The Self Correcting Nature of Knowledge

The concept of an “error-correcting system” emerges as a fundamental principle in David Deutsch’s seminal work, “The Beginning of Infinity.” This idea underpins a core thesis: that there are good reasons to be optimistic about the future of humanity. The crux of this optimism lies in the nature of knowledge itself, which is not only cumulative but inherently error-correcting.

Knowledge, in this view, functions as a self-improving system. It discards unfit ideas while retaining and refining those that withstand critical scrutiny. This process of intellectual evolution allows our understanding of the world to grow indefinitely, constantly improving and expanding.

The implications of this concept are profound, primarily because it provides a robust argument for limitless progress. It suggests that our capacity to enhance our understanding of reality is boundless, and that we can perpetually strive for better explanations.

In many ways, the retention of knowledge exemplifies the “survival of the fittest” principle in the realm of ideas. Superior explanations persist and evolve, while inferior ones are abandoned. This can be considered a universal principle, applicable to any system in our reality. The scientific method stands as a powerful exemplar - an algorithm with an intrinsic error-correcting mechanism, designed to learn from its mistakes and refine its understanding of the world.

While this may seem self-evident to many, it’s crucial to recognize how many systems in our world lack this error-correcting property. How many structures do we encounter that automatically improve over time by learning from their mistakes? The scarcity of such systems is telling.

It’s important to note the nuances in this argument. The idea that systems can learn from their mistakes is not a given. It necessitates the ability to define concepts like “error” or “mistake,” and to articulate what constitutes improvement. These are non-trivial tasks requiring a level of abstraction that is challenging to achieve. One might even argue that these are fundamentally political questions, demanding a consensus on what is beneficial and detrimental, right and wrong.

This line of thinking leads us to the fascinating realm of genetic algorithms. These optimization techniques, inspired by the principles of natural selection and genetics, serve as a computational analogue to the error-correcting systems we observe in the growth of knowledge. They provide a method for navigating complex optimization landscapes, helping us find global optima in dynamic, evolving systems.

The parallels between genetic algorithms and the evolution of knowledge are striking. Both involve a process of variation and selection, where the most successful configurations of information are more likely to persist and replicate. This demonstrates how the principles of error correction and optimization are deeply intertwined with the fabric of progress, whether in biological evolution, the growth of knowledge, or computational problem-solving.

As we continue to explore these ideas, we must remember that the power of error-correcting systems lies not just in their ability to solve specific problems, but in their capacity to generate new knowledge and open up previously unimagined avenues for progress. This is the essence of what Deutsch calls “the beginning of infinity” - the recognition that our potential for discovery and improvement is limitless, constrained only by the laws of physics and our creativity in devising better explanations.

In this light, error-correcting systems emerge as a fundamental driver of progress, offering a pathway to unlimited advancement in our understanding and capabilities. They provide a framework for optimism, grounded in the demonstrable power of knowledge to solve problems and create new possibilities.

To be continued…