DeepCreativity: measuring creativity with deep learning techniques

Measuring machine creativity is one of the most fascinating challenges in Artificial Intelligence. This paper explores the possibility of using generative learning techniques for automatic assessment of creativity. The proposed solution does not involve human judgement, it is modular and of general applicability. We introduce a new measure, namely DeepCreativity, based on Margaret Boden's definition of creativity as composed by value, novelty and surprise. We evaluate our methodology (and related measure) considering a case study, i.e., the generation of 19th century American poetry, showing its effectiveness and expressiveness.

Automated summary

This paper explores the possibility of using generative learning techniques to measure machine creativity. A new measure called DeepCreativity, based on Margaret Boden's definition of creativity, is introduced. The effectiveness and expressiveness of the proposed methodology is evaluated through a case study on 19th century American poetry.