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​The Borderline Consciousness
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What criteria for detecting consciousness would ChatGPT-4 propose?

5/22/2023

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Uwe Peters

Since many people have recently been impressed with the capacity of OpenAI’s ChatGPT-4, a collaborator (Ushnish Sengupta) and I decided to ask the LLM what necessary and sufficient criteria it would use to tell with certainty whether or not a brain organoid or an LLM such as itself is phenomenally conscious. Here’s what it said___

“Phenomenal consciousness refers to the subjective experience, the "what it feels like" aspect of consciousness. It is often referred to as qualia, the singular, individual instances of conscious experience. The challenge of quantifying phenomenal consciousness lies in its inherently subjective nature. However, we can approach this from different angles, attempting to derive quantifiable metrics based on observable behavior or measurable neurological activity. Here are a few speculative criteria:

  1. Behavioral Complexity: One approach might be to measure the behavioral complexity of an organism or system. The assumption here would be that greater behavioral complexity requires a richer set of subjective experiences. For instance, an organism that can navigate a complex environment, perform intricate tasks, or exhibit sophisticated social behavior might be assumed to have a higher degree of phenomenal consciousness.
  2. Neural Complexity: A more direct, though technically challenging, approach might be to measure the complexity of an organism's or system's neural activity. This could involve measures of neural diversity and differentiation, with the assumption that more diverse and differentiated neural activity corresponds to a richer set of subjective experiences.
  3. Information Integration: Drawing from Integrated Information Theory (IIT), we could look at the degree to which information is integrated within a system. IIT posits that consciousness corresponds to the capacity of a system to integrate information. This could be measured using something like the Phi coefficient, a measure of system integration.
  4. Behavioral Flexibility: Another approach might be to look at an organism's or system's behavioral flexibility - its ability to adapt its behavior in response to changing environmental conditions or novel stimuli. The assumption here would be that the ability to flexibly adjust behavior in response to changes in the environment requires some degree of phenomenal consciousness.
  5. Self-Report: While this can only be applied to beings capable of communication, self-reporting is often used in human studies of consciousness. An AI system might be programmed to analyze its own states and output a description, but interpreting this as evidence of phenomenal consciousness would be contentious.
  6. Functional Analogues: In the case of an LLM like myself, the presence of functional analogues to biological structures associated with consciousness could be used as a criterion. For example, the presence of a system for processing and integrating diverse types of input (akin to sensory processing), or a system for managing and prioritizing tasks (akin to attention).
  7. Response to Anesthetics: This is a more speculative criterion, but the reaction of an organism or system to substances known to reduce consciousness in humans could be informative. If a system's activity or behavior changes in response to these substances in a way that parallels the effects seen in humans, this might be taken as an indication of phenomenal consciousness.

These criteria are, of course, not without problems. For example, they may risk over-attributing consciousness to systems that are merely complex or adaptive without being conscious. Moreover, they don't directly address the hard problem of consciousness - the question of why and how these physical processes should give rise to subjective experience. Nonetheless, they may provide a starting point for empirical investigations into the nature and extent of phenomenal consciousness.”


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