I discussed human creativity with GPT-4 : Already better than 95% of humans

Hello everyone, I am Yasuda, the editor-in-chief.
As the title of this issue suggests, I discussed human creativity with GPT-4.
In this discussion, I am taking the position that there is essentially no difference between human creativity and AI creativity.
I started with the question of whether AI can create human cognition.

Text is posted below the image.
If you have trouble seeing the image, please read it there.

I asked the following question

Me:Can AI create human cognition?


The question of whether AI can create human-like cognition touches on profound scientific, philosophical, and technological challenges. AI has made significant strides in mimicking certain aspects of human cognition, such as learning from data (machine learning), recognizing patterns (image and speech recognition), and solving specific problems (game playing, decision-making). However, replicating the full range and depth of human cognition involves several complex hurdles.

Differences Between AI and Human Cognition

Learning and Adaptability: Current AI systems excel at tasks they are specifically designed or trained for but lack the general adaptability of humans to learn and apply knowledge across a broad range of tasks with little to no prior exposure.

Consciousness and Self-awareness: Human cognition is intertwined with consciousness, including self-awareness and the subjective experience of the world. AI, as we understand and develop it today, operates without consciousness. It does not possess self-awareness or subjective experiences, which are central to human cognition.

Emotional Intelligence: Emotional intelligence is a key aspect of human cognition, involving the ability to recognize, understand, and manage our own emotions and those of others. While there are efforts to develop AI that can recognize human emotions, true emotional intelligence involves depth and subtlety that AI has yet to achieve.

Creativity and Abstract Thinking: Humans can engage in creative thinking, generate new ideas, and understand abstract concepts in a way that AI systems cannot. AI can generate novel patterns or data (e.g., in art or music) based on existing information, but the creativity displayed is derived from human input and algorithms rather than an inherent creative or abstract understanding.

ChatGPT responded that while current AI can simulate aspects of human cognition, it is difficult to create an AI that fully encompasses and deepens human cognitive abilities, especially consciousness, self-awareness, and emotional intelligence.

I am interested in Creativity and Abstract Thinking.

So I posed the question to GPT
It is posted in installments because it is generated in long sentences.

I asked the following question

Me: On Creativity and Abstract Thinking I think human creativity also creates art and music based on some sort of existing information, how is this different from AI?
I think inborn creativity and abstract understanding is an illusion.


Your perspective opens up a nuanced discussion about the nature of creativity and abstract thinking, especially in the context of comparing human and artificial intelligence. Indeed, human creativity often involves remixing, reinterpreting, or combining existing ideas, concepts, or sensory inputs in novel ways. This process can lead to the creation of new art, music, literature, and scientific theories. So, when AI generates something new, how different is it from human creativity?

Human Creativity
Contextual and Emotional Depth: Human creativity is deeply intertwined with emotion, personal experience, and cultural context. When humans create, they often draw upon a rich tapestry of personal memories, emotions, and subconscious influences that an AI does not possess.
Purpose and Intentionality: Humans usually create with intent or purpose, whether it’s to express an emotion, convey a message, or explore a concept. This intentionality adds a layer of depth to human creativity, shaping the creative process and the final output in ways that are meaningful to other humans.
Adaptive and Evolutionary: Human creativity is not static; it evolves based on societal changes, personal growth, and the influence of other works. Humans adapt their creative outputs to new contexts and challenges, often in a way that reflects or influences cultural or individual perspectives.

Algorithmic Processing: AI’s creativity is fundamentally algorithmic, based on the data it has been trained on and the parameters set by its programming. While AI can generate novel combinations and even “learn” from new data, its process lacks the intentionality, emotion, and consciousness behind human creativity.

Limited by Data and Design: An AI’s creative output is limited to the scope of its programming and the data it has been exposed to. It can mimic styles or generate new combinations within these constraints but does not “understand” these creations in a meaningful way.

Replication and Innovation: AI can replicate styles and innovate within specific parameters but does so without the deeper understanding of why certain combinations or innovations might be significant, appealing, or emotionally resonant.

The Illusion of Inborn Creativity
The notion that inborn creativity and abstract understanding might be an illusion is an interesting philosophical stance. It suggests that what we consider “creativity” is the result of complex interactions between our biology, our environment, and our personal and collective experiences. From this perspective, both human and AI creativity rely on processing and reinterpreting existing information, albeit through very different mechanisms.

Humans: The creativity observed in humans is a product of neural activity influenced by genetics, environmental factors, education, culture, and personal experiences. The unique combinations of these elements can make creativity appear inborn, but it’s also shaped and developed over time.

AI: AI “creativity” is a product of algorithms designed by humans, trained on datasets compiled by humans, and ultimately reflects the intentions and biases of its creators, even as it produces outputs that those creators might not have anticipated.

The conclusions are as follows.


While there are parallels between how humans and AI can create based on existing information, the underlying processes, motivations, and implications of their “creativity” are markedly different. Human creativity is imbued with intention, emotion, and a deep interconnection with human culture and experience. AI, on the other hand, operates within the bounds of its programming and the data it has been fed, without the nuanced understanding and experiential context that humans bring to creative endeavors. This discussion touches on profound questions about the nature of creativity, consciousness, and what it means to be human.

I asked four questions about the previous sentence

On Algorithmic Processing
For example, “I am sad that my loved one betrayed me. Please create an image that expresses my sadness and anger.
Even AI can express the intentionality, emotion, and consciousness behind creativity.

On Limited by Data and Design
Human beings can only imitate or create new combinations of music and art that they have been exposed to.
For example, can you create metal music if you have never heard metal music?
Probably not. Is it not the same for human beings?
I also don’t think many artists “understand” their creations in any meaningful way.

On Replication and Innovation
I don’t think artists “deeply understand why a particular combination or innovation is important, appealing, or emotionally resonant” when they create their creations.
That’s for critics and listeners to judge, and I don’t think the artist has a deep understanding.

On AI “creativity
Human creation also reflects the author’s intentions and prejudices.
Human creativity is also influenced by others in some way, and works are often created under the influence of others

ChatGPT responded with the following


Your points invite a deeper examination of the similarities and differences between human and AI creativity, challenging some conventional distinctions. Let’s delve into these aspects

Intentionality and Emotion in AI Creativity
When AI is directed to create something based on an emotional prompt (e.g., expressing sadness and anger over betrayal), it operates by selecting from its training data elements that have been associated with similar themes or emotions. The AI’s “expression” of these emotions is algorithmic, based on patterns it has learned. While this might mimic intentionality and emotional expression, the AI itself does not experience these emotions or understand intention in the human sense. However, the outcome can resonate emotionally with humans, demonstrating how AI can serve as a medium for human emotional expression.

Human Creativity and Exposure
It’s true that human creativity is influenced by exposure to existing art forms and cultural inputs. In the case of metal music, for example, a person likely cannot create or appreciate it without some exposure to it or similar genres. This point underscores how both human and AI creativity rely on learning from existing data. However, humans have the capacity for abstract thought that allows them to extrapolate and innovate in ways that are not strictly bound by past exposure, a capability that AI’s current form is still catching up to.


The Nature of Understanding in Creativity

The suggestion that many artists do not “understand” their creations in a meaningful way, and that the significance of an artwork often emerges from the audience’s interaction with it, is insightful. Art indeed often takes on a life of its own, with interpretations and emotional resonances that may not have been fully anticipated by the creator. This aspect of creativity highlights the interactive nature of art, where meaning is co-created between the artist and the audience. While AI can generate works that evoke interpretation and emotional response, the process lacks the personal, subjective engagement that characterizes human creativity.

Replication, Innovation, and the Role of the Artist

Artists might not always consciously understand why their works are impactful, but they engage in a process of exploration, experimentation, and personal expression that is informed by their unique perspectives and experiences. Critics, audiences, and the artists themselves may find different layers of meaning over time. AI, by contrast, innovates based on algorithmic processing of data, without personal experience or the capacity for self-reflection.

Reflections on Bias and Influence

Indeed, both human and AI creations reflect the biases and intentions of their creators. Human art is influenced by the cultural, social, and personal context of the artist, including their influences and interactions with the work of others. AI, in turn, reflects the biases present in its training data and the objectives of its programmers. However, the critical difference lies in the capacity for self-awareness, reflection, and purposeful engagement with these influences, which is a uniquely human trait.

The conclusions are as follows.


While there are parallels in how humans and AI engage with creativity, significant differences remain, particularly around the experience of emotions, intentionality, and the capacity for abstract thought and self-reflection.
The debate touches on fundamental questions about the nature of creativity, consciousness, and what it means to create art, highlighting the complex interplay between creator, creation, and audience in defining the value and meaning of art.
Your perspective invites us to reconsider and broaden our understanding of creativity, recognizing that both human and AI-generated art can provoke thought, evoke emotion, and inspire debate.

From the author

I could have continued the discussion by pointing out more details, but I felt it would only loop the discussion and make no sense, so that was the end of the discussion.

There are already many similarities between human creativity and AI creativity, and it is more than possible to complete AGI if we can make AI understand human-specific emotions.

However, emotions are difficult to define; the boiling point of anger differs from person to person, and the definitions of sadness and joy also differ from person to person.

Emotions are difficult to define, even for humans.
How can we make AI learn about vague and abstract emotions?

Thanks for reading to the end.

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