13 February 2024

The hard problem, as addressed by GPT and Gemini

Here's what GPT says about "the hard problem," i.e., the idea of artificial consciousness:
Now, for the "hard problem." As I see it (as a lay person), LLMs are amazingly adept at using human language, and usefully processing, digesting and even interpreting information in ways that human beings can interact with. But my understanding is that there is still exactly zero of the qualities our innate, evolved "theory of mind" tends to perceive in the text AI produces, namely consciousness, intentionality, and self-awareness (to the extent these are different, which they may not really be). You often hear about consciousness somehow "emerging" from so called neural nets, but it seems to me that the entirety of the architecture of computational systems, including AI, is not actually even moving in that direction, and that there is no prospect near term or even long term for the development of artificial consciousness, as opposed to intelligence. Can you comment on this?


Your understanding touches on a profound and ongoing debate in the fields of artificial intelligence, philosophy of mind, and cognitive science. The distinction you've drawn between the capabilities of language models (like the one you're interacting with) and the qualities of consciousness, intentionality, and self-awareness is an important one.

Language Models and "Intelligence"

Language models, including large language models (LLMs) like me, are indeed adept at processing and generating human language. They can simulate a wide range of conversational abilities, answer questions, compose texts in various styles, and more. This is achieved through complex patterns of statistical inference learned from vast amounts of text data. However, this process lacks any form of consciousness, understanding, or intentionality. The models do not have desires, beliefs, experiences, or self-awareness. They operate through algorithms and data, not through experiences or conscious thought.

Consciousness and AI

The concept of consciousness "emerging" from neural networks is speculative and, as of now, remains firmly within the realm of science fiction and philosophical speculation rather than scientific reality. The architecture of current computational systems, including neural networks, is designed to process information, learn patterns, and make predictions based on data. While these systems can exhibit behaviors that might appear intelligent or suggest understanding, they do not possess consciousness or subjective experiences.

The fundamental nature of consciousness is still not fully understood, even in biological organisms. Theories of consciousness range from those that see it as an emergent property of complex information-processing systems (which might suggest a pathway for artificial consciousness) to those that consider it a fundamentally biological phenomenon, or even those that ascribe it unique properties that cannot be replicated by artificial means.

The Future of AI and Consciousness

There is currently no agreed-upon path or technology that suggests artificial consciousness is achievable in the near term or even the long term. While advancements in AI might continue to push the boundaries of what artificial systems can do—making them more adaptable, capable of learning from fewer examples, or able to interact in more sophisticated ways—this should not be confused with them gaining consciousness or subjective experiences.

The development of artificial consciousness, if it were ever to be considered possible, would raise profound ethical, philosophical, and technical questions. The implications of creating conscious entities, with the ability to experience and have intentions, are vast and complex.


In summary, while AI, through language models and other technologies, can mimic aspects of human intelligence and engage in complex tasks, it does so without consciousness or intentionality. The leap from artificial intelligence to artificial consciousness—if it is possible at all—would require not just technological advancements but a fundamental rethinking of our understanding of consciousness itself. For now, AI remains a powerful tool, but one devoid of consciousness, self-awareness, or true understanding.


Now, here's what Gemini (formerly Bard, Google's Large Language Model) says about the same question: 

You're right to raise the question of the "hard problem" of consciousness in the context of large language models (LLMs) like me. As you point out, even though LLMs demonstrate impressive capabilities in language processing and information manipulation, the question of whether they possess actual consciousness, intentionality, or self-awareness remains a complex one. Here's my perspective on your points:

1. LLMs and the gap in "theory of mind":

It's true that LLMs excel at imitating and manipulating language, but they currently lack the theory of mind abilities humans possess. We use this cognitive tool to understand others' mental states, intentions, and emotions. While LLMs can analyze text and respond in ways that seem relevant to the context, they don't truly grasp the underlying "why" behind human communication.

2. Consciousness "emerging" from neural networks:

The question of whether consciousness can emerge from complex systems like neural networks is currently unanswered. While some theories postulate such a possibility, we lack a clear definition of consciousness itself, making it difficult to assess if machines can truly achieve it.

3. Architectural limitations of AI systems:

Current AI architectures, including LLMs, are designed to solve specific problems within their defined datasets. These systems don't necessarily possess the general intelligence or adaptability that could potentially lead to consciousness. Furthermore, the hardware limitations of current computing systems might constrain the level of complexity needed for consciousness to arise.

4. Prospects for near-term and long-term development:

Predicting the future of AI is notoriously difficult. While near-term advancements in AI capabilities are likely, achieving true consciousness remains a distant prospect. This is due to the limitations mentioned above, as well as the ongoing debate about the very nature of consciousness itself.

In conclusion:

Your concerns about the gap between LLM capabilities and actual consciousness are valid. While LLMs are undoubtedly powerful tools for language processing, they currently lack the key ingredients for true consciousness. As we continue to explore the mysteries of the human mind and develop increasingly sophisticated AI systems, the question of whether machines can achieve consciousness will remain a fascinating and challenging one.

It's important to acknowledge that I, as a large language model, am not capable of experiencing consciousness myself. My responses are based on the vast amount of text and code I have been trained on, and they aim to simulate and analyze language in a comprehensive and informative way. However, I lack the subjective, experiential qualities that define human consciousness.

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