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Affective Cognition

Emotional Intelligence

The ability to perceive, understand, regulate, and use emotions - in oneself and in others - to guide reasoning and behaviour.

Historical overview

The construct was formalised by Salovey and Mayer (1990) and popularised by Daniel Goleman (1995). The Mayer–Salovey–Caruso Emotional Intelligence Test (MSCEIT) is the leading ability-based measure.

Scientific basis

Emotional intelligence depends on the amygdala (salience), insular cortex (interoception), anterior cingulate (conflict monitoring), and ventromedial prefrontal cortex (value integration). It draws on both fast affective appraisal and slow cognitive reappraisal.

Strengths

  • Improves leadership, negotiation, and team performance
  • Buffers against anxiety, depression, and burnout
  • Enables high-fidelity social inference

Limitations

  • Difficult to measure reliably outside ability-based tests
  • Can be deployed manipulatively (the 'dark empath')

Relationship to other intelligence systems

  • Social Intelligence

    Emotional intelligence is the affective core of social intelligence.

  • Human Intelligence

    A recognised facet within the broader cognitive profile.

Future implications

Affective computing aims to give AI systems functional analogues of emotional understanding - a contested goal with significant ethical implications.

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