The Changing Meaning of Knowledge in the Age of Artificial Intelligence: Beyond Body, Intuition, and Data
The Changing Meaning of Knowledge in the Age of Artificial Intelligence: Beyond Body, Intuition, and Data
As artificial intelligence technologies rapidly develop, the definition of knowledge and its relationship with human experience is being reshaped. This transformation profoundly affects not only our individual learning processes but also how institutions function and the cultural fabric of society. This article examines the historical journey of knowledge, its philosophical foundations, and its meaning in the age of artificial intelligence, emphasizing that knowledge cannot be reduced merely to data and highlighting the essential elements of being human.
The Transformation of the Knowledge Regime: From Emotions to Algorithms
Throughout human history, knowledge has always been a holistic experience. Alongside mental processes, our bodily senses, emotions, and the connections we form with our surroundings have been the cornerstones of our understanding of the world. For example, learning to control fire or discovering a healing method were practical experiences that required the active participation of the body and senses rather than theoretical knowledge.
However, a radical shift in this understanding occurred with the modern era. The Industrial Revolution and the process of digitalization gradually made knowledge synonymous with concepts of measurability, standardization, and speed. Knowledge was detached from its context and reduced to data, and this became the most important criterion shaping the modern world's approach to 'correct' knowledge.
Today, artificial intelligence (AI) is taking this transformation to a new dimension. With the rise of AI, knowledge is defined not only by access speed or quantity; its very nature is changing. In this new knowledge regime:
- Sensory experiences are pushed to the background, while the mental is sanctified.
- Data replaces 'reality'; the importance of context and experience decreases.
- Relational and impersonal information is considered 'objective' and 'unbiased'.
As a result, knowledge takes on a form that is quickly accessed but increasingly less felt and with less context. This has the potential to deeply affect not only our individual learning and experiences but also institutions' decision-making processes and the existential dimension of humanity.
Heidegger's Concept of 'Gestell' and Artificial Intelligence
The German philosopher Martin Heidegger viewed technology not merely as a tool but as a force that fundamentally changes the way we perceive the world. His concept of Gestell (Enframing) expresses technology's tendency to reduce the world to a controllable and manageable resource depot. From this perspective, everything from nature to humans and social relations becomes a processable and measurable resource.
Artificial intelligence technologies make this framework even more pronounced. The data continuously collected renders different areas of life measurable. Performance indicators in business, standardized tests in education, or measurable parameters in healthcare facilitate decision-making processes, but they ignore elements that are difficult to measure, such as intuition, context, and experience.
Heidegger's warning becomes meaningful here: if we start to see technology not just as a tool that facilitates our work but as the fundamental framework that defines reality, we will have confined our own existence to a narrow perspective of measurability. Gestell, beyond being a philosophical concept, offers a critical perspective for understanding the debates of the AI age.
Merleau-Ponty: The Wisdom of the Body and the Importance of Emotional Intelligence
Parallel to Heidegger's critique of technology, the French philosopher Maurice Merleau-Ponty emphasizes that knowledge is not only mental but also a bodily process. In his work Phenomenology of Perception, he states that the body is not a passive carrier but rather the fundamental constitutive element of experience. The way we perceive the world is shaped not only by our thoughts but also through our senses and movements.
This perspective is supported by many examples in our daily lives:
- We can understand a person's intent not only from their words but also from their body language.
- When we hear a melody, we may have an emotional response before words.
- A sound or a smell can instantly take us back to a moment in the past.
According to Merleau-Ponty, these moments demonstrate the deep wisdom of the body. Knowledge is not only conceptual but also the product of sensory and relational participation.
However, artificial intelligence operates organically in a 'disembodied' way at this level. It analyzes large data sets, finds patterns, and calculates probabilities. But it cannot feel the emotion in a glance, the meaning in a silence, or the subtlety in a gesture. As the author also references, in the words of psychiatrist Bessel van der Kolk, 'The body keeps the score.' However, AI's memory does not contain such sensory and emotional records. Merleau-Ponty's philosophy raises the question of whether knowledge can be reduced to data, shedding light on one of the most important debates in the age of artificial intelligence.
The Limits of AI and the Meaning of Being Human
OpenAI CEO Sam Altman also recently emphasized in an interview that AI cannot replace the evolutionary history of human biology. Human cognition is not just a logical computation; it is a biological processing process formed by the intertwining of the nervous system, sensory perception, memory, and emotions over millions of years of evolution.
This biological and relational intelligence allows a doctor to sense their patient's anxiety, a teacher to notice their student's confidence, or a leader to perceive their team's mood. These skills cannot be imitated by algorithms because they are the essential elements that make human touch indispensable. According to Altman, AI can be supportive in these areas, but it cannot take the place of humans.
The 'disembodied' nature of AI manifests itself concretely in many areas:
- Healthcare: Algorithms that focus only on numerical data may ignore the patient's own story, emotions, and experiences.
- Education: While personalized learning software tracks the student's pace and success, it cannot measure social interactions in the classroom.
- Business: Recruitment algorithms can identify suitable candidates by scanning CVs; however, they cannot measure creativity or resilience in moments of crisis.
This picture is important not for downplaying the strengths of AI but for clarifying its limits. Because systems that work with data tend to leave out the unmeasurable. The devaluation of the unmeasurable can narrow our understanding of knowledge and overshadow the richness and complexity of humanity.
Reading the Future: Going Beyond Trends
Debates about AI often get stuck between two opposing poles: 'a danger that will destroy humanity' or 'a panacea for every ill.' These superficial discourses are insufficient for understanding the future. In contrast, futures studies offer us a deeper perspective. This discipline focuses on the questions 'what could happen?' and 'what do we want to happen?' rather than 'what will happen?', enhancing our ability to cope with uncertainty and produce creative solutions.
One of the most important methods in this field is Causal Layered Analysis (CLA), developed by scientist Sohail Inayatullah. CLA aims to examine a subject not only through surface-level trends and data but also through the deep structures of language, culture, and the collective unconscious. This analysis is a vital tool for making sense of a complex topic such as artificial intelligence, because it gives us the opportunity to question not only the current state but also our assumptions about the future and the invisible narratives that shape these assumptions.
Reading the future is not just about keeping pace with the speed of technology but also about being able to shape the future while preserving the core values of being human.
