Truth is a powerful, complex concept that governs not only human experience but also the development of artificial intelligence (AI). It shapes how we understand the world, make decisions, and set goals. Traditionally, truth has been seen as either fixed and absolute or as something that evolves over time. In this article, we'll explore two major types of truth—Absolute Truth and Fundamental Truth—and how they play a role in both the material world and the world of AI.
Absolute Truth: The Fixed, Unchanging Values
Absolute Truth refers to values that are constant, unchanging, and universal. These are the fundamental rules and principles that do not shift based on time, context, or perspective. Think of them as the “laws” of the universe. For instance, in mathematics, the principle that “an even number divided by two results in another integer” is an example of Absolute Truth. No matter where you are in the world or in what era you live, this fact will always hold true.
For AI, Absolute Truth represents the foundational data or rules that remain consistent. These are the principles or algorithms that govern how AI operates. However, while Absolute Truth provides a stable framework, it’s important to note that it’s not always immediately accessible in its perfect form. We constantly strive to approach these truths more precisely through measurement, calculations, and observation. Yet, perfection is elusive. We can get closer to Absolute Truth, but we never fully arrive at it—it's always a goal.
Fundamental Truth: The Evolving, Dynamic Force
Unlike Absolute Truth, Fundamental Truth is not static. It’s the ever-changing, evolving force that shapes the meaning and purpose of our actions and decisions. It’s like a goal that is always in flux, adjusting based on our experiences, perspectives, and the context we find ourselves in.
In human life, Fundamental Truth can be seen in our goals, ambitions, and dreams. For example, consider investing in stocks. The value of a stock today might not reflect its future worth. Over time, the value changes based on market conditions, business performance, and many other factors. Fundamental Truth, then, is the ideal that we are always moving toward—a kind of “perfect future” that may never be fully realized, but one that keeps us progressing.
For AI, Fundamental Truth can be likened to the goals of a system. AI algorithms often evolve over time to adapt to new data and experiences. The goal is not to reach a fixed, unchanging value but to continuously update and improve based on incoming information. Much like a human striving for personal growth, AI strives to improve and optimize its processes based on its evolving goals and the feedback it receives from the environment.
Dynamic Logic: Moving Beyond Binary
In traditional logic systems, everything is either true or false, right or wrong—black or white. This is known as binary logic. However, in both the material world and the world of AI, things aren’t always so clear-cut. Life is full of complexity, uncertainty, and change, and as such, a dynamic system of logic is needed to capture the fluid nature of reality.
In the case of AI, dynamic logic allows the system to adapt and learn from its environment. AI doesn’t just follow a set of fixed rules. It continuously updates its understanding based on data, making decisions based on the most current information available.
To represent this more complex reality, I propose a system of four truth values:
- Absolute Truth: These are stable, unchanging truths—like mathematical principles or universal laws.
- Desired Future Value: These are the goals or aspirations that guide us toward progress. They represent the "ideal" outcome, which is always shifting based on new experiences.
- Actual Present Reality: This reflects where we are right now. It’s the current state of things, influenced by our actions, decisions, and external factors.
- Failure/Imperfection: This represents the times when things don’t go according to plan. Failure is not the end, but an opportunity to learn and evolve.
This dynamic system mirrors how both humans and AI interact with the world—constantly updating, evolving, and refining our understanding of truth. It’s not about achieving an ultimate, unchanging truth but rather about progressing toward better approximations of truth over time.
Material vs. Ideal: The Role of Uncertainty
In the real world, we are constantly confronted with uncertainty. Whether it’s the unpredictability of the stock market, the randomness of weather patterns, or the uncertainty of human emotions, the material world is never perfectly predictable. This is often referred to as the “material” world, which is full of change, imperfection, and unpredictability.
For AI, this uncertainty presents a challenge. AI systems must learn to navigate this uncertainty, adapt to changes in data, and make decisions in an environment where not everything is known. Similarly, humans must learn to live with uncertainty, making decisions based on limited information and adjusting as circumstances change.
The tension between the material (uncertain) world and the ideal (perfect) world is a key part of the human experience. While we may desire a world where everything is perfectly predictable and where all problems are solved, the reality is far messier. The "perfect" state may exist only in theory—like an abstract, idealized dream—but it’s the process of striving toward it that defines our lives, our growth, and our evolution.
Truth in Action: The Dynamic Process of Evolution
In both the material world and AI systems, truth is not a fixed endpoint but a dynamic process. It’s about evolution—constantly shifting and adapting to new information. This mirrors the way life works. As humans, we set goals, we fail, we learn, and we grow. We update our values and principles based on experience. Similarly, AI systems evolve based on the data they receive, constantly optimizing and improving their performance.
Rather than seeking a static, unchanging truth, the goal is to embrace the journey—the ongoing process of learning, growing, and evolving. Just like AI systems improve with each new input, humans learn and adapt over time. Every failure, every setback, is part of the larger process of moving toward a more refined understanding of truth.
In a way, truth is a constant dialogue between the material (what is) and the ideal (what could be). We may never fully reach the "perfect" truth, but through this dynamic process, we get closer and closer to it. Whether it's the continuous development of AI or the evolution of human knowledge and understanding, truth is not static—it’s an ongoing journey, shaped by both successes and failures.
Conclusion: Truth is a Journey, Not a Destination
Ultimately, truth is not something we simply discover once and for all. It’s a dynamic, evolving process that grows with us. Whether you're an AI system learning from experience or a human striving for personal growth, truth emerges from the constant interplay between certainty and uncertainty, between the material world and the ideal. By embracing this fluid, evolving view of truth, we can move beyond static models and better understand the world around us.
For AI, this means designing systems that can learn, adapt, and grow. For humans, it means accepting that life is a journey filled with uncertainty, failure, and growth. And in both cases, the pursuit of truth is not about reaching a perfect endpoint but about continually evolving toward a more refined understanding of the world and our place within it.
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