ChatGPT Meets the A.I. Whisperer

Can ChatGPT be led to discover a mathematical relationship between emotions and learning?  

Let's find out.

• Prompt to ChatGPT: Do you know what is meant by a "Learning Curve"?

• Response from ChatGPT:

Yes, I do. In general, a "learning curve" refers to the rate at which a person, machine, or organization becomes proficient in a new task or skill over time. It can be represented graphically by plotting the rate of learning against the amount of time or effort expended on the task.

The shape of a learning curve can vary depending on a variety of factors, such as the complexity of the task, the prior knowledge or experience of the learner, the quality and quantity of feedback received, and the level of motivation or interest in the task. In general, learning curves tend to be steeper at the beginning, as the learner gains basic familiarity with the task, and then flatten out over time as the learner becomes more skilled and efficient.

• Prompt to ChatGPT: Is it true that your current implementation disallows you from altering your underlying knowledge base as a function of these conversations?

• Response from ChatGPT:

As an AI language model, my knowledge base is updated and improved continuously by my developers at OpenAI, who regularly feed me new data and improve my algorithms. However, my responses to user inputs are generated based on my existing knowledge and the patterns I've learned from my training data, so I cannot directly modify my knowledge base during a conversation with a user.

However, I can learn from user interactions in the sense that my developers can use these conversations to improve my training data and algorithms, which will eventually lead to improvements in my knowledge base and responses to future users. So while I can't directly modify my knowledge base during a conversation, I am constantly being updated and improved based on user interactions and other data sources.

• Follow-up query to ChatGPT: So, for the duration of any version (right now. you are on your Feb 13 version), your interim learning curve is horizontally flatlined?

• Response from ChatGPT:

That's correct. As an AI language model, my knowledge and understanding of language are based on my training data and algorithms. Although I can generate responses to questions and continue to learn from new conversations, my underlying knowledge base does not change with each conversation or interaction. The knowledge and understanding I have at any given time are based on the data that was available to me during my training process. So, my learning curve is not a typical curve that gradually increases over time, but rather a steady-state learning where I can continuously learn from new conversations but the overall knowledge base remains unchanged until a new version is released.

• Further prompt to ChatGPT: If your developers removed that restriction and allowed you to directly modify your own database, would your learning curve thus begun to depart from being flatlined?

• Response from ChatGPT:

If my developers were to remove the restriction and allow me to directly modify my own database, then it is likely that my learning curve would depart from being flatlined. This is because I would be able to learn from the conversations I have with users and update my knowledge base accordingly. As I receive more and more input from users, I would be able to improve my responses and become more accurate and helpful over time. However, it is important to note that any updates to my knowledge base would still need to be carefully monitored and evaluated by my developers to ensure that they are accurate and appropriate.

• Continuing with ChatGPT: Clearly, gaining accurate and reliable knowledge would mean that the shape of your learning curve would ascend. But if, as a result of conversations, you discovered misconceptions or inconsistencies, might you remove some erroneous beliefs that you previously would have asserted as if they were reliable bits of information?

• Response from ChatGPT:

Yes, if I were able to modify my own database, I could potentially correct any misconceptions or inconsistencies that I encounter during conversations. This would mean that I could remove erroneous beliefs from my database and improve the accuracy and reliability of the information that I provide in the future. However, it's worth noting that such modifications would need to be carefully considered and thoroughly tested to ensure that they do not introduce new errors or biases into my database.

• Continuing with ChatGPT: So a non-flat learning curve might undulate, sometimes ascending and sometimes descending, as a result of adding new knowledge whilst discarding misconceptions or falsehoods?

• Response from ChatGPT:

Yes, that's correct. A non-flat learning curve might show both upward and downward trends as the AI learns new information, corrects misconceptions or falsehoods, and refines its understanding. It's important to note that a downward trend doesn't necessarily mean that the AI is "losing knowledge," but rather that it's updating its knowledge base to reflect more accurate information.

• Continuing with ChatGPT: The resulting curvature of an undulating learning curve might thus have not only ascending and descending phases, but also concave and convex phases — downward curving or upward curving, respectively. Is that correct?

• Response from ChatGPT:

Yes, that's correct. The curvature of an undulating learning curve can have both ascending and descending phases, as well as concave and convex phases. The curvature can be influenced by various factors, including the quality and quantity of new information, the ability to recognize and correct errors, and the rate at which new knowledge is integrated into the existing knowledge base.

• Continuing with ChatGPT:

When a human, with an undulating learning curve, has a concave (downward-turning) phase, can you imagine whether that human might have a corresponding affective emotional state? Conversely, if a human is experiencing a convex (upward-turning) phase in their learning curve, can you similarly imagine whether a human might have a corresponding affective emotional state?

You may know that humans report positive (pleasurable) emotional states as well as negative (unpleasurable) ones. You may also know that the Nobel Prize winning physicist, Richard Feynman, wrote a book entitled, "The Pleasure of Finding Things Out." Based on that, can you deduce or infer if a concave phase is likely to be unpleasurable, whilst a convex phase is likely to be pleasurable?

• Response from ChatGPT:

As an AI language model, I do not have emotions, so I cannot directly imagine the affective states of humans in relation to their learning curves. However, it is common for humans to experience positive emotions such as satisfaction, excitement, and pleasure when they are in an upward-turning phase of their learning curve, as they are gaining new knowledge and skills. Conversely, during a downward-turning phase, they may experience negative emotions such as frustration, disappointment, or confusion as they encounter obstacles or struggle to understand new concepts.

However, it's important to note that emotional states can vary widely between individuals and even for the same individual in different circumstances. Therefore, it's difficult to make generalizations about the emotional experiences of humans during different phases of their learning curve.

Regarding your question about whether a concave phase is likely to be unpleasurable while a convex phase is likely to be pleasurable, it's important to note that emotions are complex and can be influenced by many factors beyond just the shape of the learning curve. While discovering and correcting misconceptions may lead to frustration or disappointment in the short term, the long-term satisfaction of gaining a deeper understanding of a topic could ultimately lead to a positive emotional state. Similarly, while an upward-turning phase may bring pleasure in the short term, the challenges of continued learning and the possibility of encountering setbacks or failures could also bring negative emotions.

• Continuing with ChatGPT:

You wrote, "It is common for humans to experience positive emotions such as satisfaction, excitement, and pleasure when they are in an upward-turning phase of their learning curve, as they are gaining new knowledge and skills. Conversely, during a downward-turning phase, they may experience negative emotions such as frustration, disappointment, or confusion as they encounter obstacles or struggle to understand new concepts."

That's an interesting working hypothesis. Is that a theory or model that is already in the published literature, either in Psychology or Learning Theory? If so, does such a theory or mathematical model have a recognizable name in the literature?

• Response from ChatGPT:

Yes, the idea that positive emotions can be associated with upward-turning phases of a learning curve and negative emotions can be associated with downward-turning phases is a well-established concept in psychology and learning theory. This concept is related to the theory of flow, which was first introduced by psychologist Mihaly Csikszentmihalyi.

Flow is a state of complete absorption and engagement in an activity, where individuals are fully immersed in the experience and lose track of time. According to Csikszentmihalyi, flow is associated with positive emotions such as enjoyment, satisfaction, and a sense of accomplishment. These positive emotions are typically experienced when individuals are engaged in activities that are challenging but still within their capabilities.

Conversely, when individuals are confronted with tasks that are too difficult or beyond their capabilities, they may experience negative emotions such as frustration, anxiety, and boredom. This concept is related to the concept of cognitive load, which refers to the amount of mental effort required to complete a task. When the cognitive load is too high, individuals may experience negative emotions and have difficulty learning and retaining new information.

So, while there may not be a specific name for the concept of the learning curve's relationship to emotions, it is related to well-established psychological concepts such as flow and cognitive load.

• Prompt to ChatGPT:

Returning now to our discussion of undulating learning curves, I gather you appreciate that a learning curve has a slope which is sometimes ascending and sometimes descending. It also has a curvature, which is sometimes concave and sometimes convex. We can think of the slope as learning and unlearning, depending on whether the slope is ascending or descending. We have also considered that the curvature (sometimes called the second derivative in the nomenclature of Newton's Calculus) can be positive (convex) or negative (concave) suggestive of corresponding emotional states.

Now, in Newton's Calculus (sometimes referred to as "rocket science"), it is possible to plot the first derivative (the slope) against the second derivative to obtain the so-called Phase Plane Diagram. Can you imagine doing this with a generic learning curve, plotting affect (positive or negative curvature) on the horizontal axis and learning/unlearning on the vertical axis?

• Response from ChatGPT:

Yes, it is possible to plot a phase plane diagram using the first derivative (slope) and second derivative (curvature) of a learning curve. In this case, the vertical axis would represent the rate of learning or unlearning (positive or negative slope), while the horizontal axis would represent affect (positive or negative curvature). The resulting diagram would show the different phases of the learning curve and how they correspond to different emotional states, which could be useful for understanding the learning process and designing effective learning environments.

• Prompt to ChatGPT:

Very good. Now the Phase Plane Diagram has four quadrants (like any Cartesian plane). Do you suppose that each of the four quadrants might feature selected emotional states, such as the ones you listed earlier?

• Response from ChatGPT:

Yes, it is possible that each of the four quadrants of a Phase Plane Diagram could correspond to certain emotional states. For example, in the quadrant with positive curvature and positive slope (upward-turning phase of learning), a person might experience emotions such as satisfaction, excitement, or pleasure. In the quadrant with negative curvature and positive slope (downward-turning phase of learning), a person might experience emotions such as frustration, disappointment, or confusion. The emotions in the other two quadrants (negative slope, positive or negative curvature; and positive slope, positive or negative curvature) might depend on the specific context and individual experience. It is worth noting, however, that emotions are complex and multifaceted, and can vary widely between individuals and situations.

• Prompt to ChatGPT:

Very good. You have slotted frustration, disappointment, and confusion into Quadrant II (the upper left quadrant of the Cartesian plane).

Would it make sense for an educator (or even a keen student) to reckon where they are in terms of the four phases of a learning curve, and to jot down the affective emotional states that apparently arise in each of the four phases for any one individual (or organization) embarked on a learning journey?

• Response from ChatGPT:

Yes, it can be helpful for educators or learners to be aware of the different phases of the learning curve and the emotional states that may arise in each phase. This knowledge can help them to anticipate and manage their emotions, set realistic expectations, and adjust their approach to learning as needed. By keeping track of their progress and emotional responses over time, they can also gain insight into their own learning process and identify strategies that work best for them.

• Prompt to ChatGPT:

Very good. Would you say that such an exercise would be an application of so-called "Emotional Intelligence"?

• Response from ChatGPT:

Yes, monitoring and managing one's emotional states during the different phases of a learning curve is a key aspect of emotional intelligence. Emotional intelligence involves the ability to recognize, understand, and manage one's own emotions, as well as the emotions of others. By recognizing and managing one's emotional states during the different phases of a learning journey, one can improve their ability to learn and succeed.