Our brains come with hard-wired algorithms. Cats can catch birds or mice without thinking about it. I can grab and eat a strawberry without thinking. The Savanna-IQ Interaction Hypothesis says that general intelligence may originally have evolved as a domain-specific adaptation to deal with evolutionarily novel, nonrecurrent problems. We can derive from this hypothesis that people with better general intelligence won’t be better at routine tasks. In fact, they may fare worse at it! They may only have an edge for novel tasks. Thus, general and domain intelligence may be somewhat separate entities.
How do you recognize people with better general intelligence? They are better at adapting to new settings. They are the first to adopt new strategies. But they may not be very good at baseball or boxing, and they may be socially inept.
Modern Artificial Intelligence (and Machine Learning) is typically domain-specific. My spam filter can detect spam, but it won’t ever do anything else. Our software has evolved to cope with specific problems. Yet, we still lack software with general intelligence. Trying to build better spam filters may be orthogonal to achieving general intelligence in software. In fact, software with good general intelligence may not do so well at spam filtering.
Reference: Satoshi Kanazawa, Kaja Perina, Why night owls are more intelligent, Personality and Individual Differences 47 (2009) 685â€“690
Further reading: Language, Cognition, and Evolution: Modularity versus Unity by Peter Turney