Limits to knowledge
Science will hit the buffers at some point. There are two reasons why this might happen. The optimistic one is that we clean up and codify certain areas (such as atomic physics) to the point that there’s no more to say. A second, more worrying possibility is that we’ll reach the limits of what our brains can grasp. There might be concepts, crucial to a full understanding of physical reality, that we aren’t aware of, any more than a monkey comprehends Darwinism or meteorology. Some insights might have to await a post-human intelligence.
Scientific knowledge is unexpectedly “spotty”. We might be cocksure of esoteric and distant cosmic occurrences, but dumbfounded by run-of-the-mill matters. Astronomy is much less complex than the human sciences. We can measure black holes, but we still can’t cure the common cold.
Scientific knowledge is typically pictured as a pecking order, arranged like the floors of a property. Those addressing more complex structures are higher up, while the less complex ones drop below. Mathematics resides in the basement, trailed by particle physics, and then the remainder of physics, then chemistry, then biology, then botany and zoology, and ultimately the behavioural and social sciences (with the economists, probably, laying claim to the penthouse). “Ordering” the sciences is uncontroversial, but it’s questionable whether the “ground-floor sciences”– particle physics, in particular– are really deeper or more all-inclusive than the others.
The reductionist guiding paradigm of Science isn’t constantly the most reliable or most practical one. Reductionism is right in a sense, but it’s not often on target in a practical way. What is actually significant and intriguing is the way pattern and framework shows up as we ascend the levels, what could be referred to as emergent complexity. Macroscopic systems that comprise of enormous quantities of particles demonstrate “emergent” properties which are better comprehended in terms of fresh, irreducible principles suitable to the level of the system.
Just how do we spell out complexity? The issue of how far science can extend, to a certain extent, hinges on the response. There quite possibly are boundaries to what we can comprehend. Attempts to figure out extremely complex systems, like our own brains, may perhaps be on the top of the list to encounter such limitations.
Science will likely run into the barriers at some point. There are two good reasons how this could take place. The upbeat one is that we straighten up and organise specific specialties (such as atomic physics) to the point in which there’s no more to announce. A second, far more troubling prospect, is that we’ll arrive at the edges of things that our intellects can latch on to. There could be models, essential to a complete comprehending of physical reality, that we may not be able to wise up to, any more than a monkey understands Darwinism or meteorology. Some visions might need to wait for a post-human intelligence.
The chess champion Garry Kasparov suggests in Deep Thinking (2017) that “human plus machine” is more potent than either alone. Quite possibly it’s by capitalizing on the bolstering symbiosis between the two that new breakthroughs will be created.