I extend the existing definition of intelligence into three dimensions: IQ, the vocabulary of patterns and the depth of thinking. This allows to explain many phenomena and to suggest how one can improve intelligence if desired.
The ideas below come from the book Professor Andrew Lo‘s book Adaptive Markets, which I highly recommend. Even though its subject is a financial markets theory, it discusses a wide range of subjects. One of them is the nature of human intelligence. I liked how the hypotheses brought up by Prof. Lo appear to explain a range of intelligence-related phenomena. I have added nothing new, just combined what was in this book.
Intelligence Definition Hypotheses Mentioned in Adaptive Markets
I believe there are three intelligence definition hypotheses mentioned in Prof. Andrew Lo‘s book Adaptive Markets, as below. All of them, in one or another way, are related to artificial intelligence.
- Jeff Hawkins, a neuroscientist who invented the Palm (PDA), argues in his book On Intelligence that intelligence consists of two features: memory and prediction. This memory-prediction framework suggests that the essence of intelligence and even consciousness is a prediction.
- Patrick Winston, a prominent MIT professor, suggests in his paper “The Right Way” that intelligence is the ability to tell, understand and recombine the stories.
- Herbert A. Simon, who later pioneered AI, has introduced the concept of bounded rationality: he suggested that individuals don’t fully optimise over all potentially available options, but make the decisions when they are satisfied that these decisions are ‘good enough’, only considering the limited range of options.
What Are Three Dimensions of Intelligence?
We could combine the above-mentioned definitions of intelligence and suggest that human intelligence has three dimensions:
- dictionary of patterns,
- ability to match atomic patterns (this dimension is what’s measured by IQ tests; hereafter we will call it IQ),
- ability to combine/chain/review atomic patterns (let’s call it ‘the depth of thinking’), and time spent on it.
This model a hypothesis, it is unclear how a could prove (or disprove) it. However, the advantage of this hypothesis is that it naturally allows to explain quite a few intelligence-related phenomena and also some cognitive biases.
Implications of Our Theory
Experience vs. Intelligence
Experience (large dictionary of patterns) is important. It could be substituted by other components of intelligence (IQ and the depth of thinking), but only to a certain extent. People with higher intelligence could potentially adapt or recombine the patterns from their relatively smaller patterns dictionary to find the one that is already there is the dictionary of a more experienced person. Obviously, this adaptation capacity is limited; if taken too far, one could end up in the realm of improbable or impossible patterns.
How to become more intelligent?
Apparently, it is difficult to significantly increase one’s IQ. However, two other dimensions of intelligence can be improved on, subject to motivation and capable (healthy?) brain.
Pattern vocabulary can be improved through exposure to new experiences, interactions, activities etc.
Intelligence depth could grow as the result of exercises such as debating/stimulating discussions, playing chess, solving multistep puzzles etc.
One could imagine that the importance of patterns vocabulary volume and intelligence depth is described by a standard indifference curve map. This would mean that, in any case, the contributions to any dimension is beneficial. However, the optimal time/effort allocation requires improving on both dimensions. If one dimension (e.g. the depth) remains low, a marginal contribution to the other dimension will have a lower impact on overall intelligence.
Why highly intelligent people are often naturally interested and have advanced knowledge of a range of seemingly unrelated subjects (polymaths)
Probably because the seemingly unrelated subjects have either similar underlying patterns or else the underlying patterns are interesting to link/juxtapose.
Faulty generalization a.k.a. “the law of small numbers”
It occurs when one attempts to deduce a pattern from too small a sample of data, events etc. Obviously, the result cannot be reliable.
The confirmation bias is the illusion of bypassing the law of small numbers by having several (or a large number) of similarly thinking people. However, the law of small numbers can only be bypassed if a sufficiently large number of patterns are added in, and they are being expressed and confronted. Thus, one should accept a certain level of arguments and even conflicts to be able to avoid the confirmation bias:
The advantage of diversity
Genuine diversity is the diversity of dictionaries of patterns. People who have them need to be able to cooperate in order to build a larger dictionary or patterns and perhaps the abilities to recombine them. Diversity defined by different genders, races, ages etc. is a proxy to genuine diversity. It has the best chance to realise if people had diverse life experiences and intrinsic qualities.
The link between IQ and EQ
By our definition, IQ is the ability to match a variety of culture-neutral abstract patterns. EQ, Emotional quotient, is also the ability to match the patterns, however, unlike IQ, EQ patterns are highly culture-specific, and require experience (the real life or perhaps relevant books – movies).
One could wonder how to explain the Asperger syndrome (high IQ autism) within our framework. Indeed, its exitance might appear to contradict the previous statement about the similarities of IQ and EQ.
The possible explanation might lie not in the domain of intelligence but in the realm of emotions. Indeed, as discussed in Antonio Damasio‘s book Descartes' Error, emotions are a crucial part of learning. One could suppose that individuals who have Asperger syndrome struggle with social interactions because they find them dissatisfying, or less pleasant than the activities that they are happy to carry out repetitively.
One could argue that mindless chatting, drinking alcohol, shopping, TV watching etc. also qualify for repetitive activities, but they are normalised because they are popular with so many people. And perhaps those with Asperger’s syndrome would be more social if put in touch with those who have similar interests?
IQ/EQ differences without Asperger syndrome
There are people whose interpersonal intelligence is much higher than their “scientific” intelligence and vice versa. There are several factors that can explain it. One is the upbringing:
- Some bias can be induced deliberately. The most obvious example is gender-specific upbringing: “boys should not do this”, “please behave like a girl”, etc. In general, boys are discouraged to express emotions. One can hardly expect someone to develop high EQ (i.e. to be able to understand other’s emotions well) if he is out of touch with his own emotions!
- Some bias can be induced through a more/less stimulating environment. For example, if parents are happy to discuss scientific matters but, being emotionally illiterate, ignore EQ aspects, their children can be expected to develop a similar bias.
- Some bias can appear if a child’s “I do not want to bother” attitude is encouraged.
These phenomena occur when low depth or thinking prevents one from considering/integrating new information and reviewing/updating the patterns.
- Martin Hilbert’s ‘Toward a Synthesis of Cognitive Biases: How Noisy Information Processing Can Bias Human Decision Making’ is a great scientific paper that builds a theory to explain 8 cognitive biases.
- Here is the chart that shows 188 cognitive biases.
- Here are two non-verbal IQ tests you might want to take if you wish to have estimate your IQ:
- Roughly speaking, IQ is the equivalent of Daniel Kahneman‘s “System 1” and depth is the equivalent of his “System 2”. You can learn about these systems in his book Thinking, Fast and Slow or in his talk Daniel Kahneman: 'Thinking, Fast and Slow' | Talks at Google:
- One’s ability to use the depth dimension when making the decisions can be estimated early on using the Stanford marshmallow experiment.