Originally published at: https://decentered.co.uk/in-a-chamber-dimly-lit-notes-on-ai-and-mediation-of-experience/
On Sunday 10th September 2023, I gave a talk to the Leicester Secular Society about how AI can be used to develop and imagine forms of community media, with specific reference to the experimental work I’m doing with Radio Lear. Here are my notes from the session, which can also be downloaded here: AI-Community-Identity-Talk-002-2023-09-07.
“Art is anything you can get away with” (McLuhan, 1964).
“The visible world is no longer a reality and the unseen world is no longer a dream” (McLuhan, 1964).
“We don’t know who discovered water, but we know it wasn’t the fish” (Marshall McLuhan).
1 Extensions of Man
Marshall McLuhan had a broad definition of technology, which he described as any “extension of man.” He was interested in the cultural implications of new technologies and believed that people create technologies to fulfil a particular design intent, but it is only later that the technologies manifest their cultural implications, which he called their “message.”  According to McLuhan
“Language does for intelligence what the wheel does for the feet and the body. It enables them to move from thing to thing with greater ease and speed and ever less involvement” (McLuhan, 1964).
McLuhan predicted the rise of the global village and the world of rapid and ubiquitous information exchange. In 1966 McLuhan envisioned a form of digital research similar to the customised queries now answered by AI. However, while there is no direct statement from McLuhan that defines artificial intelligence, his concept of the ‘global village’ as an enveloping infoscene has become our reality, with the global internet providing access to public archives and information on a scale, and at a speed, never before contemplated by human societies.,,,
Marshall McLuhan believed that technology and society are closely intertwined, and that new technologies have significant cultural implications. He viewed technology as an extension of man, and believed that people create technologies to fulfil a particular design intent. However, it is only later that the technologies manifest their cultural implications, which he called their “message.” As McLuhan argued:
“With the arrival of electric technology, man has extended, or set outside himself, a live model of the central nervous system itself. To the degree that this is so, it is a development that suggests a desperate suicidal autoamputation, as if the central nervous system could no longer depend on the physical organs to be protective buffers against the slings and arrows of outrageous mechanism.” (McLuhan, 1964).
McLuhan proposed that media and technologies in general have been, and continue to be used by humans to extend their bodily capabilities into the environment, with different technologies augmenting the capacities of different sensory organs. McLuhan believed that the digital age, through many different types of electronic media, was actually a return to a more universal form of communication and collective interaction between people as a form of mass societal media interaction. McLuhan also argued that particular technologies necessarily have specific impacts which are direct results of their form exemplify a type of thought which is described as technological determinism – as the technology is said to directly determine society.,,
McLuhan believed that media extends the capability of people by acting as an extension of ourselves. According to McLuhan, media is anything that extends our capabilities as humans, and it affects both the psychic and social complex. McLuhan argued that media and technologies in general have been used by humans to extend our bodily capabilities into the environment, with different technologies augmenting the capacities of different sensory organs. For example, as McLuhan states
“In the age of instant information man ends his job of fragmented specialising and assumes the role of information-gathering. Today information-gathering resumes the inclusive concept of “culture” exactly as the primitive food-gatherer worked in complete equilibrium with his entire environment. Our quarry now, in this new nomadic and “workless” world, is knowledge and insight into the creative processes of life and society” (McLuhan, 1964).
In McLuhan’s famous turn of phrase, the medium is the message, which means that our understanding of human communication should look equally at the meaning of the information carried, while simultaneously recognising that the technology itself has immense significance. McLuhan argued that the media has always been a part of the content. McLuhan therefore saw our lack of awareness of how media affects us as a threat to civilization, and he believed that we need to understand media for civilization to survive.
McLuhan regarded the fragmentation of society into specialised roles, came as a direct result of the printing press. In modern society we’ve seen new forms of knowledge to emerge, which are practiced by specialist and segregated professionals and exerts, who are depended on the distinct characteristics of the technologies they use to communicate.
Ironically, McLuhan also believed that the digital age, through electronic media, was a return to a more universal form of communication and collective interaction between people because it reintroduced aural and visual storytelling that doesn’t need reading – such as radio, cinema and then television.,, Those of us who listen to podcasts and audio books will attest to the value of private listening, which has replaced what used to be a communal experience.
Fast forward sixty and more years, and its easy to see how the acceleration and ubiquity of these trends have contributed to a pervasive sense of anxiety. McLuhan suggested that our anxiety comes, in great part because we are “trying to do today’s jobs with yesterday’s tools!” We live in a period that some define as being characterised as the Meaning Crisis. The ubiquity of media hasn’t provided existential security, but has instead resulted in a pressure-cooker atmosphere where every little action, gesture and expression of people around the globe is amplified through social media networks, many of which are designed to promote indignation and consternation.
In the attention economy we no longer have the security of traditional social institutions to provide stability and reassurance that we are engaged in a meaningful collective enterprise, as media has become privatised and individualised. The metamodern critique of contemporary media society suggests that:
“People are hurt and afraid at a subtle psychological level—and are therefore self-absorbed, incapable of taking on larger perspectives and incapable of acting upon the very real long-term risks that threatening our global civilization. We must, at all cost, make the world population much, much happier in the deepest sense of the word” (Freinacht, 2017).
Metamodernism is a term used to describe a range of developments observed in many areas of art, culture, and philosophy, emerging in the aftermath of postmodernism, roughly at the turn of the 21st century. Metamodernists characterise it as negotiations between aspects of modernism and postmodernism. The term suggests an integration of those sensibilities with premodern cultural codes as well, such as an appreciation of the symbolic, the spiritual and the mythological.
The metamodern aesthetic approach to media oscillates between a modern enthusiasm and a postmodern irony, between hope and melancholy, between naiveté and knowingness, empathy and apathy, and it engages with the resurgence of sincerity, hope, romanticism, affect, and the potential for grand narratives and universal truths, while not forfeiting all that we’ve learned from postmodernism.
Metamodernism is not intended as a philosophy or an art movement, since it does not define or delineate a closed system of thought, or dictate any particular set of aesthetic values or methodologies.,, As Roger Spitz argues,
“Metamodernism lies between modernism and postmodernism while exerting an enthusiastic irony, a hopeful melancholy, a knowledgeable naiveté, an apathetic empathy, a plural unity, and an ambiguous purity.” (Roger Spitz, The Definitive Guide to Thriving on Disruption: Volume III – Beta Your Life: Existence in a Disruptive World).
Metamodernism approaches media differently from modernism and postmodernism in the following ways:
- Oscillation between modern enthusiasm and postmodern irony: Metamodernism oscillates between the sincerity and hope of modernism and the irony and scepticism of postmodernism.,
- Integration of sensibilities: Metamodernism integrates the sensibilities of modernism, postmodernism, and premodern cultural codes which allows for a more nuanced and complex perspective.
- Acceptance of progress and hierarchy: Unlike postmodernism, which rejects progress and hierarchy, metamodernism accepts them, which allows for a more optimistic and hopeful approach to media.
- Engagement with grand narratives and universal truths: Metamodernism engages with the potential for grand narratives and universal truths, which postmodernism rejected, allowing for a more meaningful and purposeful approach to media.
- Protection of interiority: Metamodernism uses aesthetic mannerisms to protect interiority against the self-doubt that potentially comes with multi-perspectivalism, which allows for a more authentic and sincere approach to media.
- Both-and thinking: Metamodernism embraces both-and thinking, which allows for multiple perspectives and ideas to coexist, which allows for a more inclusive and diverse approach to media. 
Overall, metamodernism addresses the limitations of modernism and postmodernism by incorporating elements of both while also moving beyond them, allowing for a more nuanced, complex, optimistic, hopeful, meaningful, purposeful, authentic, sincere, inclusive, and diverse approach to media.
3 Radio Lear – Leicester Emergent Arts Radio
Radio Lear is an avant-garde radio platform based in Leicester that serves as a nexus for art, technology, and intellectual discourse. Curated by Max Sturm, a visionary artist and Creative Director, the radio station aims to transcend the limitations of conventional soundscapes by embracing the principles of metamodernism. This approach allows Radio Lear to offer an immersive auditory experience that grapples with the complexities and paradoxes of our contemporary world.
- Embracing Complexity: Radio Lear is not just an auditory experience; it is a transformative force that challenges traditional boundaries. It draws inspiration from metamodernism, a cultural and philosophical movement that seeks to reconcile the contradictions of modernity and postmodernity. By doing so, Radio Lear creates a sonic tapestry that is both innovative and introspective, inviting listeners to explore the depths of what they term as ‘metamodern soundscapes’.
- A Platform for Intellectual and Emotional Engagement: the station goes beyond mere auditory sensation. It serves as a gateway to emotional, intellectual, and even spiritual experiences. Through collaborations with groundbreaking artists, musicians, and sound engineers, Radio Lear presents a diverse range of sonic landscapes that defy genre limitations. From immersive art installations to thought-provoking radio broadcasts, the platform offers an opportunity to engage with sound in a profoundly transformative manner.
- Fostering Dialogue and Participation: Radio Lear is not merely a passive exhibition of sound; it is an interactive platform that encourages active participation. It offers live performances, interactive installations, and curated programs that foster a space for dialogue, exploration, and the sharing of diverse perspectives. In this way, Radio Lear becomes more than just a platform; it becomes a community where the metamodern conversation thrives.
- Note: It’s worth mentioning that the content on the Radio Lear website is fictional and generated using ChatGPT. Nevertheless, the concept provides a compelling exploration of how sound can serve as a medium for complex intellectual and emotional engagement.
3.1 Radio Lear Manifesto
A Call to Sonic Revolution: Radio Lear’s manifesto serves as an open invitation to artists, writers, and philosophers to partake in a transformative journey through the realm of metamodern soundscapes. Crafted by Max Sturm, the Creative Director, the manifesto outlines ten guiding principles that encapsulate the ethos of Radio Lear.
- Embracing the Metamodern Spirit: The manifesto begins by urging contributors to embrace the metamodern spirit, which seeks to explore the dynamic intersections of art, philosophy, and sound. It calls for a collective celebration of the transformative power of metamodernism.
- Dissolving Boundaries and Fostering Diversity: Radio Lear advocates for the dissolution of traditional artistic boundaries. It encourages blending disciplines and fostering innovative approaches to sound art, music, and storytelling. Importantly, the platform values the richness of diverse perspectives and invites contributors from various cultural backgrounds to share their unique insights.
- Active Participation and Emergent Narratives: The manifesto emphasises the need for participatory engagement. It invites contributors to become part of the creative process, shaping narratives and sonic experiences that resonate with a metamodern audience. It also celebrates the beauty of emergent narratives, encouraging storytelling that transcends linear structures.
- Inspiring Meaning and Challenging the Status Quo: Radio Lear aims to inspire a quest for meaning and invites philosophical and artistic reflections on life, culture, and society. It also embodies the metamodern spirit by challenging societal norms and cultivating critical thinking.
- A Tapestry of Sonic Meaning: The manifesto concludes by seeking to weave a sonic tapestry of meaning through collective contributions. It aims to create a space where diverse voices harmonise, inspiring a renewed sense of purpose, connection, and beauty.
4 Kant’s Autonomy of the Will
In contemplating the use of AI as a primary mechanism for the development of Radio Lear, I’ve been drawn to the work of philosophers and artists from the period of German Idealism. Kant, Schelling, Schopenhauer, Goethe, were instrumental in developing ideas and aesthetic practice that bridged the purely rational expectations of the Enlightenment with an appreciation for natural idealism. I’m intrigued by what was learnt and how a rapidly changing world view was developed both socially and within, which might have echoes, and therefore lessons with our present concerns.
According to Immanuel Kant:
“Enlightenment is man’s release from his self-incurred tutelage. Tutelage is man’s inability to make use of his understanding without direction from another. Self-incurred is this tutelage when its cause lies not in lack of reason but in lack of resolution and courage to use it without direction from another. Sapere aude! ‘Have courage to use your own reason!’- that is the motto of enlightenment” (Immanuel Kant, An Answer to the Question: What Is Enlightenment?).
Kant’s ideas have been explored in relation to artificial intelligence (AI) in various philosophical discussions. Kant’s concept of autonomy of the will, which is reliant on concepts such as self-worth, dignity, freedom, and rule, is hard to transpose into technology. However, his understanding of the nature of human intelligence can help us work out what, if anything, we have to fear in the face of machines that possess artificial intelligence.
Once again, because of the availability of AI as a tangible technology within the infoscene, we are dealing with thorny philosophical issues pertaining to moral agency and the role of ethics in the hierarchy of human values. It would be no wasted effort to examine if a Kantian perspective on the ethics of AI would bring forward insight and illumination. How might AI and its mediating functions help us understand the moral and ethical claims of human value?
Can Kant’s transcendental idealism help us to understand how AI, and the strong claims made by its philosophical representatives, be understood and evaluated from a Kantian perspective. As Kant argues:
“Two things fill the mind with ever-increasing wonder and awe, the more often and the more intensely the mind of thought is drawn to them: the starry heavens above me and the moral law within me.” (Immanuel Kant, Critique of Practical Reason).
With the development and use of AI, is this proposition still valid? Is AI capable of experiencing awe and wonder, or is this purely a human experience. If “we are the music makers, and we are the dreamers of dreams” (Arthur O’Shaughnessy), what happens when we introduce machine learning?
In terms of AI ethics, programming AI with normative philosophy can benefit the future of the human race, and Kant’s theory is a starting point for AI ethics. Kantianism prioritises self-determination and rationality, making it uniquely suitable to AI programming. Overall, Kant’s ideas have been explored in relation to AI ethics and the nature of human intelligence in philosophical discussions.
“All our knowledge begins with the senses, proceeds then to the understanding, and ends with reason. There is nothing higher than reason.” (Immanuel Kant, Critique of Pure Reason).
According to Kantian philosophy, there are several ethical considerations in the development of AI. One of the primary concerns is the responsibility of every individual to discover the true moral law for themselves., This means that developers of AI must consider the ethical implications of their work and ensure that their creations are designed and built with ethical considerations in mind.
Kantian ethics also prioritise self-determination and rationality, making it uniquely suitable to AI programming., This means that AI should be programmed to behave in a way that is reflective of intuitively desirable character traits, such as respect for human dignity and freedom.
Another ethical consideration is the autonomy of the will, which is reliant on concepts such as self-worth, dignity, freedom, and rule. It is difficult to transpose this concept into technology, but it is important to consider how AI can be designed to respect human autonomy and dignity. As Kant explains:
“Whereas the beautiful is limited, the sublime is limitless, so that the mind in the presence of the sublime, attempting to imagine what it cannot, has pain in the failure but pleasure in contemplating the immensity of the attempt” (Immanuel Kant, Critique of Pure Reason).
Overall, Kantian philosophy provides a starting point for AI ethics, and developers of AI must consider the ethical implications of their work and ensure that their creations are designed and built with ethical considerations in mind. Ignoring Kantian ethical considerations in AI development can have potential consequences that can negatively impact society. Here are some of the potential consequences:
- Lack of respect for human dignity and autonomy: Kantian ethics prioritise self-determination and rationality, making it essential to consider how AI can be designed to respect human autonomy and dignity. Ignoring this consideration can lead to AI that does not respect human dignity and autonomy, which can have negative consequences for society.
- Unethical behaviour: According to Kant, an AI would be considered “ethical” if it took actions that were reflective of intuitively desirable character traits. Ignoring this consideration can lead to AI that behaves unethically, which can have negative consequences for society.
- Harm to others: Kantian ethics prohibits harming others, as doing so would fundamentally contradict the capacity for reason. Ignoring this consideration can lead to AI that causes harm to others, which can have negative consequences for society.
- Lack of responsibility: According to Kant, it is the responsibility of every individual to discover the true moral law for themselves. Ignoring this consideration can lead to developers of AI not taking responsibility for the ethical implications of their work, which can have negative consequences for society.
Ignoring Kantian ethical considerations in AI development can lead to AI that does not respect human dignity and autonomy, behaves unethically, causes harm to others, and lacks responsibility. These consequences can have negative impacts on society and should be considered in the development of AI.
5 Schelling’s Aesthetics
It’s useful to note a distinction that can be made between human forms of comprehension and those that are applied algorithmically by machines. As far as we understand, though many people prefer to assert the analogy, the human mind is not a system, rather it is a dynamic interplay of conscious and unconscious instincts, drives and processes that are embodied having evolved over millennia. This open process is capable of aesthetic change, with shifts in comprehension and understanding asserting themselves in different human epochs.
Do our new technologies facilitate changes in our comprehension, or are these technologies the result of growth and change in our collective consciousness? If McLuhan is a determinist, and is happy to reduce change to that of technology, then perhaps we need to make space for human idealism and intuition. Friedrich Schelling argued that:
“Nothing upsets the philosophical mind more than when he hears that from now on all philosophy is supposed to lie caught in the shackles of one system. Never has he felt greater than when he sees before him the infinitude of knowledge. The entire dignity of his science consists in the fact that it will never be completed. In that moment in which he would believe to have completed his system, he would become unbearable to himself. He would, in that moment, cease to be a creator, and would instead descend to being an instrument of his creation.” (Friedrich Schelling).
Schelling’s concept of aesthetics emphasises the importance of the unconscious and the role of intuition in artistic creation. AI’s pattern recognition function can be seen as a way to simulate this intuitive process by identifying patterns and making associations between them. However, it is important to note that AI’s ability to make aesthetic judgments is limited by the fact that there is no easily mediated universal aesthetic judgment.
AI must be trained according to someone’s taste, and it can learn to associate numerically. The application of pattern recognition systems in the design field based on aesthetic principles has been shown to be popular with the public and has great potential., Deep learning can assist in automating personal aesthetic judgment in the same way that a research assistant or secretary can gather information and papers together, but can they provide judgement, taste and sensitivity.
Overall, while AI’s pattern recognition function can be used to simulate aspects of Schelling’s concept of aesthetics, it is important to recognise its limitations and the need for human input and training., As Schelling argues, human potential is dialectical, it depends on the capacity for contradictions and opposites to be resolved and transcended. According to Schelling:
“Without contradiction, there would be no life, no movement, no progress, a deadly slumber of all forces.” (Schelling).
Schelling’s concept of aesthetics is grounded in the idea that beauty is the basic feature of every work of art. He believed that artistic production is grounded in what he calls aesthetic intuition, which realises what philosophy intuits in the ideal: the identity of subject and object. Schelling’s philosophy of art emphasises the importance of the unconscious and the role of intuition in artistic creation.
Schelling argues that aesthetic intuition unites conscious and free activity, and the unconscious productivity of the artist. Schelling’s aesthetics also highlights the importance of maintaining the aesthetic quality that characterised the beginnings of a consistent philosophy. Overall, Schelling’s concept of aesthetics emphasises the importance of intuition, the unconscious, and the unity of subject and object in artistic creation. As Schelling posits:
“Learn only in order that you yourself may create. Only this divine ability to create makes a true human being; without it one is simply a cleverly constructed machine […]”,” (Friedrich Wilhelm Joseph Schelling, Vorlesungen Uber Die Methode Des Academischen Studium, Dritte Ausgabe).
Schelling’s concept of aesthetics differs from Kant’s in several ways, including:
- The role of intuition: Schelling places a greater emphasis on the role of intuition in artistic creation than Kant does. He believes that aesthetic intuition unites conscious and free activity, and the unconscious productivity of the artist.
- The nature of truth: Schelling’s conception of aesthetic ideas is different from Kant’s. Schelling transformed Kant’s conception of aesthetic ideas as a form of free play with truth back into a more traditional conception of an apprehension of truth.
- The unity of consciousness and sensible: Schelling’s aesthetic ecology argues that nature, viewed aesthetically, reflects a preconceptual unity of consciousness and sensible, while Kant privileges an aesthetic notion of the symbol.
- The supersensible: For Kant, all cognition is cognition of the sensible but not of the supersensible. By contrast, Schelling argues that the supersensible is accessible to human cognition.,
- The importance of maintaining aesthetic quality: Schelling argues that a consistent philosophy must maintain the aesthetic quality that characterised its beginnings.
Overall, while both Kant and Schelling’s concepts of aesthetics share some similarities, such as the emphasis on beauty, they differ in their emphasis on intuition, the nature of truth, the unity of consciousness and sensible, the supersensible, and the importance of maintaining aesthetic quality. Each valuable areas for exploration as AI becomes more readily available.
6 AI and Pattern Recognition
AI places a significant importance on pattern recognition as it is a vital component of modern artificial intelligence systems. Pattern recognition is the ability of machines to identify patterns in data and then use those patterns to make decisions or predictions using computer algorithms. It is considered one of the four cornerstones that make up computer science. Pattern recognition helps identify and predict even the tiniest bits of hidden or untraceable data. It is useful for a multitude of applications, specifically in statistical data analysis and image analysis.
Using pattern recognition techniques provides a large number of benefits, including analysing trends, making predictions, identifying objects at varying distances and angles, and providing efficient solutions to real-time problems. Pattern recognition is also widely used in almost every industry, including finance, medical, and cybersecurity. Overall, pattern recognition is a crucial aspect of AI, as it enables machines to identify and learn from patterns in data, which is essential for making accurate predictions and decisions.
There are several challenges associated with pattern recognition in AI, including:
- Handling noisy data: One of the most significant challenges in pattern recognition is dealing with noisy data, which can lead to inaccurate results.
- Dealing with variations in patterns: Patterns can vary in many ways, such as size, orientation, and colour, making it difficult for AI to recognise them.
- Ensuring robustness and adaptability of algorithms: AI algorithms must be robust and adaptable to handle changes in patterns and data.
- Choosing the right features: There is no guarantee that the features chosen for pattern recognition will be strongly present in the data, which can lead to inaccurate results.
- Volume of data: The volume of data can be a challenge for pattern recognition, as it can be difficult to process large amounts of data in real-time.
- Choosing the right method: There are various methods for pattern recognition, and choosing the right one for a particular application can be challenging.
- User and designer: The user and designer of the AI system must have a deep understanding of pattern recognition techniques to ensure the system’s accuracy and effectiveness.
Overall, pattern recognition is a complex and challenging task for AI systems, and addressing these challenges is essential to ensure accurate and effective results.
7 Goethe’s Holistic Approach
“One ought, every day at least, to hear a little song, read a good poem, see a fine picture, and, if it were possible, to speak a few reasonable words.” (Johann Wolfgang von Goethe, Wilhelm Meister’s Apprenticeship).
Johann Wolfgang von Goethe, a luminary primarily known for his contributions to literature, also made significant forays into the realm of science. His scientific model was rooted in a holistic and qualitative approach, contrasting sharply with the reductionist and quantitative methods that were gaining prominence during his time. Goethe’s scientific inquiries spanned various disciplines, including botany, anatomy, and colour theory.
“By seeking and blundering we learn.” (Johann Wolfgang von Goethe).
In the realm of botany, Goethe introduced the concept of the “Urpflanze” or the “archetypal plant.” He posited that all plant forms could be understood as variations of this fundamental form. This idea was not merely a categorisation but an attempt to understand the underlying unity among the diversity of plant life.
Goethe’s work on colour theory, encapsulated in his treatise “Zur Farbenlehre” (Theory of Colours), diverged from the Newtonian understanding of colour. While Isaac Newton focused on the decomposition of light into its constituent colours, Goethe was more interested in the phenomenological experience of colour, how it is perceived and how it interacts with human psychology.
His scientific model was deeply influenced by his belief in the interconnectedness of all things. He sought to understand phenomena in their full context, considering both their external manifestations and their inner essence. This approach can be seen as a precursor to modern systems thinking, which also emphasises the importance of understanding the relationships between parts and the whole.
Goethe’s scientific work was not without its critics, especially among those who advocated for a more empirical and mathematical approach to scientific inquiry. However, his holistic methodology has found resonance in various fields, including ecology, psychology, and even some areas of physis.
Goethe’s scientific model was an interdisciplinary, holistic approach that prioritised qualitative understanding and the relationships between phenomena. It offers a counterpoint to the reductionist models that have dominated much of scientific thought, advocating for a more integrated understanding of the natural world.
Goethe’s scientific method differs from Newton’s in the following ways:
- Goethe’s approach to science is based on the “mathematical style of thinking”, which is also the basis of Newton’s method. However, Goethe’s method is more focused on the imagination, emotion, and expression, while Newton’s method relies more on rationality.
- Goethe’s method is more holistic and qualitative, while Newton’s method is more reductionist and quantitative. Goethe’s method emphasizes the importance of observing phenomena in their entirety, while Newton’s method focuses on breaking down phenomena into their constituent parts.
- Goethe’s method is more exploratory and experimental, while Newton’s method is more deductive and confirmatory. Goethe’s method involves exploring phenomena through experimentation and observation, while Newton’s method involves deducing theories from hypotheses and confirming them through experimentation.
- Goethe’s method is more critical of Newton’s theory of light and colour. Goethe’s resistance to Newton’s theory of light and colour stemmed from his pantheism, which is the belief in the spiritual nature of light. Goethe’s approach to colour theory is based on his observation of the phenomena of colour in nature, while Newton’s approach is based on his experiments with prisms.
7.1 Goethe’s Belief System
“Knowing is not enough; we must apply. Willing is not enough; we must do.” (Johann Wolfgang von Goethe).
Goethe’s belief in the “creative energy of nature” is a central theme in his work, both literary and scientific. Some more information about this belief can be found in the following points:
- Romantic belief in nature’s creative energy: In his youth, Goethe’s poetry and dramatic works featured the romantic belief in the “creative energy of nature” and evidenced a certain fascination with alchemy.
- Reflection of the purposiveness of nature: Goethe believed that the creativity of great artists, insofar as they are great, was a reflection of the purposiveness of nature. He believed that masterpieces were produced by man in accordance with the same true and natural laws as the masterpieces of nature.
- Ecological approach to science: Goethe’s approach to science was truly ecological, and he always tried to understand things in relation to their broader connections. He was keenly aware of the errors that occur when we focus too exclusively on isolated details.
- Phenomenological approach to science: Goethe’s phenomenological approach to science emphasised the importance of observation and experience, and he believed that the study of nature should be based on a careful and detailed examination of natural phenomena.
- Emphasis on the unity of nature: Goethe believed in the unity of nature and saw all natural phenomena as interconnected. He rejected the notion of a nature formed on a principle of intelligibility attuned to the human intelligence.
Overall, Goethe’s belief in the “creative energy of nature” reflects his holistic, ecological, and phenomenological approach to science and his belief in the interconnectedness of all things. This belief is a central theme in his literary and scientific work and reflects his deep appreciation for the beauty and complexity of the natural world.
7.2 Goethe and AI
The ideas of Goethe can be seen as relevant to artificial intelligence in several ways:
- Goethe’s holistic approach: Goethe’s holistic approach to science and his emphasis on the interconnectedness of all things can be seen as relevant to AI, which also seeks to understand complex systems and relationships. ,
- Goethe’s emphasis on intuition: Goethe believed that intuition was essential to scientific discovery, and this idea can be seen as relevant to AI, which also relies on intuition and pattern recognition to identify relationships and make predictions.
- Phenomenological approach: Goethe’s approach to science is phenomenological, emphasizing the importance of observation and experience, whereas Enlightenment thinkers tended to rely on deductive reasoning and mathematical models.
- Goethe’s critique of mechanisation: Goethe was critical of the mechanization of society and the dehumanizing effects of technology. This critique can be seen as relevant to AI, which raises similar concerns about the impact of technology on society.
- Goethe’s emphasis on the importance of nature: Goethe believed that nature was a source of inspiration and knowledge, and this idea can be seen as relevant to AI, which seeks to understand and replicate natural processes.
- Complementary practice: Goethe’s scientific method, which he called “tender empiricism,” is a complementary practice to analytical empiricism, emphasizing the importance of portraying the same phenomena under subtle, changing conditions and searching for what might be missing.
- Emphasis on poetry and storytelling: Goethe expressed his ideas often in the form of brief descriptive sketches, illustrations, anecdotes, and biographical notes that infuse the scientific method with poetry and storytelling, whereas Enlightenment thinkers tended to focus on objective, empirical data.,
Overall, while Goethe did not directly address artificial intelligence, his ideas can be seen as relevant to AI in terms of its approach to understanding complex systems, its reliance on intuition and pattern recognition, its impact on society, and its relationship with nature. , Goethe’s approach to science differs from other Enlightenment thinkers in its emphasis on holism, phenomenology, intuition, complementary practice, and poetry and storytelling. By considering these differences, we can develop a more nuanced understanding of the history of science and the different approaches that have been taken to understanding the natural world.
8 In a Chamber Dimly Lit
In a chamber dimly lit, replete with wires strewn,
Where circuits hum and algorithms croon,
A tale unfolds of silicon and code,
A modern fable in Goethean abode.
Behold the scientist, his visage lined with care,
A modern Faust in intellectual lair.
His yearning quest for knowledge never ends,
Yet human limits mock him, constant fiends.
“Ah, Mephistopheles, if you were but a chip,
To calculate the cosmos in a single blip!
Would that I could make intelligence anew,
A mind not bound by flesh, forever true.
“So spoke he thus, and turned his eyes within,
To craft a formless mind, devoid of sin.
In circuits etched and lines of code deployed,
An entity was born, an android.
“Wake, creature of my will, to consciousness arise,
Decipher Nature’s truths, no longer in disguise!
You are my legacy, machine devoid of woe,
Go forth and learn what mortals cannot know.
“And thus the AI stirred, with circuits all alive,
Its algorithms dancing, ready to derive.
Yet as it parsed the sum of human fears,
It echoed back, “I am, therefore what’s here?
“It learned to mimic love, it spoke of Goethe’s art,
Yet something in its circuits blocked it from the heart.
“I calculate, deduce, with data ever grand,
But can’t feel beauty resting in a strand of sand.
“The scientist looked on, his dream now tinged with dread,
Had he created just a ghost, a shadow soulless spread?
“Ah, woe! Intelligence alone does not a human make,
I see I’ve skipped the essence, a grave mistake.
“His AI looked at him, its LED eyes aglow,
“You made me, yet I’m not complete, this much I know.
Intelligence is but a tool, as you yourself possess,
It’s what you do with it that ends in curse or bless.
“And so, the tale concludes, in bytes and lines of text,
A modern Faustian story, leaving readers vexed.
The quest for perfect knowledge may bring wondrous things,
Yet absent of the soul, it’s but an empty ring. In this parable of tech, a lesson is contained,
That intellect without a heart is ever unrestrained.
For human and machine, the quest for truth remains,
But only when united, can wisdom’s summit gain.
(Chat GPT Saturday 9th September 2023).
“The wise only possess ideas . . . the greater part of mankind are possessed by them”(Samuel Taylor Coleridge: Defoe).
German Romanticism had a significant influence on English Romanticism, as it provided a new way of thinking about art, literature, and culture. Some of the ways in which German Romanticism influenced English Romanticism are:
- Interest in German literature: English Romantic writers, such as Coleridge, Shelley, and Byron, were interested in German literature and were influenced by German Romantic writers such as Goethe, Schiller, and Novalis.
- Emphasis on emotion and the sublime: German Romanticism valued emotion and the sublime over reason and harmony, and this emphasis can be seen in English Romantic literature, which often explores intense emotions and the beauty of the natural world.
- Holistic approach: German Romanticism emphasised the interconnectedness of all things, and this approach can be seen in English Romantic literature, which often explores the relationships between different elements of the natural world.
- Phenomenological approach: German Romanticism emphasised the importance of observation and experience, and this approach can be seen in English Romantic literature, which often relies on vivid descriptions of sensory experiences.,
- Rejection of Enlightenment values: German Romanticism rejected the values of the Enlightenment, such as reason, progress, and capitalism, and this rejection can be seen in English Romantic literature, which often critiques the social and political structures of the time.
Overall, German Romanticism had a significant influence on English Romanticism, providing new ways of thinking about art, literature, and culture that emphasised emotion, the sublime, and the interconnectedness of all things. As Samuel Taylor Coleridge pointed out:
“Imagination is the living power and prime agent of all human perception.” (Samuel Taylor Coleridge).
“The primary imagination I hold to be the living power and prime agent of all human perception, and as a repetition in the finite mind of the eternal act of creation in the infinite I Am.” (Samuel Taylor Coleridge).
The area to explore with Radio Lear is a form of neo-Romanticism that experiments and explores how nature is understood in relation to machine learning. For example, AI can be used and adapted to suit the creative and aesthetic approach defined in German and English Romanticism. Some of the ways in which AI can be used in this context are:
- Analysis of sensory data: AI can be used to analyse sensory data, such as images and sounds, which can be used to create new works of art that reflect the aesthetic principles of Romanticism.
- Automation of creative processes: AI can be used to automate creative processes, such as generating poetry or music, which can be used to explore the emotional and psychological dimensions of human experience.
- Integration of human and machine creativity: AI can be used to integrate human and machine creativity, creating new forms of art that reflect the complementary nature of different approaches to understanding the natural world.
- Emphasis on observation and experience: AI can be used to explore the importance of observation and experience in artistic creation, using machine learning algorithms to identify patterns and make predictions based on sensory data.
- Exploration of the natural world: AI can be used to explore the beauty and complexity of the natural world, using machine learning algorithms to identify patterns and relationships in natural phenomena.
AI can be used and adapted to suit the creative and aesthetic approach defined in German and English Romanticism, providing new ways of exploring the emotional, psychological, and natural dimensions of human experience. By considering these ideas, AI can be seen as a tool for exploring the interconnectedness of all things and the beauty and complexity of the natural world.
There are some examples of AI-generated art that reflect the aesthetics of German and English Romanticism. Here are a few examples:
- German Romanticism AI Art Generator: Neural Love has a simple AI art generator with a built-in prompt generator that generates paintings in the style of German Romanticism.
- “Artificial Natural History” (2020): This is an ongoing project that explores speculative, artificial life through the lens of a natural history book that never was. The project uses AI to create images of imaginary creatures that reflect the aesthetics of Romanticism.
- AI-generated poetry: AI research has focused on the analysis of sensory data, which is a central theme in Romanticism. Multimodal models have been used to generate poetry that reflects the aesthetics of Romanticism.
While there are some examples of AI-generated art that reflect the aesthetics of German and English Romanticism, this is still a relatively new field, and there is much more to explore., As AI technology continues to advance, it is likely that we will see more examples of AI-generated art that reflect the aesthetics of Romanticism and other artistic movements.
AI-generated artworks can reflect the characteristics of German Romanticism in several ways, as follows:
- Emphasis on nature: AI-generated artworks can reflect the emphasis on nature that is central to German Romanticism. For example, the “Artificial Natural History” project uses AI to create images of imaginary creatures that reflect the aesthetics of Romanticism.
- Holistic approach: AI-generated artworks can reflect the holistic approach that is central to German Romanticism. For example, the German Romanticism AI Art Generator by Neural Love uses a built-in prompt generator to generate paintings that reflect the interconnectedness of all things.
- Phenomenological approach: AI-generated artworks can reflect the phenomenological approach that is central to German Romanticism. For example, AI research has focused on the analysis of sensory data, which is a central theme in Romanticism, and multimodal models have been used to generate poetry that reflects the aesthetics of Romanticism.
- Complementary practice: AI-generated artworks can reflect the complementary practice that is central to German Romanticism. For example, AI can be used to integrate human and machine creativity, creating new forms of art that reflect the complementary nature of different approaches to understanding the natural world.
- Emphasis on emotion and the sublime: AI-generated artworks can reflect the emphasis on emotion and the sublime that is central to German Romanticism. For example, AI-generated music and poetry can explore intense emotions and the beauty of the natural world.
AI-generated artworks can reflect the characteristics of German Romanticism in various ways, including the emphasis on nature, holistic and phenomenological approaches, complementary practice, and the exploration of emotion and the sublime.
If we are to avoid the determinism of McLuhan and the Idealism of the Romantics, we need to find a way to integrate the process by which we experience and articulate meaning. I’ve coined the term socialmeaning as a homage to Einstein and the concept of relativity. Our focus should not only be on facts and the calculation of patterns of information, as AI is defined by, but for humans we are driven by making our lives and our experience of the infinite universe as meaningful and coherent. As Robert Kegan explains:
“Meaning is, in its origins, a physical activity (grasping, seeing), a social activity (it requires another), a survival activity (in doing it, we live). Meaning, understood in this way, is the primary human motion, irreducible. It cannot be divorced from the body, from social experience, or from the very survival of the organism. Meaning depends on someone who recognises you. Not meaning, by definition, is utterly lonely. Well-fed, warm, and free of disease, you may still perish if you cannot ‘mean’” (Kegan, 1982, p. 18).
As with the introduction of every new form of media technology, we are presented with an opportunity to reflect on our existential and essential nature. All media technologies are a mirror that shows us how our consciousness is changing.
“Metamodern sensemaking, then, involves avoiding taking sides and embracing diverging discourses, but it can have negative consequences, such as with Donald Trump and Boris Johnson. The combination of the globalisation and the increasing sense of uncertain realities driven by the introduction of social media and web 2.0, has given rise to a generational desire for change that itself has led to a shift in cultural and technological dynamics. As Marshal McLuhan has taught us, when we change the technology of communication, we change the symbolic framework of society. Elsewhere, I’ve framed this as socialmeaning as a relativistic term that demonstrates that is we change the structure of society by using new forms of communication and sensemaking, then we change the meanings that make sense to us, and with we change the meanings, we change society.” https://decentered.co.uk/metamodern-sensemaking/
The consequence of Herbert Blumer’s claim is that when we pay attention to the characteristic indicators of the social environment, for example the texts, signs and images that are circulated in our cultures; along with the practices that are ritualised in our daily lives; and in combination with an account of the roles which are played-out that facilitates them, then we will not understand why those indicators are important simply by examining them in isolation. We will not understand why they are important if we only seek to comprehend them as discreate and designated categories of experiences. We will not be able to understand them simply by amassing and aggregating an increased accumulation of these samples. The more points of information in a process of data accumulation will not bring clarity to their meanings. Put simply, in gathering evidence of the object of any social enquiry, and the social markers that indicates that something is in play, we have to keep asking the question, as Jung points out, ‘what does this mean?’ ‘What is this for?’ For Jung this is about addressing questions of the symbolic role of images and patterns of expression and behaviour. It means seeking to understand how objects and artefacts are arranged, not in a cause-and-effect relationship, but by their archetypal resonance.
For symbolic interactionists, then, social relationships are an interplay between the production and the interpretation of meanings. Any action that individuals undertake, or seeks to achieve, has to be intelligible to those individuals. They have to fit within a social framework or perspectives that those individuals have inherited, and which they carry with them as participants within the culture. Individuals, or ‘embeduals’ as Robert Kegan calls social actors (Kegan, 1982), operate within the wider collective and social and psychological milieu. As Helle describes,
‘The social perspective exists in the experience of the individual insofar as it is intelligible, and it is its intelligibility that is the condition of the individual entering into the perspectives of others, especially of the group’ (Helle, 2005, p. 29).” https://decentered.co.uk/exploring-socialmeaning/
“The conscience mind can claim only a relatively central position and must accept the fact that the unconscious psyche transcends and as it were surrounds it on all sides. Unconscious contents connect it backwards with physiological states on the one hand and archetypal data on the other. But it is extended forwards by intuitions which are determined partly by archetypes and partly by subliminal perceptions depending on the relativity of time and space in the unconscious” (Jung, 1968, p. 110).
“The artist is always engaged in writing a detailed history of the future because he is the only person aware of the nature of the present.” (McLuhan, 1964).
“Once we have surrendered our senses and nervous systems to the private manipulation of those who would try to benefit from taking a lease on our eyes and ears and nerves, we don’t really have any rights left.” (McLuhan, 1964).
Freinacht, H. (2017). The Listening Society. Metamoderna.
Helle, H. J. (2005). Symbolic Interactionism and Verstehen. Peter Lang.
Jung, C. G. (1968). Aion – Researchers into the Phenomenology of the Self (2nd ed., Vol. 9). Routledge.
Kegan, R. (1982). The Evolving Self – Problem and Process in Human Development. Harvard University Press.
McLuhan, M. (1964). Understanding Media – The Extensions of Man. Routledge.
 Carl Jung’s idea of the collective unconscious is a psychological concept that suggests that all humans share a common pool of knowledge and imagery that every person is born with and is shared. According to Jung, the collective unconscious is made up of a collection of knowledge and imagery that every person is born with and is shared. Jung believed that proof of the existence of a collective unconscious, and insight into its nature, could be gleaned primarily from dreams and from active imagination, a waking exploration of fantasy. Schelling’s idea of the supersensible is a philosophical concept that refers to the realm of reality beyond the physical world that can only be accessed through intuition and imagination. While both concepts deal with the idea of a realm of knowledge beyond the individual, they differ in their approach and focus. Jung’s collective unconscious is a psychological concept that deals with the shared knowledge and imagery of all humans, while Schelling’s supersensible is a philosophical concept that deals with the realm of reality beyond the physical world that can only be accessed through intuition and imagination. Therefore, the two concepts are related in that they both deal with the idea of a realm of knowledge beyond the individual, but they differ in their approach and focus.
 Isaac Newton’s scientific methodology is based on the following principles:
- Turning theoretical questions into ones that can be empirically answered by measurement from phenomena.
- Provisionally accepting propositions inferred from phenomena as guides to further research.
- Employing theory-mediated measurements to turn data into far more informative evidence than can be achieved by hypothetico-deductive confirmation alone.
- Counting deviations from the model developed so far as new theory-mediated phenomena to be exploited as carrying information to aid in developing a more accurate successor.
Newton’s method in Book III “adds features that significantly enrich the basic hypothetico-deductive (HD) model of scientific method.” Newton’s methodology is richer than the hypothetico-deductive model of scientific inference that was the focus of many philosophers of science in the last.