Some Empirical Criteria for Attributing Creativity to a Computer Program

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Four PPPPerspectives on Computational Creativity

From what perspective should creativity of a system be considered? Are we interested in the creativity of the system’s out- put? The creativity of the system itself? Or of its creative processes? Creativity as measured by internal features or by external feedback? Traditionally within computational creativity the focus had been on the creativity of the system’s Products or of its Processes, though this focus has widened recently regarding the role of the audience or the field surrounding the creative system. In the wider creativity research community a broader take is prevalent: the creative Person is considered as well as the environment or Press within which the creative entity operates in. Here we have the Four Ps of creativity: Person, Product, Process and Press. This paper presents the Four Ps, explaining each of the Four Ps in the context of creativity research and how it relates to computational creativity. To illustrate how useful the Four Ps can be in taking a fuller perspective on creativity, the concepts of novelty and value explored from each of the Four P perspectives, uncovering aspects that may otherwise be overlooked. This paper argues that the broader view of creativity afforded by the Four Ps is vital in guiding us towards more encompassing and comprehensive computational investigations of creativity

The longer term value of creativity judgements in computational creativity

During research to develop the Standardised Procedure for Evaluating Creative Systems (SPECS) methodology for evaluat- ing the creativity of ‘creative’ systems, in 2011 an evaluation case study was carried out. The case study investigated how we can make a ‘snapshot’ decision, in a short space of time, on the creativity of systems in various domains. The systems to be evaluated were presented at the International Computational Creativity Conference in 2011. Evaluation was performed by people whose domain expertise ranges from expert to novice, depending on the system. The SPECS methodology was used for evaluation, and was compared to two other creativity evaluation methods (Ritchie’s criteria and Colton’s Creative Tripod) and to results from surveying people’s opinion on the creativity of the systems under investigation. Here, we revisit those results, considering them in the context of what these systems have contributed to computational creativity development. Five years on, we now have data on how influential these systems were within computational creativity, and to what extent the work in these systems has influenced further developments in computational creativity research. This paper investigates whether the evaluations of creativity of these systems have been helpful in predicting which systems will be more influential in computational creativity (as measured by paper citations and further development within later computational systems). While a direct correlation between evaluative results and longer term impact is not discovered (and perhaps too simplistic an aim, given the factors at play in determining research impact), some interesting alignments are noted between the 2011 results and the impact of papers five years on

A Standardised Procedure for Evaluating Creative Systems: Computational Creativity Evaluation Based on What it is to be Creative

Computational creativity is a flourishing research area, with a variety of creative systems being produced and developed. Creativity evaluation has not kept pace with system development with an evident lack of systematic evaluation of the creativity of these systems in the literature. This is partially due to difficulties in defining what it means for a computer to be creative; indeed, there is no consensus on this for human creativity, let alone its computational equivalent. This paper proposes a Standardised Procedure for Evaluating Creative Systems (SPECS). SPECS is a three-step process: stating what it means for a particular computational system to be creative, deriving and performing tests based on these statements. To assist this process, the paper offers a collection of key components of creativity, identified empirically from discussions of human and computational creativity. Using this approach, the SPECS methodology is demonstrated through a comparative case study evaluating computational creativity systems that improvise music