Towards Educating Artificial Neural Systems

In the context of text-to-image generators, we discuss how a neural system could be enhanced to follow a knowledge base expressing certain moral considerations, in order to address some looming concerns. We also propose self-educating procedures that enable the system to produce rule-based approximations of its functioning, and illustrate this with an application to the creative interpretation of images.

Authors

• Simon Colton

Keywords

• Pre-trained Neural Models
• Text-to-image Generation
• Computational Creativity