emotions is derived from the semantics of the language of emotions. The sound structures of 36 Old Arabic word roots that express... Sample PDF
A Theory of Emotions Based on Natural Language Semantics
Chapter 17
Huma Shah, Kevin Warwick
The Turing Test, originally configured as a game for a human to distinguish between an unseen and unheard man and woman, through a text-based... Sample PDF
Emotion in the Turing Test: A Downward Trend for Machines in Recent Loebner Prizes
Chapter 18
Félix Francisco Ramos Corchado, Héctor Rafael Orozco Aguirre, Luis Alfonso Razo Ruvalcaba
Emotions play an essential role in the cognitive processes of an avatar and are a crucial element for modeling its perception, learning, decision... Sample PDF
Artificial Emotional Intelligence in Virtual Creatures
Chapter 19
Sarantos I. Psycharis
In our study we collected data with respect to cognitive variables (learning outcome), metacognitive indicators (knowledge about cognition and... Sample PDF
Physics and Cognitive-Emotional-Metacognitive Variables: Learning Performance in the Environment of CTAT
Chapter 20
Anthony G. Francis Jr., Manish Mehta, Ashwin Ram
Believable agents designed for long-term interaction with human users need to adapt to them in a way which appears emotionally plausible while... Sample PDF
Emotional Memory and Adaptive Personalities
Chapter 21
Dorel Gorga, Daniel K. Schneider
The purpose of this contribution is to discuss conceptual issues and challenges related to the integration of emotional agents in the design of... Sample PDF
Computer-Based Learning Environments with Emotional Agents
Chapter 22
Emotional Ambient Media  (pages 443-459)
Artur Lugmayr, Tillmann Dorsch, Pabo Roman Humanes
The “medium is the message”: nowadays the medium as such is non-distinguishable from its presentation environment. However, what is the medium in an... Sample PDF
Emotional Ambient Media
Chapter 23
Jordi Vallverdú, David Casacuberta
During the previous stage of our research we developed a computer simulation (called ‘The Panic Room’ or, more simply, ‘TPR’) dealing with synthetic... Sample PDF
Modelling Hardwired Synthetic Emotions: TPR 2.0
Chapter 24
Cecile K.M. Crutzen, Hans-Werner Hein
A vision of future daily life is explored in Ambient Intelligence (AmI). It follows the assumption that information technology should disappear into... Sample PDF
Invisibility and Visibility: The Shadows of Artificial Intelligence
About the Contributors