Simple formula for high intelligence

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This article by Dr Piotr Wozniak is part of SuperMemo Guru series on memory, learning, creativity, and problem solving.

What is intelligence?

In humans, intelligence is a measure of the ability to solve problems.

What determines intelligence?

Human intelligence depends on (1) innate qualities, (2) upbringing and (3) knowledge.

(1) The Genetic component of intelligence is most apparent in the difference between humans and apes (see: Pleasure of communication), however, it is far less prominent in a healthy human population. Some personality traits may have a greater impact on the ultimate intelligence than the actual innate brain processing power.

(2) Upbringing plays a crucial role in human intelligence. It should primarily be understood as the period when future intelligence can be undermined by disease, abuse, neglect and/or by limits on freedom. For healthy children, love and free access to rich environments is usually a sufficient condition for developing high intelligence.

(3) Knowledge: Given a basic genetic endowment and a healthy modern upbringing, most differences in adult human intelligence can be explained by learning and learning habits. There is also an important component of the interaction between the brain, the personality, and the environment. Some high-potential individuals get trapped in a set of behavioral systems that result in stagnation that may be hard to escape.

Human intelligence has self-amplifying powers that may be undercut (1) internally by a pathology (or aging), or (2) externally by limits on freedom, esp. freedom of learning (e.g. schooling).

Universal intelligence is elusive

In healthy adults, intelligence is a domain-specific problem solving capacity. The concept of innate universal intelligence is a myth. A highly knowledgeable individual may show a spark of genius across many domains and come close to the sense of universal intelligence. We may use the term, a Renaissance (wo)man or a polymath in reference to such a person. Wide learning may provide an illusion of universal intelligence. This seemingly universal intelligence often runs in families. This may be explained by family culture, personality traits, and only to a minor degree by genes associated with the actual processing power of the brain.

As much as there is no universal intelligence, there is no universal IQ test. All tests will depend on prior knowledge, interests, exposure, culture and other biases. Howard Gardner proposed the concept of multiple intelligences, where neurophysiological modalities may determine a preference for a specific type of cognitive processing. His thinking can be extended to all aspects of human knowledge where domain-specific training leads to the emergence of domain-specific intelligence. In other words, there are as many intelligences as there are intelligent human brains. Correlations that lead to the concept of g factor are all rooted in cross-domain transfers (e.g. in a set of positive feedback loops, learning may affect sleep, circulation, neurogenesis, mood, etc.).

As much as there is no universal problem solving capacity, there is no universal problem solving test (see: PISA refocuses on problem solving). This extends to artificial intelligence. We cannot dismiss a state-of-the-art system on the grounds that "all it can do is play Go". It is true that we still struggle to produce an artificially intelligent system that would show universal learn drive sufficient for the emergence of highly applicable abstract knowledge when immersed in any domain. However, once we arrive there, we will still need to train the system in specific domains to call it truly intelligent.

How does aging affect intelligence?

In a healthy adult, domain-specific problem solving capacity will usually follow a curve in which there is an ascent in youth and a decline at older ages. The shape of that curve is determined by the balance of gains and losses. Gains are usually associated with learning, esp. learning via problem solving. Losses are mostly associated with health, esp. metal health, or neglect. As intelligence is a self-perpetuating quality, those who gain intelligence early may continue thriving into a very old age. On rare occasions, the effects of aging can be entirely compensated by lifelong learning, even in octogenarians and beyond.

Intelligence prescription

The above reasoning leads to a simple formula for high intelligence:

To maximize intelligence, we should focus on maximizing the acquisition of high-quality knowledge

The term high quality stands here primarily for coherence and applicability (see: Abstract knowledge).

The above formula is universal and hermetic. It dispenses of the problem of the starting point, which will often differ vastly between individuals. It carries an important optimistic message that accelerates progress: there are few innate obstacles to high intelligence.

How can we make populations more intelligent?

Immense progress could be achieved if adults could eliminate only two factors: (1) stress and (2) sleep problems. As personality traits are set, escaping from toxic human environments may also play a role for a large proportion of the population. Millions of people fail to live up to their potential due to being suppressed by their work environment or even family. Work environments must be friendly and families must thrive on love. Without those preconditions, achieving high intelligence is difficult. The balance of gains and losses may be negative or insufficiently positive. In addition, for a large proportion of children, the chances for growth are stunted by schooling. Schools often promote bad learning habits, loss of self-reliance and unhealthy social environments. One of the best predictors of future high intelligence is a well-established and intense childhood passion.

There is nothing wrong with striving at genius. See my Genius checklist for some hints. In short, if you are unhesitantly involved in passionate problem solving associated with perpetual learning, you can rest assured: you are on the ascending curve towards high intelligence. All you need to remember is to shelter your efforts from possible disruptions to this self-empowering status quo.

Intelligence vs. knowledge

Stable knowledge and new knowledge play key roles in intelligence. For details see: Knowledge in creative problem solving.

Old and new knowledge in creative problem solving

Figure: Creative problem solving requires (1) vast expert knowledge of high stability, and (2) rich new knowledge of high retrievability. Vast stable knowledge makes it easy to solve algorithmic problems. Those problems can be solved at low energy expenditure with the help of fast thinking. Problems that require "thinking out of the box" rely on creativity, i.e. association of remote ideas. Creativity and learn drive are powered by "hungry knowledge", i.e. fresh knowledge that can easily be molded and generalized via forgetting. This plasticity provides for good pattern matching in new learning and in creative problem solving

How to solve any problem?

In a separate article, I propose a universal formula for efficient problem solving. Once you understand that formula, you are more likely to agree with my prescription above. See: How to solve any problem?

Further reading

For more texts on memory, learning, sleep, creativity, and problem solving, see Super Memory Guru