Creativity happens through our engagement with context. This context consists of our experiences, culture, knowledge, and the social and natural worlds. Navigating context, imagining new ways to use it, identifying puzzles and creative opportunities, discovering possibilities, and spanning it to create novel connections: these are the keys to successful creativity.
A key characteristic of the context in which creativity happens is that it is extremely rich and diverse, filled with a multitude of elements and almost unlimited possibilities. It is large scale. This has been true in human cultural contexts for centuries, even millennia, but is even more true today with the emergence of the Internet and access to information increasing dramatically.
The large-scale nature of context offers rich opportunities. But it also poses a great challenge: with so many options, it is simply not possible to consider them all. The range of options can be overwhelming, making it difficult to know how best to proceed. A writer facing a blank page, an artist facing a blank canvas, an engineer contemplating the design of a new product: the possibilities are nearly limitless. Even in the world of AI creativity, this issue is paramount. What makes this a great challenge is that, among the myriad possibilities, very few will lead to a highly successful creative outcome if pursued. Most will fail outright; others will lead to an outcome that is not perceived as successful by whatever standard success is measured. The question is, out of the myriad possibilities, how is it possible to discover an especially promising one that will lead to a highly successful creative outcome? This critical question, which we must address to understand the nature of the creative process in large-scale contexts, doesn’t arise in small-scale contexts. In a small-scale context all creative possibilities can be explored, but in a large-scale context the huge number of elements makes this impossible.
Creativity research and popular accounts of creativity have failed to recognize that creativity happens in rich large-scale contexts and the challenge this poses; not surprisingly given this failure, they have not addressed the question of how to go about engaging in creative endeavors in large-scale contexts. Creativity is often described as something that “comes from within”—language that leaves context out entirely. When context is considered, it is typically described as if it contains only a handful of elements. This paints a false picture of context as small scale, and because the challenge of navigating through a large-scale context is missing, creativity can seem like a relatively easy, straightforward process: if the world contains just a handful of elements, all the different possibilities and combinations can be investigated, and highly creative ones will readily be identified. In the creativity literature attention is often focused on a single creative act, such as an elegant solution to a puzzle or a novel combination that produces an innovative new product. What is truly amazing, however—and is typically missing from these descriptions—is how such creative steps come to be taken among the myriad possibilities available: the remarkable process that leads to them. The failure to recognize that context is large, filled with opportunities but also posing a great challenge due to its sheer scale, limits understanding. Thus to attain a more complete understanding of creativity we must better understand how to navigate and explore large-scale contexts.
In this book I take on this challenge and address the question of how to be successful engaging in a creative endeavor in a large-scale context. The single most important part of the creative process that stands out as new in my description is guidance. Large-scale contexts are rich with possibilities but also for that very reason difficult to navigate and easy to get lost in. In this situation it is clear that guidance of some kind is required. Guidance not in the sense of knowing the exact creative endpoint, but in the sense of having an idea about where one should look and which kinds of opportunities and creative paths to pursue among the myriad possibilities. Trying possibilities simply at random is woefully inefficient and unlikely to lead to success in any reasonable timeframe—a basic truth despite the fact that the random combination model has been quite popular in the creativity field. The alternative is guidance. I describe two kinds of guidance and present a framework that shows how they are used jointly to guide the creative process in large-scale contexts, enabling individuals to find their way to successful creative outcomes.
What makes guidance possible is that creativity contexts, although large scale, have structure. This structure arises because the context that is relevant for creativity is the world as we perceive and understand it (including the ways we recognize we are failing to understand it). Of course it is true that we make discoveries in the world around us and create using tangible materials. But these discoveries and creations, and creative ideas in general, arise out of our engagement with the world in terms of perceptions and frames of understanding. This perception and understanding of the world—our context—is based on our experiences, what we learn, our social and cultural environment, and the natural world, yet it goes beyond this “raw material” in that it is organized by us. Our context is thus our conceptual representation and organization of the world, and this is what drives our creative choices, ideas, and activities: we imagine new possibilities and see creative opportunities based on this conceptual representation and organization. Of course a representation that is missing important elements or biased can hold back creative insight. Yet this actually shows its importance, for finding our way through a limited or incorrect understanding and representation is itself part of the creative process.
Structurally, context is organized as a network. In particular, the elements of our context do not exist in isolation but are connected to other elements that they are related to in our representation of the world. The most important feature of this network is that it has a hierarchical structure: broader, more abstract elements or concepts link downward to more specific elements, their “children.” Most of our representations of the world have this hierarchy feature, with information and elements arranged in categories and subcategories. Indeed hierarchy is fundamental to the organization of knowledge, a principle that extends back at least to the ancient Greeks. But there are also additional links, so that context is not a simple hierarchy but rather has a fuller network structure. Most importantly, elements often have more than one parent, and there are lateral links among elements at the same conceptual level. Our organization of context as a network fits with how our brains are organized: brain structures and functions are organized as networks, and it makes sense that our perceptions and conceptual representations, based in the brain, also form a network.1
In this book I adopt a network framework to describe the context in which creativity occurs, consistent with the discussion above. In doing so I model context and its structure more explicitly than has typically been done in the past in creativity. My approach draws on mathematical network modeling and has connections with semantic networks and knowledge representation. The structure I employ for modeling purposes is relatively simple. It is holistic in modeling context as an integrated network. It is also scalable, which is useful for exploring how creative processes may change and evolve as context becomes larger and more complex.
There is a strong connection between context structure and guidance: in particular the hierarchical structure of context provides the basis for guidance. To find one’s way through the thicket of possibilities in a large, rich context is challenging: How can one “see the forest for the trees” and make one’s way successfully? The hierarchical network structure makes this possible. In a large-scale context conceptual vision and some degree of breadth of perspective are reqired in order to determine where to focus and to identify high-potential possibilities. Further, in viewing creativity as essentially forging new connections between elements, a widely accepted definition, more distant connections are often the most creative—thus breadth is important to span the context. Guidance based on higher-level elements in the context hierarchy provides this kind of conceptual breadth and vision, rising above and spanning context, while also penetrating down into the dense network of possibilities via downward links to more specific elements. Thus the hierarchy structure provides a natural basis for guidance.
Guidance is about using broader conceptual thinking in the creative process. My argument is not only that guidance is essential for creative work in large-scale contexts, but that in fact a great deal of creativity happens here, in the development and use of more abstract conceptual structures and processes that are themselves highly creative. The importance of this kind of higher-level conceptual thought is a topic that has been mostly neglected in the creativity field, although there are exceptions—such as Gabora’s notion of a creative worldview, my discussion of creative interests in The Nature of Creative Development, the notion of “creative vision,” and the use of templates and prompts in the emerging field of AI creativity.2 Narrowing one’s focus too soon is not a good approach in a rich context, for one is likely to get lost in details that lead nowhere. This basic point I think has not been appreciated because the richness and sheer enormity of context has not been brought into our worldview of creativity as much as it should have been. Being too broad of course is also not a good idea—it is of little use since it provides little actual guidance. Good guidance, as we shall see, has specificity, and often a good amount of creativity, as well as conceptual breadth and vision.
My purpose in this book is to show that this kind of guidance works. I will demonstrate this theoretically and also through empirical examples. Creators, by employing guidance, find their way, although admittedly frequently with many failures along their journey, ultimately producing successful creative outcomes.
I focus on several different functions guidance has in the creative process. First, it helps individuals navigate in large-scale rich contexts to identify areas rich with creative opportunities and generate seed ideas for projects. Second, it helps individuals decide which seed projects to pursue—for in large-scale rich contexts there are many options. Finally, it is also pivotal in bringing projects to a successful completion once they are underway by helping individuals identify just the right element, the “missing piece” that makes a project come together and work.
The approach I describe, grounded in empirical observation, specifically has two forms of guidance that work in tandem. The first is guiding conceptions, which imagine creative possibilities and opportunities. These conceptions are often highly creative. Virginia Woolf’s conception of a literature that would be based on reflections described in Chapter 8 is a great example. Many important innovations start from these kinds of conceptions: Twitter, for example, started from a guiding conception rooted in Jack Dorsey’s personal history. Guiding conceptions are not the same as “final” creativity, and in that sense are often not recognized for their creativity; but when we examine the creative process more closely, we find that they are the basis for exploration and imaginative thinking that leads to later creative success.
The second, guiding principles, defines principles that individuals desire their creative work to adhere to. Guiding principles rule out “easy” solutions. This was the case for Albert Einstein, for whom the guiding principle of relativity was an important factor motivating and guiding his long search for what became relativity theory—I discuss this in Chapter 12. It was also the case for Steve Jobs, also discussed in Chapter 12, with his aesthetic principle of simplicity in design, who was legendary for his critical eye, pushing his design teams to refine products. Guiding principles are also central for locating critical “missing pieces” that make a project come together successfully.
I believe most successful creators use both kinds of guidance, in different ways and in different stages of their creative process. In fact the two are complementary, as will be very clear in the core two-step model I present. Interestingly, the formal network model also reveals a natural complementarity shown in Chapter 13: guiding principles that lean more toward efficiency pair naturally with guiding conceptions that are associated with larger domains of possibilities, while guiding principles that are highly creative pair naturally with guiding conceptions associated with smaller domains.
Several factors support the conceptual guidance approach. First, it makes logical sense. In a rich large-scale context it is logical that guidance will be required to generate successful creativity. The guidance framework shows how this happens in steps, first with focus that narrows the range of possibilities, and then with acumen and creative reach to successfully complete projects. I demonstrate the logic of the approach with the formal modeling framework.
Second, it is empirically grounded, the approach followed by many successful creators across a wide range of fields. I have developed it based on empirical data drawn from many case studies, including Virginia Woolf, Albert Einstein, Indigenous Australian artist Clifford Possum, biochemist Hans Krebs, Twitter cofounder Jack Dorsey, Steve Jobs, and VLSI designer and transgender activist Lynn Conway, all discussed in this book, as well as many others, some of whom I discuss in brief. The specifics vary—every creative path is unique and every creative contribution has its own unique story—but conceptual guidance is integral to each case study I present, and we learn from each about how conceptual guidance can be developed and used.
Third, the approach makes intuitive sense. This not only supports its validity at face value but also makes it useful as an educational approach to help individuals develop their creativity. Although guidance approaches of the kind I describe are developed intuitively by many successful creators, for many other people understanding the approach may help them learn how to be successful in their creative enterprises. I discuss this throughout the book and also devote Chapter 18 to a discussion of how to use the approach to support individuals in their creative pursuits, drawing on my experience teaching creativity at Yale and presenting the approach in workshops and at conferences. The idea of using guidance to enhance creativity resonates with students and managers because it provides them a constructive way to think about creativity: it provides defined steps to work on to generate creativity—a point that is most clearly made in Chapter 14 where the core two-step creativity model is described and illustrated with examples.
Of course the model in this book simplifies what is inherently a complex process. The conceptual thinking involved in generating creativity can be highly fluid as ideas and complexes of thought emerge, are used and developed, and then may give way to others. Guiding conceptions and principles can be thought of as the more stable and defined part of this conceptual process. I believe and will argue that they provide core guidance, but there may be other less stable conceptual factors and influences also at work in the creative process. I discuss how the framework can be extended to model richer processes, in particular the evolution of guiding conceptions, in Chapters 15 and 16; but this is more in the manner of a sketch, and there are many open issues that hopefully will be explored in future work.
One critique of the approach I take in this book will be that it is excessively “top-down.” I focus on guidance, based on broader conceptual elements and structures, and how this helps guide individuals to creative ideas, projects, and outcomes. “What about the other direction, ‘bottom-up’?” is sure to be one response. The truth is that the standard view in creativity tends mainly to focus on the specifics, thus the “bottom,” tending as a result also to call attention to the “bottom-up” flow. The emphasis is on brilliant creative moments, sudden random discoveries, insights, and connections—generally highly specific acts of creativity that crystalize into great creative contributions, generating revolutions in our ideas and practices, thus percolating up through the conceptual hierarchy. Unconscious processes have often been described as part of this, especially in the earlier literature—for example, by Poincaré in his discussion of the generation of random combinations in the unconscious and by Wallas in his well-known model that includes the stage of incubation followed by illumination.3
In reality both directions—“bottom-up” and “top-down”—are important in the larger cycle of creative development. Further, throughout the creative process there is an ongoing interplay between broader conceptual thinking and specific, more narrowly focused processing, so that movement in both directions is occurring. Specific experiences and elements trigger broader conceptual thinking, which in turn guides creative activity, in turn leading to a dive back down into specific possibilities, which can trigger another round of the creative cycle. One example of the interplay is response to failure. Failure itself normally occurs on the level of specifics, like a project whose elements don’t quite work together. But even so, it is by means of conceptual guidance, in particular guiding principles, that individuals evaluate a failure, understand why it has occurred, and identify ways to revise a project, in particular new elements to try, a step that can be highly creative.
The principle that creativity involves dual conceptual processing modes is assuredly not new. Most famously, the creative process has been described as an interplay between divergent and convergent thinking. The dual processes of my model are different, spanning conceptual levels and integrated with the description of context. This larger dual process is fascinating and can, I believe, be modeled building upon the framework I present; see my discussion in Chapters 15 and 16. But for the most part this discussion is beyond the confines of this book and must be left to the future.
Overall, in relation to the larger creative cycle, with processes flowing both up and down the conceptual hierarchy, what I focus on is the part that has arguably been the most neglected. My perspective in this book will, I hope, be useful in drawing attention to the importance of these “top-down” processes and how they function in theory and practice.
Another challenging issue, which I address but not fully, is the mix between generally agreed-upon representations of context and more subjective idiosyncratic representations. At a sufficiently fine-grained level every individual in a creative field will have their own particular representation and knowledge of the world and their field, which will overlap partially but not completely with those of others. Thus, while many of the conceptual links in a context are recognized and accepted by most people in a field, other links are subjective and particular to a given person—for example, a web of interrelated memories based on individual experiences. This mix between widely recognized representations of context and more idiosyncratic reprsentations comes to the fore in empirical applications and in modeling the development of creative fields, in which different individuals working in a field contemporaneously may have different views and knowledge of the field, leading them to pursue different creative paths. I do not fully confront this topic in the formal modeling in this book, but it is evident in the case studies, especially in Chapter 17 on the development of creative fields, and can naturally fit in the conceptual framework suitably extended.
In fact this topic has greater importance, at least to me, than might at first appear. It is at the core of the vision I articulated in my first book, The Nature of Creative Development, which I remain committed to as an aspiration: to develop a rigorous modeling structure that has sufficient richness and scope to be able to depict each individual’s rich, distinctive conceptual world yet also include all individuals in a common framework. This kind of modeling framework is missing in the social sciences. Without it we are not truly able to depict individuality and hence cannot fully explore its role in creativity and innovation and other important social and cultural processes. Individualism is also a lynchpin of a free society; hence modeling it is vital to supporting freedom. The modeling framework presented in this book can contribute toward attaining the aspiration I have set and developing models of individualism; again, much work remains.
Taken as a whole and recognizing its limitations, the framework in this book does introduce new elements into the creativity field. It will hopefully help to advance creativity modeling, maintaining roots in traditional creativity and innovation while introducing modeling techniques for large-scale contexts. I hope it will be used practically, explored empirically, and developed further theoretically.
My approach in this book intersects with several different strands of literature in creativity studies and more broadly. I focus on two aspects of the creative process: the rich context and the role of guidance. Each of these is discussed in the literature, and there are some important connections; however, I do not believe these aspects have been brought together previously, certainly not in the way I do. My approach also draws upon and has connections with the biographical approach to creativity, but is quite different in terms of modeling. In this section and the next I discuss these areas of intersection to help place the book in context. I discuss more specific connections with the literature in later chapters, especially 2 (knowledge representation and context/concept modeling), 9 (guiding conceptions), 11 (guiding principles), and 16 (ways to develop the approach further). I note that the field of creativity is large, with many different approaches and subfields; it is not my purpose to provide a general review of the literature. Sawyer’s book Explaining Creativity: The Science of Human Innovation provides an excellent review, and the recent handbook edited by Kaufman and Sternberg includes chapters that discuss a wide range of creativity topics.4
Context is not the dominant focus in the field of creativity, but has been recognized by some. Csikszentmihalyi pioneered the study of creativity in its system context, an approach that also has some resonance with sociological approaches such as the work of Bourdieu.5 This approach emphasizes the interactions among the individual, the field, and the broader culture/society, including the reception of creative contributions. The breadth of this approach is especially noteworthy; however, the approach differs from mine in fundamental ways, especially in that the knowledge environment is not discussed in detail, and there is no formal model of the kind I present. In A Cognitive Historical Approach to Creativity, Dasgupta emphasizes that creative individuals and acts are situated within larger historical contexts; his argument and examples, linking many strands of literature together, help us understand the importance of context for creativity.6 What I mean by context overlaps with his meaning, but I focus on describing the structure of context and how guidance is used to navigate in this structure.
Sternberg and coauthors have developed propulsion theory, which models the different ways in which creative steps forward occur in creative fields.7 The taxonomy is useful, especially in encompassing many different kinds of creativity contributions, and it intersects with my approach in thinking about how individuals work with the elements in their fields to create something new. But there are important differences: context is kept very general, as is standard in the creativity field, so its sheer scale and richness is missing, and as a result guidance in the way I describe it doesn’t have a significant role; also there is no formal model structure. There may, however, be synergies with the approach I develop in this book.
In the literature on innovation in economics, context is an important element but is described differently than the way I describe context. An important long-standing literature focuses on institutions that support creativity and their impact on economic outcomes and growth. Most notable is intellectual property protection, but other modes of support are also discussed.8 This is quite different than my focus, although these factors could potentially be introduced into the framework I present. Knowledge as context is recognized to be important in the large literature on knowledge spillovers.9 Geography, social connectivity, and other measures of local connection are viewed as important, which overlaps with the notion of context as network.10 However, knowledge is generally not modeled in detail as a conceptual network the way I do and as is done in knowledge representation; rather, much of the literature is empirical and focuses on the challenge of measuring spillovers using standard data sources like patents and productivity data.11 I note that networks as a more general mathematical structure have been introduced into economics, notably by Matthew Jackson, but these networks describe social and production linkages, not concepts.12
Regarding the second key focus of this book, guidance, while it has not been described the way I describe it, there are connections with literature focusing on the role of conceptual thinking in creativity. Gabora’s honing theory considers the conceptual world of individuals and the interaction of individuals with their context, with creativity emerging through the generation of a global coherent state.13 Although Gabora does not model context or the conceptual world the way I do, there is an affinity with my approach. This kind of focus on the broader conceptual world is relatively rare—most of the work in creativity has emphasized more focused processes.
The creative cognition approach emphasizes that individuals generate provisional solutions to a problem or challenge via exploration, followed by refinement to generate a solution, sometimes going through this process multiple times until developing a satisfactory outcome.14 There is a sense of gaining clarity and specificity through the process, and the approach links in some ways with the latter part of my model in which individuals strive to find the “missing piece” to make a project work. Ward and Kolomyts review work in this tradition, including a few studies that show the value of abstraction in creative task definition, which calls attention to broader conceptual thinking but in a focused task-oriented setting.15 Overall in this approach, as with most work on creativity coming from the fields of psychology and cognitive science, context is not modeled and guidance is in general not mentioned and certainly not described the way I model it.
More generally, a number of cognitive approaches to generating creativity are discussed in the literature; these are not generally about guidance, but do have connections with my approach. Problem solving is a long-standing, important area of research in psychology. In relation to creativity this dates back at least to Wertheimer’s original contribution in 1945.16 In this branch of the literature, specific tools for generating creative solutions have been identified and shown to have validity in various empirical and experimental settings; see for example the interesting work of Weisberg.17 One well-known tool is conceptual blending, which is one route to solving problems creatively.18 In general, the problem-solving literature focuses on the later stages of the creative process; hence the overlap with my approach is mainly with the second stage of the model, in which projects are brought to completion. I focus on the role of guiding principles in project completion and not on the details of problem solution techniques, but these techniques can be seen as complementary. The importance of guiding principles in solving problems is recognized to be important in some areas of creativity, notably the design literature—I discuss this in Chapter 12 with examples including Steve Jobs and Edward Tufte.
A related strand of literature focuses on metaphor as a way to think creatively and identify creative solutions.19 Metaphor may be seen as one way to generate guidance; hence the insights of this literature are relevant for my approach, but the modeling is different and the focus is generally on the elements used to create the metaphor while the surrounding context (“all the roads not taken”) is not modeled in detail. Gruber’s notion of images of wide scope is a related conceptual tool; true to their name, such images have breadth of application and therefore can provide general guidance, and in this regard they are connected with my approach, though again the modeling approach is very different.20
Linked with problem solving is a smaller literature on problem finding—for example as discussed by Runco.21 Problem finding focuses earlier in the creative process, which aligns with my approach. However, as with much of the creativity literature, the focus tends to be on more narrowly focused conceptual processes, so that finding a problem to work on is not linked to broader guidance, which is the way I model this process.
There is also a literature, spanning both the creativity field and economics, that views creativity as generated via a random search process. The economics model specifies a distribution for potential productive innovations with random draws made from the distribution.22 In psychology the model of random search dates back to Donald Campbell’s 1960 article; in this model the distribution from which draws are made is not specified in as much detail, but the idea of making random attempts is similar.23 In these literatures, the “context” is the distribution out of which draws are made, and this has no underlying structure—it is just a population out of which elements are drawn at random. In contrast, I specify context as a network through which elements are linked to form ideas, thus adding important structure. I also include higher-level guidance, which as I have noted above is essential in large-scale contexts for which completely random search is almost sure to fail. Thus my approach can be seen as significantly enriching the random search model.
Beyond search theory there has been surprisingly little work on modeling creativity in economics, although there has been somewhat more in recent years. Weitzman models creativity as combinations, but the focus is not on the creative process itself but rather on the selection of ideas for further development.24 I have modeled learning and the development of ideas as recombinations in the context of creative fields.25 In recent work Rodet explores the impact of personal factors and experiences on creativity and Dutcher and Rodet explore knowledge transfer in creative domains—both papers relate to the model of context, exploration, and guidance in this book.26 Other recent work includes Dasaratha’s model of idea formation in a social network in which individuals meet to form ideas; Akcigit, Caicedo, Miguelez, Stantcheva, and Sterzi’s model of innovation as a choice between individual or collaborative activity; and Giorcelli and Moser’s study of the effect of copyright on creativity in the field of opera.27 As interesting and diverse as this work is, the modeling of context and creative process is limited and there is no role for guidance.
The lack of attention to creativity in economics has always surprised me, as one of the important principles of a free society is the freedom for individuals to pursue their own creative paths and ideas, a viewpoint associated with Mill and Hayek.28 Related to this is the notion that economic progress depends on entrepreneurs perceiving opportunities and having the freedom and capability to act on them, a view emphasized by Kirzner among others; this is a form of creativity and fits with my approach in this book.29 It is interesting that Bloom, Jones, Van Reenen, and Webb have recently published an article presenting evidence that it may be becoming more costly to generate ideas; while my focus is different, there is a connection with the idea that the context of creativity is changing and becoming larger scale.30 Support for creativity has always been valuable, but given that its context is changing, support may be becoming even more important, and it is my hope that the framework I present will help spur development in this neglected area.
A noteworthy emerging field is the neuroscience of creativity.31 The neuroscience approach is surely relevant for any approach to creativity that considers rich context and representation of knowledge and experiences, providing potentially a window into these representations and how individuals use them in creative work. The 2020 edited volume by Nalbantian and Matthews illustrates this, as many chapters make links between the neuroscience of creativity and more traditional and life-course descriptions of the creative process.32 The approach at least thus far focuses on quite short time spans and most likely will not pick up on the first stage of my model, but may map better into the second stage, project completion. See also the 2020 edited volume on creativity and the wandering mind, which has been an area of investigation in the past two decades.33
Another noteworthy emerging field is computational creativity—see for example recent conference volumes produced out of the International Conference on Computational Creativity conferences.34 There are some overlaps with my approach, especially in the way templates and prompts are used to help generate creative possibilities. But what is striking is that the focus is on creativity generated out of more specific elements, what I will call the lower level of the context, and there is far less attention paid to creative intuition at the higher guidance level—I discuss this in Chapter 9.35 There may be potential synergies of the framework in this book with computational approaches.
There is also overlap between my approach and both technology studies and the history of science. An important strand of the technology literature focuses on the process through which innovations come about based on perceived need, using what is at hand, or as a byproduct of activity.36 These insights may be able to be brought into my model as ways individuals interact with their context. In both technology studies and especially the history of science, the discussion of fields is an area of overlap with my approach, as the field an individual works in establishes a large part of their context. Kuhn’s famous work on scientific revolutions is an example of a framework in which the field is paramount; but the individual creative process is not focused on and how exactly an individual traverses a path to a revolutionary idea is not described in any detail.37 Hull discusses field-level processes in biology, simultaneously from conceptual and social perspectives, but again the focus is not on the individual creative process.38 Overall, much of the work on fields has focused less on the creative process in itself. However, there is much to be learned from the many outstanding contributions and valuable synergies to be developed.
The biographical literature on individuals engaged in creative endeavors both informs and inspires my approach. When we study an individual’s creative path in detail, we see the richness both of their process and the surrounding context. Within the creativity literature Howard Gruber brought attention to this aspect of creativity, initially in his landmark study of Charles Darwin’s notebooks and then in his evolving systems framework. Another inspiring early work is Lowes’s description of Samuel Taylor Coleridge’s creative process.39
Unfortunately much of the biographical literature exists quite separately from the creativity literature. Bringing the two together is a facet of this book as it was also of my earlier book The Nature of Creative Development. Specifically, I draw on both biographical and archival materials for the case studies. Frederic Holmes’s scientific biography of Hans Krebs is remarkable, a model for assembling rich details to show how creativity unfolds. Vivien Johnson’s biography of Clifford Possum provides a rich perspective on his development. Every biography fits in a network with other historical materials. In this case Possum fits within the Indigenous Australian modern art movement, which I discuss in Chapter 17, drawing on a range of works including Papunya: A Place Made After the Story, based on Geoffrey Bardon’s notes from his time at Papunya where, at least on some accounts, this movement began. There are many other outstanding biographies that have informed my thinking across the arts, sciences, and technology; indeed, it is always a joy to find another outstanding biography and learn through the care, scholarship, and thoughtfulness of its author.
Archival materials are a very rich source of information. Virginia Woolf left us a treasure trove of materials, including not only her fiction but also her diaries, many volumes of letters, and her essays; I draw on these materials in my description of her creative path. Engineer and transgender activist Lynn Conway has posted a large collection of historical materials on her website documenting both her life path as well as her role in the development of VLSI design principles; these are the basis for my discussion of her creative journey, supplemented with materials posted by her collaborator Carver Mead. I draw on Albert Einstein’s “Autobiographical Notes,” a model of clarity, as well as other articles he wrote and the extensive scholarship on his development of relativity theory. We are fortunate to have such rich materials for these individuals. But we have much less for most, and can only hope the collection and preservation of such materials, for all individuals engaged in creative endeavors no matter the scale and scope, can improve and come to match them.
As rich and informative as the biographical and archival material is, however, it does not provide a general framework for describing the creative process in a systematic, structured way. Gruber makes the imporant point that creativity comes about through many small steps, not one giant leap; but his framework is descriptive in nature, not structural. Holmes also presents a framework for creative paths in the sciences, which he calls “investigative pathways,” but again his framework has limited structure.40
The approach in this book shows how to structure archival and biographical material and analyze it more systematically. A key step for this—a focus of this book—is developing a framework for describing the rich context in which individuals engaged in creative endeavors function. It is far too easy to focus on only a handful of contextual elements and influences, even in a very good biographical account of a creator’s journey. Archival materials sometimes include more of this, but normally the individual creating these materials does not view a full description of context as the main purpose. A related key step is to recognize all the “roads not taken”—all the possibilities in the rich context that were not pursued. Even very good biographies do not generally discuss this in much depth, yet from the viewpoint of modeling and predicting the creative process, it is critical to know this. By describing context and creative paths and possibilities more systematically and more fully, we will come to a deeper, more developed understanding of creativity and the creativity inherent in every person’s life journey.
1. See Alex Fornito, Andrew Zalesky, and Edward Bullmore, Fundamentals of Brain Network Analysis, 2016, Academic Press, for an edited volume discussing the brain and its analysis as a network.
2. See Liane Gabora, “Honing Theory: A Complex Systems Framework for Creativity,” 2017, Nonlinear Dynamics, Psychology, and Life Sciences, Vol. 21, No. 1, pp. 35–88; Liane Gabora and Diederik Aerts, “A Model of the Emergence and Evolution of Integrated Worldviews,” 2010, Journal of Mathematical Psychology, Vol. 53, No. 5, pp. 434–51; Jonathan S. Feinstein, The Nature of Creative Development, 2006, Stanford University Press, especially Chapter 2. For templates see my discussion in Chapter 3, and for creative vision my discussion in Chapter 9.
3. See Henri Poincaré, Science and Method, trans. F. Maitland, 1952 (originally published 1924 in French), Dover, especially pp. 52–53; Graham Wallas, The Art of Thought, 1926, Harcourt, Brace and Company. Wallas’s description actually involved more detail than is typically discussed: see Eugene Sadler-Smith, “Wallas’ Four-Stage Model of the Creative Process: More than Meets the Eye?,” 2015, Creativity Research Journal, Vol. 27, No. 4, pp. 342–52.
4. R. Keith Sawyer, Explaining Creativity: The Science of Human Innovation, 2006, Oxford University Press; James C. Kaufman and Robert J. Sternberg, The Cambridge Handbook of Creativity, 2019, Cambridge University Press.
5. Mihaly Csikszentmihalyi, The Systems Model of Creativity: The Collected Works of Mihaly Csikszentmihalyi, 2014, Springer, especially Chapter 4, “Society, Culture, and Person: A Systems View of Creativity”; Pierre Bourdieu, Distinction: A Social Critique of the Judgement of Taste, 1984, Harvard University Press.
6. Subrata Dasgupta, A Cognitive Historical Approach to Creativity, 2019, Routledge.
7. Robert J. Sternberg, “A Propulsion Model of Types of Creative Contributions,” 1999, Review of General Psychology, Vol. 3, pp. 83–100; Robert J. Sternberg, James C. Kaufman, and Jean E. Pretz, “The Propulsion Model of Creative Contributions Applied to the Arts and Letters,” 2001, Journal of Creative Behavior, Vol. 35, pp. 75–101.
8. Ben Depoorter, Peter Menell, and David Schwartz, Research Handbook on the Economics of Intellectual Property Law, 2019, Edward Elgar, for intellectual property; Joel Mokyr, The Gifts of Athena, 2002, Princeton University Press; Petra Moser, “How Do Patent Laws Influence Innovation? Evidence from Nineteenth-Century World Fairs,” 2005, American Economic Review, Volume 95, No. 4, pp. 1214–36.
9. Kenneth J. Arrow, “Economic Welfare and the Allocation of Resources for Invention,” 1962, in The Rate and Direction of Inventive Activity, ed. R. Nelson, Princeton University Press, pp. 609–26.
10. Adam Jaffe, Manuel Trajtenberg, and Rebecca Henderson, “Geographic Localization of Knowledge Spillovers as Evidenced by Patent Citations,” 1993, Quarterly Journal of Economics, Vol. 108, No. 3, pp. 577–98.
11. A good example is Zvi Griliches, “The Search for R&D Spillovers,” 1992, Scandinavian Journal of Economics, Vol. 94, Supplement, pp. S29–47.
12. Matthew O. Jackson, Social and Economic Networks, 2010, Princeton University Press. Daron Acemoglu, Ufuk Akcigit, and William R. Kerr, “Innovation Network,” 2016, Proceedings of the National Academy of Sciences, Vol. 113, No. 41, pp. 11483–8 do have a network orientation but quite different: they discuss innovation in terms of network links between industries that are based on input-output flows and hence production based.
13. Gabora, “Honing Theory: A Complex Systems Framework for Creativity”; Gabora and Aerts, “A Model of the Emergence and Evolution of Integrated Worldviews.”
14. Steven M. Smith, Thomas B. Ward, and Ronald A. Finke, The Creative Cognition Approach, 1995, MIT Press.
15. Thomas B. Ward and Yuliya Kolomyts, “Creative Cognition,” 2019, Chapter 9 in The Cambridge Handbook of Creativity, ed. J. Kaufman and R. Sternberg, Cambridge University Press. See also Victoria S. Scotney, Jasmine Schwartz, Nicole Carbert, Adam Saab, and Liane Gabora, “The Form of a ‘Half-Baked’ Creative Idea: Empirical Explorations into the Structure of Ill-Defined Mental Representations,” 2020, Acta Psychologica, Vol. 203, 102981.
16. Max Wertheimer, Productive Thinking, 1945, Harper and Brothers.
17. Robert W. Weisberg, Creativity: Beyond the Myth of Genius, 1993, W. H. Freeman; and Robert W. Weisberg, Creativity: Understanding Innovation in Problem Solving, Science, Invention, and the Arts, 2006, John Wiley & Sons.
18. Gilles Fauconnier and Mark Turner, The Way We Think: Conceptual Blending and the Mind’s Hidden Complexities, 2002, Basic Books.
19. Dedre Gentner, “Structure-Mapping: A Theoretical Framework for Analogy,” 1983, Cognitive Science, Vol. 7, pp. 155–70; Adam Green, “Creativity, within Reason: Semantic Distance and Dynamic State Creativity in Relational Thinking and Reasoning,” 2016, Current Directions in Psychological Science, Vol. 25, No. 1, pp. 28–35, links to cognitive neuroscience.
20. Howard E. Gruber, “Darwin’s ‘Tree of Nature’ and Other Images of Wide Scope,” 1978, in On Aesthetics in Science, ed. Judith Wechsler, MIT Press, pp. 121–40.
21. Mark A. Runco, Problem Finding, Problem Solving, and Creativity, 1994, Ablex.
22. Robert E. Evenson and Yoav Kislev, “A Stochastic Model of Applied Research,” 1976, Journal of Political Economy, Vol. 84, No. 2, pp. 265–81; Samuel S. Kortum, “Research, Patenting, and Technological Change,” 1997, Econometrica, Vol. 65, No. 6, pp. 1389–419.
23. Donald Campbell, “Blind Variation and Selective Retentions in Creative Thought as in Other Knowledge Processes,” 1960, Psychological Review, Vol. 67, No. 6, pp. 380–400; Dean K. Simonton, “Scientific Creativity as Constrained Stochastic Behavior: The Integration of Product, Person, and Process Perspectives,” 2003, Psychological Bulletin, Vol. 129, No. 4, pp. 475–94. Random combinations also figure in Poincaré’s discussion in Science and Method.
24. Martin L. Weitzman, “Recombinant Growth,” 1998, Quarterly Journal of Economics, Vol. 113, No. 2, pp. 331–60.
25. Jonathan S. Feinstein, “Optimal Learning Patterns for Creativity Generation in a Field,” 2011, American Economic Review, Papers & Proceedings, Vol. 101, No. 3, pp. 227–32.
26. Cortney S. Rodet, “The Wellspring of Creativity? Using Divergent-Thinking Tasks to Understand Creative Characteristics,” 2021, Managerial and Decision Economics, Vol. 42, No. 6, pp. 1435–53; E. Glenn Dutcher and Cortney S. Rodet, “Learning by Doing What? Learning and Knowledge Transfer in the Creative Domain,” 2021, working paper, Ohio University.
27. Krishna Dasaratha, “Innovation and Strategic Network Formation,” 2021, working paper; Ufuk Akcigit, Santiago Caicedo, Ernest Miguelez, Stefanie Stantcheva, and Valerio Sterzi, “Dancing with the Stars: Innovation through Interactions,” 2018, NBER Working Paper 24466; Michela Giorcelli and Petra Moser, “Copyrights and Creativity: Evidence from Italian Opera in the Napoleonic Age,” 2020, Journal of Political Economy, Vol. 128, No. 11, pp. 4163–210.
28. John S. Mill, On Liberty, 1978 (originally published 1859), Hackett; Friedrich A. Hayek, The Constitution of Liberty, 1960, University of Chicago Press.
29. See as one noteworthy contribution in this tradition Israel M. Kirzner, Discovery and the Capitalist Process, 1985, University of Chicago Press.
30. Nick Bloom, Charles I. Jones, John Van Reenen, and Michael Webb, “Are Ideas Getting Harder to Find?,” 2020, American Economic Review, Vol. 110, No. 4, pp. 1104–44.
31. R. Keith Sawyer, “The Cognitive Neuroscience of Creativity: A Critical Review,” 2011, Creativity Research Journal, Vol. 23, No. 2, pp. 137–54; Anna Abraham, The Neuroscience of Creativity, 2018, Cambridge University Press. Adam Green provides a review focusing on links with analogical reasoning in his article “Creativity, within Reason.”
32. Suzanne Nalbantian and Paul Matthews, Secrets of the Mind: What Neuroscience, the Arts, and Our Minds Reveal, 2020, Oxford University Press.
33. David D. Preiss, Diego Cosmelli, and James C. Kaufman, Creativity and the Wandering Mind, 2020, Academic Press.
34. For example, International Conference on Computational Creativity (ICCC), Proceedings of the Eleventh International Conference on Computational Creativity, 2020, ed. F. Amílcar Cardoso, Penousal Machado, Tony Veale and João Miguel Cunha, Association for Computational Creativity.
35. This same view echoes in some critiques of the field—for example, Joanna Zylinksa, AI Art: Machine Visions and Warped Dreams, 2020, Open Humanities Press.
36. On perceived need, Subrata Dasgupta, Technology and Creativity, 1996, Oxford University Press; on using what is at hand, Navi Radjou, Jaideep Prabhu, and Simone Ahuja, Jugaad Innovation: Think Frugal, Be Flexible, Generate Breakthrough Growth, 2012, Jossey-Bass; and as a byproduct of activity, Ainissa Ramirez, The Alchemy of Us, 2020, MIT Press.
37. Thomas S. Kuhn, The Structure of Scientific Revolutions, 1962, University of Chicago Press.
38. David L. Hull, Science as a Process, 1988, University of Chicago Press.
39. Howard E. Gruber, Darwin on Man: A Psychological Study of Scientific Creativity, 1974, E. P. Dutton; Doris B. Wallace and Howard E. Gruber, Creative People at Work, 1989, Oxford University Press; John L. Lowes, The Road to Xanadu: A Study in the Ways of the Imagination, 1927, Houghton Mifflin.
40. Frederic L. Holmes, Investigative Pathways: Patterns and Stages in the Careers of Experimental Scientists, 2004, Yale University Press.