Prolegomena to a Theory of Communication and Affect
Aaron Sloman
School of Computer Science
The University of Birmingham, UK
http://www.cs.bham.ac.uk/~axs
Abstract
1
As a step towards comprehensive computer models of communication, and
effective human machine dialogue, some of the relationships between
communication and affect are explored. An outline theory is presented of
the architecture that makes various kinds of affective states possible,
or even inevitable, in intelligent agents, along with some of the
implications of this theory for various communicative processes. The
model implies that human beings typically have many different,
hierarchically organized, dispositions capable of interacting with new
information to produce affective states, distract attention, interrupt
ongoing actions, and so on. High "insistence" of motives is defined in
relation to a tendency to penetrate an attention filter mechanism, which
seems to account for the partial loss of control involved in emotions.
One conclusion is that emulating human communicative abilities will not
be achieved easily. Another is that it will be even more difficult to
design and build computing systems that reliably achieve interesting
communicative goals.
1 Introduction
It isn't only for poets that communication and affect are often
inextricably linked. We all know of cases where ill-chosen phrases
provoke bad feeling then hurtful responses, escalating in a positive
feedback loop that ends in tragically damaged relationships. Similarly,
felicitous phrases can soothe painful wounds, or plant the seeds of an
intense and fruitful relationship. What are the mechanisms that make all
this possible? Affective states (as loosely defined below) are among the
most important to us, and also among the least understood. Will
cognitive science ever be able to explain the diversity of communicative
processes found in, for example, flirting, teasing, taunting,
threatening, consoling, enthusing, enthralling, entertaining,
demoralising, deflating, encouraging, inspiring, and inducing
uncontrollable fits of laughter or rage? Can these processes be
simulated on computers? Will intelligent machines ever be able to
advise, help or teach people, without falling foul of the complexities
of human affective reactions?
Full answers would need to delve into many difficult
questions concerning the relationships between affect and information
transfer. It is not only content that can have affective significance:
there are diverse communicative modes, media and
formalisms, many with emotional, motivational, or aesthetic
significance. Besides words, we react to tone of voice,
intonation contours, amplitude, facial expression
and gestures. In all cultures, the mutually enhancing effect of words
and music is found in songs expressing joy, sorrow, resolve, and many
other emotions and attitudes.
Not only deliberate communication needs to be taken into account,
especially as regards affective states. Involuntary changes in facial
expression and color, changes in posture, weeping, wincing, gasping and
the like all help to reveal to others states that we might prefer to
conceal, and sometimes even states (e.g. anger) that we are not aware of
ourselves. Such behavioral expression of affect is surely not just
accidental: from Darwin on, theorists have speculated about the
evolutionary pressures in social organisms that could account for them.
These involuntary communications could have functions for the group or
the species, even if they do not serve the explicit purposes of the
individuals concerned. A society of intelligent agents all able fully to
conceal their internal states at will might be too inefficient: the
constant second-guessing would lead to too many errors of judgement in
which individuals ended up harming each other unnecessarily because they
suspected non-existent malevolence, etc. This point is especially
important in view of the fact, discussed at length in this volume by
Cristiano Castelfranchi, that communication is often not co-operative.
A further complication is that
"third" persons may also be involved, in a variety of different ways.
Their real or imagined affective states may be referred to, expressed
by, a cause of, or caused by the communication. Once again, different
aspects of the communication can be involved in these relations, for
instance the content, the style, or the medium. An example might be the
use by fearful underlings of a whisper, or a special tone of voice, to
avoid offending an awesome overseer.
In order to appreciate the full complexity of our topic the reader may
imagine adding arrows to the diagram below to represent all the
----------
| |
| Others |
| |
----------
------------- -------------
| |--->--content-->--| |
| Utterer |--->---style--->--| Recipient |
| |==>===medium===>==| |
------------- -------------
possible semantic, expressive or causal relations between aspects of an
utterance and the people indicated, including unintended as well as
intended effects.
It may help to use different kinds of arrows for semantic, for
expressive, and for causal relations. It will quickly become apparent
that there is a very tangled network of relationships. The tangle
depicts the topic of this paper. No wonder so many people are so poor at
communication. Can machines do half as well?
I have suggested that an affective state can be involved in
communication, as one of its causes, as a reason or justification, as
its intended effect, as unintended effect, as a side effect of the
medium or mode, or as the content of what is communicated, implicitly or
explicitly. Although I cannot hope to address all of these issues fully,
I shall try at least to give a flavour of some of the
implications for the design of human-machine interfaces and natural
language systems. I hope to show that designers of interactive systems
need caution and humility: it is too easy to overlook something,
when dealing with such a complex and
ill-understood set of mechanisms. I shall present an outline theory of
some of the mechanisms involved in human affective states and use it to
account for some of the ways in which communication can interact with
affective states in the hearer. This will explain why it is
often difficult
for communicators to achieve their goals
and avoid unintended effects. This has implications both for
computer models of human communication and for intelligent machines
designed to communicate with humans, where the communication has
a practical purpose, such as teaching,
persuading or counselling.
2 What Is Affect?
The words "affect" and "affective" do not have a clear, well-defined,
meaning. Different professional groups and even
the same individual at different times use the words in different ways.
The survey by Ortony et al. (1987) implicitly defined affect by contrast
with other categories of mental states. But that assumes we can already
intuitively make the distinction. Moreover their interest was in
describing the structure of the affective lexicon, not in our topic,
namely
explaining how
affective states come about and interact with other states and
processes. Some people and some
dictionaries treat affect as primarily concerned with emotions. The
Concise Oxford Dictionary hints at a more general definition:
"affect n. (Psych) feeling, emotion, desire, esp. as leading to action."
Two questions arise: (a) What does "leading to action" mean
here? (b) What are feeling, emotion and desire supposed to have in
common that distinguishes them from other mental phenomena, such as
thinking, attending and remembering, since all can lead to action? I
shall first give a partial answer to (a), in terms of dispositional
control hierarchies, then discuss (b), and then return to issues of
control and their implications for communication.
Many kinds of mental states are connected with action, but not as
necessary or sufficient conditions. Rather they are
dispositionally related to action. The importance of dispositional
analyses of mental states was argued at length by Ryle (1949,
e.g. chapters IV and V). He was widely misunderstood as proposing a
behaviorist analysis of mental states as dispositions to produce
external behavior. In fact he was far more subtle than that, allowing
some dispositions to produce mental states and processes, which
themselves involve
dispositions to produce other dispositions. In short, dispositions can
be related to one another hierarchically, some having very indirect
links with external behaviour. There are several states that are
dispositional in that they are causally related to possible forms of
behavior that may not actually occur: for example propensities,
inclinations, tendencies, abilities, aptitudes, flairs, traits,
potentialities and the like. All these are capable of issuing in, and
explaining, behavior without constituting necessary or sufficient
conditions for that behavior. They produce their effects via indirect,
defeasible causal links.
The number of steps in the dispositional hierarchy can vary. For
example, a personality that covets popularity might include a high-level
disposition to self-modification so as to acquire attitudes, knowledge
and skills that involve more specific dispositions to do things that
will produce approval and liking in others. Insincere individuals simply
have dispositions to produce the behavior to make them popular, whereas
more sociable and generous personalities have a disposition to react to
the needs of others by desiring to do what will please them, and these
desires involve dispositions to produce the required behavior. All these
dispositions have causal powers that are defeasible: they can be
overridden by other attitudes or desires such as concern for one's
family or fear of losing one's job. Noticing conflicts between attitudes
or desires usually depends on reasoning about the consequences of
various actions. Such inferences are not always made automatically, so
inconsistencies may go unnoticed if the agent lacks the reasoning
ability or is distracted by something else.
So causal connections between mental states and action are sometimes
fairly direct (as in startles), but more often very indirect, going
through several layers of dispositions, where, at each stage, other
dispositions may cause the the effects to be suppressed. (This is
one reason why it is almost impossible to find universal
laws
governing human behavior.)
Later I shall try to show how the hierarchy of dispositions could
explain some of the unintended effects of communication: dispositions at
different levels in the hearer may interact with incoming information in
unexpected ways.
Since dispositions can form hierarchies, the trait/state distinction,
often assumed by psychologists, is not really an absolute distinction.
There are not two kinds of properties, but two kinds of relationships
between properties. What is a state relative to one trait may be trait
relative to another state. Your trait of generosity may produce in you a
state of wanting to help me, and this new state, which is also a trait,
may itself produce in you a state of wanting to know what my troubles
are, and so on. So something can be both a state (produced by a higher
level trait) and a trait (producing lower level states). In this paper,
therefore, whether something is described as a "trait" or as a
"state" will depend on the context.
A partial answer to question (a) then is that affective states are often
dispositions, in various levels of a complex hierarchy. Question (b)
remains unanswered: what distinguishes affective states? Is there
something common to affective states and processes such as moods,
emotions and desires that sets them apart from other mental states and
processes such as perceiving, attending and noticing? Since some
non-affective states are also dispositionally linked to action (e.g.
believing), something else is needed to characterise affect. An easy
answer often attracts people: identify affect with emotion. That might
be acceptable (though possibly too narrow) if there were an accepted,
empirically accurate, theoretically based, notion of emotion. There
isn't. Moreover the suggestion ignores affective states that are not
emotional, such as wanting, liking, and enjoying some physical
sensation. It will be useful to investigate mechanisms underlying
affective states before returning to the question.
3 The Need For Design-Based Theories
I believe a proper analysis of the concept of
an "affective" state or process must be based on a more general
theory of the coarse-grained architecture of mind.
Such a theory, should describe the main sub-mechanisms,
showing how they are related and how their causal roles within the total
system differ. Various functions for mechanisms and states can
be distinguished, but only relative to the whole architecture. For
instance, you can't describe something as a brake except in the context
of an architecture that has at least one component whose speed is
controlled by another sub-mechanism; and without the presence of a brake
you can't describe a system as being in a state of "braking",
though you
can describe it as slowing down. Similarly, a collection of electronic
switches cannot be described as a memory unless they are used by other
parts of the system to store information. Like "braking",
and "memory",
many mental states, including affective states, presuppose a certain
architectural richness. I shall argue that some aspects of the
architecture have implications for communication.
A design-based theory about mental states can be contrasted with two
more common kinds, semantics-based theories and phenomena-based
theories. Semantics-based theories attempt to make sense of the
structure of some portion of the lexicon of ordinary language (e.g.
Ortony et al., 1987; Clore & Ortony, 1988; and Johnson-Laird &
Oatley, 1989, unlike Oatley & Johnson-Laird, 1987, which is a
design-based theory). Phenomena-based theories abound in the writings of
psychologists: they assume that some particular kind of phenomenon can
be intuitively recognized (e.g. emotional states) and then investigate
other phenomena that are correlated with it in some way, e.g.
physiological causes, physiological effects, behavioral responses,
cognitive processes. The three kinds of theories are not incompatible:
some authors combine two or more.
A design-based theory locates human mechanisms within a space of
possible designs, covering both actual and possible organisms and also
possible non-biological intelligent systems. Considering alternative
possible designs leads to deeper theories, partly because the contrast
between different design options helps us understand the trade-offs
addressed by any one design, and partly because an adequate design-based
theory of human affective states would describe mechanisms capable of
generating a wide range of phenomena, thereby satisfying one of the
criteria for a good scientific theory: generality. Such a theory can
also demonstrate the possibility of new kinds of phenomena, which might
be produced by special training, new social conditions, brain damage,
mental disturbance, etc. An ambitious outline design-based theory that
overlaps with those discussed below, is sketched in Johnson-Laird
(1988).
There is
no requirement that a good design-based theory of the
mechanisms underlying affective states should fit colloquial concepts
well, since our language reflects only our common presuppositions about
how minds work, and these presuppositions may well be erroneous.
Although ordinary language is often a suggestive starting point, it is
also, as Simon (1967) warns, a source of muddle and confusion:
" `Emotion', like `learning' and other traditional categories, refers
to a mixed bag of phenomena, which may involve diverse mechanisms"
(page 35n.) Dennett's paper `Why a computer can't feel pain' (in
Dennett, 1978) illustrates some of the incoherence in the concept of
pain - the real reason why a computer can't feel pain. Related muddles
pervade many words and phrases of ordinary language denoting mental
phenomena, especially nouns, such as "consciousness", "sensation"
and "emotion". When we have an architectural theory on the basis of
which we can systematically derive good ways of classifying possible
states and processes, we should expect to revise ordinary language with
a taxonomy of affective states, just as the development of physics and
chemistry gave us a richer and more systematic set of concepts for
talking about different kinds of matter.
4 Towards a Design-Based Theory of Affect
What should a design-based theory of affect look like? Since there is no
well-defined generally used concept of "affect" this is not a
well-defined question. In the light of the preliminary analysis given
above, I suggest that affective states are (a) dispositional states
(long term and short term), (b) at various levels in a control
hierarchy, (c) that include positive or negative evaluations of
something and (d) have at least a tendency to produce motivational
states, (e) which in turn have a tendency to produce behavior. (Some of
the terms used will not be defined here: their ordinary intuitive
meanings, partially clarified in the rest of this section,
will have to suffice for the purposes of this paper.) We'll see
that there is no sharp boundary between affective and cognitive states,
and affective states need not be states the agent is aware of since one
can, for example, be angry or have an attitude, all unawares.
In what follows I shall describe features of an architecture in fairly
non-technical terms. This should be treated as a preliminary
specification, that still needs to be fleshed out with further
implementation details. For example, I have already mentioned
dispositional control hierarchies, without describing any mechanism that
could produce them. There are
obviously various possible implementations.
For example, in a neural net,
higher level networks could modify some of the weights in lower level
networks; and in a rule-based mechanism there could be a hierarchy of
production-systems where the actions of one system include creating or
modifying rules in another lower level system. The neural network model
has the advantage of appearing to be closer to the structure of the
brain. The rule-system model has the advantage of great flexibility if
it allows new collections of rules, corresponding to new attitudes, to
be created easily, as opposed to simply modifying weights associated
with a fixed set of rules.
Other implementations would have to be considered
in a full design-based study, along with detailed analyses of
the implications of the differences.
States in which something is enjoyed, relished, found pleasant, admired
etc., involve explicit positive evaluations and therefore tend to
produce motivations to preserve or extend or reproduce the current
state, or something that causes it, while states in which something is
suffered, disliked, found painful, found unpleasant, despised, etc.,
involve negative evaluations and therefore tend to produce motives to
terminate, shorten, or prevent the state, or something that causes it.
The preceding uses of the word "therefore" presuppose a mechanism
linking positive and negative evaluations with specific classes of
dispositions to produce motivational states. (Having such dispositions
may, in certain simple organisms, be all that such an evaluation amounts
to.)
"Higher level" affective states, for instance, liking jazz or disliking
people of a certain race, may be dormant dispositions until some
cognitive process interacts with the
general attitude to create a specific state directed positively or
negatively at some instance. The new more specific affective state can
either involve a motive to do something, or further relatively high
level dispositions (possibly also dormant for a while) to acquire
motives as a result of later events.
The motivational states themselves (wanting, desiring, etc.) may also be
called "affective",
though some people might wish to exclude motivations
that do not involve a positive or negative evaluation of what is being
done or achieved, as in compulsive desires like nail biting.
People often assume that affective states necessarily involve
some kind of
self-awareness. However, dispositions can lie dormant until their
triggering conditions occur. Such states exist without being involved in
anything one is currently conscious of, attending to or doing. For
example, a person who dearly loves his or her children need not be
constantly aware of that fact, or even thinking about the children: That
would be obsession, not love. Love in its most common
form is best classified as an attitude not an emotion, though most
people, if asked, tend to classify it as an emotion.
The connection between affective states and the motivation that they can
generate is only dispositional, since other things (e.g. guilt,
masochistic enjoyment, fear of consequences, ethical standards, or
distraction of attention)
can override or suppress
any particular tendency
inherent in an affective state.
The same goes for the link between motives
and behavior: you may want to do something, but decide not to,
or believe you don't have the opportunity, etc.
The fact that affective states are related to action only indirectly,
sometimes via several levels in the hierarchy, makes possible
great flexibility of response to the presence, promise or threat of harm
or benefit. The flexibility is achieved by allowing
cognitive states to modulate the way affective states control behavior.
In particular, when
conflicting motives are generated, cognitive processes can play
a role weighing up the pros and cons of the options, or devising a
compromise plan, or selecting a means that achieves one goal while doing
as little damage as possible in relation to the other.
So cognitive states like believing, imagining, attending, perceiving,
pondering, planning, etc. also influence motivation and behavior, but
not normally on their own: they require affective states.
5 Cognitive Reflexes
The rich array of ways in which communication can trigger dispositions
associated with affective states is part of the general flexibility of
control achieved by allowing interacting affective and cognitive states.
This is one of the ways in which intelligent agents differ from
organisms that are dependent primarily on innate reflex responses.
Sometimes, however, there is no time for evaluation, reasoning,
planning, etc., so even intelligent agents often need highly trained and
very rapid responses to new information - "reflexes" in the
non-technical sense. These are cases where a
cognitive state
directly produces (internal or external) action, bypassing processes of
decision-making, production of motives, formation of intentions or
plans, etc. Many skilled performances depend on this kind of shortcut
mechanism linking cognition and behavior. It is not worth arguing
whether the pre-scientific concept of "affect" applies to these
processes or not. The important thing is that they have a role that can
be described precisely in terms of the architecture within which they
function: they short-circuit, or over-ride the normal "intelligent"
control hierarchy, trading risk of error for speed.
Reflex links between cognition and external action can be
directly triggered by verbal communication, but that is rare: they
seem to be mainly designed to cope with fast moving
entities in the physical environment. However, internal trained
reflexes play an important role both in production and in understanding
of speech.
All this is still very vague. In order to be able to design a machine
that can model the affective states involved in communication, or one
that takes account of potential affective states in deciding what to
say to other agents, we need to know more about the nature of these
various dispositional states, the control hierarchies they can
participate in and how they interact with new information to generate
and modify both internal processes and external behavior.
6 Control Hierarchies and Ease of Change
One purpose of communication is to produce or change affective states.
For some states this is much harder than for others. If affective states
include attitudes, moods, emotions, desires, impulses,
and also flushes of embarrassment or sudden pain that
produces involuntary wincing, then different time scales are involved as
well as more or less indirect links with behavior. Moreover, not all of
these states are subject to communicative influence (except perhaps
through hypnosis). This variety of time scales and links with behavior
is to be expected in a dispositional control hierarchy. If state S1
involves a disposition to produce and maintain state S2 or S3 or S4
depending on circumstances, then S1 must be a longer lasting state than
S2, S3 or S4. Compare this with non-hierarchical relations: if S1 merely
initiates
the other states, which then don't require S1 to keep them going, then
they may last longer than S1. X's intense but short term infatuation for
Y can produce long term hatred if Y betrays or callously rejects X.
Closely related to different time scales are different degrees of
changeability and ease of external control. Many painful or pleasurable
sensations can be turned on or off by the addition or removal of the
appropriate external stimulus. Some desires are externally triggered and
turned off (e.g. finding half a worm in the apple you are enjoying), but
many are not directly under external control and often persist till
satisfied or forgotten. Some emotional states can come and go fairly
quickly, but many are deeper and more persistent. Certain moods, like
depression, happiness, calmness, and optimism, are persistent states
with the dispositional power to color and modify a host of other states
and processes. Such moods can sometimes be caused by cognitive events
with semantic content, though they need not be: their causes can, for
instance, be chemical. Similarly, their control function does not
require specific semantic content, though they can influence cognitive
processes that do involve semantic content. Sometimes depression reduces
the likelihood of believing any positively evaluated hypothesis and
increases the likelihood of adopting negatively evaluated ones. Thus if
X is depressed he may be less likely to believe Y's assertion "You are
sure to do well in your examinations", even though X's depressed state
has no cognitive content linking it with examinations. So a machine that
tries to cheer you up may fail miserably if all it can take account of
are your beliefs and attitudes, and not your current mood.
There is a use of "mood" as in "I'm in the mood for X (or
to do Y)" that is close to a desire or inclination and is not a
global semantics-free control state. Although not all such moods can be
influenced by communication, some can, for instance bad tidings that
remove a mood to go to a party. I suspect that there is no general
category of moods. Rather what sort of state the word "mood" refers to
depends on what other words it is combined with: depressed mood,
energetic mood, contented mood, mood for dancing, mood for a cup of
coffee, are all different kinds of temporarily dominant state, some of
which are no more than desires.
Attitudes are longer lasting than moods, yet more changeable than
personality traits, and
more semantically directed than either. They are persistent high level
clusters of beliefs and preferences concerned with the object of the
attitude (a political party, a style of art, a person,
etc). Many different (and potentially inconsistent)
attitudes can coexist in one person and lie dormant
until some specific item of information turns up that interacts with one
or more of them and generates more specific, shorter-lived affective
states.
Thus a prejudiced attitude to people of a certain color may make one
more likely to believe stories about their bad behavior even when there
is little evidence, and can make one both want harsher punishment for
them, and want it more intensely. So, among the internal states that an
attitude can influence are other attitudes, beliefs, the contents of
desires, and the intensity of desires. Sometimes such attitudes can be
changed by new information (e.g. you stop liking someone when you learn
that he has been deceiving you for a long time), but often general
attitudes are very hard to change, a point that skillful communicators,
human or machine, need to understand. (Social psychologists have
explored some of the conditions under which such changes occur, but
I am not aware of any detailed models of the control hierarchies and
cognitive mechanisms involved.)
Unlike global moods, many attitudes, including potentially conflicting
ones, can co-exist, as dormant dispositions, in the same individual.
This means that a communication that is intended to do something about
changing a manifest attitude risks triggering some unwanted reaction
from another hitherto unrevealed attitude. Since dormant attitudes
usually have no visible manifestation, the only ways to check which
attitudes must be allowed for are either to do thorough investigations
of the people one talks to, or to use prior knowledge about their
attitudes. The former option is impractical in most communicative
contexts, and the latter is generally available only if one knows the
person very well. We are therefore inevitably driven to rely on
stereotypes. Intelligent machines will have to do the same.
One aspect of being part of a culture is learning
about the attitudes likely or unlikely to be found in different
sorts of people in that culture. A person (or machine)
that lacks this culture-specific know-how can slip up badly, as
sometimes happens in advertisements in foreign markets, or television
propaganda prepared in one country for broadcasting to another.
Personality and character traits are generally even more durable than
attitudes, and their relationship to action is very indirect, usually
via attitudes that flow from them, and which in turn produce beliefs,
motives, emotional reactions, intentions, etc. and thereby (sometimes)
plans and, ultimately, actions. Communications intended to alter or
mould personality are to be found in psychotherapy, which currently
appears to be more an art than a science. It is sometimes supposed that
computers might one day be psychotherapists (perhaps with more patience
and lower fees than human psychotherapists). However, we need far better
theories about the nature of these high level dispositions and the
mechanisms through which they are formed and modified if this is to be
done well. Apart from psychotherapy there are many forms of personal
counselling to which similar comments apply.
Probably the most common communications intended to shape or change
personality or character are to be found between adults and children at
home and in schools. Judging by the state of the world, it would appear
that computers could hardly do worse than most human adults.
Communication is often more directly aimed at initiating or changing
behavior than at changing personality. Persuading and giving advice
both aim to influence the behavior of the hearer, and this is normally
much easier than changing personality or attitudes. If you
know that a person has a particular attitude this can be used to
generate behavior, simply by giving information that will interact with
that attitude ("There's a spider creeping up behind you"). However,
there are pitfalls: if the communicator does not know about all the
relevant attitudes in the hearer, or does not understand the differences
between relatively low level, easily changed desires,
preferences, plans or intentions, and relatively high level enduring
attitudes or traits then the communication may, at
best, fail, and at worst be crass and insensitive, e.g. "If you think
the manager doesn't value your work enough, why don't you try flattery,
or offering sexual favours: it has worked for others."
All this suggests the following very crude
design-based taxonomy of types of affective states (addressing different
issues from the taxonomies proposed by Ortony et al., and Johnson-Laird
& Oatley, though similar in outline).
1. Dispositional
1.1. Long term, and hard to change by communication
E.g. Personality, character, temperament
1.2. Medium term, and easier to change, though still hard
Co-existing, enduring, mostly dormant, clusters of sub-states:
e.g. ideals, principles, attitudes, interests, desires,
Global states: moods (only one of which can exist at a time),
e.g. depression, undirected happiness.
1.3. Short term, and still easier to change
E.g. Emotions, pains, pleasures, irritations, inclinations.
2. Episodic (with dispositional elements)
2.1. Very short term, some externally controllable, some not
E.g. Pangs, twinges, urges, startles, orgasms, "reflexes" (innate,
trained, etc.)
Other involuntary responses tied to feelings, e.g. wincing, gasping,
smiling, along with the
urge
to do these things (which is sometimes suppressed).
This is not intended to imply that there are only three or four control
layers in the hierarchy of affective dispositions. There is probably no
fixed number: the number of intermediate dispositional states between a
disposition and the behavior that it influences may be different in
different cases. Some architectures would allow new layers to be added
on the basis of learning.
7 Cognition, Affect and Architecture
What has been said so far implies that a theory of communication has
to allow for several kinds of relationship between affective states and
cognitive states with which they interact. For example:
- A cognitive state may interact with a dispositional state to produce
or modify or terminate a manifestation of the disposition in lower level
dispositions, or behavior.
Learning that a spider is approaching can produce a desire to
move away. Learning that most spiders are not at all dangerous may
change the manifestations of one's fear of spiders, even though the fear
persists.
-
A cognitive state or process may modify an existing affective state,
e.g. by increasing or reducing its intensity, or redirecting it.
Learning some new facts may increase or reduce anger, or redirect
it towards another target.
I claimed earlier that a theory of affect requires a design-based theory
of the architecture of intelligent agents. Different architectures
permit different sorts of affective states and processes, just as the
variety and relations of sub-mechanisms in an engine determine the kinds
of dynamic states it can be in. Intelligent agents (e.g. mice, monkeys,
human infants, human adults, and perhaps one day intelligent machines)
can have different architectures, including different cognitive
sub-mechanisms, and this limits the kinds of affective states they can
be in. The sub-mechanisms within an architecture will include some that
determine representational capabilities, which depend for example on the
kinds of structural variation that can be supported. This will make a
difference to the kinds of semantic content available in affective
states: could a goldfish wish its mother were still alive, or have any
other affective state whose cognitive content used the concepts of
mother, being alive,
etc.? Not if the available representational apparatus cannot support the
representation of absent individuals, non-existent states of affairs and
abstract relationships, for example.
Even when mechanisms are available that in principle could have this
representational power, they may not be embedded in an architecture that
gives them this functional role in affective states. Functions of
available sub-mechanisms depend on relationships with other
sub-mechanisms: a pedal in a vehicle would not be an accelerator if it
were not connected to an engine in such a way as to alter its speed. So
certain descriptions and questions that make sense for one organism or
machine may not make sense for another: could a goldfish weigh up
present pain against future pleasure? Could a mouse desperately want its
children to do well? Not if they don't have architectures supporting a
sufficiently rich collection of motivational sub-processes.
If humans have different cognitive architectures at different stages of
development then this needs to be taken into account when communicating
with them. This is grasped intuitively by some parents: they would not
dream of trying to dissuade a very young child from eating sweets by
talking of the sufferings likely to follow in old-age. This is a
pointless exercise if the child lacks the representational apparatus
required to conceive of himself as an old man. Even if suitable
representational apparatus is present, it may be pointless for other
reasons: the child might not yet have developed an architecture with the
functional differentiation required for sub-processes weighing up short
term and long term costs and benefits and deciding accordingly. (Some
people never seem to develop this.)
I suspect that the vast majority of parents do not have any insight into
these matters, though the patient and sensitive few manage without any
explicit theory, by using genetically determined and socially learnt
communicative strategies enhanced and modified by feedback from the
child that indicates whether their attempts at communication are working
or not. Intelligent machines lacking adequate knowledge about the
mechanisms in people would also have to use feedback, but this will
often require powerful perceptual mechanisms.
8 H. A. Simon's Theory
A system that can support a collection of simultaneously active
dispositional states that interact with other states needs a
coarse-grained parallel architecture that makes possible coexisting,
intercommunicating processes. By a coarse-grained architecture I mean a
division into major co-existing, functionally distinct, components that
can influence one another. This functional division does not imply
physical distinctness, as shown by the way in which
a collection of interacting
virtual
processes can be implemented on a time-shared computer. This
coarse-grained parallelism is different from the fine-grained
parallelism of neural-nets studied by connectionists, though neural nets
can support coarse-grained parallelism, if different sub-nets perform
different tasks.
I know of no theory in psychology, AI or cognitive science that begins
to address the full range of architectural requirements, including the
relationships between the dispositional hierarchy and mechanisms of
perception, reasoning, learning, attention, motor-control,
self-monitoring, and so on. There have been some useful initial moves,
however. One influential theory is by H.A. Simon (1967). He attempted to
address criticisms of information processing theories made by Neisser
(1963), by presenting a computational theory according to which all
human thinking involves "an intimate association with emotions and
feelings",
and "almost all human activity, including thinking, serves a
multiplicity of actions at the same time."
Simon sketched a fairly sophisticated computationally inspired
architecture, aspects of which are often re-invented, and used it to
give an analysis of emotions as states in which ongoing activities are
interrupted or disrupted (an idea that others before and after him have
espoused). He did not define the architecture in great detail, and, as
far as I know, no attempt has been made to produce a detailed
implementation, which would require a solution to many hard problems in
AI, including modelling perception, learning, reasoning, planning and
motor control. I shall first summarize Simon's theory and then describe
some recent developments, including a version that allows emotional
states to have the
potential
for interruption without requiring actual interruption. An important
distinction will be made between interrupting behavior and interrupting
attention. The mechanisms proposed will then be related to the task
of understanding how communication can interact with affective states,
and some of the implications for computer models and interfaces
discussed.
Simon's work is based on several fairly obvious key ideas, some already
discussed. Human beings (and other animals) have multiple independent
sources of motivation (including social motives). In particular, new
motives can arise in response to changing external situations or
changing internal states. Humans are also resource-limited (both
relatively slow and largely serial), which is a problem in view of the
fact that the environment (including other agents) is complex, partly
unpredictable and often fast moving, so that constant, asynchronous,
monitoring is required in order to detect unforeseen dangers, obstacles
or opportunities. He outlines some of the control issues, and suggests
suitable mechanisms, inspired in large part by developments in computer
science and AI, including software techniques for generating new
sub-goals at run time, techniques for queueing and scheduling processes,
techniques for forming plans in order to achieve goals, techniques for
assigning priorities and resolving internal conflicts, and techniques
for generating and handling interrupts. He claims that these processes,
especially the interruptions resulting from new information, account for
the states we typically call emotional.
Although he stressed the importance of multiple, changing, motives he
did not say much about where they come from, apart from postulating a
collection of drives whose intensity is a function of the length of time
of deprivation. However, it is clear this does not cover all cases.
Additional sources of motivation are attitudes and other high level
dispositions discussed previously, interacting with incoming
information. More generally, goals that produce new actions or interrupt
or disturb existing actions can arise from new information coming from:
(a) the environment, (b) new internal physiological needs, and (c)
cognitive processes in which associations are triggered, for instance
suddenly remembering something that implies that what you are doing has
a serious danger. Case (a) would include communications from others.
Case (c) could be thought of as communication with oneself.
Simon notes that monitoring of other agents is an important feature of
human processing, and a major source of emotional states. Human beings
need to be particularly good at detecting and interpreting the behavior
of others. Moreover, because people are so complex we often misinterpret
what is happening. Hence, two important kinds of learning are required:
one that increases sensitivity to others and thereby the likelihood of
emotional disturbance, another that improves one's ability to
anticipate, forestall, or cope with interrupting stimuli and therefore
reduces the likelihood of emotional disturbances in social interaction.
Which of these predominates will vary from individual to individual and
over time within one individual. He suggests that adolescence is often a
peak period for the dominance of the first over the second.
Many human beings find such learning very difficult, and consequently
never learn to get on well with others. Some manage to cope only with
others in their own, rather restricted, sub-culture. These are pointers
to the great difficulty of giving machines such knowledge. Perhaps, like
people, intelligent machines in the foreseeable future will be able to
interact well only with members of a restricted sub-culture. Unless they
have powerful learning capabilities of the kinds mentioned by Simon,
along with more general inductive and abductive capabilities, they could
not be expected to deal with a wide variety of individuals. However, our
analysis will show that such learning is very difficult indeed.
9 The Global Signal Theory of Emotions
There are at least two different more detailed lines of development of
Simon's theory. The first can be found in the "global interrupt signal"
theory of Oatley and Johnson-Laird (1987; Johnson-Laird, 1988) and the
second, in the "attention filter penetration" theory of Sloman and
Croucher (1981; Sloman, 1985b; Sloman, 1987).
Oatley and Johnson-Laird (like Sloman, 1978 and 1981b) postulate a
hierarchy of parallel processors all asynchronously dealing with
different tasks, but ultimately managed by some kind of "top level", or
"central", control system. This sort of architecture makes it possible
for processors that detect problems to send out signals that propagate
through the system. Oatley and Johnson-Laird suggest that the global
effect of such signals sets the whole system into a new state when a
problem occurs with an ongoing plan or activity. The new state may
interrupt ongoing plans. The spread of such signals, they claim, is
essentially what an emotion is, though many emotions involve additional
phenomena produced as a result of this disturbance.
They claim that the global signals have no "propositional content". I
suspect that this does not express precisely what they mean.
Propositional content would require the use of bivalent predicates
applied to arguments, logical connectives, quantifiers and the like. It
seems unlikely that most organisms use internal states with a
propositional syntax. But there are many other ways of expressing
semantic content, as I have tried to show, for example, in Sloman
(1971; 1985a). It is probable that many or most animal and human mental
states have
semantic
content but no
propositional
content. If so, saying that emotion signals have no propositional
content does not distinguish emotions from other states, including
some cognitive states using non-propositional representations. I
suspect that what they really mean is that the signals have no
semantic
content - they simply have a
control
function, without including elements that refer to, depict, or describe
objects, events, processes, relationships etc. Related points are made
in Sloman (1989) concerning the way perceptual processes can sometimes
directly produce control signals that change behavior, without always
going via descriptive databases.
One way in which communication could produce an emotional state,
according to Oatley and Johnson-Laird is by providing information that
reveals a new obstacle in an ongoing plan. This would trigger the global
signals that indicate a need to interrupt or perhaps modify the plan. It
is not clear what the full range of possible interactions between
communication and affect would be on this theory, partly because the
theory does not attempt to account for higher level dispositional
affective states.
The global signal theory mainly stresses episodic phenomena as
constituting emotions, i.e. states in which signals are actually
generated and disturb or modify behavior. Our alternative approach, the
filter penetration theory, described below, stresses dispositions,
tendencies, and the like: strong jealousy need not actually divert
attention and disturb or reorganize other processes, if, for instance,
some unrelated activity is temporarily engrossing; but, given half a
chance, the green gremlin will emerge to color thoughts, decisions and
plans. So the theory allows temporarily dormant emotions (if strong
jealousy is an emotion). It also permits more complex and subtle
interactions between information communicated and resulting affective
states, by stressing the impact of emotional states on the potential to
disturb current cognitive processing (attention) rather than on more
general disturbances. I shall now explain this in more detail.
10 Insistent Motives and Filter Penetration
The filter penetration theory is similar to the global signal
theory, but requires extra architectural complexity (implicit in
Simon's paper). Cognitive processes can sometimes involve switches of
attention without interrupting ongoing actions. For example, while
driving on an important errand one can think about other things or enjoy
the scenery before reaching one's destination. This requires an
architecture that allows several high level concurrent processes,
including monitoring the environment whilst controlling actions.
Some activities require a strong focus of attention: perceptual
attention especially, but also sometimes concentrated thought processes
are needed for dealing with a stream of difficulties. If one's thoughts
wander whilst listening to complex instructions the consequences could
later be disastrous. This suggests a need for variable-threshold
interrupt filters to control the ability of new motivators, thoughts, or
percepts to disturb or divert attention. An example would be the soldier
or football player who does not notice an injury that occurs during a
battle or an important match, even though the pain would normally divert
attention. (Attention filters need not be separate mechanisms: all that
is required is that the overal architecture ensures that the potential
for new information to interrupt or disturb ongoing perceptual
or thinking processes is highly context sensitive.)
I am using "attention" in its ordinary non-technical sense: what one is
attending to in this sense is what one is currently thinking about,
looking at, taking care over. (There is a complex family of concepts
related to attention, whose full analysis is not possible here.) The
filter concept makes an architectural assumption that some activities
use cognitive and physical resources that are limited, and that in some
situations diverting them is either dangerous or likely to sabotage some
important goal. Attention filters provide protection against this.
Variable-threshold filtering allows the level of protection to depend on
the importance and vulnerability of the current task.
This mechanism is important only when interruption or diversion of
attention would undermine important activities, which is not necessarily
the case for for all important tasks, for instance those that are
automatic or non-urgent. Keeping the car on the road while driving at
speed on a motorway is very important, but a skilled driver can do it
while thinking about what a passenger is saying, whereas sudden arm
movements could cause a crash. However, in situations where speed and
direction of travel must be closely related to what other cars are
doing, even diverting a driver's attention could be dangerous. So our
theory's focus on diverting or interrupting cognitive processing is
different from the focus in Simon and the global signal theory on
disturbing or interrupting current
actions.
We'll see that some emotional states involve a disposition to divert
attention without necessarily disturbing any action.
All this has implications concerning dimensions of variability of
affective states. Simon mentioned drives, whose intensity increases with
deprivation until a threshold is exceeded whereupon they interrupt
ongoing activities. This does not account for all the phenomena. I have
argued (e.g., in Sloman, 1987) that it is necessary to distinguish several
dimensions along which motivational states can vary, including
insistence, importance and urgency.
"Insistence", of a motive is the basis of its ability to generate
emotional states. This depends on its disposition to divert attention
from other activities. So insistence is defined as the propensity to get
through attention filtering processes and thereby divert and hold
attention. A highly insistent motive will divert attention unless
current activities set the filter threshold level very high. Even then,
the potential for diversion may persist. This is
different from other dimensions of variation of motives, such as
"subjective urgency" (perceived or supposed time remaining before it
will be too late) and relative "importance" to the agent (which may
depend on more or less sophisticated comparisons of means, goals and
higher level ideals and aspirations). These depend on the agent's
assessments, which may, of course be mistaken: subjective urgency may or
may not correspond to actual urgency, and the agent's view of long term
importance of a goal may prove quite mistaken.
Although insistence is different from these other dimensions, it should,
in a well engineered system, bear some relationship to them. Thus the
mechanisms that assign an insistence level, or which do the filtering,
should tend to ensure that only relatively important and urgent topics
will be allowed to divert attention. But this must happen without
complex cognitive processing of the kind that would divert resources! So
insistence is assessed on the basis of relatively quick and simple
(possibly learnt) heuristics, which could be erroneous in some cases.
High insistence of a new motive can cause attention to be diverted
without actually causing any current action to be interrupted or
disturbed. For example feeling very hungry can make a driver consider
whether to stop for a meal, without interfering with the driving.
Interruption might occur if the new goal is judged more important than,
and inconsistent with, the purpose of the current activity, or if the
new one is judged to be very urgent (although not necessarily very
important) whereas the (more important) current activity is not
time-critical and can be temporarily suspended: for instance stopping
for a meal because one has plenty of time before the important meeting.
Alternatively a highly insistent motive that gets through the filters
can be considered and then rejected as relatively unimportant, without
interrupting any important current action. So insistence, the propensity
to divert attention, is not the same as a propensity to interrupt
current actions, except those that require full attention.
None of these kinds of variability of affective states (insistence,
urgency, importance) need be measured on ordinal or other
uni-dimensional scales. Relative importance, for instance, has a number
of facets relating to different needs, ideals, preferences, plans, etc.
and there may be only a partial ordering. Moreover in some cases only
descriptive assessments make sense: "the importance of this goal is
that it contributes to such and such objectives and supports such and
such ideals". In these cases the process of selection between competing
goals could involve very complex reasoning.
There is a lot more to be said about the hardware and software
mechanisms that might implement attention filters, assign insistence
levels, and control thresholds. Different designs will have different
implications, and only some will be fully consistent with how human
beings work. In some designs the filter mechanisms may be only partially
effective, so that although a certain state with high insistence does
not get through the filter it can nevertheless reduce the efficiency or
accuracy of ongoing cognitive processes. This could, for example, be a
consequence of a design based on activity propagation through networks,
where filtering is a matter of degree. We'll ignore such details and
turn to some of the implications of the architecture so far described.
11 Insistent Motives and Loss of Control
In certain situations, insistent motives (and other states) have a
strong tendency or disposition repeatedly to get through the filter,
divert attention and possibly interfere with other ongoing processes,
even if they have already been considered and rejected or even adopted
for future action, for instance when you can't put the worry, shame, or
fiendishly clever scheme for revenge out of your mind; or rather you can
do so only when engaged in some other powerful attention-grabbing
activity (such as sex, gossiping, or watching a film). This sort of
state seems to be common to what we normally think of as strong
emotions: states in which we are "moved" and at least partly out of
control, or would be partly out of control if there weren't a current
activity that makes the filter thresholds unusually high. They are
dispositional states, where the disposition may or may not be realized
in actual diversion of attention.
Insistence, on this analysis, is a
dispositional
state: the highly insistent motive or thought need not actually get
through the filter and interrupt anything. Even if it does get through
it need not actually disturb any current activity. I suggest it is this
strong
potential
for such disturbance and diversion of attention that characterizes many
of the states we describe as emotions. Such states can exist whether or
not attention is actually diverted, and whether or not actions are
thereby interrupted or disturbed. Thus, like jealousy, anger (in the
form of a very insistent desire to harm someone because of something he
is believed to have done that is strongly negatively evaluated) can
persist even though something else occupies attention for a while.
During that time there is no diversion of attention or disturbance of
any action. Dormant dispositions include such emotional states.
As explained above, (and in Sloman & Croucher, 1981; Sloman, 1987) the
assignment of interrupt priorities in a resource-limited agent cannot
depend on complex cognitive processing, for that would defeat the
purpose of the interrupt filter. Such filtering therefore depends on
"quick and dirty", potentially fallible, heuristics. So one of the
tragedies of resource-limited agents in complex, fast changing, only
partly knowable environments, will be that insistence is imperfectly
correlated with subjective and objective importance. What tends to grab
and hold attention is therefore not necessarily always in our long term
interests: one source of inspiration for much great literature.
A detailed computational model of language understanding able to cope
with stories will have to include some understanding of these
mechanisms. Otherwise it might fall into the `rationalist' error of
assuming that human agents always act and think in accordance with their
judgement of relative importance of various options. Some philosophers
have even suggested that such rationality is a defining characteristic
of having such states as beliefs and desires. However, our analysis of
design options for resource-limited agents shows that this is wrong. The
philosophers have not analysed design requirements for intelligent
agents with resource limits (compare the discussion of the `intentional
stance' in Dennett 1978, pages 7-12). Nevertheless, people have an
implicit comprehension of these mechanisms, as shown by their ability to
understand stories of the sort hinted at above. Unfortunately, their
more explicit theories usually oversimplify by assuming insufficiently
sophisticated architectures. (An accurate computer simulation would make
the same mistake!)
Since insistence, as I have defined it, is a matter of degree, the
theory implies that there are only differences of degree between
emotional and non-emotional motivational states. It also implies that
there is much in common between emotional states and those cognitive
states where a particular thought or something like a remembered
experience or tune has high insistence, but does not involve any
particular motivation or positive or negative evaluation.
Some people would restrict the word "emotion" to the case where the
disturbance actually occurs. This seems to be the view of Simon, though
Oatley and Johnson-Laird suggest that an emotional tone can persist
without actually interrupting any action. I think they require this tone
at least to be noticed by the agent, whereas on our theory the state
can persist without any effect on consciousness. It is not clear whether
they would require attention to be diverted. A theory of emotion that
requires
actual
interruption or diversion would imply that if X's anger is temporarily
put completely out of mind by the need to deal with some unrelated
emergency, then X would temporarily not be in a state of emotion.
Someone holding such a theory would either have to say that X was
temporarily no longer angry or else that being angry is not necessarily
an emotional state.
The important point for us is not how to use ordinary language, but to
note that certain designs make it possible for a certain potentially
disturbing dispositional state to continue to exist in a `dormant' form,
during an interval in which some other high priority state dominates
attention and uses a high filter threshold to prevent the disturbance
from occurring. Quibbling about whether the anger or the emotion
`really' exists during this interval is fruitless. The important point
is that there is a state that persists, and can manifest itself as soon
as the diversion is over, and for proper descriptions of the human mind
we need a vocabulary for describing such states, whether or not it
accords with ordinary language.
An implication for a working machine communication system is that an
individual who appears not to be angry, jealous or afraid, may actually
be in a strong, but temporarily dormant, emotional state, masked by some
temporarily engrossing distraction. In such a state, badly chosen words
or phrases might alter insistence levels or filter thresholds,
triggering the emotion to manifest itself and thereby defeating the
purpose of the communication.
The theory also implies that several different emotional
states can co-exist, since many different things may simultaneously have
high insistence with the potential to divert attention. In fact one
emotional state can cause another, even while the first persists.
12 Consequences of the Theory
The extra architectural complexity postulated by the filter penetration
theory beyond what is required for the global signal theory has several
consequences including allowing different kinds of learning. For
instance one kind of learning made possible by the presence of filters
is discovering how to map goals and activities of various degrees of
importance onto appropriate filter thresholds so that when they are
active they will not be interrupted by other things of lesser
importance. Another kind of learning, more like training of a skill, is
modification of the mechanisms or rules for assigning
easily computed
insistence levels to new motives and other potential sources of
disturbance. Too low an insistence level can mean that a matter of life
and death fails to interrupt an activity of only medium importance. Too
high a level can cause attention to be diverted by trivia during
important tasks. Resource limits imply that all such strategies will be
dependent on fallible heuristics, although if there is enough regularity
in the environment, the heuristics can be improved with experience.
Whereas Simon postulated a queue of pending plans or goals, the current
proposal allows several different kinds of queues or information stores
containing motives, for instance one containing motives awaiting
consideration as to whether they should be accepted or rejected and one
containing accepted motives that have not yet been assigned temporal
priorities or conditions for action. Information stores are also
required for current actions, some being pursued in parallel, and some
temporarily suspended for one reason or another. This architecture
allows for idle wishes, and other affective states that generate no
plans or actions.
Different kinds of affective states would be related to whether anything
is in these various stores, what their content is, how they relate to
one another (e.g. inconsistent desires) and what their causal powers are
(e.g. whether they tend to get through the interrupt filter again and
again, and whether they influence other processes, as optimistic and
pessimistic moods do). There is still much work to be done to clarify
this theory, including analysing the similarities and differences
between motives and other attention distractors.
The theory allows that a new piece of information interacting with a
dormant attitude, or with the fact that there is something one has
always wished for but thought could not be achieved, can raise the
insistence level of a motive, thereby generating great excitement, even
if there is no need to interrupt or disturb any current action.
For instance, one might learn unexpectedly that a long-standing wish, on
which one had given up hope, could be achieved by taking action on the
following day, for which one had not yet formed any plans. This example
shows another way in which emotional states need not involve actual
interruption or disturbance of any action or current plan, though the
potential is there, insofar as they would have caused a disturbance had
the current actions been incompatible with the newly awakened goal.
13 Some Computer Modelling Goals
Before discussion the implications further it will be useful to
distinguish different purposes for which a model of affect might be
used. There are different sorts of goals in designing systems
intended to communicate with human beings, including (in order of
increasing difficulty):
- G1
- Getting machines to understand human utterances in the
ways
that people do, for various practical purposes, such as answering
questions or obeying commands.
- G2
- Getting machines to achieve various goals by
communicating
with human beings, such as teaching them, advising them, helping them
solve their emotional problems, etc.
The distinction between
G1 and
G2 is orthogonal to the
distinction between the scientific attempt to model and explain human
capabilities and the engineering goal of building something potentially
useful: both engineers and scientists may adopt either
G1 or
G2, though they will pursue them in different ways. The scientific
modelling task could be characterized as:
- G3
- Getting machines to simulate human affective states
and
processes in detail, including those involved in communication.
In what follows I shall concentrate on the practical goals
G1 and
G2,
while showing how they differ in their requirements for a deep
scientific understanding of the human mind. In particular, if ordinary
language is based, in part, on erroneous theories, that implies that
G1 and
G2 have different requirements. A machine designed
for purpose
G1, or an organism that can do
G1, needs only a
system of concepts based on the same set of possibly erroneous
presuppositions as ours. On the other hand, a machine (or organism)
designed for
G2, i.e. one for which communication is not just an
end in itself, but is a means to such ends as teaching, giving advice
effectively, and more generally communicating with people about various
topics without upsetting, confusing or misleading them, will need to
have, or be based on, a good (i.e. non-erroneous) theory about how minds
work. It may need a whole family of theories, if different people's
minds work partly in different ways (e.g. people in different cultures,
children and adults, men and women). In short, a machine to achieve
G2 reliably would either have to be far superior to most people in
its understanding of the human mind, or else have a collection of
heuristic rules based on a superior theory. For reasons indicated below,
it is unlikely that a really good set of rules could be learned
empirically. Moreover without a good theory underpinning such rules, the
designers couldn't understand how such a machine worked.
Having a (correct) explicit theory about how other minds work might not
be very helpful in practical contexts, if deducing from it how best to
communicate took a very long time. Shallow heuristics might work much
faster. However,
a comprehensive set of heuristics would have to take account of a huge
variety of combinations of mental states that might be dealt with more
economically by a good model.
The deeper theory would enable one to cope with a wider
range of contexts and communicative goals, so ideally an intelligent
communicator should have both, even though the more explicit theory
would be useful only when there's time for complex reasoning.
(Compare knowing multiplication tables and
understanding the principles from which they are derived.) Few people
have both kinds of knowledge about affective mechanisms, and most have
neither, except for a smattering of more or less shallow heuristics.
Because we lack good theories of affective processes it will be a long
time before we can program either kind into a robot nursemaid, or even
provide it with the wherewithal to learn enough itself.
14 Implications of the Theory for Communication
Several implications for processes of communication and the design of
models of communication have already been mentioned, especially the
potential for unanticipated responses when a communication interacts
with one or more dormant dispositions. This is a source of difficulty
for goal
G2. In addition, the attention filter hypothesis implies
that when a person is in an emotional state, communication with that
person may be made more difficult because of the competition for his or
her attention. In order to communicate effectively in such cases special
devices may be necessary to gain and hold the hearer's attention. This
could be important in designing human-machine interfaces intended to
deal with safety-critical situations. If human beings are likely to
become emotionally disturbed in such situations, then strong action may
be needed to ensure that they attend properly to instructions, etc.
Conversely, when a serious problem arises and the human concerned is in
a relaxed and unemotional state, it may be necessary for the machine to
take action to generate an appropriate state of anxiety, or concern,
etc. in order to ensure that the problem receives the person's full
attention. This is obviously the sort of factor that has (wittingly or
unwittingly) influenced the design of alarm systems. However in contexts
where just making a disturbing noise to get people moving is not enough,
for example because detailed instructions have to be given, it will be
necessary for the machine to adopt more sophisticated means of
generating an appropriate level of concern, possibly even using some
irrelevant but attention-getting or anxiety-arousing stratagem to start
with.
In teaching situations more subtle techniques are sometimes required.
These include such things as the use of entertaining examples or
relating what is taught to something the pupil already knows and is
interested in. Detecting situations when these techniques are needed,
and inventing strategies to suit particular individuals, will be beyond
the likely capabilities of intelligent tutoring systems for some time to
come.
Another implication of the theory is that new information provided in
communicative acts can interact not only with current plans and actions,
but also with higher level attitudes, motives, plans, and actions that
are queued, pending, or suspended. A new piece of information can
interact with an attitude to generate a new motive, or can reveal an
unexpected opportunity to achieve something you were not planning to do
but would very much like to do. These processes can interfere seriously
with what the communication was intended to achieve.
Finally, the filter penetration theory offers the germ of an account of
pain and pleasure: both include attention-holding and attention-grabbing
capabilities: the one combined with disposition to want the current
state to continue and the other with a desire for it to end. Some states
of pleasure and pain, bound up with perceptual processes, also include
semantic content, such as reference to a bodily location and what is
happening there.
A comprehensive theory of human emotions would probably have to
incorporate both the global signal theory and the filter penetration
theory, along with, no doubt, other mechanisms.
15 Are Computer Models Possible?
A major difference between the theory proposed here and most other
theories of emotions, is that the latter are intended primarily as
accounts of human and animal emotions, whereas the filter penetration
theory emerges from a general theory about design requirements and
possibilities for intelligent systems, whether biological or artificial.
So this theory regards as peripheral certain aspects of human emotion
(e.g., facial expression and physiological reactions) which other
theories treat as central. They are peripheral because essentially
similar emotional states, with similar social implications, could occur
in alien organisms or machines lacking anything like our expression
mechanisms. Could such states occur in computers?
Although Simon (1967) (and some of my own early papers) suggests that
the kinds of processes we are concerned with here are all computational,
I now think that the notion of mechanism is more general than the notion
of a (Turing-equivalent) computer (see Sloman, forthcoming). For
example, moods might be influenced by chemical, or hormonal, processes
in ways that would not naturally be described as "computational"
except in such a loose sense as to cover almost any process, thereby
making the description trivial and uninformative. What remains in
question is whether the kinds of affective states that can be produced
by such non-cognitive, non-computational, non-semantic mechanisms are
very different in kind from those that are influenced by cognitive
processes. Is a mood of depression or euphoria that is produced by
chemical processes a totally different state from the depression
produced by repeatedly failing to pass your examinations or the euphoria
produced by passing with distinction? Or does the latter kind of process
actually use the former? Even if certain mechanisms that don't look like
computations are used in human beings, functionally similar states might
be produced in robots implemented using standard computing techniques.
Certain human affective states are intimately bound up with our
physiology and the presence of massive and constant feedback from
physiological processes to central monitors. Organisms or machines
without this kind of architecture, e.g., organisms whose bodies had
relatively few built in proprioceptive sites, would not be capable of
having those of our affective states in which a bodily gestalt plays a
key role e.g. physical disgust or sorrowful weeping. Nevertheless, such
alien beings (or intelligent machines), if they had the other mechanisms
I have described, could have closely related states: for instance they
could find certain information disturbing, extremely objectionable and
hard to put out of mind, and the strong desire to take remedial action
might also have high insistence. Thus even without our physical
reactions they could share significant aspects of emotional states such
as disgust or anger. Moreover, like human mathematicians they might feel
great disappointment at the news that some mathematical conjecture had
been refuted: an affective state that need have no accompanying bodily
reaction (outside the brain).
Doubts about the possibility of exact replication of emotions might be
based on the common assumption that emotional states are necessarily
bound up with various kinds of external expression tied to our physical
structure: e.g. smiling, weeping, grimacing, wincing etc. This causal
linkage certainly occurs in human beings and in some cases may be part
of a primordial communicative mechanism, like mating dances in birds,
chemical signals in moths, etc. But there is nothing intrinsic to the
general concept of emotional states like anger and fear, or attitudes
like love, hate or pride, that implies that they should have any direct
bodily effects. Certainly these bodily processes are not essential for
emotions to be important in our social relationships. What makes intense
jealousy matter to us is not the feeling in the belly or the tension,
sweating, shaking or weeping, but the way it interacts with motives,
decisions, beliefs and tendencies to act, and its strong disposition
repeatedly to gain control of one's thought, making it impossible to get
on properly with other tasks, or deal properly with other personal
relationships, etc. Even if a pill could remove the physical effects,
that would not get rid of the jealousy.
The discussion so far suggests that many of the physiological processes
involved in human affect should be regarded as
contingent
features, relics of our evolutionary history (though perhaps some of
them still play an important role in involuntary mechanisms for
revealing internal state in social agents). The more socially
significant, `intrinsic' features of states like grief, fear, joy, love
or hate, could occur in machines or organisms that lack automatic
mechanisms of external expression. For agents without such
uncontrollable external reactions, the communication of an affective
state would
always
have to be a deliberate act, just as it
sometimes
is with us.
One reason why it is important that human physiology is not required for
many of the familiar features of human affective states is that it
leaves open the possibility of certain kinds of empathy between machines
and people. It is a commonplace that one way of trying to understand
another person's reactions is to "put yourself in his place". This is
generally thought of as doing a kind of simulation of the other person
by using one's own imagined reactions. If computer-based machines that
lacked our physiology, and therefore were incapable of simulating our
physiological reactions, could nevertheless simulate the other
significant features of our emotional states, that might help them cope
with the some of the problems of communicating with us. This may not be
all that different from empathising in human beings: one can
imaginatively put oneself the place of a happy or suffering friend
without experiencing any of the physiological reactions.
16 The Boundary between Cognitive and Affective States
I have so far implied that there is a relatively
clear distinction between affective and cognitive states, so that for
example believing that there is a tiger in the next room would be a
cognitive state and being afraid of tigers in general and that one in
particular would be affective states. However the division is not so
clear cut, as can be seen by considering beliefs such as that the tiger
is dangerous.
It is clear that many words and phrases that function grammatically like
factual descriptions of properties of things have a wider significance
than this, relating those things to the needs, preferences, hopes, fears
etc. of speakers and listeners. Words like "dangerous", "safe",
"lovely", "poisonous", "nourishing", "wicked", "admirable", do not only
describe things, they also have affective connotations. Somehow, they
are linked with high level affective states and dispositions.
Philosophers have called these "emotive" or "evaluative" words. In the
classification of Ortony et al. (1987) these would probably go into
something like their category "Subjective evaluations of external
objects".
By using these terms to sum up inferences from factual information to
practical or affective consequences, and storing the conclusions using
such affectively laden words, we can remove the necessity to make the
inferences repeatedly, and we reduce the necessity for separate types of
information store for different kinds of information, e.g. with "X is a
tiger" in one store and some specific association between tigers and
avoidance behavior in another. By combining representations or symbols
with different kinds of meaning, in this sort of way, we seem to be able
to economize on mechanisms for both `internal' and `external'
communication. The same mechanisms that are used for processing factual
information and drawing inferences can therefore be directly integrated
with mechanisms for generating or controlling motives and actions.
Some affective influences of factual descriptions are not part of the
meaning in this extended sense but derive indirectly from what the words
denote, for example the name of someone you hate or fear, a place name
that reminds you of a terrifying experience. Even privately reading or
thinking of words for human body-parts can produce embarrassment or
erotic feelings. Although there are many theoretically possible
computational models that would explain such triggering, it will not be
clear what the design trade-offs between them are until we have a more
complete model of affective states and processes.
17 Further Developments of the Theory
A more complete and detailed model for all this will have to take
account of a wide range of cases, including the effects of known
falsehoods. For example, a story that you know is pure fiction can make
you weep or feel apprehension, relief, joy and the like. Stories, plays
and films work on some deep-seated general link between the mechanisms
used for envisaging or contemplating possible states of affairs and the
mechanisms that trigger affective responses. An odd example of this
mechanism at work is the way verbal mention of fingernails scratching on
a blackboard can cause the same kind of horrible cold shudder as hearing
the event itself. Sorry about that! Much of the power of literature and
effectively persuasive communication depends on these mechanisms that
apparently by-pass or override rational cognitive processes.
A peculiarity of the affective states induced by fictional or imagined
situations is that although they can trigger behavioral expressions of
affect (weeping, shuddering, etc.), and can also generate states that
are close to having real motives (you hope the murderer will be caught,
you want the hero to forgive the heroine, you are disappointed that a
clue is not noticed, etc.) nevertheless these states are decoupled from
the mechanisms that generate decisions and plans for action in the real
world: you are not for a moment tempted to report the murder to the
police, or pass on information about the culprit, unlike children who
want to warn the endangered heroine at a pantomime. There are clearly
different kinds of routes between dispositional affective states and
behavior.
Additional phenomena that need to be explained by a general design-based
theory of the mechanisms involved in communication and affect include
the following:
- Emotional contagion in crowds, as exploited for example by
rabble-rousers and pop stars.
-
How requesting, pleading, begging, exhorting can influence short term
or long term motivational affective states, without depending on
power or authority in the speaker and without relying on arguments to
the self-interest of the hearer.
-
How `powerful' stories, novels, allegories can work on high level
dispositions that are not easily changed.
-
How humour works
-
Hypnotism
-
The nature of aesthetic responses.
-
The influence of communicative media (as opposed to content)
on emotions, including the combined impact of words and music.
18 Implications for Human-Machine Interaction
I have tried to present a design-based theory (admittedly very
incomplete) about some aspects of affective states, along with some of
the implications both for modelling human communication (goals
G1
and
G3) and for designing machines that communicate with human
beings in order to achieve other goals, such as teaching, advising,
helping, or dealing with emergencies (goal
G2).
The latter designs will be very risky unless based on a good theory of
human affective mechanisms. Even people designing unintelligent
interfaces need to remember that users can have all sorts of affective
responses even to relatively simple machine behavior.
2
Intelligent interface designers need to remember that affective states,
whether produced deliberately or not, can have all sorts of influences
on other processes, including the ability to attend, to take in new
information, to perform in tests, etc.
Often the problems are much harder than the obvious HCI issues of
choosing suggestive labels for boxes, selecting the word to denote
errors, designing an `attractive' screen layout, etc. A tutoring
system that always interprets student failings in terms of lack of
ability or lack of knowledge and tries always to give help on that
limited basis will be a failure for many (though not all) students
(du Boulay & Sloman, 1988).
A good teacher often has to know what a student is
feeling and why, and be
able to help the pupil overcome bad feelings that are getting in the way
of both learning and performing. This requires insight into particular
kinds of emotional states in order (a) to be able to detect their
presence and (b) know how to deal appropriately with them. A
student who is frightened of the task or the teacher has to be treated
differently from one who is worried about a suspected disease, or who is
in pain after dental treatment.
However, detecting some affective states, especially dormant attitudes,
that have no behavioral symptoms,
can be very difficult. Predicting how a known attitude will interact
with the next utterance can also be difficult, because it will depend on
which other, possibly dormant, states are present. The problems cannot be
dealt with simply by doing some initial tests to determine the student's
affective state (e.g. using a standard questionnaire) and then assuming
the result for the rest of the interactive session. Depending on the
type of interaction it may be very important to be continually on the
lookout for evidence of motivational or emotional change, and then to
adjust the communicative strategy accordingly.
19 Doing Without a Good Model of the User
I have tried to show that for certain purposes, e.g. producing a machine
that understands human linguistic utterances as well as people do (i.e.
for goals of type
G1) it may not be necessary to have a
correct
theory about how people work. It will generally suffice that the machine
shares the presuppositions, right or wrong, that are built into our
ordinary language for describing mental states. Examples of pioneering
attempts to give machines this kind of ability are reported in Colby
(1982), Lehnert (1987), and Dyer (1987). Doing this well requires the
designers, if not the machine, to have a correct theory about the
(possibly wrong!) theories presupposed by ordinary language.
Alternatively it may be possible to design machines that learn such
things by interacting with people.
However, designing machines in such a way that they not only share human
understanding, but can actually use communication effectively for the
other purposes listed above (i.e. goals of type
G2) requires a
correct theory of how human minds work. Practical success, however, does
not require that the whole theory be explicitly formulated: some aspects
may be implicit in successful heuristic rules, including rules that
allow the interaction to be modified using corrective strategies based
on feedback from the client or student.
This would require great advances in computer vision and speech
understanding in order to detect relevant changes in facial expression,
or tone of voice, etc.
For scientific purposes the use of heuristic rules that give adequate
results, without any explanatory theory, would not be so satisfactory.
Moreover the communicative task is harder when there is no scope for
correction because the instruction or information has to be expressed the
right way the first time. This is more likely to be achieved if based on
good models of listeners, even if they are only models of general
types of user rather than very detailed models developed separately for
each individual. Often there is not enough time, so using some
stereotype is inevitable: this may be satisfactory as long as (a) there
are enough different stereotypes to match the variety of potential
users, (b) the tests for identifying the appropriate stereotype are good
enough, and (c) the stereotypes are based on rich and deep enough models
or rules to cope with the complexities described above.
Failure to understand the extreme context sensitivity of affective
control hierarchies can mislead mathematically minded psychologists into
postulating purely probabilistic mechanisms linking situations with
behavior. Equally, it may tempt designers of intelligent interfaces to
use probabilistic rules for predicting or interpreting human behavior,
or for generating communicative actions. It must be admitted that
statistical inferences do give remarkably precise predictions for some
kinds of mass behavior (otherwise psephologists would be out of
business), but predicting what proportion of the masses will vote for X
is no basis for knowing how to talk to an individual. Successful
communication often needs to take account of that individual's precise
set of relevant affective states, including those that are currently
dormant but might easily be triggered. There is probably no foolproof
way of achieving that, for humans or for machines. Dormant dispositions
that interfere with communicative intentions are often impossible to
detect, and may surprise even the individual concerned. So machine
advice, tutoring, etc. will be at least as risky as communication
between humans.
20 Conclusion
I have presented the outlines of a theory of affect that
shows that some of the more ambitious attempts to design machines that
can communicate effectively with human beings will need to take
account of at least the following:
- A hierarchy of long term affective dispositional states that can be
difficult to discern, difficult to change, and likely to interact with
new information in a manner that depends on other affective and
cognitive states.
-
Relatively easily changeable global states, like depressed or
optimistic moods
that can influence responses to new information without
having any relation of cognitive content.
-
Relatively short term emotional states that may interfere with the
attention required for coping with new information, or may interact
with new information in unexpected ways.
-
The need to generate new emotional states in order to hold the
receiver's attention properly.
-
The existence of dormant plans, goals, wishes, including actions that
were suspended, previously formed intentions and conditional plans
waiting for opportunities.
-
The existence of learnt `reflexes' linking the advent of new
information with fast, uncontrollable mental or physical reactions.
All of these phenomena are difficult to cope with in others because
discovering the relevant information about an individual's state of mind
can be very difficult, though sometimes involuntary expressive behavior
gives clues. These phenomena would also need to be understood in order
to produce realistic models of human communication.
- The need to base communication on culture-specific and other
stereotypes, because of the impossibility of checking all relevant facts
about the hearer.
Sometimes an alternative to discovering the individual's
state of mind is to use a collection of general models of the
kinds of attitudes and high level dispositions to be expected in certain
sub-classes of people, for instance members of a sub-culture, or
children of a certain age. The task of assigning an individual to such a
class is often easier than discovering his beliefs and attitudes. This
strategy is apparently (unconsciously) employed by people, but has
obvious dangers and limitations. A powerful learning system would be
needed in order to build up a set of such models, but because of the
difficulty of checking the classification of individuals even the
learning task is inherently error prone.
Even when a lot is known about an individual's current affective state,
it may be very difficult to give effective advice or persuasion because
changing some of the higher level states can be difficult. In extreme
cases nothing short of writing powerful novels will suffice.
A more complete design-based investigation would consider the brain
mechanisms underlying these functional states, and would survey
different possible mechanisms in which all this might be implemented, in
order to understand fully the advantages and disadvantages of any one
design. This would give insight into selective pressures that could help
us understand how human mechanisms might have evolved.
I think it is clear that giving machines all, or even most, of these
abilities will be well beyond the state of the art for many years to
come. But it is important to keep trying, both as one of many ways to
increase our self understanding and because there may be worthwhile
practical results. At the very least, studying the problems may give us
clues as to how to remedy some of the many deficiencies in communication
between people.
Acknowledgements
I am grateful to several colleagues who have either commented on an
earlier draft or discussed these issues with me, including
Aluizio Araujo,
Margaret Boden,
Monica Croucher,
Glyn Humphreys,
Keith Oatley (the respondent at the workshop),
Helen Petrie,
David Young,
Nicola Yuill and
Andrew Ortony,
whose editorial criticisms and suggestions have been particularly
helpful. Some of the ideas reported here were developed while the
author held a GEC Research Fellowship.
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NOTE:
Since this paper was written many of the theoretical ideas have
been further developed. For more information see
http://www.cs.bham.ac.uk/research/projects/cogaff/
http://www.cs.bham.ac.uk/research/cogaff/talks/
http://www.cs.bham.ac.uk/research/cogaff/misc/AREADME.html
Footnotes:
1
Paper presented, Nov 1990, to NATO Advanced Research Workshop
on "Computational theories of communication and their applications:
Problems and Prospects". Published in
Ortony, A., Slack, J., and Stock, O. (Eds.)
Communication from an Artificial Intelligence Perspective:
Theoretical and Applied Issues.
Heidelberg, Germany: Springer, 1992, pp 229-260.
Also available as Cognitive Science Research Paper,
CSRP-91-05, The University of Birmingham.
Accessible online at http://www.cs.bham.ac.uk/research/cogaff/
2
We found, when we first started teaching programming using the
language Pop-11, that printing the word "Error" caused distress in some
students. We therefore changed it to "Mishap".
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