Fluid and crystallized intelligence are elements of general intelligence, originally identified by Raymond Cattell. The concepts of fluid and crystallized intelligence were further developed by Cattell’s student John L. Horn. Here are Wikipedia’s definitions:
Fluid intelligence or fluid reasoning is the capacity to reason and solve novel problems, independent of any knowledge from the past. It is the ability to analyze novel problems, identify patterns and relationships that underpin these problems and the extrapolation of these using logic. It is necessary for all logical problem solving. Fluid reasoning includes inductive reasoning and deductive reasoning.
Crystallized intelligence is the ability to use skills, knowledge, and experience. It does not equate to memory, but it does rely on accessing information from long-term memory. Crystallized intelligence is one’s lifetime of intellectual achievement, as demonstrated largely through one’s vocabulary and general knowledge. This improves somewhat with age, as experiences tend to expand one’s knowledge.
So the basic difference is that fluid intelligence involves our current ability to reason and to deal with complex information, while crystallized intelligence involves learning, knowledge, and skills acquired over a lifetime. Research has shown that these two factors of general intelligence peak at different times in life. Fluid intelligence peaks early in life, typically in the late teens or early twenties, while crystallized intelligence peaks much later in life, often in one’s sixties or seventies.
And recent research, using large online samples, reveals that specific mental capabilities peak at different times. Here are the ages at which various capabilities peak:
- 18-19: Information-processing speed peaks early, then begins to decline.
- 25: Short-term memory gets better until around age 25.
- 30: Memory for faces peaks and then starts to gradually decline.
- 35: Short-term memory begins to weaken and decline.
- 40s-50s: Emotional understanding peaks in middle to late adulthood.
- 60s: Vocabulary abilities continue to increase.
(If interested you can find many graphs about age and various mental capabilities here.)
While I am not an expert on this topic the findings above match my experience. I found that teaching symbolic logic became more difficult to teach as I aged but understanding and synthesizing philosophy became easier as the storehouse of my knowledge increased.
I’m not sure how this all relates to clichés like “you can’t teach an old dog new tricks” or “old people are set in their ways.” I am a lifelong learner who believes that unlearning old falsehoods is the essence of having a childlike, inquisitive mind. To keep learning we must fight against the mental grooves that accumulate with time. Still, I admit to being more open-minded—or impressionable if you prefer—when I was younger. As I’ve gotten older some ideas have simply been discarded and I don’t have the time or inclination to revisit them.
I suppose then that we need to strike a balance between being open to novel ideas and not discarding previous ones that were adopted after careful and conscientious deliberation. As the late Carl Sagan put it in one of my favorite books, The Demon-Haunted World: Science as a Candle in the Dark
I had never known of this analytic approach; it’s fascinating, and my own thinking on mentation parallels it. I model the mind as a huge network of interconnected ideas. As we learn, that network expands in two ways. First, it adds new ideas (nodes), such as F=ma for a physicist or ego for a psychologist. Second, it adds new connections between existing ideas, such as the realization that the sky is blue for the same reason that the sunset is red (for a physicist). I’m sure that you’ve had many such realizations in philosophy (“Garsh, Plato’s notion of the reality of ideals is just like an ice cream cone!” Well, maybe not that…)
I’m guessing that the correlations in my model to crystallized versus fluid intelligence is that fluid intelligence corresponds to the ability to generate completely new nodes (ideas) solely from the existing network (which, in a young person, is rather skimpy). Crystallized intelligence corresponds to the ability to recognize connections between existing nodes.
An interesting aspect of my model is that it has no place for “static memory” — recollection of simple facts, such as names and faces. Instead, each node in my model is a statement or tiny story. I can tell you lots of stupid things about Mount Potosi in Bolivia and the history of its silver. I remember all these ridiculous details (such as people hired to walk around the town carrying heavy bags of silver coins so as to generate silver powder from the jingling of the coins, which could be extracted without violating the law) because they are part of a story of human avarice.
In the physics community, it is believed that a physicist passes his prime around age 30 and is thereafter valued for experience, not creativity.
I’m no expert but your model seems reasonable to me. And you’re right in physics and math great discoveries are usually made by youngsters whereas in philosophy many don’t write their best stuff until their 50s or even 60s. I bet if I went back to high school geometry or trig (which I was pretty good at as a teenager) my 67 year old self would have a much harder time.
I kind of get the terms, after reading the explanation/definitions given. I suppose there are more-or-less ideal examples of real people whose minds epitomize these capacities, though I would not try to name more than one (Richard Feynman) in the fluid category…someone will, no doubt, dissent from that assessment. Most of us would like to think we have steady-state fluidity. Few do, or ever will.
I can certainly validate some of the author’s findings. For example, children; they suck up knowledge and languages like a sponge, which means there is a critical period when they ought to be exposed to as many opportunities as possible. Getting a later start, I tried all the quick gimmicks to accelerate the process such as listening to tapes as I slept and even taking Evlevyn Woods’ speed reading courses, without much success. Nothing beat the old fashioned way of due diligence– studying. One old botany professor told me he stopped memorizing students names as they caused him to lose hold on to the latin names he had spent years committing to memory. These days experiencing “a brain fog” occurs more often. So much still to learn for a lifelong learner . So little time/energy to do so.
Consistent with Chris Crawford’s final statement, Albert Einstein published E=mc^2 in 1905 at about age 26 and Werner Heisenberg published his uncertainty principle of quantum mechanics in 1925 at about age 24. But the 46-year old Einstein could not accept the uncertainty principle and spent many of his remaining years trying to disprove it. Somehow, I cannot imagine Heisenberg to be intrinsically more intelligent than Einstein nor can I imagine that Heisenberg somehow possessed more physics knowledge in his brain than Einstein. Possessed of the same information, it would seem that Einstein’s 46-year old brain simply could not grasp the fundamental truth of Heisenberg’s uncertainty principle. Perhaps Chris’s node model of the mind can make sense of this age-related effect.
I picture Chris’ model of the mind to be a huge lattice of interconnected nodes, with each node containing a bit of information (true or false) or a more complex idea (true or false). I imagine the lattice to be very densely packed with information nodes, but with idea nodes more sparsely spread throughout. An idea node gets formed by some complex interconnection of critically-important information nodes and other idea nodes. But the lattice is also filled with many unimportant, irrelevant or false information and idea nodes and their complex connection pathways. As one ages and accumulates more nodes, the lattice becomes more and more densely packed. I can imagine that all the random, unimportant and false information and ideas, with their complex connections, clog up the lattice making it harder to for the critically-important true information nodes to form a particular true idea node. Thus, it is possible that the young physicist’s brain simply has cleaner mental lattice – allowing a more direct connection between the critical set of information and the idea.
Or maybe not. But it is an interesting topic.
And your comments are really interesting. Perhaps Chris will reply.
Jim, my explanation of Mr. Einstein’s resistance to quantum mechanics is that his network of ideas had become so extensive that it was unable to re-arrange itself to accommodate QM. Every day we experience a massive amount of new information, far more than our mental networks can accommodate. So at night, our brains sort through all the information of the day, discarding most of it. Each experience is tested for how it fits into the network. If it merely replicates well-established portions of the network, it is discarded. But information that doesn’t quite fit requires some re-adjustment of the network to allow it to fit in. This re-adjustment of the network is what we call “learning”. And the process of sifting through all that information is too complicated for us to grasp, so we afterwards interpret it in our standard data protocol: stories. That’s what dreams are. Just as a very small child interprets a complex sequence of events that he witnesses as a simple story, we do the same with dreams.
Thanks, Chris. I always enjoy reading your comments, which are clear, concise and thought-provoking.