A FFECTIVE MEANING , NATURAL MEANING , AND PROBABILISTIC MEANING

« … I imagined my god confiding his message to the living skin of the jaguars

… May the mystery lettered on the tigers die with me. » – Jorge Luis Borges, The God’s Script

Abstract. In this chapter, I discuss two main ways in which philosophers have argued that information can be naturally encoded in stimuli: natural meaning and probabilistic meaning. I evaluate how useful they are when it comes to analyzing affective meaning. I argue that natural meaning, because it is a factive relation, is too strict for this purpose. The notion of probabilistic meaning seems adequate for analyzing non-communicative signs, but it faces several difficulties when it comes to analyzing signals, i.e. communicative signs. In the next chapter, we will see how notions from teleosemantics may overcome these difficulties.

7.1. I

When studying affective meaning, we are very often confronted with cases that are produced not only without communicative intentions but without any control over the effects they have on the audience. This is true if we focus on non-communicative signs as well as on cases of affective communication – cases where the affective meaning has the function to be transmitted.

Think about betraying one's emotion, despite one's will, through a facial expression or a scream. Think about nonhuman animals communicating their affects through alarm calls, food calls, or hormonal releases, where the senders cannot control the effects on their peers. Even though intentions to communicate are absent from these cases, they belong to the realm of affective communication insofar as both the sending (e.g. a scream) and the receiving of the information (hear a scream and understanding that the screamer is afraid) are designed to transmit the information that is so transmitted. In these cases, there is no intentional design, but supposedly the design was done through natural selection.

Outside the realm of communication, we can think about the physiological manifestations used to detect one’s emotion which one cannot help but produce, the kinds of manifestations that could be used in lie detectors:

sweating, pupil dilatation, heart rate, or brain activity. Such cases aren’t

communicative because information transfer is not the purpose of the manifestation: the manifestation (e.g. heart rate) is not designed for transferring the information that is so transferred.

All of these are examples of what I call affective non-Gricean meaning.

They are examples of meaning, because we may say, for instance, that Sam’s blushing means that he is embarrassed: it carries this piece of information. The meaning is affective because they are examples where the information carried is about someone’s affective state. And I classify them as a non-Gricean type of meaning because what is distinctive about Gricean models of information transmission does not apply to them; in particular, such cases don't involve implicatures of any kind.

They don’t because the signs are produced in such a way that pragmatic principles such as Grice’s Cooperative Principle don’t apply to them. Such principles only apply to cases where the information is transmitted either in an intentional way or, at least, with a certain degree of control (see Chapters 1 and 2). When the effects produced on the audience, including what information is transmitted, are not controllable, we cannot infer that certain implicatures are carried by the signs, because there are no goal-oriented reasons why the creature has produced these signs (or: omitted to refrain from producing them).

As we have also seen in Chapter 1, when there are no implicatures of any kind, it should be possible to account for information transmission through some code model. So, the examples of non-Gricean affective meaning given above should be analyzable through a code, an established pairing between stimuli and the information they transmit.

A main theoretical construct put forward to analyze non-Gricean meaning is that of natural information (Drestke, 1981, 1986; for a review, see Stegmann, 2015), itself based on Grice’s notion of natural meaning (1957).

At the heart of this notion is the idea that lawful relations hold between states or events in the world – e.g. between fire and smoke – and that this is what explains that information is encoded in these states or events. The code, the established pairing, is that between a stimulus and that with which it is lawfully related. If an observer can somehow use this established pairing, it can allow her to decode what information is encoded in the stimulus. We can learn from lawfully related entities, and they thus have a meaning.

In this chapter, I will present several ways to exploit the idea that lawful relations explain some cases of information transmission and see how they apply to cases of non-Gricean affective meaning. First, I will present Grice’s

(1957) notion of natural meaning and explain why it fails to apply to most cases of affective meaning.¹³⁹ I will then present how Dretske (1981, 1986) elaborated upon Grice’s notion, but explain why, once again, it is hard to see how it applies to affective meaning. Finally, I will present more recent developments of the notion of probabilistic meaning (Millikan, 2004;

Scarantino, 2015; Scarantino & Piccinini, 2010; Shea, 2007; Skyrms, 2010;

Stegmann, 2015).¹⁴⁰ We will see that probabilistic theories seem to apply well to the affective meaning of non-communicative signs, but face three problems with respect to affective signals, signs whose function is to carry the affective information they carry.

7.2. A

I understand natural meaning as factive indication, which is how Grice (1957) introduced this notion. This means that if x means naturally that p (in context C), then whenever x is the case, it is also the case that p (in C).

Only if this entailment holds may we say that x naturally means p or that x is a natural sign of p. Here is a classic example: if the number of growth rings of a tree naturally means how many winters the tree has lived through (in a context in CW), then whenever a tree has 28 growth rings, this tree must have lived through 28 winters (in CW). For this strong constraint to be realistic, we may restrict CW to a context where winters are the coldest season of the year and where trees grow as they do on Earth.

Now, if there is only one tree in a million that has 28 rings in CW but has lived only 27 winters, then growth rings are not a natural sign of a tree's age in CW. They don’t possess this natural meaning, at least in this context.

Because only one exception to the rule is enough to rule out natural meaning, it has a very strict necessary condition.

7.2.2.NATURAL MEANING AND AFFECTS

Because of this strictness, it is hard to find rock-solid candidates for affective natural meaning. This is so although philosophers often claim that facial expressions of emotions may have natural meanings, starting with Grice himself, who talked about frowning as a natural sign of displeasure (1957). However, pace Grice, I don't think that there are good

139 Natural' here is not to be contrasted with 'super-natural'. I take it to have the same meaning as in 'natural sciences', which we oppose to e.g. social sciences or humanities.

140 Most of these views, just like Dretske’s, are based on (Shannon, 1948); for a relevant case outside philosophy see (Hauser, 1996). See also Denkel (1992) for an early move in this direction.

candidates for affective natural meaning to be found in the domain of facial expression (see also the discussion in Chapter 3).

For one thing, facial expressions may be faked, and so one may display a typical 'angry face', but not be angry. Secondly, the muscles of our face may, in certain situations, inadvertently form a pattern that is normally associated with a certain emotion, even though we do not undergo this emotion. Take the following picture as an example:

Fig. 7.1. Giannis Antetokounmpo displaying the facial expression associated with fear according to Ekman and Friesen’s code model (Ekman & Friesen, 1971),

Here Giannis Antetokounmpo is displaying the facial expression associated with fear (Ekman & Friesen, 1971), but, of course, he is not afraid of slamming the basket.

Here is another example, borrowed from Barrett, Mesquita, and Gendron (2011), where Serena Williams displays an ‘Ekmanian angry face’ even though she certainly is not angry, as she has just scored an important point.

Fig. 7.2. Serena Williams displaying a facial expression associated with anger according to Ekman and Friesen’s code model (from Barrett et al., 2011)

Similarly, the Duchenne smile or 'real smile' has been thought to naturally mean a positive affective state, because people usually cannot control the relevant activation of the zygomatic muscles. But it actually doesn't. First, the Duchenne smile – i.e. activation of lip corner puller (AU 12) together with a contraction of the zygomatic muscles or ‘cheek raiser’ (AU 6) – may be faked by a substantial portion of the population (Gunnery et al., 2013).

Secondly, people also display Duchenne smiles when frustrated (Hoque &

Picard, 2011). Thirdly, we may inadvertently activate the muscle configuration of the Duchenne smile, for instance when we are screaming certain words (personal communication from psycho-physiologist Sylvain Deplanque).

So if facial expressions are not natural signs of affects, where should we find examples? Well, an obvious place to look is in the affective neurology literature. Here is an example: it appears that whenever humans’

amygdala is activated above a certain level, they have (unconsciously) detected a stimulus that is emotionally relevant (Murray et al., 2014). At least this appears to be so given a context CA where the people in question don’t suffer from emotional or neurophysiological malfunctions, where their amygdala is not artificially manipulated through chemical or electric stimuli, where their brains work as that of typical humans, and other

‘normal’ contextual conditions. So, it seems, this amygdala activation means naturally that something is appraised as affectively relevant by the subject in CA, and so that the person is in an affective state (for the link

between appraisals and affects, see Chapter 9). Many other correlations may be proposed between neurological activations and affective states, even if most of them are debated in the field (see Nummenmaa &

Saarimäki, 2019 for a review). However, neurologists are generally interested in statistically significant correlations, not in the strict natural meaning relation defined by Grice, since the latter requires that 100 percent of cases are correlated, something quite foreign to neurological reality. Even the amygdala results, which appear to be pretty robust, do not give enough evidence for such a strong demand: we don't know whether there is a one-one correlation between amygdala activation and affective states, i.e. that there is a probability of 1/1 that the one indicates the other, even if we restrict the context to CA.

Is there an example where such results would be established? Where a brain signature naturally means an affective state? Perhaps, but since we are especially concerned with communication, and since we don't communicate by using brain signatures, the affective natural meanings that we may potentially find in neurology are not central to our inquiry.

Maybe someday we will be walking around with portable fMRI and EEG scanners connected to some screen which will allow us (or force us) to communicate our emotions by displaying the activity of our amygdala.

Since we are not there yet, I will now put aside neurological affective meaning.

Other candidates for affective natural meaning are the cues discussed in the psychophysiology literature. Such cues may be used in affective communication since at least some physiological signs are observable with the naked eye. What are the psycho-physiological candidates? When it comes to affects, signs used by the psycho-physiologists concern in particular affective arousal and valence. In a context CB where we know that the person has not been subjected to physical efforts (e.g. has not run in the last hour), has not been artificially manipulated through electric stimulation of their brain or chemical injection, and where we put aside extraordinary scenarios (e.g. the person is a very realistic android), then the following set of physiological changes are credible candidates for being physiological states which mean naturally that the subject is undergoing emotional arousal: blushing, sweat increase, pupil dilatation, heart rate modification, increase in respiratory rhythm, decrease in the deepness of breath (panting), and exacerbated muscular tonus. We may even consider each of these stimuli taken individually to naturally mean arousal if we restrict the context CB further (e.g. if we take pupil dilatation as a sign, we need to restrict CB to a context where there is no change in light intensity).

And indeed, each of these signs is used by affective scientists to measure

arousal (Bradley et al., 2008; Cacioppo et al., 2017, Chapter 20).

Concerning valence, some evidence shows that a decrease in heart rate is correlated with negatively valenced affective states (Cacioppo et al., 2017, Chapter 20).

When it comes to candidates of physiological cues observable with the naked eye which can be taken to possess an affective natural meaning, that’s it. Psycho-physiologists do not (or at least should not) infer more than negative valence and increase in arousal from physiological cues.¹⁴¹ And, in fact, these candidates may not be cases of natural meaning. Some psycho-physiologists dispute the claim that these changes (pupil dilatation, increased sweating, deceleration of heart rate, etc.) naturally mean an increased arousal and a negative valence (Bradley & Lang, 2007; Turpin, 1986). This is because these changes seem to also be correlated with information-seeking behavior, where the person is alert but is not reacting strongly enough to genuinely be affectively aroused by the situation or be undergoing a negatively valenced affect (Bradley & Lang, 2007; Turpin, 1986). Imagine for instance that you hear an unfamiliar noise in your apartment and try to listen and figure out what it is, but you are not afraid or undergoing any other arousing or negatively valenced affect. The signs mentioned above may well be present in this situation.

So, after due consideration, it seems that there are no rock-solid candidates for natural affective meaning. There are two main solutions to this problem. The first one is to sufficiently restrict the set of contexts so as to reach factive indication, which is the path followed by Dretske as we will shortly see, and the second one is to relax the notion of natural meaning to allow for non-factive but probabilistic indication, a path which we will explore in §7.3.

7.2.3.CONTEXTUALIZING NATURAL MEANING

Dretske (1981, 2008) proposes to focus on contexts where we do have a one-to-one correlation between the sign and what it means. This allows us to secure a perfect epistemic relation and have cases where we can learn from signs, where we can acquire knowledge from observing them. According to Dretske, a sign carries the natural information that p just in case the probability of p given the occurrence of the sign is one, and less than one

141 Personal communication with Sylvain Deplanque (April 2020). Note that psycho-physiologists may infer more from signs that are not observable with the naked eye. Note also that some evidence shows that when we look at pleasant pictures – but not when we listen to pleasant sounds – an increase in heart rate is correlated with a positively valenced affective state (Cacioppo et al., 2017, Chapter 20).

otherwise. So, we can say that blushing naturally means that someone is aroused if we concentrate only on those contexts, given background knowledge, where blushing is indeed a factive indicator of higher arousal and not an indicator of physical efforts or high body temperature.

This theory of natural information may well be sound, but it is not an appealing solution for someone concerned with communication: how are communicators supposed to know which contexts are such that there is a 100 percent chance that a sign means an affective state? There does not appear to be an answer to this question. For this reason, many commentators consider Dretske's natural information, just like Grice's natural meaning, to be too restrictive to be useful in analyzing communication or even knowledge acquisition (Godfrey-Smith, 1992;

Millikan, 2000; Scarantino & Piccinini, 2010; Stegmann, 2015; Suppes, 1983).

Another solution that is more implementable and certainly more popular nowadays is to move away from factive indication and define a new theoretical construct that is less strict and allows x to mean that p even if p is not the case. We will now turn to such a notion – that of probabilistic meaning. For the record, let me observe that Dretske did move to another notion as well, a teleosemantic one called 'functional meaning'. We will turn to it in the next chapter.

7.3. A

To allow for cases where a sign x can mean that p even when p is not the case, but without appealing to intentions and mindreading, several authors have parted from Grice’s factive notion to define what we may call

‘probabilistic meaning’ (Millikan, 2004; Scarantino, 2015b; Scarantino &

Piccinini, 2010; Shea, 2007; Skyrms, 2010; Stegmann, 2015). What I call probabilistic meaning includes several theoretical constructs that are defined in different manners, but which all make use of less-than-1 correlations between the sign and what the sign is a sign of, i.e. statistical correlations that are not factive.¹⁴² There are two main ways to define probabilistic meaning: using objective or subjective probabilities. I will

142 To make a clear distinction between natural meaning and probabilistic meaning, I will only talk of natural meaning and not of probabilistic meaning when the relation between the sign and what it indicates is factive, although, according to the definitions I will give, natural meaning is a species of probabilistic meaning, since factivity is a correlation where the probability is 1.