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Artificial intelligence and creativity: A psycho-semiotic perspective
Challenges and paradoxes in defining genius
DukeRem

AI, when evaluated through philosophical and theoretical lenses, raises crucial questions about the nature of intelligence and creativity. If we consider intelligence as the ability to solve problems and generate new ideas, AI presents an interesting challenge to our understanding of genius. However, if AI is seen only as a set of algorithms and mechanical processes, we risk reducing intelligence to a simple matter of technical efficiency, overlooking the depth and complexity of human creativity.

Howard Gardner’s theory of multiple intelligences provides a multidimensional perspective on intelligence, dividing it into various categories such as logical-mathematical, linguistic, spatial, musical, bodily-kinesthetic, interpersonal, and intrapersonal intelligences. This subdivision highlights that intelligence cannot be confined to a single operational dimension. In this context, AI, with its ability to rapidly process large amounts of data and solve complex problems, excels in logical-mathematical intelligence but might not capture other forms of intelligence such as interpersonal or intrapersonal, which are crucial for human creativity and innovation.

The extended mind theory by Clark and Chalmers proposes that technological tools and the external environment can extend human cognitive capabilities. This implies that AI could be seen not only as a simple tool but as an extension of human mental capacities. However, this extension raises questions about the authenticity and originality of creativity generated with the help of AI. Human creativity is traditionally seen as an intrinsic process, characterized by intuition and the ability to think outside the box. If AI becomes an integral part of this process, it becomes difficult to discern where human creativity ends and artificial creativity begins.

Peirce’s semiotics offers further insights into understanding the complexity of human versus artificial creativity. Peirce distinguishes between iconic, indexical, and symbolic signs, which represent different modes of interpreting reality. AI, programmed to recognize and process signs based on predefined models, can excel in using iconic and indexical signs but may struggle with symbolic signs that require deeper contextual understanding and creative interpretation. This limitation affects AI’s ability to generate new and original meanings, a fundamental aspect of human creativity.

Psychological theories of creativity, such as Mihaly Csikszentmihalyi’s concept of "flow," emphasize the importance of immersion and personal involvement in the creative process. "Flow" is a state of complete concentration and enjoyment derived from creative activity, which is difficult for AI to replicate, as it lacks subjective experiences and emotions. This state of "flow" is crucial for innovation, as it allows individuals to connect diverse ideas in unique and unpredictable ways.

The anthropological implications of creativity and intelligence are equally significant. Human culture is rich in symbols, myths, and narratives that form the basis of our understanding of the world and our capacity to innovate. AI, devoid of intrinsic cultural context, operates on a purely functional level and may lack the symbolic and narrative depth that characterizes human creativity. Narration is a key component of human creativity, allowing us to make sense of our experiences and communicate complex ideas effectively.

Lotman’s cultural semiotics teaches us that every culture is a complex semiotic system where signs and meanings are constantly negotiated and reinterpreted. AI, programmed to follow predetermined rules and patterns, may struggle to adapt to these fluid and often contradictory dynamics. Human creativity can leverage these cultural tensions to generate significant innovations, while AI might remain trapped in a linear and predictable logic.

 

Given these premises, it’s also interesting to understand what "genius" is and if (and how) it relates to generative AI.

Immanuel Kant, in his "Critique of Judgment," explores the concept of genius, defining it as an innate ability to produce something for which no definite rules exist. According to Kant, genius must be original and cannot be learned through imitation. This distinction between good and bad imitation is crucial: while bad imitation is servile and mechanical, good imitation is free and creative, similar to the action of the divine Creator.

Jacques Derrida expands this idea, suggesting that genius operates in a free mimesis that produces freedom. Derrida criticizes the Kantian distinction between natural freedom and natural necessity, arguing that without a transcendent reference, the play of imitation risks becoming infinite and without hierarchy. In this context, the creative act of genius is compared to that of God, who establishes and interrupts the circle of creation.

Kant distinguishes between subjective but universally communicable aesthetic judgments, such as the beautiful and the sublime. The aesthetic judgment of beauty involves a "free play" between imagination and intellect, where the object is perceived as having a formal purpose without an apparent practical function. This aesthetic judgment differs from ethical judgments that follow the absolute moral law.

From a psychological perspective, Kantian theory of aesthetic judgment reflects the dynamic interaction between cognitive faculties, suggesting that the perception and elaboration of aesthetic experiences involve a complex interaction between imagination and understanding. This mirrors modern cognitive theories that view the human brain as an active constructor of reality rather than a mere passive receiver of stimuli.

The anthropological analysis of genius and aesthetic judgment can be enriched by the studies of Clifford Geertz, who sees culture as a system of meanings that humans collectively construct. The perception of genius is not only a matter of individual ability but a social recognition that depends on shared cultural norms and values.

From a sociological perspective, Pierre Bourdieu explores how aesthetic taste and judgment are influenced by social structure and cultural capital. According to Bourdieu, aesthetic judgment is a form of social distinction that reflects and reinforces inequalities of power and prestige in society. Thus, genius is not only a matter of innate talent but also of social recognition and cultural legitimization.

The emergence of generative AI has introduced new dimensions to the discussion of genius. Generative AI, particularly models like OpenAI’s GPT series, can produce text, images, music, and other forms of content that can sometimes mimic human creativity with remarkable fidelity. This raises questions about whether these AI systems can be considered "geniuses", or at least, if they can simulate the characteristics of genius.

As we noted several times in our insights and guides, Generative AI operates through sophisticated algorithms and large datasets, using patterns and structures derived from vast amounts of information to create new content. These systems excel in generating outputs that appear creative, often producing works that are surprising and novel. For instance, AI-generated art has been exhibited in galleries, and AI-composed music has been performed in concert halls.

One critical difference between AI and human genius, however, lies in the process of creation. Human geniuses are driven by intrinsic motivations, personal experiences, emotions, and unique perspectives that infuse their work with depth and meaning. In contrast, generative AI lacks consciousness, emotions, and subjective experiences. Its creations are the result of programmed algorithms and data processing rather than an inner creative drive.

Generative AI can mimic the styles of various artists, writers, and musicians by learning from existing works. This ability to imitate is impressive but also raises questions about originality. True genius often involves not just creating something new but also challenging existing paradigms and pushing the boundaries of a field. While AI can produce original outputs, these are often derivative of the data they were trained on, lacking the transformative vision that characterizes human genius.

Another perspective is to view generative AI as a tool that extends human creativity. AI can assist artists, writers, and scientists by generating ideas, optimizing processes, and exploring possibilities that might be time-consuming or difficult for humans to achieve alone. In this sense, AI can be seen as augmenting human genius rather than replacing it.

The relationship between genius and generative AI also involves ethical and philosophical considerations. The use of AI in creative fields raises questions about authorship, originality, and the value of human creativity. If AI can produce works indistinguishable from those of human geniuses, what does this mean for our understanding of creativity and intellectual property?

So, while generative AI can exhibit characteristics that mimic aspects of human genius, such as creativity and novelty, in our opinion it fundamentally differs in its lack of subjective experience and intrinsic motivation. AI can enhance and extend human creative capabilities, acting as a powerful tool for innovation. However, the essence of genius remains uniquely human, rooted in the deep, personal, and often ineffable aspects of the human experience.