Artificial Psychology: A New Research Line in Psychological Research

The assumptions and philosophy underlying artificial psychology (AP) have been presented and we motivate the need for a set of models which can incorporate information from complex mental systems using ideas such as fuzziness of a system and supervised and unsupervised algorithms which use artificial intelligence. We discuss the need for a multiplicity of modelling approaches to help us to understand the world. We mention issues involving hypothesis testing, in particular we introduce and define the p-value and highlight its shortcomings including p-hacking where data is manipulated so that it yields statistically significant results with an associated bias towards publishing studies which have p-values below a certain threshold. We mention widespread misunderstandings in the interpretation of the p-value and associated dangers such as giving the impression that the world is ‘black and white’ and motivate the need for complementary more nuanced approaches to testing statistical hypotheses which can overcome these deficiencies.