Abstract:

Researchers who study creativity in real-world situations have found that a primary hurdle facing human creativity is in stepping outside of our habitual conceptual association. A few techniques have been suggested to aid this process: making-the-familiar-strange and de-conceptualization, for example. The main objective of these techniques is to help the cognitive agent break the bond of conceptual association it has acquired culturally and through a lifetime of experiences. In this process, imagery, perceptual similarities, and visual metaphors play a key role, as we will demonstrate using several examples.

 

We are following a number of research veins to explore the role of imagery and visual metaphor in creativity and cognition, and in this talk I will present some of our results. In particular, we will present some experiments to compare and contrast mono-modal (text-text or image-image) vs. cross-modal (text-image) metaphors. We have also investigated how explicit imagery, presented before or after the metaphor, influences the comprehension of metaphor.

 

We have argued, and demonstrated, in our past research, that computer-based systems can be very helpful in stimulating creativity. For instance, we found that incorporating one familiar but unrelated object in a picture setting, or presenting unrelated pairs of objects to a cognitive agent, and asking them to make a story out of it, or to make sense of it in some other way, stimulates their creativity and imagination.

 

In another line of research, we are exploring the hypothesis that low-level perceptual similarity — that is, similarity based on low-level perceptual features like color, shape and texture — plays a key role in creation of novel conceptual associations. In other words, we are claiming that if the unrelated object that is introduced into a picture or paired with another object bears some low-level perceptual similarity with other objects in the picture, or with the paired object, it is likely to be more effective in stimulating creativity than a random unrelated object. We will present here the results of some of our preliminary experiments to explore this hypothesis.

 

As the similarity with respect to low-level perceptual features is determined algorithmically using image-based pattern matching, our approach can be used to design more effective computer-based creativity-support systems. We will present an outline of such architecture and mention a number of possible application domains for such systems.