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A Jungian based framework for Artificial Personality Synthesis

The field of computational intelligence has enjoyed much success in developing a variety of algorithms that emulate human cognition. However, a framework to tie these algorithms together in a coherent manner to create a machines that possess the full spectrum of human-like personalities is still needed. To date, research on artificial personality synthesis has focused on using the Big Five model from the field of personality psychology. The overlooked Achilles heel of Big Five (BF) is that it is purely datadriven model, and thus offers only marginal guidance on how a machine with a personality might actually be created. In this work an alternative computational personality framework is presented based on the work of Carl Jung. There are two key insights that suggest a Jungian type-based framework is suitable for synthesizing an artificial personality. First, the cognitive functions which form the building blocks of the Jungian personality model can be mapped to classes of algorithms used to emulate cognition. Second, the Jungian framework suggests that at any given time humans are only using one of the cognitive functions. This suggests that a human personality could be emulated using a state machine with each state implemented using the appropriate class of algorithms.