Paper on Loops in AI and Consciousness

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Title: A Characterisation of processing loops in AI and biological neural networks and its implications for understanding Consciousness

Abstract

Shows that any sufficiently advanced processing system requires loopy processing, which requires regulation, which requires a self-model, and that this structure can lead to self-referential conclusions about an agents own mental faculties and their involvement in its own agency.

Introduction

Any computational system is limited in the complexity that it can handle within a single computational step. For embodied agents, this appears as a limit on the environmental complexity that they can sufficiently model and respond to within a single "time step" (citation needed). For more complex problems, multiple steps of processing are required in order to determine the next physical action. Such multiple processing steps may entail, for example, further analysis of the environment in order to better model its state; or it may entail action planning over multiple iterations.

In biology, this provides scope for evolutionary pressures to trade off between a more energy hungry complex brain and a simpler less energy intensive one that takes longer to make some decisions.

An agent that regulates its environment operates within a system described in Fig 1. The environment state S_env changes with some ambient dynamics env dynamics, and the agent performs action A_env against the environment in order to regulate it towards some target. The environment state outcome O_env is influenced by both D_env(t) and A_env. Fig 1:
{diagram} S_env + D_env(t) + A_env = O_env {diagram}

According to the good regulator theorem, if the agent is to regulate the environment state it must be a model of the system (Conant & Ashby, 1970). Furthermore, we can say that the efficiency of the agent to regulate its environment depends on its accuracy in modelling the system. Errors in the accuracy of the model result in errors in the regulation of the system. For learning agents, those errors must be used to adjust the model. An agent that must regulate its external environment requires the tuple <S_env, A, O_env> in order to adjust its model.

An embodied agent with complex actions requires an additional level of regulation. Not only must it regulate its external environment, it must also regulate its own physical state. This includes both maintaining homeostasis and controlling action. Such an agent thus operates in a system that additionally has body state S_body with ambient dynamics D_body(t). The agent performs action A_body against its body, producing outcome O_body. Summarised as follows:

S_body + D_body(t) + A_body = O_body

The agent's actions are performed in order to regulate it towards some target, which is dynamically inferred based on its requirement for body homeostasis and for environment action A_env. Like for regulation of the environment, the agent requires a tuple <S_body, A_body, O_body> in order to train its model. Neuroscience has identified such a model in mammals, known as the body schema (Proske & Gandevia, 2012).

Agents that incorporate multi-step processing have a third kind of action: one that changes its internal data state without affecting its physical state. Importantly, as such non-physical actions may not elicit any change to S_body or S_env, this system also requires regulation. Thus the agent has non-physical state S_mind with ambient dynamics D_mind(t), and performs action A_mind producing outcome O_mind, summarised as follows:

S_mind + D_mind(t) + A_mind = O_mind

The agent's non-physical actions are performed in order to regulate towards some target, which is dynamically inferred based on its requirement for environment action A_env, body action A_body, and possibly for some form of non-physical homeostasis. Like for both the environment and body, the agent must train its model for regulation from a tuple <S_mind, A_mind, O_mind>.

By way of example, consider the case of fluent aphasia, caused by damage to the Wernicke's area of the brain. Individuals with fluent aphasia can easily produce speech, but it is typically full of many meaningless words and often unnecessarily long winded. Wernicke's area is associated with language comprehension and, as such, provides a corrective mechanism during speech production in a neurotypical individual (Wernicke's area).

The need for a mind-regulating agent to model the behaviour of its mind suggests that it must incorporate a functional equivalent of the body schema, which this paper refers to as the mind schema. Other research has drawn similar conclusions (Graziano, 2017).

Visceral Loop

This paper introduces the concept of a visceral loop as a characterisation of processing within a looping biological or AI agent. The visceral loop is so named because it refers to an agent concluding that it experiences consciousness "in a visceral way". It identifies that a processing loop with sufficient representational capabilities can, at the most optimum, conclude itself as conscious within three iterations of the loop. Each of those iterations have specific characteristics, and the visceral loop characterises thought as falling into one of those three iterations.

Let:

• E be the agent's set of beliefs about the external world
• B be the agent's set of beliefs about its own physical body (drawn from the body schema) and of bodies in general, and if it has a concept of "I" then this set includes a belief that relates other body beliefs to "I"
• M be the agent's set of beliefs about its own mind (drawn from the mind schema) and of minds in general, and if it has a concept of "I" then this set includes a belief that relates other mind beliefs to "I"
• f(..) be the function executed by the agent on the specified inputs in order to draw inferences

M can be thought of as an agent's "theory of mind", because it relates to not such itself but also its ability to predict the hidden mental state of others.

Iteration 1:

Let x be an inference produced as the result of a processing step, such that it does not draw any reference to M (ie: if x is a value then x ∉ M, or if x is a relation of two values then x = relation{a:b} such that a ∉ M and b ∉ M, or if x is a relation involving a set then x = relation{a:B} such that a ∉ M and B ⊄ M). Given some sense input or past state s, a processing step is characterised as visceral loop Iteration 1 if it is of the following form:

• f(s, E ∪ B ∪ M) -> x

Iteration 2:

Iteration 2 requires an agent to have sufficient representational capabilities to draw inferences that represent relations involving M. Given some prior inference y, a processing step is characterised as visceral loop Iteration 2 if it is of the following form, and the relation with respect to M is non-empty, and it can not be characterised as Iteration 3:

• f(y, E ∪ B ∪ M) -> relation{y:M}

Iteration 3:

Iteration 3 likewise requires the agent can represent relations involving M. Given some prior inference relation{z, M}, and some belief m ∈ M, a processing step is characterised as visceral loop Iteration 3 if it is of the following form and the relation with respect to M is non-empty:

• f(relation{z:M}, E ∪ B ∪ M) -> relation{m:M}

Iteration 1 represents the most common kind of data processing, such as spending multiple processing cycles to refine the identification of something within the visual field. While an agent's mind schema may be used to control the thought process, the result of Iteration 1 never makes any reference to the agent's own mind schema.

Iteration 2 processing steps draw conclusions that relate past conclusions to the agent's theory of mind.

..tbd.. examples...

Consciousness

The visceral loop can be applied to understand the thought processes whereby an individual concludes themselves as conscious. Consider the following sequence of internal mental observations:

1. "What's that red blob in the tree? Oh, it's an apple".
2. "Oh, those thoughts just came from my mind, and not from the outside world".
3. "That's what consciousness is. I am conscious".

The first observation is a straightforward example of Iteration 1 that does not make any self-reference to the agent's theory of mind (of their own mind or of others).

The second observation is an example of Iteration 2. However it is of specific form, whereby the individual produces an inference that identifies the source of the past thought in relation to their own mind schema (recall that this is a subset of M).

The third observation is additionally a specific form of Iteration 3, whereby the individual produces an inference based on the prior specialisation of Iteration 2, and produces an inference as a statement of fact about their own mind-schema. In this observation, the resultant inference is in relation to some a priori conception about consciousness in general.

The concept of the visceral loop may appear simple, but it has important implications for understanding consciousness. By way of example of its descriptive power, a theorem of consciousness is offered in the text that follows.

Let's first establish a baseline. The author is unable to think of any rationale way in which I may consciously experience something and yet be unable to subsequently knowingly think about that experience. Thus, it would seem that being able to knowingly think about our conscious experiences is a fundamental component of consciousness. The following claims are derived from this statement, without further proof:

Claim 1:

• All conscious experience is subsequently available for further thought.

Claim 2:

• For all thought about conscious experience, the individual can identify that thought as being their own.

Note that these claims do not assume that all conscious experience is actually thought about; only that it is available for such thought. Additionally, no assumption is made about other kinds of thought, which may or may not be consciously experienced.

Theorem 1:

• what data is possible to be identified within a visceral loop iteration 2 inference defines an upper boundary on the content of conscious experience.

Proof:

• The content of conscious experience refers to the set of data represented and/or processed within the brain which is consciously experienced by that individual, in distinction to other data represented and/or processed in the brain which is not consciously experienced.
• As per claims 1 and 2, all of conscious experience must be available for further thought and the individual must be able to identify that thought as their own.
• In order for an individual to identify thought as being their own, they must have some beliefs about thought and how it relates to themselves as an individual entity. This is included in the set M, which iteration 2 produces inferences in relation to.
• Imagine some supposed experience for which thought about it cannot be referenced within an inference produced as a result of iteration 2. For example, due to some incompatibility of structure, lack of data path to iteration 2 processing capabilities, or inherent limitations in iteration 2 processing capabilities. That thought cannot be identified in relation to the individual.
• As such, the supposed experience fails on Claim 2, and any supposed thought about the supposed experience must be in actual fact thought about a non-conscious experience.
• Thus, any experience that leads to thought that cannot be included in an iteration 2 inference is not a conscious experience.

A couple of additional points of interest are worth mentioning....

An example of Theorem 2 is where an event occurs that is potentially available for conscious experience, but it does not become an iteration 2 inference at the time. The individual may still have a memory of that past event, and upon recalling that past event may draw an iteration 2 inference about it, at which time it becomes a conscious experience.

If we ascribe phenomenal experience as a feeling, and recognise that feelings are just additional data input produced through heuristic predictions, then we see that a simulation of a visceral loop, that we intuit to have no phenomenal experience, is computationally indistinguishable from a biological visceral loop that we know to be accompanied by such phenomenon.

Summary and Conclusions

Visceral loop explains why fRMI studies have shown that we become aware of a decision after its made. Because it takes extra processing cycles to consciously consider the fact of the decision being made. In short: we can only think about one thing at a time, so the decision itself and thought about the decision require separate steps.

The visceral loop can be used to explain how someone concludes themselves as conscious. It can also be used to classify the kinds of thought that occur within an agent, and the kinds of thought that it's possible for an agent to have. For example, it may be the case that simpler organisms only ever operate with Iteration 1 thought.

References

Conant, R. C., and Ashby, W. R. (1970). Every good regulator of a system must be a model of that system. Int. J. Systems Sci., vol. 1, No. 2, pp 89-97. https://doi.org/10.1080/00207727008920220. [Full Text]

Graziano, M. S. A. (2017). The Attention Schema Theory: A Foundation for Engineering Artificial Consciousnes. Front. Robot. AI. https://doi.org/10.3389/frobt.2017.00060.

Proske, U., and Gandevia, S. C. (2012). The Proprioceptive Senses: Their Roles in Signaling Body Shape, Body Position and Movement, and Muscle Force. Physiological Reviews 2012 92:4, pp 1651-1697. https://doi.org/10.1152/physrev.00048.2011.

Wernicke's area. (n.d.). In Wikepedia. https://en.wikipedia.org/wiki/Wernicke%27s_area.