Intelligence, Where to Look, Where to Go?

Paul De Boeck
2013 Journal of Intelligence  
2. Agreement Neural Substrate and Processes The participants of the preliminary discussion largely agree that the neural substrate and processes are important and promising to investigate, with brain imaging and other approaches. Understanding what in the brain accounts for intelligence is considered a major aim of intelligence research. This includes the location of brain activity, as well the density of neurons, the size and connections of areas, the functioning of the brain as a system, and
more » ... hanges in the brain as a consequence of learning and experience, commonly called brain plasticity. Better Measurement Several participants insist that the measurement of intelligence can and should be improved. The suggestions for improvement are of a psychometric and substantive kind. Some psychometric suggestions refer to classic measurement aspects such as construct validity, and other refer to the quality of psychometric modeling. The more substantive suggestions point to a type of data other than from classic intelligence tests, such as data regarding real world activities in real time, and data from games and virtual reality tasks. No Divergence Many interesting points came from one or a few participants and do not show divergence. This does not make these suggestions less valuable. An interest is expressed in the effects of pharmaceutical ingredients, cognitive enhancers, the environment and lifestyle, in the CHC model, longitudinal studies, big data, implicit learning, social impact, item generation, and in artificial intelligence. These are all important topics, some of which imply that more attention is given to other disciplines. For example, engineers are building intelligent systems and systems of artificial intelligence. The domain within psychology where there is some interaction with engineering is mainly cognitive psychology, but surprisingly the domain of human intelligence has not interacted much with engineering.
doi:10.3390/jintelligence1010005 fatcat:hprxc56po5dg3pdy5ylk3rfzxy