I previously posted the
abstract and conference slides of this working paper, presented a few weeks ago at the annual conference of the Philosophical Society of Southern Africa, held in Port Elizabeth this year. What appears below is a working draft of the paper, edited down to the word limit for submission to the conference volume.
The
Natural History of Desire
David Spurrett – UKZN –
spurrett@ukzn.ac.za
Abstract
In Thought
in a Hostile World (2003) Kim Sterelny develops an idealised natural
history of folk-psychological kinds. He argues that under certain selection
pressures belief-like states are a natural elaboration of simpler control
systems which he calls detection systems, and which map directly from
environmental cue to response. Belief-like states are distinguished by the
properties of robust tracking (being occasioned by a wider range of
environmental states, including distal ones), and response breadth (being able
to feature in the triggering of a wider range of behaviours). A key driver,
according to Sterelny, of the development of robust tracking and
response-breadth, and hence belief-like states, are properties of the
informational environment. A transparent environment is one where the
functional relevance to an organism of states of the world is directly
detectable. In a translucent or opaque environment, on the other
hand, states significant to an organism map in less direct or simple ways onto
states that the organism can detect. A hostile environment, finally, is
one where the specific explanation of translucency or opacity is the design and
behaviour of competing organisms. Where the costs of implementing belief-like
states pay their way in more discriminating behaviour allocation under
conditions of opacity and hostility, Sterelny argues, selection can favour the
development of decoupled representations of the environment.
In the
case of desires, however, Sterelny maintains that the same arguments do not
generalise. One justification that he offers for this view reasons that unlike
the external environment, the internal processes of an organism are under
significant selection pressure for transparency. Parts of a single organism,
having coinciding interests, have nothing to gain from deceiving one another,
and much to gain from accurate signalling of their states and needs. Key
conditions favouring the development of belief-like states are therefore absent
in the case of desires. Here I argue that Sterelny’s reasons for saying that
his treatment of belief doesn’t generalise to motivation (desires, or
preferences) are insufficient. There are limits to the transparency that
internal environments can achieve. Even if there were not, tracking the
motivational salience of external states calls for pervasive attention to
valuation in any system in which selection has driven the production of
belief-like states.
1.
Introduction
In his (2003)Thought in a Hostile
World Sterelny develops a detailed articulation of an approach suggested in
Godfrey-Smith (1996, 2002). Godfrey-Smith’s proposal, the Environmental
Complexity Hypothesis (ECH), maintains that “the function of cognition is to
enable the agent to deal with environmental complexity.” That is, as an explanatory
hypothesis, the ECH proposes that the capacity which cognition gives
organisms having it, and which is responsible for its success under natural
selection, is responding more effectively to heterogeneity in their
environments. For present purposes I simply accept the ECH. I happen to support
it as a fruitful research programme, but won’t offer a defence. (For broadly
supportive lines of critical comment on Sterelny 2003 see Papineau 2004, and
for criticism on points of detail see Christensen 2010.) My aim, rather, is to
develop a line of thinking internal to the ECH, and which concerns the
specific treatment of motivational states in Sterelny’s (2003) book.
Sterelny
describes his objective as combining two integrative projects that arise when
humans are studied from a naturalistic perspective. One ‘internal’ project
concerns the “wiring and connection facts” about human cognitive architecture,
and aims to assemble a “coherent theory of human agency and human evolutionary
history”. The other ‘external’ project attempts to relate the conclusions of
the first project to the ways some social sciences (including psychology,
anthropology, and economics) have produced “refined versions of our folk
self-conception”, where that self-conception is that we are intentional beings.
Complementing the “wiring and connection facts” these projects focused on
intentional action have produced the “interpretation facts” (Sterelny 2003,
3-5).
Sterelny
frames his own proposal against the backdrop of a position he calls the “Simple
Co-ordination Thesis” (SCT). According to adherents of the SCT, which comes in
various forms:
“… (a) Our interpretative concepts constitute something like a theory
of human cognitive organization: they are a putative description of the
wiring-and-connection facts; (b) Our interpretative skills depend on this
theory, and our ability to deploy it on particular occasions; (c) We are often
able to successfully explain or anticipate behaviour because this theory is
largely true.” (Sterelny 2003, 6).
In the first part of Thought in a
Hostile World, entitled ‘Assembling Intentionality’, Sterelny
argues, in effect, that the Simple Coordination Thesis is approximately
correct. He rejects the eliminativist view that belief and desire talk is
false, and also the Dennettian attributionist view that the interpretation
facts ‘do not have the function of describing the internal organization of
agents’ (Dennett 1987; Sterelny 2003, 7). There are, Sterelny argues, internal ‘belief-like’
states that have features approximately like those expected by the SCT. They
are elaborations of simpler systems, and it is unclear to what extent they are
found in animals other than humans, but some other primates plausibly have
them. In the case of preferences, Sterelny maintains that the SCT is less
approximately correct, and ‘desire-like’ states incompletely found even in
humans.
My critical concern is specifically
with Sterelny’s treatment of desire. Sterelny argues that there are important
functional dis-analogies between belief-like states and desire-like states, so
that the considerations that explain why selection could in some cases favour
the kinds of cognitive elaboration culminating in belief-like states largely
don’t apply to motivation. In his view simpler control systems can achieve much
more there, and so there’s even less evidence that desire-like states are found
in non-human animals. I begin with Sterelny’s account of belief.
2.
Sterelny on the descent of belief
Sterelny develops an evolutionary
history of beliefs starting with the ‘detection system,’ an idealised and very
simple control system that falls well short of belief. A detection system’
mediates “a specific adaptive response to some feature (or features) of
[an organism’s] environment by registering a specific environmental signal”
(Sterelny 2003, p14). One of Sterelny’s examples is the cockroach flight
response, which triggers running away from gusts of air, registered by hair
cells on their heads (Sterelny 2003,
p14). The idea is that the creature has a specific behavioural response
(running away in this case) to a single environmental cue (the moving air caused
by a striking toad, or magazine-wielding human). It seems clear enough that it
could sometimes be a satisfactory solution to a control problem to have a
behaviour triggered by a single cue.
It isn’t clear whether any specific
organism is actually supposed to instantiate a detection system strictly
understood. At least some of Sterelny’s examples are of animals whose
flexibility in either detection or response is greater than a detection system
as described would allow.
He also suggests that detection systems can be acquired by simple associative
learning.
For present purposes these worries can be set aside. The notion of a detection
system is a useful idealisation even if there are no confirmed pure
examples (Godfrey Smith 2014, Chapter 2). Sterelny puts the notion of a
detection system to work by thinking about the costs and benefits of such
simple mechanisms, and possible forms of incremental modification that might
lead to more discriminating control.
The most obvious benefit of detection
systems is that they’re relatively simple, and so cheap to build and run. As
Sterelny points out, though, organisms with cue-driven behaviours can be
vulnerable to exploitation. Fireflies which approach species-typical flash
sequences to locate mates are lured by predators generating the same sequences
to attract meals (Sterelny 2003, p15). Ants using the absence of
chemical signals to distinguish (and attack) invaders are exploited by
parasitic beetles mimicking the signals, and food-eliciting gestures (Sterelny
2003, p15).
Sterelny refers to the general
condition in which environmental signals that an organism can detect are
reliably good occasions for specific responses it is capable of producing, that
is where cue-driven behaviour will be successful, as informationally
transparent (Sterelny 2003, p20). A transparent environment is “characterized
by simple and reliable correspondences between sensory cues and functional
properties.” A key insight that he develops in his (2003) is that not all
environments have this property. than In cases where relevant features of the
environment “map in complex, one to many ways onto the cues [an organism] can
detect” then it occupies an informationally translucent environment
(Sterelny 2003, p21). In some cases the translucency is not the result of brute
heterogeneity in the surrounding world, but is produced by other living things
with an interest in misleading (for example by being camouflaged to fool
predators or prey) in which case Sterelny calls the environment informationally
hostile.
No general prediction follows from
either transparency or hostility. But we can, Sterelny argues, make the conditional
prediction that where the gains from more discriminating control outweigh the
cost, then selection will favour certain kinds of elaboration of detection
systems, if means are available. He discusses two particular kinds of
elaboration - robust tracking, and response breadth.
Robust tracking is elaboration on the ‘input’ side. Where a detection system
triggers a behaviour in response to a single cue, robust tracking links response
to multiple, integrated cues. This can allow tracking of some environmental
states under conditions of translucency or hostility. Reed-warblers are
exploited by cuckoos, and face a serious problem distinguishing parasitic eggs
from their own. Sterelny suggests that the muti-modal discrimination they draw
on determining whether to reject an egg, including sensitivity to size, colour,
shape, timing of appearance, and whether a cuckoo has recently been sighted
near the nest, is an example of robust tracking (Sterelny 2003, p27-29).
Response breadth, on the other hand, is elaboration on the ‘output’ side, and occurs
when more than one behaviour might be produced in response to the same
registered contingency. One of Sterelny’s illustrations concerns responses to
predators. Having registered the presence of a predator, an organism with
response breadth might make one of a variety of responses including immediate
flight, approach, or continuing with heightened vigilance, perhaps depending on
the state of the organism itself (Sterelny 2003, p33-40).
When
robust tracking and response breadth are combined, we get what Sterelny calls
‘decoupled representation’. Now behaviour can be partly contingent on
relatively high level patterns of environmental information, perhaps integrated
over time scales reaching beyond the present and sensitive to the state of the
behaving organism. Decoupled representations are “internal states that track
aspects of our world, but which do not have the function of controlling
particular behaviors” (Sterelny 2003, p39). Such sophisticated states are, as
found in humans at least, worth calling ‘belief-like states’. These are genuine
cognitive states which, while they may not share all of the features associated
with any particular version of the Simple Co-ordination Thesis, are close
enough that Sterelny’s position regarding the interpretation facts in humans is
neither eliminativist nor Dennettian attributionist.
3.
Sterelny on the Descent of Preference
Sterelny devotes less attention to
desire, or preference, than to belief. Three chapters of his (2003) focus
mostly on the natural history of belief-like states, followed by a single
chapter on the descent of preference. Although there is some overlap, the
comparative brevity of the treatment of motivation is not because it is
continuous with the account of belief. In fact, a major order of business in
the motivation chapter is to argue that the account previously developed for
belief cannot be generalised to motivation. The conclusion Sterelny
eventually draws is, furthermore, more friendly to a kind of eliminativism.
Although he finds a plausible rationale for the evolutionary development of
belief-like states, he says that he does not “think that there is even a rough
mapping between preferences identified in our interpretive frameworks, and
states of the internal cognitive architecture that controls human action”
(Sterelny 2003, p87).
This is the conclusion that I wish to
reject. I do so here by undermining Sterelny’s argument that the belief
treatment doesn’t generalise to motivation. I therefore need to lay out
Sterelny’s reasoning in more detail than in the belief case. The criticism I
offer here is rather restricted, and negative. I won’t develop other lines of
criticism of Sterelny’s account of motivation, and will only be able to hint at
an alternative positive view, sharing more than Sterelny envisages with his
account of belief.
3.1
Sterelny’s explanatory target
In the
case of beliefs, Sterelny’s explanatory target is relatively close to a
standard (teleosemantic) conception. Belief-like states, as described, have
representational content. They have satisfaction conditions and can be more or
less supported by, and responsive to, environmental information. It is less
clear that we are on such familiar ground regarding desires. Sterelny mostly
doesn’t refer to ‘desire like states’, and favours the term ‘preference’ for
the motivational component of folk-psychological explanation. He describes his
explanatory target as “motivation based on representations of the external
world” (2003, p79). He seems, furthermore, to endorse the distinction drawn by
Tony Dickinson between ‘habit based’ and ‘intentional’ agents, where intentional
agents are sensitive to the value of actions, including values not explicitly
cued by occurrent external information, and to the causal connections
between acts and their consequences (e.g. Dickinson and Balleine 2000; Sterelny
2003, p82).
Sterelny
thus associates ‘preferences’, with means-end reasoning, suggesting that the “most
incontrovertible cases” of the applicability of belief and preference
psychology are “in complex calculating games like bridge and chess” (Sterelny
2003, p95). Such very cognitive and deliberative motivational systems are, says
Sterelny, to be distinguished from motivation by drives, or feeling. Drives, in
his view, signal departures from homeostasis and in at least some cases
motivate directly by feeling (he does not say that all drive based
control involves feeling). He also maintains that drives can solve a wide range
of control problems, and consequently that it is less clear that there is a job
for preferences to do. As he poses the problem “… what selective payoff could
there be through routing action (say) through preferences about drinks rather
than through sensations of thirst?” (Sterelny 2003, p81).
Various
commentators have expressed dissatisfaction with how Sterelny opposes desire
and preference based motivation here (e.g. Schulz 2013, Papineau 2004). I’ll
return to some of the difficulties with it in due course. For now, we need to
be clear that Sterelny maintains that the motivational counterpart to beliefs
is motivation focussed on representations of goal states, involving means-end
reasoning, and that for preferences to be predicted, they need to do better
(given the costs of implementing them) than motivation by drives signalling
departures from homeostasis.
3.2
Why the belief case won’t generalise
It might
seem as though the considerations favouring the development of belief-like
states would also explain the construction of motivational systems. Detection
systems are ‘pushmi-pullyu’ (Millikan 1995) control solutions that yoke an indicative
aspect (the environmental information to which each is sensitive) to an imperative
one (the activity that each triggers).
Decoupled representations replace these simple mappings with the more
discriminating responses to environmental information that Sterelny calls
robust tracking and replace single imperative output with response
breadth — behaviour drawn from a wider repertoire of possibly relevant
activities. The latter elaboration, specifically, might seem by itself to
create work for motivational states, to prioritise among the resulting
repertoire of activities. This is the very inference that Sterelny wishes to
block. The conditional argument from translucency or opacity to belief-like
states cannot, he says, be generalised to give an account of “motivation
based on representations of the external world.” (Sterelny 2003, p79.)
The main reason Sterelny offers for
this is that the departures from transparency that explain the existence of
belief-like-states, are absent from internal environments. This is not, furthermore,
accidental: Since internal environments have homogenous evolutionary
interests, in the sense that all parts of an organism are - so to speak - on
the same team, they both lack hostility, and will be under selection pressure
for transparency. This means that signals of biological needs will tend to be
trustworthy. “The natural physiological side-effects of departures from
homeostasis”, says Sterelny, “have the potential to be recruited as signals for
response mechanisms. Over time, we would expect these signals to be modified to
become cleaner and less noisy; and internal monitoring systems to become more
efficient in picking them up and using them to drive appropriate responses”
(Sterelny 2003, p80).
Drives might, of course, be
simultaneously triggered in incompatible ways, but Sterelny maintains that one
fairly robust solution to the control problem this poses is to have a “built in
motivational hierarchy” (2003, p81). He doesn’t really flesh this proposal out
very much, but the idea seems to be that a relatively fixed ranking of drives
can determine behavioural priorities in ways that depend neither on
representations of the values of outcomes, nor the connections between actions
and their consequences. He refers approvingly to Rodney Brooks (1991) here,
encouraging the suggestion that this fixed motivational hierarchy might depend
to a significant extent on low bandwidth trumping relationships between drives.
(In the early 1990s Brooks argued that ‘intelligent’ systems could be based on
‘subsumption architectures’ which were, roughly, hierarchies of detection
systems operating without significant representational resources.)
3.3
Sterelny’s positive view
While
Sterelny holds that many organisms solve motivational problems without “representing
their needs”, relying instead on a “built-in motivational hierarchy” which
ranks various drives mostly based on transparent internal signals, sometimes
supplemented with a little external information, this is not true of all
of them. The advantages of preferences over drives, according to Sterelny,
include that they liberate motivation from ‘immediate affective reward’, that
they allow more efficient decision making in cases where the range of available
behaviours is large, that they allow a creature to have a smaller number of
motivational states, that they permit motivational conflict resolution by means
other than ‘winner take all’, and that preference based systems are able to
cope with changing needs, including needs that are phylogenetically novel
(Sterelny 2003, pp 92-95, See also Schulz 2013, p598). Preferences, as well as
representing goal states, can be ranked, and they can be learned.
Sterelny’s
exposition is fairly cryptic on these points, and some commentators have
expressed the view that the supposed advantages of preferences aren’t explained
clearly enough, or that the contrast with what drive-based motivation could
achieve is insufficiently motivated (again, see Papineau 2004). Certainly,
Sterelny says very little to justify the claims that the number of
motivational states would be smaller for drives than for preferences, or that
drive based motivation would have to resolve conflict on a winner take
all basis. Nonetheless he maintains that a small sub-set of species (hominids
definitely, and maybe some others) are capable of more richly intentional and
preference-based action, that is aimed at planning activities to achieve
desired states of the external world. This, he thinks, does require some
representation of value. But this transformation “is very unlikely to be
complete” (Sterelny 2003, p95). Sterelny maintains that much other behaviour
allocation is likely based on fairly quick and dirty procedures, and various
kinds of distributed and non-representational control processes (as noted
above, he explicitly and approvingly cites Brooks 1991).
The view
that he reaches is, therefore, still clearly a version of the environmental
complexity hypothesis (ECH), insofar as the development of preferences is a response
to external complexity. But it is rather more friendly to eliminativism than
his position in the case of belief, because the (alleged) transparency of
internal environments means that there is much less complexity for cognition to
‘deal with’.
4.
Criticisms of Sterelny
Sterelny,
then, argues that internal environments will tend to be transparent, and that because
of this, the inference from informational complexity to belief-like states
does not generalise to the motivation. His argument identifies preferences with
means-end reasoning.
In what
follows I criticise all three of these commitments. First, I undermine Sterelny’s
claim regarding the transparency of internal environments. I argue, in section
(4.1) below, that his defence of the claim is insufficient, and consequently
that internal environments can also favour robust tracking.
Second, I
argue that even if internal environments were transparent, it would not follow
that cue-based control processes would be generally sufficient. I call the
condition in which cue-based control is sufficient ‘motivational transparency’,
analogous to informational transparency. In section (4.2) I argue that
motivational transparency does not generally follow from internal
transparency.
Finally I
maintain that Sterelny has made an unsatisfactory choice of explanatory target
in his discussion of preference. I argue in section (4.3) that rather than
focusing on means-end reasoning, or represented goal states, what is needed,
and prior to either, is a notion of incentive values, attached to occurrent
environmental information and possible actions.
The lines
of critical thinking offered here are not exhaustive, and the arguments I
provide are brief. I aim to highlight some difficulties with what Sterelny
himself identifies as ‘tentative’ moves in the area, with the aim of advancing
the same general project. I won’t have space to develop or defend a positive
view distinct from Sterelny’s, although some hints will emerge.
4.1
Limits on Internal Transparency
As explained above, Sterelny maintains
that internal environments, having homogenous interests, will be devoid of
hostility, and so be under pressure to develop accurate and transparent signals
of biological states and needs. The interests within an organism are presumably
homogenous (Sterelny does not spell this out explicitly) because all parts of a
single organism are in some sense equal shareholders in whatever reproductive
success the individual organism enjoys.
This suggestion plausibly applies,
subject to cost constraints, to internal signals, to the extent that internal
interests coincide. This they mostly do.
The relative absence of hostility does indeed imply the internal absence of one
source of pollution in the external informational environment.
But hostility is not the only
source of departures from transparency. As Sterelny says, an environment is informationally
translucent when states that matter to it “map in complex, one to many ways
onto the cues they can detect” (Sterelny 2003, p21). These conditions can, and
do, arise in hostility-free internal environments, in a number of different
ways. Here I identify three considerations:
Limits on transduction: Not all internal states have unique signatures that cost-effective
transducers can specialise in detecting. Here are a few examples in humans.
Non-nutritive sweeteners trigger transducers whose proper function is to
respond to sugars that can be digested. The responses of salt receptors,
depending on ion channels, are also sensitive to the ambient sodium
concentration in the organism, so the resulting neural signals can be highly
ambiguous (e.g. Bertino, Beauchamp & Engelman 1982) Thermoreceptors don’t
come in a single type detecting ‘objective temperature.’ Instead information
about temperature depends on combinations of receptors for cold and heat, as
well as additional nociceptive receptors for extremes of each (for a
philosophically rich discussion of peripheral thermoreception see Akins 1996).
Complex mappings: Motivationally relevant states can also depend on multiple cues.
Information about temperature in humans, to continue with that example, is
drawn from multiple receptors of different types that are distributed non-uniformly
across the surface of the body. As Akins notes, even on the face the ratio of
cold to warm receptors varies from about 8:1 on the nose, 4:1 on the cheeks and
chin, while the lips have almost no cold receptors (Akins 1996, 346). Any ‘net’
signal that might drive behaviour will require these signals to be integrated
in some way. More generally, internal states can span multiple organs and
tissue types, with varying speeds of signalling, and latencies in responding to
actions that affect them.
Cost versus accuracy
tradeoffs: There are costs to improvements in
tracking, just as in the external case. Simply adding internal transducers
increases information load, along with metabolic and other costs building and
running the receptors. Psychophysical processes generally don’t try, but rather
compress transduced variation into a baseline-dependent encoding, where the
baseline itself is variable (Barlow, 1961). In addition, the further a body is
from being a dimensionless point, the more internal signals will tend,
sometimes, to be distal or delayed, and subject to the typical error types that
arise from distal signals (such as false positives from stimulation on any
‘labelled line’ channel between transducer and brain).
We should conclude that even though
internal environments aren’t generally hostile, they can certainly be translucent.
And translucency favours robust tracking. So Sterelny’s premise is at least not
straightforwardly or generally true. What about the inference that he draws
from it?
4.2
Internal transparency doesn’t imply Motivational Transparency
In the previous section I
argued that there could be benefits to robust tracking in internal environments
because (just as with external ones) there are limits to transparency. Since
Sterelny argues from internal transparency to the non-generalisability of his
treatment of belief, this is a problem for his position. But it is not the only
one. To see this, let us assume that internal environments are fully
transparent, in the sense that the precise level of deviation from homeostasis
of all relevant internal variables are signalled in a consistently high
fidelity way. Even then, cue-bound control can be inefficient.
One reason for this is that
needs can have multiple satisfiers. A cold animal might be able to make
itself warmer, inter alia, by shivering, by huddling with conspecifics,
or relocating to a warmer spot. A dehydrated animal can drink, or it can eat,
since almost all food contains some water. And so forth. A hungry animal might
have more than one foraging option.
Accurate information about needs does not always, then, suggest a unique ‘good
enough’ response which would favour cue-bound control.
A further reason is that actions
typically have multidimensional costs and benefits. As noted most eating
rehydrates as well as nourishing. Different opportunities to eat, or drink,
have their own costs in energy, time, extent of competition for the same
resource, etc., and their own risks including predation en route, or at
the site itself, as well as payoffs in quality and quantity of the resource
itself. Costs and benefits can have sharply varying fitness implications -
being a little tired or hungry quite frequently is nowhere near as bad as being
eaten even once. Even if an animal had
accurate information about all of these contingencies, it would not generally
be obvious what course of action was appropriate or efficient. (We already know
that it can be difficult to work out what to do in games of perfect information
such as chess.) And animals mostly don’t have most of this information, which
favours - for at least some of them - being able to sample the environment and
be sensitive to the returns from various policies.
Sterelny is aware of these
considerations, but does not regard them as favouring the development of
preferences. An important part of the reason for this is his view that many
animals can deal with the problem of trading off different courses of action by
means of a “built-in motivational hierarchy” (2003, p81). This seems likely to
be correct, up to a point. But it is not a reason for thinking that the
arguments (conditionally) favouring decoupled representation don’t generalise
to motivational states. As with detection systems, and belief-like states, we
should consider the relative strengths and weaknesses of more or less quick and
dirty, or inflexible, procedures.
A fixed hierarchy can probably produce
quick, and good enough, responses in a wide range of situations. But such
brittle solutions have the very problems of inefficiency under conditions of
informational translucency that Sterelny explained when focusing his attention
on beliefs including vulnerability to exploitation (See section 2 above). And
if the gains in efficiency from a less rigid approach outweigh the costs, then
something other than a fixed hierarchy might pay its way. What this something
else might be, I suggest, is relatively general (across actions and
environmental states) sensitivity to reward. Then the specific profile
of things found rewarding can be set by processes of natural selection, and the
organism’s behavioural dispositions partly shaped by experience of
action-reward relationships. If we combine the argument of the preceding
section and this one, we see a case for the robust tracking of motivationally
relevant states, and a role for motivation in prioritising actions given
response breadth. What motivation should do, what it is for, is prioritising on
the basis of the returns from actions.
What I’m describing, though, sounds
rather different from what Sterelny sets up as his explanatory target. This is
deliberate, and in the following sub-section I attempt to justify it.
4.3
The wrong target
As noted
above (section 3.1) Sterelny takes the target for an account of the
motivational part of folk psychology to be representations of goal states, and
capacity for means end reasoning selecting actions that bring the goal states
closer. Recall, though, how he describes his overall project, as relating the “wiring
and connection facts” about human cognitive architecture to the “interpretation
facts” which are the elaborations of our folk self-conception as intentional
agents. This means relating wiring and connection facts to beliefs, on the one
hand, and desires on the other. Or, perhaps, desires as elaborated or
regimented by some science (or group of them) that takes the folk conception as
a starting point. So, we can ask, what is the approximate functional content of
the folk notion of desire, or an appropriate scientific regimentation of it,
for relating these two kinds of fact?
I propose
that the core of the folk conception is a fairly general (and sometimes
imprecise) notion of motivational strength. An intentional agent desires
different goals, or to perform different actions, to varying degrees. When two
mutually exclusive actions are available, it does the one that it wants the
most.
Such a
general notion is compatible with some of the leading philosophical accounts of
desire, even though the field is contested.
A leading contender is the view that desires are dispositions to action, given
beliefs (e.g. Smith 1987). Teleosemantic theories of desire are dispositional,
and also offer an analysis of the biological function of desires (e.g. Millikan
1984, Papineau 1987). One competing approach is provided by theories of desire
based on pleasure, for example Morillo (1990) which in addition identifies the
dopamine system in the brain as the basis of pleasure. Details of this view are
disputed by Schroeder (2004) who associates desire with learning, and
identifies the dopamine system with reinforcement learning, rather than
pleasure. (There are also theories of desire less obviously friendly to
naturalists, such as broadly Socratic ones connecting desire to judgements
about what is good.) Without joining those disputes, I note that the
disposition, pleasure and learning accounts all have weaker commitments than
Sterelny’s target (‘representations of the external world’, or means-end
reasoning).
Where these theories require representations of the world, those are provided
by beliefs. What desires do is relate world-states, whether represented
or cued by occurrent experience, to tendencies to actions. As Papineau puts it,
beliefs should be thought of as having “no effects to call their own”, but then
which effects are produced depends on the motivational states (Papineau 2004,
494).
Matters do
not change substantially if we shift focus to consider scientific theories as
another source of what Sterelny calls “refined versions of our folk
self-conception”. In behavioural psychology and economics (which are among the
leading scientific regimentations of something that might be related to the
folk concept of desire) the key notions are reward or reinforcement or utility,
which are considered to provide an ordering of desirability for states and
actions (See Spurrett 2014). In addition, in behavioural neuroscience the drive
based theories that Sterelny seems to favour for organisms in which preferences
(as he understands them) have no developed have largely been displaced by incentive
based approaches.
Here too, the theories have more modest commitments than Sterelny. What
preferences represent are rewards (or reward expectancies), not states of the
external world.
None of
this is to say that means-end reasoning is neither interesting nor important.
When it occurs it plausibly stands in need of an evolutionary rationale. From
the perspective suggested here, though, means-end reasoning is primarily a
representational achievement, consisting in the capacity to simulate
transitions between world-states, including transitions occasioned by actions,
and evaluate them using the same general sensitivity to incentives as apply in
‘on-line’ experience (see Shea et al, 2008). Sterelny is probably
correct, furthermore, that means-end reasoning is relatively incompletely
developed even in humans, and only found marginally in relatively few nonhuman
animals.
5.
Conclusion
According to the Environmental
Complexity Hypothesis (ECH) “the function of cognition is to enable the agent
to deal with environmental complexity” Godfrey-Smith (1996, 2002). Sterelny
(2003) develops an account of folk psychology within the general terms of the
ECH. He argues that belief-like states can be explained as a response to
failures of environmental transparency, combining robust tracking (sensitivity
to multiple types of detectable information) and response breadth (the
relevance of registered states to more than one behaviour). But, he argues, in
the case of motivation internal environments will tend to be transparent, and
because of this the inference from translucency to (an approximation of) a
folk-psychological kind doesn’t apply. Preferences, understood as capacity for
means-end reasoning about representations of the external world, aren’t
predicted, at least for most organisms, because transparent signals of internal
state plus a built-in hierarchy of drives are a pretty good way of prioritising
actions.
I have accepted the Environmental
Complexity Hypothesis, and broadly support Sterelny’s treatment of belief-like
states, but argued against significant parts of his treatments of desire-like
states. Internal environments are not as transparent as he thinks, with the
result that there is work for robust tracking there too. Motivational
transparency does not follow from informational transparency either, and so
there is work for relatively generalised sensitivity to reward. The view of
preference that is predicted here is different from what Sterelny sets out to
find, but I’ve also argued that means-end reasoning isn’t the most important feature
of desire. Preferences are representations of a sort, but they represent the
returns (experienced or anticipated) from experienced states, or from possible
actions.
Most of the burden of argument has been on the negative project of blocking
Sterelny’s ‘no generalisation’ argument. The fuller development of the positive
picture suggested here is a task for another occasion.
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