Computer programs are generating artworks of astonishing novelty and aesthetic value. By the standard definition of creativity, these programs would count as being creative. But if you still hesitate to call a program creative, that's for good reason, we argue. It's because real creativity requires AGENTS who are responsible for what they make, and it's not at all clear that these programs are agents. -/- (The title was imposed by the editor. It was supposed to be called, "ARE (...) COMPUTERS CREATIVE?"). (shrink)

Computational Creativity, Concept Invention, and General Intelligence in their own right all are flourishing research disciplines producing surprising and captivating results that continuously influence and change our view on where the limits of intelligent machines lie, each day pushing the boundaries a bit further. By 2014, all three fields also have left their marks on everyday life – machine-composed music has been performed in concert halls, automated theorem provers are accepted tools in enterprises’ R&D departments, and cognitive architectures (...) are being integrated in pilot assistance systems for next generation airplanes. Still, although the corresponding aims and goals are clearly similar (as are the common methods and approaches), the developments in each of these areas have happened mostly individually within the respective community and without closer relationships to the goings-on in the other two disciplines. In order to overcome this gap and to provide a common platform for interaction and exchange between the different directions, the International Workshops on “Computational Creativity, Concept Invention, and General Intelligence” (C3GI) have been started. At ECAI-2012 and IJCAI-2013, the first and second edition of C3GI each gathered researchers from all three fields, presenting recent developments and results from their research and in dialogue and joint debates bridging the disciplinary boundaries. The chapters contained in this book are based on expanded versions of accepted contributions to the workshops and additional selected contributions by renowned researchers in the relevant fields. Individually, they give an account of the state-of-the-art in their respective area, discussing both, theoretical approaches as well as implemented systems. When taken together and looked at from an integrative perspective, the book in its totality offers a starting point for a (re)integration of Computational Creativity, Concept Invention, and General Intelligence, making visible common lines of work and theoretical underpinnings, and pointing at chances and opportunities arising from the interplay of the three fields. (shrink)

Algorithms and automated learning systems have been successfully applied to produce images, pieces of music, or texts that are appealing to humans and that are often compared to artworks. Computational technologies are able to find surprising and original solutions–new patterns that humans cannot anticipate– but does this mean we ascribe to them the kind of creativity that is expressed by human artists? Even though AI can successfully detect humans’ preferences as well as select the objects that satisfy taste, (...) can we ascribe to them the capacity of recognizing the intrinsic value of artworks? To answer these questions, I am first going to explain the kind of creativity that is expressed by contemporary predictive systems, then, in the second part of this paper, I will try to show the difference between the creativity of algorithms and the creativity of artists by expanding on Deleuze’s reflections. (shrink)

Computational Creativity: A Continuing Journey Content Type Journal Article DOI 10.1007/s11023-010-9212-0 Authors Tony Veale, Departamento de Ingeniera del Software e Inteligencia Artificial, Universidad Complutense de Madrid, Madrid, Spain Pablo Gervás, Departamento de Ingeniera del Software e Inteligencia Artificial, Universidad Complutense de Madrid, Madrid, Spain Rafael Pérez y Pérez, Departamento de Ingeniera del Software e Inteligencia Artificial, Universidad Complutense de Madrid, Madrid, Spain Journal Minds and Machines Online ISSN 1572-8641 Print ISSN 0924-6495 Journal Volume Volume 20 Journal Issue Volume (...) 20, Number 4. (shrink)

Dynamic conceptual reframing represents a crucial mechanism employed by humans, and partially by other animal species, to generate novel knowledge used to solve complex goals. In this talk, I will present a reasoning framework for knowledge invention and creative problem solving exploiting TCL: a non-monotonic extension of a Description Logic (DL) of typicality able to combine prototypical (commonsense) descriptions of concepts in a human-like fashion [1]. The proposed approach has been tested both in the task of goal-driven concept invention [2,3] (...) and has additionally applied within the context of serendipity-based recommendation systems [4]. I will present the obtained results, the lessons learned, and the road ahead of this research path. -/- . (shrink)

Inventing novel knowledge to solve problems is a crucial, creative, mechanism employed by humans, to extend their range of action. In this talk, I will show how commonsense reasoning plays a crucial role in this respect. In particular, I will present a cognitively inspired reasoning framework for knowledge invention and creative problem solving exploiting TCL: a non-monotonic extension of a Description Logic (DL) of typicality able to combine prototypical (commonsense) descriptions of concepts in a human-like fashion. The proposed approach has (...) been tested both in the task of goal-driven concept invention and has additionally applied within the context of serendipity-based recommendation systems. I will present the obtained results, the lessons learned, and the road ahead of this research path. (shrink)

In recent years, the gastronomy industry has increased the demand for rigorous and reliable tools to evaluate culinary creativity; but conceptually, creativity is difficult to define and even more difficult to measure. In this paper, we propose an AI-based method for assessing culinary product creativity by using the renowned high cuisine restaurant elBulli as a case study to understand the proliferation and scale of an entity’s creativity and innovation. To achieve so, we trained a Random Forest (...) Classifier to assess the level of creativity within the restaurant’s recipes. The application of this model to elBulli’s recipes allowed us to answer the following questions: how can creativity in a culinary product be characterized? Is there a single trait that is the key to culinary creativity? Is the creative culinary product a truly original outcome? Our key findings are (1) although ingredients and preparation techniques prove to be suitable attributes to characterize creativity in a recipe, none of them nor an elite subset clearly identifies creative cuisine, (2) new products are not radically novel with respect to previous creations, (3) creativity is more related to new uses and combinations of existing ingredients and techniques rather than to new ingredients or techniques. We believe that our method can find practical applications in supporting and guiding the creation of culinary products, identifying their strengths and weaknesses, and helping restaurants maintain a sustainable competitive advantage. (shrink)

We link Ivancovsky et al.'s novelty-seeking model (NSM) to computational models of intrinsically motivated behavior and learning. We argue that dissociating different forms of curiosity, creativity, and memory based on the involvement of distinct intrinsic motivations (e.g., surprise and novelty) is essential to empirically test the conceptual claims of the NSM.

To make the interface design of computer application system better, meet the psychological and emotional needs of users, and be more humanized, the emotional factor is increasingly valued by interface designers. In the design of human-computer interaction graphical interfaces, the designer attaches great importance to the emotional design of the interface, and enhances the humanized design of the interface, which cannot only improve the comfort of the interface, but also improve the fun of the interface, to ensure the psychological and (...) emotional needs of users can be better satisfied. It may acquire information that is favorable to innovative design by utilizing cluster analysis algorithm to tackle the problem of complicated cultural information, and then utilize cellular genetic algorithm to carry out creative design of cultural items. It increases the availability of cultural and creative goods. The classic cluster analysis technique offers the maximum data clustering effect of 53.3%, according to the findings of this paper’s experiments. While the improved cluster analysis algorithm has the highest data clustering effect of 90%. It can be seen that the improved cluster analysis algorithm can effectively perform cluster analysis on a large amount of data in cultural and creative products. It thus finds out the most suitable designer’s creative information, which helps designers create better products. (shrink)

Scientific discovery is often regarded as romantic and creative - and hence unanalyzable - whereas the everyday process of verifying discoveries is sober and more suited to analysis. Yet this fascinating exploration of how scientific work proceeds argues that however sudden the moment of discovery may seem, the discovery process can be described and modeled. Using the methods and concepts of contemporary information-processing psychology (or cognitive science) the authors develop a series of artificial-intelligence programs that can simulate the human thought (...) processes used to discover scientific laws. The programs - BACON, DALTON, GLAUBER, and STAHL - are all largely data-driven, that is, when presented with series of chemical or physical measurements they search for uniformities and linking elements, generating and checking hypotheses and creating new concepts as they go along. "Scientific Discovery examines the nature of scientific research and reviews the arguments for and against a normative theory of discovery; describes the evolution of the BACON programs, which discover quantitative empirical laws and invent new concepts; presents programs that discover laws in qualitative and quantitative data; and ties the results together, suggesting how a combined and extended program might find research problems, invent new instruments, and invent appropriate problem representations. Numerous prominent historical examples of discoveries from physics and chemistry are used as tests for the programs and anchor the discussion concretely in the history of science. Pat Langley is an Associate Professor in the Department of Information and Computer Science at the University of California, Irvine.Herbert Simon is a Professor in the Departments of Psychology, Computer Science, and Philosophy at Carnegie-Mellon University. Gary L. Bradshaw is an Assistant Professor in the Department of Psychology and Institute of Cognitive Science at the University of Colorado, Boulder. Jan M. Zytkow is an Associate Professor in the Computer Science Department at Wichita State University. (shrink)

In a historical perspective, what is novel about computer games is that they are not pure games but cultural objects which allow the playful desires identified by Caillois to be fused with craftsmanship, the desire to do a job well for its own sake (Sennett). Play is often defined in opposition to work, for example by Huizinga and Caillois, but craftsmanship has two qualities which can be found in both. Firstly, craftsmanship entails creative attention to the material at hand pleasurably (...) and patiently built up through rehearsal (cf. Sennett on “material consciousness”)—“creative” is used in a sense read from Bergson which is almost synonymous with “possibility-widening”. Secondly, craftsmanship entails the satisfaction of seeing the end result of one's labours. Both qualities are essential to human well-being (Marx, Sennett, Smith). (shrink)

This paper questions the notion of creativity found in certain artworks produced with A.I. technologies. The artistic examples concerned are: The Giver of names by David Rokeby, Oscar by Catherine Ikam and Louis Fléri, and Emotion Vending Machine by Maurice Benayoun. These artworks were selected because they stand out for their autonomous behavior in front of the human public. In this context, creativity is revealed as a consequence of the functional autonomy, which is very typical of these pieces (...) of art. The intention is to establish a relationship between the notion of autonomy and that of creativity, reviewing their meanings and applications in philosophy and in the field of life science. (shrink)

Computer science only became established as a field in the 1950s, growing out of theoretical and practical research begun in the previous two decades. The field has exhibited immense creativity, ranging from innovative hardware such as the early mainframes to software breakthroughs such as programming languages and the Internet. Martin Gardner worried that "it would be a sad day if human beings, adjusting to the Computer Revolution, became so intellectually lazy that they lost their power of creative thinking" (Gardner, (...) 1978, p. vi-viii). On the contrary, computers and the theory of computation have provided great opportunities for creative work. This chapter examines several key aspects of creativity in computer science, beginning with the question of how problems arise in computer science. We then discuss the use of analogies in solving key problems in the history of computer science. Our discussion in these sections is based on historical examples, but the following sections discuss the nature of creativity using information from a contemporary source, a set of interviews with practicing computer scientists collected by the Association of Computing Machinery’s on-line student magazine, Crossroads. We then provide a general comparison of creativity in computer science and in the natural sciences. (shrink)

Biological evolution provides a creative fount of complex and subtle adaptations, often surprising the scientists who discover them. However, because evolution is an algorithmic process that transcends the substrate in which it occurs, evolution’s creativity is not limited to nature. Indeed, many researchers in the field of digital evolution have observed their evolving algorithms and organisms subverting their intentions, exposing unrecognized bugs in their code, producing unexpected adaptations, or exhibiting outcomes uncannily convergent with ones in nature. Such stories routinely (...) reveal creativity by evolution in these digital worlds, but they rarely fit into the standard scientific narrative. Instead they are often treated as mere obstacles to be overcome, rather than results that warrant study in their own right. The stories themselves are traded among researchers through oral tradition, but that mode of information transmission is inefficient and prone to error and outright loss. Moreover, the fact that these stories tend to be shared only among practitioners means that many natural scientists do not realize how interesting and lifelike digital organisms are and how natural their evolution can be. To our knowledge, no collection of such anecdotes has been published before. This paper is the crowd-sourced product of researchers in the fields of artificial life and evolutionary computation who have provided first-hand accounts of such cases. It thus serves as a written, fact-checked collection of scientifically important and even entertaining stories. In doing so we also present here substantial evidence that the existence and importance of evolutionary surprises extends beyond the natural world, and may indeed be a universal property of all complex evolving systems. (shrink)

Ever since 1956 when details of the Logic Theorist were published by Newell and Simon, a large literature has accumulated on computational models and theories of the creative process, especially in science, invention and design. But what exactly do these computational models/theories tell us about the way that humans have actually conducted acts of creation in the past? What light has computation shed on our understanding of the creative process? Addressing these questions, we put forth three propositions: (I) (...) Computational models of the creative process are fundamentally flawed as theories of human creativity. Rather, the universal power of computational models lies elsewhere: (II) Computational models of particular acts of creation can serve as effective experiments to test universal hypotheses about creative processes and mechanisms; and (III) Computation-based architectures of the creative mind provide metaphorical frameworks that, like all good metaphors, can serve as rich sources of insight into aspects of the creative process. In this paper, we provide evidence for these three propositions by drawing upon some particular episodes in the cognitive history of science, technology, and art. (shrink)

This entry provides a substantive overview of research and debates concerning creativity in philosophy and related fields. Topics covered include definitions of creativity, whether creativity can be learned, whether it can be explained, attempts to explain creativity in cognitive science, and whether computer programs or AI systems can be creative.

CHAMELEON is a computational melodic harmonization assistant. It can harmonize a given melody according to a number of independent harmonic idioms or blends between idioms based on principles of conceptual blending theory. Thus, the system is capable of offering a wealth of possible solutions and viewpoints for melodic harmonization. This study investigates how human creativity may be influenced by the use of CHAMELEON in a melodic harmonization task. Professional and novice music composers participated in an experiment where they (...) were asked to harmonize two similar melodies under two different conditions: one with and one without computational support. A control group harmonized both melodies without computational assistance. The influence of the system was examined both behaviorally, by comparing metrics of user-experience, and in terms of the properties of the artifacts that were created between the two experimental conditions. Results suggest that appreciation of the system was expertise-dependent. At the same time, users seemed to adopt more explorative strategies as a result of interaction with CHAMELEON based on the fact that the harmonizations created this way were more complex, diverse, and unexpected in comparison to the ones of the control group. (shrink)

This paper proposes a deep analysis of the latest research of digital humanities scholar Beatrice Fazi, and especially her critique of computational automation, to understand the roles of digital creative technologies, and more specifically of creative software. After a close analysis of Fazi’s main contribution to a new understanding of computational aesthetics, we will briefly outline the potential implications of her work to understand the contemporary evolution of creative software, and especially the implementation of machine learning algorithms in (...) these kinds of software. This will lead us to contextualise the contemporary anxieties regarding how machines could replace humans in the act of artistic creation. (shrink)

Over recent decades there has been a growing interest in the question of whether computer programs are capable of genuinely creative activity. Although this notion can be explored as a purely philosophical debate, an alternative perspective is to consider what aspects of the behaviour of a program might be noted or measured in order to arrive at an empirically supported judgement that creativity has occurred. We sketch out, in general abstract terms, what goes on when a potentially creative program (...) is constructed and run, and list some of the relationships (for example, between input and output) which might contribute to a decision about creativity. Specifically, we list a number of criteria which might indicate interesting properties of a program’s behaviour, from the perspective of possible creativity. We go on to review some ways in which these criteria have been applied to actual implementations, and some possible improvements to this way of assessing creativity. (shrink)

Creativity is the hallmark of human cognition, yet scientific understanding of creative processes is limited. However, there is increasing interest in revealing the neural correlates of human creativity. Though many of these studies, pioneering in nature, help demystification of creativity, but the field is still dominated by popular beliefs in associating creativity with "right brain thinking", "divergent thinking", "altered states" and so on (Dietrich and Kanso, 2010). In this article, we discuss a computational framework for (...) creativity based on Baars' global workspace theory (Baars, 1988) enhanced with mechanisms based on information theory. Next we propose a neurocognitive architecture of creativity with a strong focus on various facets (i.e., unconscious thought theory, mind wandering, spontaneous brain states) of un/pre-conscious brain responses. Our principal argument is that pre-conscious creativity happens prior to conscious creativity happens prior to conscious creativity and the proposed computational model may provide a mechanism by which this transition is managed. This integrative approach, albeit unconventional, will hopefully stimulate future neuroscientific studies of the inscrutable phenomenon of creativity. (shrink)

We propose expanding the authors’ shared novelty-seeking basis for creativity and curiosity by emphasizing an underlying computational principle: Minimizing prediction errors (mismatch between predictions and incoming data). Curiosity is tied to the anticipation of minimizing prediction errors through future, novel information, whereas creative AHA moments are connected to the actual minimization of prediction errors through current, novel information.

This paper explores the intersection of art history and AI technology. Special attention is paid to Generative Adversarial Networks (GANs), a machine learning technology widely used in AI art. This technology is particularly interesting to art history and the philosophy of art because it raises enduring questions about the creative process of artmaking, especially what constitutes a new and original work of art. While this is a relatively new area, it is possible to discern emerging directions where art and AI (...) intersect. One pressing issue concerns the use (or misuse) of algorithmically enabled technologies and datasets to perpetuate longstanding art-historical biases. The critical position adopted in this paper shares this concern. I examine a notable example of GAN technology that claims to create original art styles. While such experiments in computational creativity are technically interesting, their artistic aims can be questionable. I argue a mechanical model of artistic development based solely on the autonomy of style is problematic for at least two reasons: 1) it uncritically reinstates a formalist view of art history; 2) it recreates a narrow style-centric ‘historical modernism.’ However, despite voicing these reservations, I also discuss the potential of this technology to engage with topics of critical relevance to art history and the philosophy of art. (shrink)

Goswami proposes to replace the current scientific paradigm of physical realism with that of a quantum-based monistic idealism and, in the process, accomplish the following goals: establish a basis for explaining consciousness, reintegrate spirituality, mysticism, morality, a sense that the universe is meaningful, etc., with scientific discoveries and the scientific enterprise, and support the assumption that humans possess free will - i.e., that they are not controlled by the apparently inexorable causality of the physical laws that govern the functioning of (...) their brains. Here, we critically examine this approach, from an artificial intelligence and neural network perspective, and point out what appear to be some inherent weaknesses in Goswami's arguments. (shrink)

: Creativity, mostly ignored in Western philosophy due to its supposed mysteriousness, has recently become a respected research topic in psychology, neuroscience, and artificial intelligence. We discuss how in science the approach has mainly been to describe creativity as an information-based process, coherently with a computational view of the human mind started with the cognitive revolution. This view has produced progressively convincing models of creativity, up to current artificial neural network systems, vaguely inspired by biological neural (...) processing, but already competing with human creativity in several fields. These successes suggest that creativity might not be an exclusively human function, but actually a way of functioning of any natural or artificial system implementing the creative process. We conclude by acknowledging that the information-based view of creativity has tremendous explanatory and generative power, but we propose a thought experiment to start discussing how it actually leaves out the experiential side of being creative. Keywords: Creative Cognition; Cognitive Neuroscience; Computational Creativity; Generative Algorithms; Cognitive Science La creatività come processo basato sull’informazione Riassunto: La creatività, spesso ignorata dalla filosofia occidentale per la sua presunta oscurità, in tempi recenti è diventata un rispettabile oggetto di ricerca per la psicologia, la neuroscienza e l’intelligenza artificiale. Vogliamo illustrare il modo in cui lo sguardo scientifico sia rivolto prevalentemente a considerare la creatività come processo information-based, coerentemente con la prospettiva computazionale sulla mente umana aperta dalla rivoluzione cognitiva. Questa prospettiva ha prodotto modelli della creatività sempre più convincenti, fino agli attuali sistemi di reti neurali artificiali, vagamente inspirati al processamento biologico neurale, ma già competitivi rispetto alla creatività umana in molti ambiti. Questi successi suggeriscono che la creatività possa non essere una funzione esclusivamente umana ma in effetti un modo di funzionare di un sistema naturale o artificiale capace di implementare il processo creativo. In conclusione, pur riconoscendo come il considerare la creatività come processo information-based possieda grande potere esplicativo e generativo, proporremo un esperimento mentale per aprire una discussione sul come questa prospettiva non copra in effetti il lato esperienziale dell’essere creativo. Parole chiave: Cognizione creativa; Neuroscienza cognitiva; Creatività computazionale; Algoritmi generativi; Scienza cognitiva. (shrink)

In this essay we collect and put together a number of ideas relevant to the under- standing of the phenomenon of creativity, confining our considerations mostly to the domain of cognitive psychology while we will, on a few occasions, hint at neuropsy- chological underpinnings as well. In this, we will mostly focus on creativity in science, since creativity in other domains of human endeavor have common links with scientific creativity while differing in numerous other specific respects. (...) We begin by briefly introducing a few basic notions relating to cognition, among which the notion of ‘concepts’ is of basic relevance. The myriads of concepts lodged in our mind constitute a ‘conceptual space’ of an enormously complex structure, where con- cepts are correlated by beliefs that are themselves made up of concepts and are as- sociated with emotions. The conceptual space, moreover, is perpetually in a state of dynamic evolution that is once again of a complex nature. A major component of the dynamic evolution is made up of incessant acts of inference, where an inference occurs essentially by means of a succession of correlations among concepts set up with beliefs and heuristics, the latter being beliefs of a special kind, namely, ones relatively free of emotional associations and possessed of a relatively greater degree of justification. Beliefs, along with heuristics, have been described as the ‘mind’s software’, and con- stitute important cognitive components of the self-linked psychological resources of an individual. The self is the psychological engine driving all our mental and physical activity, and is in a state of ceaseless dynamics resulting from one’s most intimate ex- periences of the world accumulating in the course of one’s journey through life. Many of our psychological resources are of a dual character, having both a self-linked and a shared character, the latter being held in common with larger groups of people and imbibed from cultural inputs. We focus on the privately held self-linked beliefs of an individual, since these are presumably of central relevance in making possible inductive inferences – ones in which there arises a fundamental need of adopting a choice or making a decision. Beliefs, decisions, and inferences, all have the common link to the self of an individual and, in this, are fundamentally analogous to free will, where all of these have an aspect of non-determinism inherent in them. Creativity involves a major restructuring of the conceptual space where a sustained inferential process eventually links remote conceptual domains, thereby opening up the possibility of a large number of new correlations between remote concepts by a cascading process. Since the process of inductive inference depends crucially on de- cisions at critical junctures of the inferential chain, it becomes necessary to examine the basic mechanism underlying the making of decisions. In the framework that we attempt to build up for the understanding of scientific creativity, this role of decision making in the inferential process assumes central relevance. With this background in place, we briefly sketch the affect theory of decisions. Affect is an innate system of response to perceptual inputs received either from the exter- nal world or from the internal physiological and psychological environment whereby a positive or negative valence gets associated with a perceptual input. Almost every sit- uation faced by an individual, even one experienced tacitly, i.e., without overt aware-ness, elicits an affective response from him, carrying a positive or negative valence that underlies all sorts of decision making, including ones carried out unconsciously in inferential processes. Referring to the process of inferential exploration of the conceptual space that gener- ates the possibility of correlations being established between remote conceptual do- mains, such exploration is guided and steered at every stage by the affect system, analogous to the way a complex computer program proceeds through junctures where the program ascertains whether specified conditions are met with by way of generating appropriate numerical values – for instance, the program takes different routes, depending on whether some particular numerical value turns out to be positive or negative. The valence generated by the affect system in the process of adoption of a choice plays a similar role which therefore is of crucial relevance in inferential processes, especially in the exploration of the conceptual space where remote domains need to be linked up – the affect system produces a response along a single value dimension, resembling a number with a sign and a magnitude. While the affect system plays a guiding role in the exploration of the conceptual space, the process of exploration itself consists of the establishment of correlations between concepts by means of beliefs and heuristics, the self-linked ones among the latter having a special role in making possible the inferential journey along alternative routes whenever the shared rules of inference become inadequate. A successful access to a remote conceptual domain, necessary for the creative solution of a standing problem or anomaly – one that could not be solved within the limited domain hitherto accessed – requires a phase of relatively slow cumulative search and then, at some stage, a rapid cascading process when a solution is in sight. Representing the conceptual space in the form of a complex network, the overall process can be likened to one of self-organized criticality commonly observed in the dynamical evolution of complex systems. In order that inferential access to remote domains may actually be possible, it is necessary that restrictions on the exploration process – necessary for setting the context in ordinary instances of inductive inference – be relaxed and a relatively free exploration in a larger conceptual terrain be made possible. This is achieved by the mind going into the default mode, where external constraints – ones imposed by shared beliefs and modes of exploration – are made inoperative. While explaining all these various aspects of the creative process, we underline the supremely important role that analogy plays in it. Broadly speaking, analogy is in the nature of a heuristic, establishing correlations between concepts. However, analo- gies are very special in that these are particularly effective in establishing correlations among remote concepts, since analogy works without regard to the contiguity of the concepts in the conceptual space. In establishing links between concepts, analogies have the power to light up entire terrains in the conceptual space when a rapid cas- cading of fresh correlations becomes possible. The creative process occurs within the mind of a single individual or of a few closely collaborating individuals, but is then continued by an entire epistemic community, eventually resulting in a conceptual revolution. Such conceptual revolutions make pos- sible the radical revision of scientific theories whereby the scope of an extant theory is broadened and a new theoretical framework makes its appearance. The emerging theory is characterized by a certain degree of incommensurability when compared with the earlier one – a feature that may appear strange at first sight. But incommen- surability does not mean incompatibility and the apparently contrary features of the relation between the successive theories may be traced to the multi-layered structureof the conceptual space where concepts are correlated not by means of single links but by multiple ones, thereby generating multiple layers of correlation, among which some are retained and some created afresh in a conceptual restructuring. We conclude with the observation that creativity occurs on all scales. Analogous to correlations being set up across domains in the conceptual space and new domains being generated, processes with similar features can occur within the confines of a domain where a new layer of inferential links may be generated, connecting up sub- domains. In this context, insight can be looked upon as an instance of creativity within the confines of a domain of a relatively limited extent. (shrink)

Human creativity generates novel ideas to solve real-world problems. This thereby grants us the power to transform the surrounding world and extend our human attributes beyond what is currently possible. Creative ideas are not just new and unexpected, but are also successful in providing solutions that are useful, efficient and valuable. Thus, creativity optimizes the use of available resources and increases wealth. The origin of human creativity, however, is poorly understood, and semantic measures that could predict the (...) success of generated ideas are currently unknown. Here, we analyze a dataset of design problem-solving conversations in real-world settings by using 49 semantic measures based on WordNet 3.1 and demonstrate that a divergence of semantic similarity, an increased information content, and a decreased polysemy predict the success of generated ideas. The first feedback from clients also enhances information content and leads to a divergence of successful ideas in creative problem solving. These results advance cognitive science by identifying real-world processes in human problem solving that are relevant to the success of produced solutions and provide tools for real-time monitoring of problem solving, student training and skill acquisition. A selected subset of information content (IC Sánchez–Batet) and semantic similarity (Lin/Sánchez–Batet) measures, which are both statistically powerful and computationally fast, could support the development of technologies for computer-assisted enhancements of human creativity or for the implementation of creativity in machines endowed with general artificial intelligence. (shrink)

The ultimate focus of the current essay is on methods of “creative abduction” that have some guarantees as reliable guides to the truth, and those that do not. Emphasizing work by Richard Englehart using data from the World Values Survey, Gerhard Schurz has analyzed literature surrounding Samuel Huntington’s well-known claims that civilization is divided into eight contending traditions, some of which resist “modernization” – democracy, civil rights, equality of rights of women and minorities, secularism. Schurz suggests an evolutionary model of (...) modernization and identifies opposing social forces. In a later essay, citing Englehart’s work as an example, Schurz identifies factor analysis as an example of “creative abduction”. The theories of Englehart and his collaborators are reviewed again in the current essay. Published simulations and standard statistical desiderata for causal inference show the methods Englehart used, factor analysis in particular, are not guides to truth for the kind of data Schurz recognizes as common in political science. Recent work in statistics, philosophy and computer science that makes advances towards such methods is briefly reviewed. (shrink)

Storytelling is a pervasive part of our daily lives and culture. The task of creating stories for the purposes of entertaining, educating, and training has traditionally been the purview of humans. This sets up the conditions for a creative authoring bottleneck where the consumption of stories outpaces the production of stories by human professional creators. The automation of story creation may scale up the ability to produce and deliver novel, meaningful story artifacts. From this practical perspective, story generation systems replicate (...) the creative abilities of humans and can thus be considered instances of computational creativity. Computational systems that are purported to be creative typically utilize one of three general approaches: exploration of a space of concepts, combination of concepts, and transformation of concepts. In this article we present an approach to story generation that utilize exploration, combination, and transformation. Our approach, implemented in the Vignette Based Partial Order Causal Link story planner, is an algorithm that searches through a space of possible story solutions, guided by combinations of existing story fragments called vignettes. The vignettes are made relevant to novel story generation contexts through an automated transformation pre-process. Through these processes, we show that story generation can incorporate multiple perspectives on computational creativity. Our approach is presented at both the theoretical and technical levels. (shrink)

The paper explores the creative thinking process and throws light on creativity enhancement. From the perspective of possible creativity enhancement both the characteristics of creativity and the creative thinking process are discussed, together with an analysis of the process and its common factors. Constraints on innovation (as a special type of creativity), innovation management and the acceptance of change are discussed; creativity between cooperating individuals is also examined. Some possible computer-based tools to enhance creativity, (...) including innovation, are discussed. A framework of facilities to help promote and support the use of creativity enhancement techniques and tools (SOLI) is proposed. The paper is the result of a study undertaken by the author into creativity, innovation and cooperation. (shrink)

The Turing Test is claimed by many to be a way to test for the presence, in computers, of such ``deep'' phenomena as thought and consciousness. Unfortunately, attempts to build computational systems able to pass TT have devolved into shallow symbol manipulation designed to, by hook or by crook, trick. The human creators of such systems know all too well that they have merely tried to fool those people who interact with their systems into believing that these systems really (...) have minds. And the problem is fundamental: the structure of the TT is such as to cultivate tricksters. A better test is one that insists on a certain restrictive epistemic relation between an artificial agent A, its output o, and the human architect H of A – a relation which, roughly speaking, obtains when H cannot account for how A produced o. We call this test the ``Lovelace Test'' in honor of Lady Lovelace, who believed that only when computers originate things should they be believed to have minds. (shrink)

In scientific communications, journal articles, and philosophical aesthetic debates the words “art”, “creativity”, and “machine” are put together more and more frequently. Since some machines are designed to, or happens to, imitate human artistic creativity, it seems natural to use the same words to talk about human artists and machines which imitate them. However, the evolution of language in light of technology may conceal specific features of the phenomena it is supposed to describe. This makes it difficult to (...) understand what machine creativity actually is and how it is connected to human creativity. The aim of the paper is to investigate why, and in what sense, the functioning of some machines may be described in terms of artistic creativity and what is the relation between machine creativity and its human archetype. I start (§1) by introducing some general ideas concerning how language evolves alongside new technologies and focusing on the case of machine creativity. In §2 I review how some creative machines have been presented to the public, thus showing that a linguistic habit which connects machines to artistic creativity has already formed. In §3 I survey the debate on machine aesthetics and I highlight the main traits of the issue. In §4 I submit a primary scheme of machine creativity which draws on the concept of functional autonomy. Finally (§5), I argue that machine creativity cannot be mistaken for a substitute of the human kind, despite the fact that the word is the same. Creative machines are technological mediums by which new forms of human aesthetic experience can be explored. The kind of creativity machines enjoy displays a functional nature. (shrink)

How is it possible to think new thoughts? What is creativity and can science explain it? And just how did Coleridge dream up the creatures of The Ancient Mariner? When The Creative Mind: Myths and Mechanisms was first published, Margaret A. Boden's bold and provocative exploration of creativity broke new ground. Boden uses examples such as jazz improvisation, chess, story writing, physics, and the music of Mozart, together with computing models from the field of artificial intelligence to uncover (...) the nature of human creativity in the arts. The second edition of The Creative Mind has been updated to include recent developments in artificial intelligence, with a new preface, introduction and conclusion by the author. It is an essential work for anyone interested in the creativity of the human mind. (shrink)

Creativity pervades human life. It is the mark of individuality, the vehicle of self-expression, and the engine of progress in every human endeavor. It also raises a wealth of neglected and yet evocative philosophical questions: What is the role of consciousness in the creative process? How does the audience for a work for art influence its creation? How can creativity emerge through childhood pretending? Do great works of literature give us insight into human nature? Can a computer program (...) really be creative? How do we define creativity in the first place? Is it a virtue? What is the difference between creativity in science and art? Can creativity be taught? The new essays that comprise The Philosophy of Creativity take up these and other key questions and, in doing so, illustrate the value of interdisciplinary exchange. Written by leading philosophers and psychologists involved in studying creativity, the essays integrate philosophical insights with empirical research. CONTENTS I. Introduction Introducing The Philosophy of Creativity Elliot Samuel Paul and Scott Barry Kaufman II. The Concept of Creativity 1. An Experiential Account of Creativity Bence Nanay III. Aesthetics & Philosophy of Art 2. Creativity and Insight Gregory Currie 3. The Creative Audience: Some Ways in which Readers, Viewers and/or Listeners Use their Imaginations to Engage Fictional Artworks Noël Carroll 4. The Products of Musical Creativity Christopher Peacocke IV. Ethics & Value Theory 5. Performing Oneself Owen Flanagan 6. Creativity as a Virtue of Character Matthew Kieran V. Philosophy of Mind & Cognitive Science 7. Creativity and Not So Dumb Luck Simon Blackburn 8. The Role of Imagination in Creativity Dustin Stokes 9. Creativity, Consciousness, and Free Will: Evidence from Psychology Experiments Roy F. Baumeister, Brandon J. Schmeichel, and C. Nathan DeWall 10. The Origins of Creativity Elizabeth Picciuto and Peter Carruthers 11. Creativity and Artificial Intelligence: a Contradiction in Terms? Margaret Boden VI. Philosophy of Science 12. Hierarchies of Creative Domains: Disciplinary Constraints on Blind-Variation and Selective-Retention Dean Keith Simonton VII. Philosophy of Education (& Education of Philosophy) 13. Educating for Creativity Berys Gaut 14. Philosophical Heuristics Alan Hájek. (shrink)

The greatest rhetorical challenge to developers of creative artificial intelligence systems is convincingly arguing that their software is more than just an extension of their own creativity. This paper suggests that “creative autonomy,” which exists when a system not only evaluates creations on its own, but also changes its standards without explicit direction, is a necessary condition for making this argument. Rather than requiring that the system be hermetically sealed to avoid perceptions of human influence, developing creative autonomy is (...) argued to be more plausible if the system is intimately embedded in a broader society of other creators and critics. Ideas are presented for constructing systems that might be able to achieve creative autonomy. (shrink)

Paradoxes are an unavoidable part of work life. The unusualness of attempting to simultaneously satisfy contradictory imperatives can result in creative outcomes that simultaneously satisfy both imperatives by inducing search for, and selection of, novel and useful solutions. Likewise, extant research suggests that paradoxes can also result in anxiety, defensiveness, and persistence of old ways of doing things. However, there is little work attempting to describe how paradoxes affect cognition and when it results in higher or lower creativity. To (...) tackle this issue, a theory of paradoxical creativity is developed. Paradoxical creativity is the attempt by an individual to creatively resolve a contradiction by simultaneously achieving competing demands. The theory is implemented into a computational model and a simulation is used to describe how paradoxes affect creative cognitive process and how these processes in turn result in higher or lower degrees of creativity. The results show that creative output is enhanced when paradoxes have a balanced effect on the cognitive processes responsible for an individual’s capacity to search for new information and willingness to tolerate new ideas. Hence, individuals with high baseline levels of creative cognition are more likely to suffer negative creative performance consequences resulting from contradictory demands. For those individuals, contradictory demands may produce more alternatives, which increases uncertainty and time to insight (if insight is ever reached). This suggests that incentives or rewards to resolve contradictions may have the unintentional effect of reducing creative output in some circumstance. (shrink)

We argue that creative ideas are potentially valuable improbable constructions. We arrive at this formulation of creativity after considering several problems that arise for the theories that suggest that creativity is novelty, originality, or usefulness. Our theory avoids these problems. But since we also derive our theory of creativity from the scientific commitments of a more general theory of cognitive development, a theory called rational constructivism, our theory is unique insofar as it explains creativity in both (...) adults and children through reference to a set of computational mechanisms that have been posited on the basis of independently plausible experimental research. (shrink)

In this paper we propose a computational framework aimed at extending the problem solving capabilities of cognitive artificial agents through the introduction of a novel, goal-directed, dynamic knowledge generation mechanism obtained via a non monotonic reasoning procedure. In particular, the proposed framework relies on the assumption that certain classes of problems cannot be solved by simply learning or injecting new external knowledge in the declarative memory of a cognitive artificial agent but, on the other hand, require a mechanism for (...) the automatic and creative re-framing, or re-formulation, of the available knowledge. We show how such mechanism can be obtained trough a framework of dynamic knowledge generation that is able to tackle the problem of commonsense concept combination. In addition, we show how such a framework can be employed in the field of cognitive architectures in order to overcome situations like the impasse in SOAR by extending the possible options of its subgoaling procedures. (shrink)