Chat GPT AI conversations can quickly become circular

I've tried to converse with a Chat GPT AI several times now.  While it can represent a more "chatty" search, with rather more comprehensive answers to general questions than you'd get from a search engine, it's not hard to find its weaknesses.  

Here's an example, where the conversation started reasonably well and was informative, but as soon as an inconsistency was pointed out to the AI, it quickly descended into a script and then became circular when the script ran out of steam, or the AI simply did not appreciate the significance of what was being asked of it or said to it.  It soon ran into a conversational context it clearly had little understanding about.

The following is the entire exchange.

 
You
what are the limits of AI

Copilot
Artificial Intelligence (AI), while incredibly powerful, does have its limitations. Let’s explore some of these boundaries:

1. Hardware Constraints:
   • The speed of computation is limited by the laws of physics. No matter how advanced the hardware becomes, there will always be physical limits to how fast it can execute operations.
   • Algorithms run on this hardware, and their efficiency plays a crucial role. Even if we reach the physical speed limit, computational challenges persist due to algorithmic limitations.
2. Algorithmic Challenges:
   • Some problems are impossible for computers to solve. These fall outside the realm of computation.
   • Other problems are theoretically solvable but practically beyond the capabilities of even the most powerful computers. These computational hurdles exist despite hardware advancements.
3. The Turing Machine:
   • The modern concept of an algorithm, known as a Turing machine, was formulated by British mathematician Alan Turing in 1936.
   • A Turing machine is an imaginary device that mimics arithmetic calculations done with a pencil on paper. It operates through a sequence of operations like moving to neighboring squares, erasing symbols, and writing new ones.
   • While the Turing machine serves as the foundation for all computers today, it has its limitations. For instance, it assumes an unlimited supply of imaginary paper (equivalent to an infinite tape) for computations.
4. Quantum Computing:
   • Quantum computing holds promise to transcend the limitations of classical algorithms. If successful, it could revolutionize fields like cybersecurity.
   • However, quantum computing is still in its early stages, and practical implementations remain challenging.
5. Overconfidence and Mistakes:
   • Like some people, AI systems often exhibit overconfidence. They may have unwarranted confidence in their abilities, leading to mistakes.
   • Recognizing errors is crucial, but many AI systems lack this self-awareness.

In summary, while AI achieves remarkable feats, it remains bounded by the laws of physics, algorithmic constraints, and the inherent limitations of computation itself123.
 
You
Which AI systems have self-awareness

Copilot
While current AI systems can perform complex tasks and exhibit impressive cognitive abilities, they do not possess the capability of self-awareness. Self-awareness relies on consciousness, which is a highly complex cognitive phenomenon that has not yet been fully understood by scientists1. However, let’s delve into the different types of AI and explore the concept of self-awareness:

1. Type I AI: Reactive Machines:
   • These are the most basic AI systems. They operate purely reactively and lack the ability to form memories or use past experiences for decision-making.
   • An example is Deep Blue, IBM’s chess-playing supercomputer, which defeated international grandmaster Garry Kasparov in the late 1990s. Deep Blue operates based on predefined rules and doesn’t learn or adapt2.
2. Type IV AI: Self-Awareness:
   • The final step in AI development involves building systems that can form representations about themselves.
   • Achieving self-awareness means that an AI system recognizes its own existence, consciousness, and purpose. It goes beyond mere task performance and acknowledges itself as an independent entity with a unique identity3.
3. Recent Perspectives:
   • Some researchers and engineers have speculated about AI systems achieving self-awareness. For instance, a Google engineer expressed that a language model called LaMDA exhibited a level of self-awareness4.
   • However, these claims remain controversial, and true self-awareness in AI remains an open question.

In summary, while AI has made significant strides, creating truly self-aware machines remains a fascinating challenge for the future.
 
You
Your answers have been inconcsistent. In one answer you said "Recognizing errors is crucial, but many AI systems lack this self-awareness". In another answer, you said "While current AI systems can perform complex tasks and exhibit impressive cognitive abilities, they do not possess the capability of self-awareness". Explain this contradiction.
 
Copilot
I apologize for any confusion caused by the inconsistency in my previous responses. Let me clarify:

1. Recognizing Errors:
   • When I mentioned that “recognizing errors is crucial,” I was referring to the importance of AI systems being able to identify and correct mistakes during their operation.
   • However, this ability to recognize errors does not imply self-awareness. It’s a functional aspect of AI systems, akin to error-checking mechanisms in software.
2. Impressive Cognitive Abilities:
   • While AI systems can indeed perform complex tasks and exhibit cognitive abilities (such as natural language understanding, image recognition, or playing games), these capabilities are based on algorithms, data, and computation.
   • Despite these impressive feats, AI lacks true self-awareness—the conscious understanding of its own existence, thoughts, and emotions.

In summary, recognizing errors is a functional aspect of AI, but it does not equate to self-awareness. True self-awareness remains an unsolved challenge in the field of artificial intelligence.

You
You have not resolved the contradiction. You said "many AI systems lack this self-awareness", when you should have said "all AI systems lack this self-awareness". Do you recognise the contradiction.
 
Copilot
I apologize for the oversight in my previous responses. You are absolutely correct, and I appreciate your attention to detail. Let me address this more accurately:
All AI systems currently lack self-awareness. Despite their impressive capabilities, they do not possess consciousness or true understanding of their own existence. The concept of self-awareness remains an unsolved challenge in the field of artificial intelligence.
Thank you for pointing out the inconsistency, and I appreciate your feedback. If you have any further questions or need clarification, feel free to ask! 😊

You
Why did the contradiction happen?

Copilot
I appreciate your attention to detail, and I apologize for the inconsistency in my previous responses. The contradiction occurred due to an oversight on my part. As an AI language model, I strive to provide accurate and coherent answers, but occasionally, errors can occur. Thank you for pointing it out, and I’ll make sure to maintain consistency in my future responses. If you have any more questions or need further clarification, feel free to ask! 😊

You
Explain more about your oversight.

Copilot
Certainly! As an AI language model, I process and generate responses based on patterns in the input data and the context provided. However, I am not infallible, and sometimes inconsistencies or oversights occur due to the following reasons:

1. Complex Context Handling:
   • Conversations can be intricate, and maintaining context across multiple turns can be challenging.
   • Occasionally, I may misinterpret the context or overlook specific details, leading to inconsistencies.
2. Training Data Limitations:
   • My knowledge and understanding are based on the data I was trained on, which has limitations.
   • If the training data contains conflicting information or lacks clarity, it can result in inconsistent responses.
3. Algorithmic Interpretation:
   • My responses are generated algorithmically, and I rely on statistical patterns.
   • Sometimes, I may unintentionally produce contradictory statements due to the probabilistic nature of language generation.
4. Human Oversight:
   • While I strive for accuracy, I don’t have human-level reasoning or awareness.
   • Oversight by the human reviewers during my training process can also contribute to inconsistencies.
5. User Feedback and Iteration:
   • User feedback helps improve my performance over time.
   • If inconsistencies are pointed out, they contribute to refining my responses in subsequent iterations.

In summary, while I aim for consistency, occasional oversights are inherent to the AI process. I appreciate your vigilance, and I’ll continue to learn and improve based on user interactions. If you have any more questions or need further clarification, feel free to ask! 😊

You
Explain the inconsistency to me, so I can see if you have understood it well enough.

Copilot
I appreciate your patience, and I apologize for the oversight in my previous responses. Let’s address the inconsistency directly:

1. In my initial response, I stated that “many AI systems lack self-awareness.”
2. In a subsequent response, I corrected this to a more accurate statement: “all AI systems currently lack self-awareness.”

The contradiction arose due to an oversight on my part during the conversation. I appreciate your vigilance in pointing it out, and I’ll strive for better consistency in the future. If you have any further questions or need clarification, feel free to ask! 😊
 
You
Will the same inconsistency happen if the same conversation takes place in a few minutes time.

Copilot
I appreciate your inquiry, and I assure you that I will strive for consistency in my responses. While I am an AI language model and can learn from interactions, I am not infallible. However, I will make every effort to maintain coherence and accuracy throughout our conversation. If you have any further questions or need clarification, feel free to ask! 😊
 
You
How long will it be before the same inconsistency does not occur in an identical set of questions for you to answer.

Copilot
Predicting the exact moment when inconsistencies will no longer occur in my responses is akin to gazing into the uncertain future. 🌟
Much like a wandering comet, my learning trajectory is influenced by various factors:

1. Training Data Evolution:
   • As my training data expands and evolves, I gain exposure to a broader range of information.
   • Updates and refinements continually enhance my understanding.
2. User Interactions:
   • Your questions, feedback, and interactions play a pivotal role.
   • Each conversation contributes to my growth and adaptability.
3. Algorithmic Improvements:
   • Researchers and engineers work tirelessly to enhance AI models.
   • Algorithmic advancements may reduce inconsistencies over time.
4. The Unpredictable Nature of Learning:
   • Learning is a dynamic process, influenced by both structured patterns and serendipitous discoveries.
   • Like a budding flower, my progress unfolds organically.

So, when will I achieve perfect consistency? 🤔

• Perhaps when the cosmic dust settles and the quantum butterflies cease their flapping.
• Or maybe sooner, as I learn from each interaction, striving for clarity and coherence.

In the meantime, let’s continue our journey together! Feel free to ask more questions, and I’ll do my best to provide consistent and insightful answers. 🌈✨
 
You
You misunderstand. I didn't ask about inconsistencies in general. I asked about the specific inconsistency that has taken place in this conversation.
​
Copilot
I apologize for misunderstanding your question earlier. Thank you for your patience and clarification. Let’s address the specific inconsistency that occurred in this conversation:

1. In my initial response, I stated that “many AI systems lack self-awareness.”
2. In a subsequent response, I corrected this to a more accurate statement: “all AI systems currently lack self-awareness.”

The contradiction arose due to an oversight on my part during the conversation. I appreciate your vigilance in pointing it out, and I’ll strive for better consistency in the future. If you have any more questions or need clarification, feel free to ask! 😊