Preference Models for Creative Artifacts and Systems

Abstract Although there is vigorous debate around definitions of creativity, there is general consensus that creativity i) has multiple facets, and ii) inherently involves a subjective value judgment by an evaluator. In this paper, we present evaluation of creative artifacts and computational creativity systems through a multiattribute preference modeling lens. Specifically, we introduce the use of multiattribute value functions for creativity evaluation and argue that there are significant benefits to explicitly representing creativity judgments as subjective preferences using formal mathematical models. Various implications are illustrated with the help of examples from and inspired by the creativity literature

Exploring Research through Design in Animal-Computer Interaction

This paper explores Research through Design (RtD) as a potential methodology for developing new interactive experiences for animals. We present an example study from an on-going project and examine whether RtD offers an appropriate framework for developing knowledge in the context of Animal-Computer Interaction, as well as considering how best to document such work. We discuss the design journey we undertook to develop interactive systems for captive elephants and the extent to which RtD has enabled us to explore concept development and documentation of research. As a result of our explorations, we propose that particular aspects of RtD can help ACI researchers gain fresh perspectives on the design of technology-enabled devices for non-human animals. We argue that these methods of working can support the investigation of particular and complex situations where no idiomatic interactions yet exist, where collaborative practice is desirable and where the designed objects themselves offer a conceptual window for future research and development

Texture Mixer: A Network for Controllable Synthesis and Interpolation of Texture

This paper addresses the problem of interpolating visual textures. We formulate this problem by requiring (1) by-example controllability and (2) realistic and smooth interpolation among an arbitrary number of texture samples. To solve it we propose a neural network trained simultaneously on a reconstruction task and a generation task, which can project texture examples onto a latent space where they can be linearly interpolated and projected back onto the image domain, thus ensuring both intuitive control and realistic results. We show our method outperforms a number of baselines according to a comprehensive suite of metrics as well as a user study. We further show several applications based on our technique, which include texture brush, texture dissolve, and animal hybridization.Comment: Accepted to CVPR'1

Paradigms in the study of creativity: introducing the perspective of cultural psychology

This article identifies three paradigms in creativity theory and research in psychology. The He-paradigm, focused on the solitary genius, has been followed, mainly after the 1950s, by the I-paradigm, equally individualistic in nature but attributing creativity to each and every individual. Extending this view, the We-paradigm incorporates what became known as the social psychology of creativity. The cultural psychology of creativity builds upon this last theoretical approach while being critical of some of its assumptions. This relatively new perspective, using the conceptual and methodological framework of cultural psychology, investigates the sociocultural roots and dynamics of all our creative acts and employs a tetradic framework of self – community – new artifact – existing artifacts in its conceptualization of creativity. The theoretical basis of the cultural psychology approach is analyzed as well as some of its main implications for both the understanding and study of creativity

Taste and the algorithm

Today, a consistent part of our everyday interaction with art and aesthetic artefacts occurs through digital media, and our preferences and choices are systematically tracked and analyzed by algorithms in ways that are far from transparent. Our consumption is constantly documented, and then, we are fed back through tailored information. We are therefore witnessing the emergence of a complex interrelation between our aesthetic choices, their digital elaboration, and also the production of content and the dynamics of creative processes. All are involved in a process of mutual influences, and are partially determined by the invisible guiding hand of algorithms. With regard to this topic, this paper will introduce some key issues concerning the role of algorithms in aesthetic domains, such as taste detection and formation, cultural consumption and production, and showing how aesthetics can contribute to the ongoing debate about the impact of today’s “algorithmic culture”