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Unlimited Associative Learning and the Natural Kind Status of Phenomenal Consciousness

philosophy

Unlimited associative learning as phenomenal consciousness, using a natural kind framework.

1 Introduction

The difference between a system with a first-person subjective point-of-view and a system without is the explanatory gap between our physical theories and what it is to have a mental life (Godfrey-Smith 2019, 1–2). There is undeniably something it is like to be a person working on an essay for a class and seemingly nothing it is like to be the chair in which the essay is written. Phenomenal consciousness, henceforth referred to as p-consciousness, is what this experience of something it is like to be something is called (Block 1995, 230).
Humans are confident in one another’s phenomenal consciousness through the process of verbal reporting. We communicate using language and convince each other of the existence of our p-consciousness through the similarity of our described experience. We remain relatively confident in the p-consciousness of other mammals due to the similarity of their brains to ours; mammalian brains possess all the same key features as our own, albeit smaller (Birch 2020, 288). We run into methodological problems; however, in the case of non-mammals, non-mammals may possess a homologous neural structure to mammals, but they may not. To write off all other animal classes immediately from possesing p-consciousness does not entertain the possibility of multiple realizability, the ability of different underlying mechanisms to perform the same functions.
In this essay, I will examine the work of Simona Ginsburg and Eva Jablonka; they have developed an approach that links a certain forms of enhanced learning with p-consciousness. They argue that organisms that can perform these types of learning are p-conscious and thus have their own subjective experience. These learning types are grouped and collectively called unlimited associative learning (UAL). This means an organism can learn about its environment and itself in an open-ended manner (Birch et al. 2020, 56). The constraints on this learning still allow that it is functionally impossible for all of the possible associative links to be exhausted in the finite lifetime of a real organism (Birch et al. 2020, 56).
To identify UAL with consciousness, Ginsburg and Jablonka use a cluster of enhanced associative learning forms that in humans, are believed to be facilitated by p-consciousness (Birch 2020, 291–92). These are; (1) compound stimuli, the stimulus can be made of more than one perceptual feature in either a single or multiple sense modalities (Birch et al. 2020, 56). (2) Novel stimuli, the conditioned stimulus can be novel to the organism, (3) second-order conditioning, the organism can build up open-ended chains of association between stimuli and actions (Birch et al. 2020, 56). (4) Trace conditioning, there can be a time gap between conditioned and unconditioned stimuli and, (5) Flexible, easily rewriteable associations with value, stimuli can be either positive or negative and the organism can alter the value in response to environmental changes (Birch et al. 2020, 56).
These five points indicate how UAL can be useful as a research programme once we have ascertained how UAL relates to a minimally sufficient functional description of p-consciousness. We will examine the relation of UAL to p-consciousness in the next section. First, is UAL p-consciousness or just an indicator? Then we shall look at the implications of UAL on p-consciousness. Finally, we shall examine the some of the support and criticism of UAL.

2 Natural or nominal kind

In this section, we will further explore UAL, as its authors and later collaborators envisage and understand it to be. Next, we shall examine UAL in the context of another theory created by Nicholas Shea and Tim Bayne, and we shall use their framework to assess the relation between UAL and p-consciousness. Then finally, for this section, we shall discuss the implications of whatever we find the status of the relationship between UAL and p-consciousness to be.
Ginsburg and Jablonka’s theory is an evolutionary theory and proceeds in stages marked by three transitions. First from non-life to life, from automata to p-consciousness and, finally, to rational-symbolic (Ginsburg and Jablonka 2020, 158). An evolutionary transition marker signals each transition; once this diagnostic is present, the transition has occurred, and the organism has gained a new mode of being not possessed by its progenitors (Ginsburg and Jablonka 2020, 157–59). We concern ourselves with the second transition from automata to p-consciousness; UAL is Ginsburg and Jablonka’s proposed evolutionary transition marker for this transition. The authors maintain that UAL is diagnostic to positively mark p-consciousness in an evolutionary lineage (Ginsburg and Jablonka 2019, 226) and not necessarily anything more. However, if it is a good minimal description of what is required functionally for p-consciousness, then does it not constitute essentially being p-consciousness?
To examine this question, we will use the theory mentioned above by Shea and Bayne, their ‘natural kind methodology’. This framework is related to our beliefs about p-consciousness; whether it is an underlying natural property that entails our perceived ‘symptoms’ of p-consciousness meaning, it is a natural kind (Shea and Bayne 2010, 470). Alternatively, is it simply a family of cognitive abilities with no underlying natural property, i.e., a nominal kind like the concept of dirt (Shea and Bayne 2010, 470). If p-consciousness is a natural kind, to use Shea and Bayne’s example, it is more like hepatitis C than dirt (Shea and Bayne 2010, 470). We can detect or diagnose hepatitis C without a near-perfect detection method if we find enough symptoms of it and can rule out other causes. This is the approach that the natural kind methodology proposes; if p-consciousness is a natural kind we can detect it with a diagnostic toolkit. Identifying a cluster of properties is not a guarantee of the presence of a natural kind property to best explain the cluster. However, suppose p-consciousness was a natural kind. In that case, the methodology does allow more investigation than can be made by pre-theoretic approaches that we already possess, such as verbal reporting (Shea and Bayne 2010, 470). Should p-consciousness be a natural kind, we can collect a wide array of evidence and form nomological clusters. A nomological cluster is a set of evidential properties that are ‘instantiated together better than chance’ and where ‘subsets of the cluster supports induction to other elements of the cluster’ (Shea and Bayne 2010, 471).
Ginsburg and Jablonka’s UAL seems to fulfil these criteria for a nomological cluster, each of the five features of UAL overlap and are not individual and separate capacities. They have co-evolved with one another (Birch et al. 2020, 56). For Jonathon Birch, Ginsburg and Jablonka to believe that UAL is a good diagnostic, they must believe that it requires the existence of the functionally coupled systems that result in p-consciousness (Birch et al. 2020, 57). In other words, they have found a natural cluster of evidential properties for which the best explanation is an underlying natural kind property, i.e., p-consciousness. Hence, UAL is not equivalent to p-consciousness; it is a nomological cluster that is best explained by the existence of p-consciousness. Ginsburg and Jablonka are p-consciousness realists and aim for their chosen nomological cluster to provide evidence of natural kind p-consciousness.
A consequence of formulating their evolutionary transition marker in Shea and Bayne’s natural kind methodology is explicitly stating the pluralistic nature of the nomological cluster. Ginsburg and Jablonka’s central thesis for UAL is that some forms of learning are facilitated by p-consciousness (Ginsburg and Jablonka 2007, 219). Using the ‘natural kind methodology’, more evolutionary transition markers (nomological clusters) could be found to add support to Ginsburg and Jablonka’s theory. A synthesis of Ginsburg and Jablonka’s and Shea and Bayne’s theories provides a comprehensive research programme. We are licensed to search for UAL in non-human animals, and we are licensed to search for more evidential properties that are best explained by being facilitated by the natural kind existence of p-consciousness. Discovering more interrelated evidential properties allows us to form more nomological clusters to further aid empirical research.
In the next section, we shall see support and criticism for Ginsburg and Jablonka’s theory of their methodology and realist stance on p-consciousness.

3 Support and criticism

Firstly, supporting evidence for UAL comes from the fossil record. Ginsburg and Jablonka argue that in the fossil record for the Cambrian period (542-485 million years ago (Ginsburg and Jablonka 2019, 407)), we can see features in some vertebrate organisms, i.e., a nervous system (Ginsburg and Jablonka 2007, 222–23). Neural structure is strongly associated with UAL in modern humans and other animals and allows for the five criteria contained within the UAL nomological cluster. Ginsburg and Jablonka argue that from an evolutionary perspective, the arrival in the Cambrian period of open-ended associative learning is very sensible. There was a sudden diversification of life and a massive increase in the number of species during this period, known as the Cambrian explosion (Godfrey-Smith 2016, 11). Ginsburg and Jablonka believe that this ‘explosion’ was due to the development of UAL (Ginsburg and Jablonka 2019, 419–20). UAL endowed organisms with the ability to adapt their behaviour to their benefit within single organism lifetimes, which in turn spurred on morphological diversity as an animal that discovered and exploited a novel food source was likely to stay and reproduce in that environment (Ginsburg and Jablonka 2019, 420–21). The organism’s offspring were more likely to exploit the same food source, and from there, the pressures of natural selection created more morphological niches to fill (Ginsburg and Jablonka 2019, 421). This is a compelling hypothesis and lends some strength to the evolutionary approach that Ginsburg and Jablonka due to its explanatory power. Additionally, it strongly uses the continuity principle of the broader biogenic approach, that there is a continuous unbroken lineage with our most complex cognition in the present day with simpler forms in the past (Lyon 2006, 15). Ginsburg and Jablonka determine the origins of p-consciousness to be far in the past, allowing for a wide distribution of p-consciousness in the present day.
The first criticism we will examine is the application of UAL as an indicator of p-consciousness to artificially intelligent systems. It looks pretty conceivable that an AI system that could currently or in the near future be built able to demonstrate UAL fully. Would this AI then be considered p-conscious? The position of Birch, Ginsburg and Jablonka is simply no (Birch et al. 2020, 56). They argue that UAL is an evolutionary transition marker for biological systems, not computer systems (Birch et al. 2020, 56). I find this a somewhat weak argument; they imply that what matters are biology and the fact that some evolution has occurred; we shall examine these two premises. The premise of biological necessity seems contradictory to the weight they place on functionalism. Ginsburg and Jablonka state that a form of learning, UAL, is a marker for p-consciousness and that it is multiply realisable so that non-mammalian animals can become candidates for p-consciousness. Suppose the crucial aspect of p-consciousness is UAL functionalism. In that case, I do not see why AI is logically ruled out, as Birch, Ginsburg and Jablonka believe, as a candidate for functionally realising UAL in a different material substrate. The second point regarding evolution is perhaps even easier to critique. Many AIs are evolutionary algorithms; staggeringly large numbers of iterations of the AI are produced in discrete generations, and a form of Darwinian evolution is applied (Mirjalili et al. 2020, 3). The ‘fittest’ AI is the end product. Hence the evolutionary aspect need not be a barrier to AI being considered a candidate for p-consciousness using the UAL evolutionary transition marker. From the realist position on p-consciousness we would need to know more about what sort of natural kind p-consciousness actually is. This is something that theory-light approaches, frameworks that do not operate with a fully specified theory of consciousness (Birch 2022, 140–41), such as Ginsburg and Jablonka’s and Shea and Bayne’s, purposefully avoid preventing overt anthropomorphism. So it seems inconsistent to reject artificial cases without careful examination when they undergo evolution to achieve UAL functionally.
Now we shall examine a criticism of the markers of UAL. UAL, as an indicator of p-consciousness, cannot give verdicts on organisms that do not display the five criteria listed in the introduction. There is a risk of false negatives. Animals that do possess p-consciousness run the risk of being labelled as not p-conscious. The problem here is that criteria such as (4) trace conditioning might provide evidence of p-consciousness in humans. However, it is unclear why its absence in a non-human animal should mean that the animal does not possess p-consciousness (Shevlin 2021, 308). An organism that relies heavily on one sense would have very little reason to have developed or retained a capacity for multisensory learning (Shevlin 2021, 308). The connection between learning and p-consciousness can be more broadly questioned. Henry Shevlin suggests that many examples of p-conscious examples in humans, such as perceptions and bodily sensations, are seemingly unconnected to the human capacity for learning (Shevlin 2021, 308). Although Shevlin’s point is not without merit, Ginsburg and Jablonka’s UAL does provide the ability for assessment and diagnosis; knowledge of perception and bodily qualia in humans requires a verbal report. This cannot be done with other animals. We should perhaps not use UAL to rule out an organism from p-consciousness but only to positively ascribe p-consciousness to animals capable of UAL. Perhaps with the identification and addition of more nomological clusters, we may be able to strengthen the negative case to a tolerable uncertainty.
Our final point is to question whether p-consciousness is a natural kind at all. The ‘natural kind methodology’ that Ginsburg and Jablonka have contributed to relies on the premise that p-consciousness is a natural kind. If it is not and is, in fact, a nominal kind, their methodology will not identify p-consciousness, only unlimited associative learning. Daniel Dennett proposes a qualia irrealist stance that equates p-consciousness with access consciousness (Dennett 2015, 2). Access consciousness henceforth referred to as a-consciousness, is the availability of a perception for reasoning and rationally guiding action (Block 1995, 227). Dennett argues that whilst it seems intuitive that the qualia of subjective experience exist, this is, in fact, only an intuition (Dennett 2004, 60–61). Furthermore, Dennett argues that we do not know the limits of sufficiently detailed physical theories. Therefore, it is at least possible that some piece of supposedly non-scientific knowledge, such as the ‘redness’ of red, could be determined scientifically (Dennett 2004, 60–61). Hence, there is a possibility that p-consciousness is not a natural kind. Suppose this is the case and it is a nominal kind; Ginsburg and Jablonka’s research programme would be doomed. UAL testing would only be able to tell us about varying capacities of a-consciousness in animals and not provide a definitive and helpful diagnostic of p-consciousness as intended.

4 Conclusions

To conclude, we have seen that Ginsburg and Jablonka’s evolutionary transition marker theory fulfils the description of the natural kind methodology proposed by Shea and Bayne. This leads us to believe that Ginsburg and Jablonka must be p-consciousness realists. Shea and Bayne’s framework allows us to answer the question as to whether UAL is equatable to p-consciousness. We have found it is not and is a nomological cluster of evidential properties, best explained by the natural kind existence of p-consciousness in the realist position. The connection between Ginsburg and Jablonka’s and Shea and Bayne’s respective frameworks allows us to note the possibility of a more comprehensive research programme following the natural kind methodology.
The evolutionary perspective of Ginsburg and Jablonka’s theory provides a compelling hypothesis as to the early origins of p-consciousness and its role in the Cambrian explosion of new species. This contains that the distribution of p-consciousness in the animal phyla may be extensive across many different neural structures, all realising p-consciousness in different ways.
I also dispute that UAL can be dismissed out of hand when applied to AI due to the functionalism approach employed by Ginsburg and Jablonka. They appeal to multiple realisability to allow for animals with wildly different neural structures to mammals to be included as candidates for p-consciousness. Additionally, AIs are already produced with evolutionary algorithms, so their dismissal from the evolutionary transition marker framework could be categorised as biased and biological chauvinism.
We have also concluded that UAL is susceptible to false negatives and should be supplemented with other nomological clusters to reduce this uncertainty. We should also exercise caution when applying the UAL diagnostic to exotic organisms that differ significantly from ourselves. Some UAL criteria do not seem reasonable when applied to some creatures in some environments where the precise form of learning being tested would have little use.
Whilst we admit the possibility due to Dennett’s critique that p-consciousness might not be a natural kind, the possibility for further empirical research using the natural kind methodology is too alluring to give up at present. Not only can researchers into non-human p-consciousness perform empirical research with animals using the UAL diagnostic. Additionally, they can search for more nomological clusters to reduce uncertainty in their assessments, making UAL and its underlying natural kind methodology a profitable investment of time and resources going forward.

References

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