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

Abstract

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.

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Notes

  1. The components of creativity are strongly recommended as a basis for this definition.

  2. In the context of music generation systems, which often contribute to computational creativity literature.

  3. Both Bundy [5] and Pearce et al. [6] stress that specific goals and value may vary across types of systems; this assertion is upheld in this paper.

  4. Definition taken from the computationalcreativity.net website [13], which hosts relevant information about the field, including details of research events and of the steering committee who act to shape the general directions that computational creativity research takes.

  5. Knowledge-Based Systems 2006: 19(7), New Generation Computing 2006: 24(3), AI Magazine 2009: 30(3), Minds and Machines 2010: 20(4).

  6. Computational Creativity workshops have been held in conjunction with several AI conferences (AISB’99, AISB’00, AISB’01, ECAI’02, AISB’02, IJCAI’03, AISB’03, IJCAI’05, ECAI’06) case-based reasoning conferences (ICCBR’01, ECCBR’04) and linguistics conferences (LREC’04, NAACL’09).

  7. Autonomous workshops grew out of the International Joint Workshop on Computational Creativity series (2004–2008), which started through the coming together of communities from AI and from Cognitive Science, to hold joint research events on computational creativity. Separate symposiums have also been held, in Stanford, California (twice).

  8. The pre-2004 workshops typically contained 10–15 papers, with programme committee sizes around 5–15 depending on the event. This has grown to an average of 33 accepted papers and an average of 42 programme committee members over the 2010–2012 conferences.

  9. Existing evaluation methodologies for computational creativity are examined later in this section of the paper.

  10. This paper will return later to these discussions at ICCC’11.

  11. This view was also expressed in [19].

  12. The combination of novelty and originality is often used as a reductionist definition of creativity [2, 2025]. Definitional issues shall be returned to later in this paper.

  13. For ICCC’11, this phrasing appeared with a qualifier: “quasi-formal approaches that, for example, argue for recognition without definition or that define the absence of creativity may have interesting implications for computational creativity”. This was probably in response to just such a evaluation framework offered by Colton [3], which quickly became adopted more often than more formally stated predecessors such as [2, 20], as shall be shown later in this paper.

  14. See for example the proceedings for ICCC’11, ICCC’10 or IJWCC’07 [2729] where a position paper is distinguishable from a full technical paper only by its number of pages.

  15. Whether creativity is contained in the creative process, or in the output generated by a system, or in both (and other aspects besides), is a debate which shall be returned to in greater depth later in this paper, in “The Product/Process Debate” section. At this stage of the paper, Ritchie’s product-focussed perspective on this debate is highlighted; it will be argued in “The Product/Process Debate” section that this can lead to disregarding of crucial evidence of creativity, and is a somewhat misunderstood interpretation of creativity

  16. Here Colton makes an important distinction; rather than positing the creative tripod qualities as necessary components of a creative system, he argues that the system merely needs to be perceived to have these qualities. In other words, the challenge is to engineer a system that appears to be creative to its audience, rather than engineering a system that possesses a level of creativity existing independently of an audience’s perception.

  17. Proceedings from annual events in 2007–2010 were included in the survey, which was conducted in late 2010-early 2011. Proceedings from creativity research events prior to 2007 are not readily available in an online format, making them difficult to locate for this survey and also less likely to have influence on researchers today unless they were one of the relatively few people who attended that workshop (in comparison with attendances of such events in more recent years).

  18. The case study reported below demonstrates the incorporation of value judgements and considerations of domain competence into creativity evaluation.

  19. A similar variety of points of views was acknowledged during discussions on evaluation at the 2009 computational creativity seminar at Dagstuhl, including the perspectives of ‘viewer/experiencer’, ‘creator’ and ‘interactive participant [38, p. 1].

  20. All comments in this section are anonymised.

  21. Another issue mentioned during this part of the discussion was that it was often difficult to obtain up-to-date, maintained and fully working materials to use for evaluation, such as the system’s source code or products.

  22. The evaluation survey looks at 75 papers describing such systems.

  23. ERI-designer, mentioned above, could perhaps be compared to architectural design systems or game design systems.

  24. The work in the “Key Components of Creativity” section will adopt a confluence-style approach, seeking to capture a wider disciplinary spectrum of perspectives on creativity that has previously been attempted [58, 78, 79].

  25. What does appear when reviewing legal research are interesting discussions of whether or not computational creativity can be legally recognised [83, 8890].

  26. Conceptual art is where the concepts and motivations behind the artistic process form a significant contribution of the artwork.

  27. Colton’s solution is to report systems in high-level terms only, rather than giving details of the program [3, p. 8].

  28. This set of components is pictured in Fig. 1.

  29. Some non-musicians were included in the questionnaire as they had experience of listening to musical improvisation and were therefore able to give a slightly different perspective. The questionnaire distribution was however weighted towards professional musicians and improvisers.

  30. This was partly due to the demographics of the participants, whose nationalities ranged from British to Brazilian, though the majority of participants were recruited from UK-based contacts.

  31. An additional two judges were used in pilot studies, but the data provided in these pilot studies is excluded from the evaluation results presented in this paper.

  32. Judges were restricted to evaluating two of the four systems rather than all four due to practical restrictions on time.

  33. Judges could use ratings of x.5 out of 10 if they specifically asked to. Hence the rating scale was effectively a 21-point numeric scale, with 5 as the midpoint between the two extremes of 0 and 10.

  34. The FACE/IDEA models [4], published after the evaluations in this case study had been performed, will also be applied in the near future and results will be published in [126].

  35. Definitions of creativity are often supplied as a list of components or contributory aspects of creativity [54, 58, 65, 77]. The Fig. 1 components are offered as a working definition because the empirical methods used to derive them are based around writings from the time period 1950–2009; as creativity changes over time, the components may need to be updated in the future, but for the present time, they are derived from writings from the last sixty years of research on creativity.

  36. Principle Component Analysis (PCA) is another dimensionality reduction technique. PCA identifies the minimal representation of data by combining and merging components, using eigenvectors and eigenvalues for dimensionality reduction. As PCA therefore does not keep the components distinct and examine the importance of components individually, this has an adverse affect on how evaluative results can be used as formative feedback, as the correlations between component and results have been lost,

  37. Additionally, in the context of the specific domain investigated in the case study (musical improvisation), respondents to the questionnaire about creativity in musical improvisation collectively mentioned each component at some point (to varying degrees).

  38. Perhaps this issue was replaced with the issue of whether the judges understood each component well enough—a possibility despite careful attention paid to describing the components to judges.

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Acknowledgments

Thanks to Nick Collins for his support and supervisory input during this work, and to all the participants who took part in the case study. Communications and discussions with Alison Pease and Steve Torrance have also been extremely beneficial, as have the comments by the three anonymous reviewers of this article. The quality of computational linguistics work to derive the components of creativity reported in this paper was greatly enhanced by the collaborative involvement and knowledge of Bill Keller. The contents of this paper are the result of doctoral research conducted at the Department of Informatics, University of Sussex, UK, who provided a doctoral stipend to partially fund this work. Some financial assistance was also received from the Sir Richard Stapley Educational Trust and the Society for the Study of Artificial Intelligence and the Simulation of Behaviour (AISB).

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Jordanous, A. A Standardised Procedure for Evaluating Creative Systems: Computational Creativity Evaluation Based on What it is to be Creative. Cogn Comput 4, 246–279 (2012). https://doi.org/10.1007/s12559-012-9156-1

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Keywords

  • Computational creativity
  • Creativity evaluation
  • Cognitively inspired evaluation
  • Methodology
  • Creativity
  • Musical creativity