## 1. The Philosophy of Creativity: Past and Present



Given the significance creativity has in our lives and the deep
philosophical questions it raises, one might expect creativity to be a
major topic in philosophy. Curiously, it isn't.



To be sure, some of the most prominent figures in the history of
Western philosophy have been fascinated with creativity--or what
we now call "creativity". According to some scholars, the
abstract noun for creativity did not appear until the nineteenth
century--but the phenomenon certainly existed and many
philosophers took an interest in it (McMahon 2013; Nahm 1956; Murray
1989; Tatarkiewicz 1980: chapter 8).



To name just a few examples: Plato (4th century BCE) had
Socrates say, in certain dialogues, that when poets produce truly
great poetry, they do it not through knowledge or mastery, but rather
by being divinely "inspired" by the Muses, in a state of
possession that exhibits a kind of madness (*Ion* and
*Phaedrus*). Aristotle (3rd century BCE), in
contrast, characterized the work of the poet as a rational,
goal-directed activity of making (*poeisis*), in which the poet
employs various means (such as sympathetic characters and plots
involving twists of fate) to achieve an end (of eliciting various
emotions in the audience). Margaret Cavendish (1623-1673) and
Emilie du Chatelet (1706-1749) championed the
creative use of the imagination to pursue freedom, overcome prejudice,
and cultivate natural abilities even despite social and political
oppression. Immanuel Kant
(1724-1804) conceived of artistic genius as an innate capacity
to produce original works through the free play of the imagination, a
process which does not consist in following rules, can neither be
learned nor taught, and is mysterious even to geniuses themselves.
Schopenhauer (1788-1860) stressed that the greatest artists are
distinguished not only by the technical skill they employ in the
production of art, but also by the capacity to "lose
themselves" in the experience of what is beautiful and sublime
(Schopenhauer 1859: Vol. I: 184-194 and Vol. II: 376-402).
Friedrich Nietzsche (1844-1900) argued that the greatest feats
of creativity, which he took to be exemplified by the tragic poetry of
ancient Greece, was being born out of a rare cooperation between the
"Dionysian" spirit of ecstatic intoxication, which imbues
the work with vitality and passion, and the "Apollonian"
spirit of sober restraint, which tempers chaos with order and form
(Nietzsche 1872 [1967]). William James (1842-1910) theorized
about creative genius exerts the causal power to change the course of
history (Simonton 2018). This is just a glimpse of what each of these
philosophers had to say about creativity, and many other figures could
be added to their number.



Nevertheless, while some of the topics explored by earlier thinkers
have come to occupy a central place in philosophy today--such as
freedom, justice, consciousness, and knowledge--creativity is not
among them. Indeed, "philosophy of creativity" is still a
neologism in most quarters, just as, for example, "philosophy of
action" and "philosophy of gender" were not too long
ago. However, philosophical work on creativity has been picking up
steam over the last two decades (as shown, for example, in a few
important collections of essays: B. Gaut & Livingston 2003;
Krausz, Dutton, & Bardsley 2009; Paul & Kaufman 2014; B. Gaut
& Kieran 2018). We'll now dive into those contributions,
along with earlier work, beginning with what is perhaps the most basic
question one can ask in this field.


## 2. What is Creativity?



As we noted at the outset, the term "creative" can be
applied to three kinds of things: a *person*, a
*process*, or a *product* (where a product could be an
idea, performance, or physical artifact).



Most definitions focus on the product. According to one common
approach, persons or processes are creative to the extent that they
produce creative products, and a product is creative if it meets two
conditions: in addition to being *new* it must also be
*valuable*. Many theorists argue that novelty is not
sufficient, because something can be new but worthless (e.g., a
meaningless string of letters), in which case it doesn't merit
the compliment of being called "creative". Immanuel Kant
is often cited as anticipating this definition of creativity in his
discussion of (artistic) genius. According to a common interpretation,
Kant defines (artistic) genius as the ability to produce works that
are not only "original"--since "there can be
original nonsense"--but also "exemplary" (Kant
1790: SSSS43-50 [2000: 182-197]). (Hills &
Bird [2018] challenge this reading of Kant.) This definition is so
widely accepted among psychologists that it has come to be known as
"the standard definition" of creativity in psychology. In
practice, "creativity is often *not* defined" (J.C.
Kaufman 2009: 19) in psychological experiments--more on this in
 SS5
 below. When psychologists do explicitly adopt a definition, however,
they usually say that creative products are not only new, but also
valuable in some way, though they variously express the
product's value in terms of its being "useful",
"effective", "worthwhile", "fit",
or "appropriate to the task at hand" (Bruner 1962: 18; A.
J. Cropley 1967: 67; Jackson & Messick 1965: 313; Kneller 1965: 7;
Cattell & Butcher 1968; Heinelt 1974; J.C. Kaufman 2009:
19-20; S.B. Kaufman & Gregoire 2016; Stein 1953; Sternberg
& Lubart 1999: 3--for an overview, see Runco & Jaeger
2012). A few psychologists have suggested that the standard definition
doesn't fully capture the concept of creativity (Amabile 1996;
Simonton 2012b). As for philosophers, at least one of them defends the
standard definition with qualifications (Klausen 2010), but many of
them challenge it, as we'll soon see.



While it is uncontroversial that novelty is required for creativity,
philosophers have refined that point. Certain examples may seem, at
first, to suggest that novelty isn't really necessary for
creativity. Newton's discovery of calculus was creative even if,
unbeknownst to him at the time, Leibniz got there first--one of
many examples of what are called "multiples" in the
history of science (Simonton 2004). A beginning student's idea
that freedom is compatible with causal determinism might be creative
even if, as she will soon learn, philosophers have been defending such
"compatibilist" theories for millennia. However, examples
like these do not force us to abandon the novelty requirement, but
only to qualify it. Newton's calculus and the student's
compatibilism were not new in all of history, but they were new to
their respective creators, and that is enough for them to count as
creative. In the terminology of philosopher Margaret Boden, these
ideas are "psychologically creative" (P-creative) even
though they are not "historically creative" (H-creative).
Notice that P-creativity is more fundamental. Anything that is new in
all of history (H-creative) must also be new to its creator
(P-creative). Thus, creativity always exhibits psychological novelty,
though it doesn't always exhibit historical novelty.



Again, no one denies that a creative product must be new, at least to
its creator. But as we'll now see, some philosophers depart from
the standard definition of creativity by rejecting the value condition
 (SS2.1),
 or by proposing some further condition(s)
 (SS2.2),
 or by doing both.


### 2.1 Challenges to the value condition



Some theorists have argued that although creative things are valuable,
we shouldn't build value into the definition of creativity,
because doing so is not informative or explanatory:



> 
> 
> Knowing that something is valuable or to be valued does not by itself
> reveal *why* or *how* that thing is. By analogy, being
> told that a carburetor is useful provides no explanatory insight into
> the *nature* of a carburetor: how it works and what it does.
> (Stokes 2008: 119; Stokes 2011: 675-76)
> 
> 
> 



Those who maintain that value is required for creativity might reply
that it doesn't need to be informative or explanatory. Being a
man is required for being a bachelor even though it's not
informative or explanatory to say that bachelors are men. Stokes notes
that "creative" is a term of praise, and uses this point
to argue that what is creative must be produced intentionally (since
we don't rightly praise what is unintentional or
accidental)--an idea we'll return to below. But the same
point also seems to imply that what is creative must also have value
(since we don't rightly praise what doesn't have value).
And while the concept "carburetor" is value-neutral, as
shown by the fact that a carburetor can be worthless or useless (if
it's broken), "creative", one might argue, is a
value-laden concept, like "progress". Progress necessarily
involves novelty or change, but we don't praise change as
progress unless it's good change. Likewise, defenders of the
value condition urge, creativity necessarily involves novelty, but we
don't praise novelty as creative unless it's good
novelty.



Other critics use counterexamples to argue that value isn't
necessary for creativity, the most prominent cases being ones of
immoral creativity. (For a collection of essays by psychologists on
the phenomenon of immoral or so-called "dark"
creativity', see D. Cropley et al. 2010). Putative cases of
immoral creativity include creative accounting to cheat investors or
creative testimony to mislead jurors, and the stock example in the
literature is creative torture or murder. One can imagine novel and
well-designed murders, as Thomas De Quincey once did in a satirical
essay:



> 
> 
> [S]omething more goes to the composition of a fine murder than two
> blockheads to kill and be killed--a knife--a purse--and
> a dark lane. Design, gentlemen, grouping, light and shade, poetry,
> sentiment, are now deemed indispensable to attempts of this nature.
> Mr. Williams has exalted the ideal of murder to all of us [...]
> Like AEschylus or Milton in poetry, like Michael Angelo in
> painting, he has carried his art to a point of colossal sublimity. (De
> Quincey 1827; see also discussion in Battin et al. 1989)
> 
> 
> 



Innovative ways of inflicting needless agony and craftily designed
murders are not good (they have no value), and yet they can be
creative. If this is right, then it seems to follow that creativity
doesn't require value.



One way of trying to save the value condition is by flatly denying
that torture methods can be creative, and by denying more generally
that creative things can be bad (Novitz 1999). But such denial seems
ad hoc and implausible--"evil creativity" is not a
contradiction in terms--and some have argued that this denial
faces other problems besides (Livingston 2018).



Other theorists revise or qualify the value condition in order to
accommodate examples of immoral creativity. Paisley Livingston (2018)
proposes that a creative product only needs to be instrumentally
valuable or "effective" as means to its intended end,
regardless of whether that end is morally good, bad, or indifferent.
Berys Gaut (2018) distinguishes between something's being
*good* (or good, period) versus being *good of its
kind*. In his view, a new way of wielding blades and pulleys may
be creative if it's a good of its kind--good as a method of
torture--even though it isn't good. In order for something
to count as creative, Gaut says, it doesn't need to be good; it
just needs to be good of its kind.



Alison Hills and Alexander Bird (2018) are unconvinced by such
qualifications. They contemplate an elaborate torture device that ends
up killing its victims immediately, "without enough suffering on
the way". The device may still be creative, they hold, even
though "as a method of torture, it's no good" (2018:
98). Indeed, they argue, a creative item needn't be good in any
way at all, not even for its creator. The ineffective torture device
just described doesn't satisfy its creator's preferences,
it doesn't give him pleasure, it isn't an achievement, it
doesn't contribute at all to his well-being--and yet, they
contend, it may be creative, provided that it's new and was
produced in the right way. Exactly what "the right way"
amounts to is the topic we turn to next.


### 2.2 Other proposed conditions



With or without the value condition, some theorists argue that a
product must satisfy one or more further conditions, beyond being new,
in order to count as creative. The four most prominent proposals are
that the product must be (i) surprising, (ii) original (i.e., not
copied), (iii) spontaneous, and/or (iv) agential. Each of these is a
condition on the process of creativity. To be clear, we are still
concerned with what it means for a product to be creative, but the
proposals we'll now consider say that in order for a product to
count as creative, it must be brought about in the right way.


#### 2.2.1 Surprise



Margaret Boden holds that a creative product must be "*new,
surprising, and valuable*" (2004: 1; cf. Boden 2010; 2014).
It is perhaps most natural to assume that being surprising--like
being new and valuable--is a feature of a product. But while
Boden does think of creative products as surprising, her interest is
more fundamentally in the underlying generative process, in how a
creator manages to make something surprising. In her view, there are
"three types of creativity"--combinatorial,
exploratory, and transformative--"which elicit different
forms of surprise, [and] are defined by the different kinds of
psychological *processes that generate* the new
structures" (2010: 1, italics added).



*Combinatorial* *creativity* occurs when old ideas are
combined in new ways. Obvious examples include fictional hybrid
creatures or chimeras: add wings to a horse (Pegasus), add the tail of
a fish to a woman's head and upper-body (a mermaid), add a
lion's body to a woman's head and torso (Sphinx), and so
on. Other combinations are found in analogies, such as when Niels Bohr
compared an atom to the solar system. The term
"combination" can refer either to the product of things
combined or to the process of combining them, but Boden's focus
is on the process here, on the fact that one way to generate new ideas
is to begin with old ideas and combine them in new ways.



To explain her other two kinds of creativity, Boden invokes the notion
of a "conceptual space", which is roughly a system
comprising a set of basic elements (e.g., basic ideas or
representations) as well as rules or "constraints" for
manipulating or re-combining those elements. A conceptual space is not
a painting, song, or poem, for example; it's a *way of
creating* a painting, song, poem, or theory. The rules or
constraints are "the organizing principles that unify and give
structure to a given domain of thinking". And so a conceptual
space is



> 
> 
> the generative system that underlies that domain and defines a certain
> range of possibilities: chess moves, or molecular structures, or jazz
> melodies. (1994: 79)
> 
> 
> 



We could think of a conceptual space as not just a set of thoughts but
also a style of thinking defined by rules for generating new
thoughts.



"Within a given conceptual space", Boden observes,
"many thoughts are possible, only some of which may have been
actually thought" (2004: 4). Some conceptual spaces contain more
possibilities than others. Consider different games. Tic-tac-toe is
such a simple game that all of its possible moves have already been
made many times over. The same is not true in chess, by contrast,
which allows for a mind-boggling number of possible moves. The range
of possible ideas is also practically inexhaustible in literature,
music, the visual and performing arts, as well as the various domains
of theoretical inquiry. And within those pursuits, there are various
"structured styles of thought"--genres, paradigms,
methodological orientations--which Boden thinks of as conceptual
spaces.



Boden argues that the elements as well as the operating rules of a
conceptual space can be, and in some cases have been, captured in
computer programs. She has used this point not only to argue that
computers can be creative (a topic we'll return to below in
 SS5),
 but also to suggest that we should employ the computational model of
the mind in order to explain how humans create.



With her notion of conceptual spaces in hand, Boden says that
*exploratory creativity* occurs within a given conceptual
space. The new idea that emerges is one that was already possible
within that space, because it was permitted by its rules. "When
Dickens described Scrooge as 'a squeezing, wrenching, grasping,
scraping, clutching, covetous old sinner,'" Boden writes,
"he was exploring the space of English grammar" in which
"the rules of grammar allow us to use any number of adjectives
before a noun" (Boden 1994: 79). Dickens's description may
strike us somewhat surprising, unexpected, or improbable, but it
doesn't have an air of impossibility about it.



By contrast, Boden argues, another form of creativity does. In this
kind of case, the creative result is so surprising that it prompts
observers to marvel, "But how could that possibly happen?"
(2004: 6). Boden calls this *transformational creativity*
because it cannot happen within a pre-existing conceptual space; the
creator has to transform the conceptual space itself, by altering its
constitutive rules or constraints. Schoenberg crafted atonal music,
Boden says, "by dropping the home-key constraint", the
rule that a piece of music must begin and end in the same key.
Lobachevsky and other mathematicians developed non-Euclidean geometry
by dropping Euclid's fifth axiom. Kekule discovered the
ring-structure of the benzene molecule by negating the constraint that
a molecule must follow an open curve (Boden 1994: 81-3). In such
cases, Boden is fond of saying that the result was "downright
impossible" within the previous conceptual space (Boden 2014:
228).



Boden's definition of creativity has perhaps been most
influential among researchers who share her intertest in computer
creativity (e.g., Halina 2021; Miller 2019: ch. 3; du Sautoy 2019). In
a variation of Boden's account, one philosopher proposes that
what makes a mental process creative is not that it actually involves
"the recombination of old ideas or the transformation of
one's conceptual space", but rather that the creator
*experiences* the process as having one of those features
(Nanay 2014).


#### 2.2.2 Originality



Maria Kronfeldner (2009; 2018) argues that the process of making
something creative must exhibit *originality*. As she uses the
term "original", it does not simply mean
"new"; instead, it has to do with the kind of causal
process the creator must employ. She motivates her view by asking why
it's the case that, as we noted earlier, psychological novelty
is required for creativity while historical novelty is not. Why is it,
for example, that Newton's invention of calculus was creative
even if Leibniz invented it first? The answer, of course, is that
it's because Newton didn't *copy* his calculus from
Leibniz. Insofar as Newton came up with calculus independently, on his
own, then he exhibited *originality* in his discovery, even
though someone else got there first. This originality, Kronfeldner
argues, is essential to creativity.


#### 2.2.3 Spontaneity



Kronfeldner (2009; 2018) also argues that *spontaneity* is
required for creativity. An idea occurs spontaneously to the extent
that it is produced without foresight or intentional control. If you
were to foresee the output of the creative process at the beginning of
that process, then you wouldn't need any further process to come
up with it. So if an idea is creative, you cannot have fully seen it
coming. To that extent, insight comes as a surprise, hence the common
phenomenological observation that creative breakthroughs feel like
they come unbidden or out of the blue: "Eureka!",
"Aha!", a lightbulb turns on.



Gaut (2018: 133-137) agrees that creativity requires
spontaneity, and he points out, as Kronfeldner does, that it comes in
degrees. He explains that you do something spontaneously to the extent
that do it without planning it in advance. If you are going to act
creatively, he argues, you cannot set out to follow an "exact
plan"--a mechanical procedure, routine, or algorithmic
rule--which would give you advance knowledge of exactly what the
outcome will be and exactly the means you'll take to achieve it. At
the outset of a creative act, you have to be to some extent ignorant
of the end, or the means, or both. That ignorance opens up room for
spontaneity and creativity.


#### 2.2.4 Agency



Some philosophers argue that an item does not count as creative unless
it has been produced by an agent. Consider a unique snowflake with an
intricate shape, a distinctive sunset with stunning layers of
red-orange hues, a novel patterning of dunes across a wind-blown
desert. All of these things are aesthetically valuable and new. None
of them are creative, however, insofar as they all occurred naturally
and were not made by an agent. Gaut uses examples like these to argue
that creative things must be created by *agents* (B. Gaut 2018:
129-30; cf. B. Gaut 2010, and B. Gaut 2014b) and several other
philosophers agree (Carruthers 2006, 2011; Kieran 2014a, 2014b; Stokes
2008, 2011, 2014; Paul & Stokes 2018).



Of course, many theists would maintain that everything in nature is
the handiwork of an agent--namely, God--and so arguably it
would make sense for them to regard a natural phenomenon as creative
if it is valuable and new. For theists, the unparalleled beauty of
nature is a reason to praise the Creator. But this only supports the
conceptual point that creativity, by definition, requires agency. We
may coherently regard valuable new things as creative if we attribute
them to a creative agent, as the theist does with the natural world;
otherwise, we can't. So again, it seems, creativity requires
agency.



This leaves open the question of exactly how a creator's agency
must be exercised in order for the result to count as creative. Some
philosophers argue that the agent's act of creation must be
*intentional*. Suppose you are snowboarding on a powder day
and, unbeknownst to you, the tracks from your board result in a
pleasing new pattern as viewed from high above. The new pattern has
aesthetic value, but it isn't creative. And that is because you
didn't intend to make it. Underlying this intuition, as well as
our intuitions about the natural phenomena above, is the fact that
"creative" is a term of praise, and we do not extend
praise (or blame) for things that are not done by an agent, or for
things that an agent doesn't do in some sense intentionally.



While a number of philosophers endorse some version of the agency
requirement for creativity, many theorists make no mention of it,
whether to endorse it or reject it, including all of the psychologists
cited above. Further, at least two philosophers are willing to
attribute creativity to natural phenomena like trees and evolutionary
processes: Arnheim (2001) and, in recent work, Boden (2018). These
latter theorists don't discuss agency as such, but insofar as
the natural phenomena they call creative are not the result of agency,
their view would imply that agency isn't required for
creativity.



The four proposals we've just considered all say that a product
must arise from a certain kind of process--a process that
exhibits surprise, originality, spontaneity, or agency--in order
to count as creative. While there is wide agreement among philosophers
that creativity requires *some* special kind of process, not
just a special product, there is no consensus on what is required of
the process. Of the four process conditions described here, the agency
condition seems to be the one that is explicitly endorsed by the
greatest number of philosophers thus far, though even they are still
just a handful. And as we've seen, the other proposed conditions
have serious arguments in their favor as well.



Some philosophers argue that if *any* process requirement is
correct, this has an intriguing corollary for judgements about
creativity: Even when we are explicitly judging only that a
*product* is creative, we are implicitly assuming something
about the process by which it was made. Suppose, for illustration,
that the agency requirement is correct--that being generated
through an agential process is built into the very concept of a
creative product. Suppose further that you are applying that concept
competently. It follows that if you come across a captivating
arrangement of stones on the beach and you judge it to be creative,
you are at least implicitly assuming that it was created through an
agential process. If someone later persuades you that the stones
happened to be moved into place by the wind and waves, not by any
agent but just by chance, then you may still regard the result as
aesthetically interesting but you would have to rescind your judgement
that it is creative. So if the agency condition is correct, whenever
you point to some item and say, "This is creative", what
you are saying, in part is, "This resulted from a creative
process". Furthermore, on this view, analogous implications
follow if any other process condition is correct (Paul & Stokes
2018).


### 2.3 Is creativity a virtue?



Having considered what is required for something to count as a
creative *product*, and whether it must be produced by a
certain kind of *process*, we now turn to analysis of the
creative *person*.



Some theorists suggest that creativity, as an attribute of persons, is
an ability to perform creative acts or produce creative things (Boden
2004). Others argue, however, that creativity isn't merely an
ability. An ability is something you can possess without ever putting
it to use. You might have the ability to learn Swahili, for example,
without ever making the effort to learn that language, despite having
ample opportunities to do so. Creativity is different in this regard.
If someone has the ability to be creative but never uses that ability
when given numerous chances to do so, we would not call that person
creative. Creative people are not merely able to act creatively. They
are, moreover, disposed to exercise that ability, such that they do
act creatively, at least some of the time, when the occasion arises.
On this view creativity is a *disposition*, also referred to as
a *trait* (Grant 2012; cf. B. Gaut 2014b, 2018).



Philosophers have long distinguished *virtues* as a special
subclass of dispositions or traits. In Western philosophy, the
tradition of theorizing about virtues goes back to the ancient Greeks,
and over the last half-century it has enjoyed a renaissance in ethics
(see entry on
 virtue ethics)
 and, more recently, in epistemology (see entry on
 virtue epistemology)
 and aesthetics (Lopes 2008; Roberts 2018; Hills 2018). Traditional
examples of virtues include wisdom, justice, temperance, and courage.
Should creativity be added to the list?



The answer depends, of course, on what it means for a trait to be a
virtue. At the very least, a virtue is a trait that is good or
valuable. So whether creativity counts as a virtue in this minimal
sense depends on whether creativity is necessarily valuable, a point
which is contested, as we saw in the previous section. In fact, those
who contend that creativity isn't necessarily valuable often do
so in order to prove that it isn't a virtue.



But let's suppose for the sake of argument that creativity is
indeed a valuable trait. Is it also a virtue in some more robust
sense? Virtue theorists commonly take their cue from Aristotle's
classic discussion in the *Nichomachean Ethics*. Citing justice
and temperance as paradigm virtues, Aristotle asserts that a trait
must meet at least three conditions to count as a virtue:



> 
> 
> For actions in accord with the virtues to be done temperately or
> justly it does not suffice that they themselves have the right
> qualities. Rather, the agent must also be in the right state when he
> does them. First, he must know [that he is doing virtuous actions];
> second he must decide on them, and decide on them for themselves; and
> thrid, he must also do them from a firm and unchanging state.
> (*EN* II.4, 1105a28-1105a33)
> 
> 
> 



So, for example, if you return something you've borrowed, that
act exhibits the virtue of justice if and only if (1) you know that
you're returning what you borrowed, (2) you choose to do so
because it is the just thing to do, and for no other reason, and (3)
you are disposed to do the just thing across the range of
circumstances when the opportunity arises. In addition to justice and
temperance, Aristotle enumerates other ethical virtues like prudence,
generosity, and courage, as well as the intellectual virtue of
theoretical wisdom. In his view, each of these traits requires one to
meet the three conditions above. While he does not consider whether
creativity is a virtue, we may ask whether creativity also has these
three criteria. Does one have to meet these three requirements in
order to count as creative?



We'll begin with the third requirement to set it to one side.
Does a person's act count as creative only "if he does it
from a fixed and permanent disposition of character"? Examples
suggest otherwise. Consider the poet Arthur Rimbaud, who abandoned
poetry at the age of 21 to pursue a life of adventure. The fact that
he never produced another poem after that does not count against the
fact that he was a creative poet in his youth (B. Gaut 2014b). Unlike
the Aristotelian virtues, then, creativity does not have to be a
permanent disposition.



Even so, it would still be significant if creativity turned out to be
like an Aristotelian virtue in meeting the first two requirements. And
arguably, creativity does meet the first requirement. A person
doesn't count as doing something creative unless "he knows
what he is doing". This was already implied by the agency
condition for creativity discussed earlier.



Where things get interesting is with Aristotle's second
criterion for virtue. In order for your action to count as virtuous,
he says, you have to do it "for its own sake"--i.e.,
you have to do it because you value virtue as an end itself, and not
as a means to some external reward like praise, money, status, fame,
or winning a competition. Consider the virtue of generosity, for
instance. If you give money to someone in need merely because it will
make you look good in the eyes of your friends, then you aren't
really being generous. Your act may outwardly look like generosity,
but it's not the real thing. To exhibit real generosity, you
have to pursue generosity as an end in itself; you have to help others
just for the sake of helping others. Now contrast being generous with
being polite. If you compliment your colleague on the good work
she's done, then even if you're doing this in order to
manipulate her, you are being polite to her. You can have an ulterior
motive for being polite. So politeness is not a virtue the way
generosity is.



Is creativity a virtue in this respect? That is, does being creative
require acting creatively for its own sake? Matthew Kieran's
(2014a, 2014b, 2018) answer is a qualified yes. While he grants that
you can be motivated by external rewards to exhibit "minimal
creativity" in producing valuable new things, he maintains that
"exemplary creativity" requires you to be motivated by the
value of creativity itself. Thus, in his view, exemplary creativity is
a virtue.



To support this claim, Kieran points to a research program in
psychology which purports to show that creativity is driven by
"intrinsic motivation" rather than "extrinsic
motivation". A classic experiment in this program is "the
magic markers study", in which kids end up producing less
creative drawings when they are offered a prize (Lepper et al. 1973).
Many other studies have reported similar results, which lead Teresa
Amabile to conclude, at first without qualification, that creativity
is enhances by intrinsic motivation and hampered by extrinsic
motivation (Amabile 1983: 107).



Further research introduced complications. In some studies, subjects
were given "immunization techniques" whereby they were
first primed or trained to focus on intrinsically motivating factors
like the pleasure or aesthetical value of engaging in artistic
activities, and it was found that when they engaged in those
activities afterward, external rewards actually *enhanced*
their creativity.



As researchers interpreted these findings, offering reward can support
one's intrinsic motivation, provided that the reward works
either to boost one's sense of agency or to provide useful
feedback about what's working and what isn't. Intrinsic
motivation is still what fuels creativity, on this interpretation;
rewards help only indirectly, when they reinforce intrinsic
motivation. This lead Amabile to revise her hypothesis as the
Intrinsic Motivation Principle (IMP):



> 
> 
> Intrinsic motivation is conducive to creativity; controlling extrinsic
> motivation is detrimental to creativity, but informational or enabling
> extrinsic motivation can be conducive, particularly if initial levels
> of intrinsic motivation are high. (1996: 107)
> 
> 
> 



Kieran takes this as evidence for his claim that creativity, or at
least what he calls exemplary creativity, requires intrinsic
motivation and is therefore a virtue in that respect.



Objecting to this proposal, Gaut cites evidence that extrinsic
motivation is not always detrimental to creativity. In one study,
students in an introductory psychology class came up with more
creative short story titles if they were offered a financial reward
(Eisenberger & Rhodes 2001). In the studies where immunization
techniques were used, proponents of IMP argue that rewards enhance
creativity only indirectly, by buttressing intrinsic motivation. But
in this case no such techniques were used, and so it seems the
prospect of a reward enhanced creativity directly.



Further, Gaut argues that this point coheres with the role that
rewards seem to play in so many real-world cases of creative
achievement. In their quest to discover the structure of the DNA
molecule, Watson and Crick were driven "to imitate Linus Pauling
and beat him at his own game" (Watson 1968 [1999: 46]). Picasso
and Matisse were both spurred on by their rivalry with each other
(Flam 2003: 37). Paul McCready says he was driven to invent his
award-winning human-powered glider in 1977 because he needed the
prize-money to pay off his debts:



> 
> 
> I felt that I didn't have the time to mess with such things, but
> I had this strong economic motivation to take an interest in
> man-powered flight, so I charged around trying to figure out a way to
> solve it. (quoted in Sternberg & Lubart 1995: 242)
> 
> 
> 



One historian argues that in World War II the Poles beat the French in
cracking the Germans' Enigma Code because they were more
terrified of German invasion (Singh 1999: ch. 4). Gaut quips:
"Fear of death is a more powerful motivator than the intrinsic
satisfactions of code breaking" (Gaut 2014b: 196).



Finally, Gaut points out that even if IMP is true, it is only a
causal, probabilistic claim: intrinsic motivation is
"conducive" to creativity; extrinsic motivation is
"detrimental". But for a trait to be a virtue, intrinsic
motivation must be *conceptually necessary* for the exercise of
that trait. If we learn that someone gave to charity just to enhance
his reputation, we conclude that he wasn't really being
generous. By contrast, if we discover that someone created gorgeous
artwork just for the fame and glory, we may then lose some of our
admiration for her creativity, but we do not deny that she was being
creative.



Kieran could remind us that, in his view, intrinsic motivation is not
required for all creativity, but only for the special form of it that
he calls exemplary creativity. Anticipating this reply, Gaut says that
to distinguish between two forms of creativity is just to concede his
point. There are not two forms of generosity, one that requires
intrinsic motivation and another that does not. If your act of giving
isn't motivated by the right kind of reason, then it
doesn't count as an act of generosity at all. Thus, Gaut argues,
to grant the possibility of non-exemplary creativity is to grant that,
unlike generosity, creativity isn't a virtue in the traditional
Aristotelian sense.



Another way to examine relations between creativity and virtue is
through the lens of virtue epistemology. Linda Zagzebksi defines a
virtue



> 
> 
> as a deep and enduring acquired excellence of a person, involving a
> characteristic motivation to produce a certain desired end and
> *reliable success* in bringing about that end. (1997: 137,
> italics added)
> 
> 
> 



While there is a lot packed into this definition, what we'll
pinpoint here is the idea that virtue involves reliable success in
achieving a desired end, and that the agent who is epistemically
virtuous, in particular, is one who is reliably successful in
achieving knowledge. Knowledge requires truth, of course, so an
epistemic virtue is a trait that is "truth-conducive".
Epistemologists typically regard a process as truth-conducive to the
extent that the beliefs it produces are more often true than false.
But Zagzebksi proposes that a process or trait may be truth-conducive
in a different sense, insofar as it is necessary for advancing
knowledge in some area, even if it produces a very small proportion of
true beliefs. Creativity, she claims, is truth-conducive in this
sense, and thus it qualifies as an epistemic virtue (1997: 182). Also
note the emphasis on agency. In contrast to contemporary western
epistemology, virtue epistemology identifies the agent (rather than,
say her beliefs) as the essential locus of epistemic valence; it is
the agent who is epistemically good (or not). This emphasis comports
well with the proposal, discussed above, that the creator's
agency is necessary for genuine creative achievement. A
virtue-theoretic approach thus illuminates what may (as we will
discuss again later) be essential to creativity, namely, a process
that non-trivially involves a responsible agent.



We've seen that even after we fix a specific referent for the
term "creative"--whether it be a person, process, or
product--there are lively disagreements about what it means.
These debates often seem to presuppose that the term always expresses
the same concept, for which we can seek necessary and sufficient
conditions. But we've also seen that some theorists distinguish
between different concepts of creativity, corresponding to different
senses of the term "creative". In future work we may see
theorists develop such pluralistic approaches in more detail. The
trick, though, will be to give principled reasons for multiplying
different concepts of creativity so that the analyses do not simply
reduce to saying that anything goes.


## 3. Can Creativity be Learned?



There is a long tradition of thinkers who answer *no* to the
question above. Two of the most influential are from the eighteenth
century--Edward Young and Immanuel Kant--who were concerned
specifically with *genius*, the capacity for achieving the very
highest levels of creativity. In *Conjectures on Original
Composition* (1759), Young says,



> 
> 
> An *Original* may be said to be of a *vegetable* nature;
> it rises spontaneously from the vital root of genius; it
> *grows*, it is not *made* .... (1759 [1966: 7])
> 
> 
> 



His idea is that originality emerges naturally from something
implanted in us by nature, and it can only be hindered by learning.
Young seems to think of learning as proceeding either through
imitation or through the following of rules, and both, he thinks, are
detrimental to originality. Regarding imitation he writes,



> 
> 
> Born *Originals*, how comes it to pass that we die
> *Copies*? That meddling ape *Imitation*... destroys
> all mental individuality.... (1759 [1966: 20])
> 
> 
> 



And insofar as learning is "a great lover of rules", he
warns that it "sets rigid bounds to that liberty, to which
genius often owes its supreme glory" (1759 [1966: 13]).



Kant makes similar claims in his *Critique of Judgment* (1790).
Like Young, he takes genius to be a natural capacity, though a very
rare one:



> 
> 
> such a skill cannot be communicated, but is apportioned to each
> immediately from the hand of nature and dies with him. (1790: SS47
> 5:309 [2000: 188])
> 
> 
> 



It certainly cannot be learned through imitation:



> 
> 
> genius is entirely opposed to the *spirit of imitation*. Now
> since learning is nothing but imitation, even the greatest aptitude
> for learning, facility for learning (capacity) as such, still does not
> count as genius. (1790: SS47 5:308 [2000: 187])
> 
> 
> 



Nor can it be learned through rules, Kant holds, for genius is



> 
> 
> the talent (natural gift) that gives the rule to art ... the
> inborn predisposition of the mind (*ingenium*) *through
> which* nature gives the rule to art. (1790: SS46 5:307 [2000:
> 186])
> 
> 
> 



For Kant, a genius does not follow rules; a genius *invents*
the rules, indirectly, by creating exemplary works from which other
artists might extract rules and undertake "a methodical
instruction in accordance with rules" (1790: SS49 5:318
[2000: 196]).



Young and Kant are concerned with genius, specifically, but if we
extend their reasoning to creativity in general, as Berys Gaut (2014a)
has noted, we can discern two lines of argument:



> 
> 
> *The imitation argument*
> 
> 
> 1. All learning is a form of imitation.
> 2. Imitating someone or something is incompatible with being
> creative.
> 3. So, one cannot learn to be creative.
> 
> 
> 
> *The rules argument*
> 
> 
> 1. All learning consists in the following of rules.
> 2. Following rules is incompatible with being creative.
> 3. So, one cannot learn to be creative.
> (2014a: 266)
> 
> 
> 



Gaut points out, first of all, that both arguments are invalid. In
both cases, what the premises would entail is that learning cannot be
creative, that, in other words, you cannot *learn creatively*
(a claim about *how* you can learn). But even if that were
true, it wouldn't follow that you cannot *learn* *to
be creative* (a claim about *what* you can learn). If you
absorb the advice of a creative writing manual then this act of
learning may not itself be creative. But if the manual is
effective--and we'll see in a moment how it can
be--then what you will learn is how to become more creative.



Gaut also challenges the premises of these arguments. To start with
the first premise of the imitation argument, it simply isn't
true that all learning proceeds through imitation, as we learn many
things through direct experience, trial and error, and many other
means.



The second premise is also suspect. Something superficially close to
it is true: mere *copying* is incompatible with being creative.
But to the extent that we learn from others by imitating them, this is
not merely a matter of copying them. When a child learns to speak the
language of those around her, she doesn't simply parrot the
exact same sentences she hears; she absorbs the vocabulary and
underlying grammar in a way that enables her to form new sentences of
her own devising.



Now for the rules argument. Contrary to the first premise, it cannot
be the case that all learning consists in following rules, Gaut
argues, because for any given rule there will be hard cases where it
is unclear whether or how the rule applies to them, and so an
individual still has to use her own judgment in applying the rule.



The second premise is false too. Recall the distinction from
 SS3
 above between two kinds of rules. An *algorithm* serves as an
exact plan, specifying both the outcome and the path for getting to it
in exact detail. In contrast, a *heuristic* is a looser
"rule of thumb" that leaves room for an agent to exercise
her own judgment, choice, and creativity in determining whether, when,
and how to follow the rule. While algorithms, in this sense, may
preclude creativity, heuristics do not, which is why, as we'll
see below, the teaching of creativity so often takes the form of
heuristics.



There is a sense in which the question at hand can be answered
empirically: We can show that creativity *can be* taught simply
by pointing to cases where it *has been* taught. Gaut himself
discusses such examples as they occur in mathematics and fiction
writing, which we'll turn to below. But while such cases may
suffice to show *that* creativity can be taught, Gaut further
enriches our understanding by explaining *how this is
possible*. He does so partly by articulating and then debunking
the imitation and rules arguments to the contrary. But in addition, he
offers the following positive argument to show that creativity can be
taught and learned. He calls it "the constitutive
argument" because it begins with his view of what constitutes or
defines creativity itself.




*The constitutive argument*


1. Creativity is a disposition--involving both the
**ability** and the **motivation**--to
produce things that are new and valuable, and to do so in ways that
express one's agency through "the exercise of choice,
evaluation, understanding, and judgment" (Gaut 2014a: 273).
2. At least some people can learn to enhance their creative
**motivation**.
3. At least some people can learn to enhance their creative
**abilities**.
4. So, at least some people can learn to
become more creative.




Premise 1 recapitulates the point we've already seen Gaut and
others defend (in
 SS2.3
 above), that creativity is not merely an ability but a disposition or
trait, whereby the creative person is disposed or motivated to
exercise that ability when given the opportunity.



In support of premise 2, Gaut argues that you can strengthen both your
intrinsic motivation to be creative (when you take pleasure in your
creative activities), as well as your extrinsic motivation to be
creative (when you are rewarded with praise, grades, pay, etc. for
your creative efforts).



Defending premise 3, Gaut points out that you can develop your ability
to produce valuable new things by practising and strengthening the
relevant skills. And this development can be substantially aided by
learning certain heuristics.



Heuristics are indeed a staple of education in creative pursuits from
mathematics (draw the figure; consider special cases; consider extreme
cases; generalize the problem; look for a related problem,
etc.--see Polya 1945; Schoenfeld 1982, 1987a, 1987b) to
creative writing (write what you know; be specific and detailed in
describing sensory experiences; practice seeing similarities between
dissimilar things; show, don't tell, etc.--see Bell &
Magrs 2001; Anderson 2006; Maybury 1967; S. Kaufman & J. Kaufman
2009). Gaut also identifies several heuristics that might be used to
foster creativity in philosophy, even among children (cf. M. Gaut
2010; B. Gaut & M. Gaut 2011).



With this last theme, Gaut has a kindred spirit in Alan Hajek
(2014, 2016, 2017, 2018), who has independently proposed that by using
various heuristics, philosophers can enhance their abilities to make
valuable contributions to their field, including ideas that are
distinctively creative. It has been said that anyone of average talent
can become a strong chess player by learning and internalizing certain
*chess heuristics:* "castle early", "avoid
isolated pawns", etc. Analogously, Hajek suggests,
philosophy has a wealth of heuristics--*philosophical
heuristics*--although they have not been as well documented
and studied. Sometimes these take the form of useful heuristics for
generating counterexamples, such as "check extreme cases".
Sometimes they suggest ways of generating new arguments out of old
ones, as in "arguments involving possibility can often be recast
as arguments involving time, or space". Sometimes they provide
templates for positive arguments (e.g., ways of showing that something
is possible). Hajek offers a catalogue of such philosophical
heuristics to show that, contrary to a common assumption, creativity,
even in philosophy, can be compatible with, and enhanced by, following
rules.


## 4. Can Creativity be Explained?



Upon observing the work of creative people, it is natural to wonder:
How do they do that? How do people create? The issue we turn to now is
whether we could, at least in principle, answer this question
*scientifically,* using the methods of modern empirical
psychology and other cognitive and behavioral sciences. Those who take
a negative stance on this matter are not merely saying that, in
practice, it would be exceedingly difficult for science to explain
creativity. They are saying that it's altogether impossible that
science could ever explain creativity.



Hospers (1985) defends this kind of pessimism based on the variety and
complexity of creativity, given that creativity occurs not only in
art, but in science, theorizing of any sort, engineering, business,
medicine, sport, gaming, and so on. At least two worries may follow.
First, given the complexity of any one of these individual domains,
one might worry that there are simply too many variables to allow for
a clear explanation. Art provides a paradigmatic example. Consider an
artwork that you judge to be masterful (a sculpture, a painting, a
film). Now imagine attempting to describe or identify all the reasons
for which you think it is masterful. Take as much time as you like
but, the skeptic will urge, any long description you construct will
invariably strike you as woefully incomplete by comparison to the
artwork, and the experience thereof. So, if the creative achievements
of artists, in all of their complexity, cannot even be adequately
described, we have little reason to think that such achievements can
be explained.



How can theorists respond to these skeptical worries? Both the
complexity and generalizability worries might be partially disarmed by
noting analogies between creativity and other phenomena. For instance,
consider the range of bodily movement involved in some of the very
domains of activities listed above: art, science, engineering,
medicine, sport. The kinds of bodily action specific to these domains
are complex and vary dramatically: the relevant physical movements of
the surgeon are much different from the tennis player. However, it is
not plausible that this complexity and variety precludes explanation
of bodily action in those domains. It simply implies that some
features of the explanation will be context-sensitive, that is,
specific to that domain of activity. And further to the analogy: the
fact that the long description of, say, the tennis serve is incomplete
does not preclude it from being apt and explanatory. If this line of
reasoning is sound for bodily action, why not also for creative
action?



At this point, one might argue that while complexity and
generalizability worries would only show that creativity is difficult
to explain in practice, the very nature of creativity implies, more
strongly, that it could never be explained, not even in principle.
Resources to support this kind of pessimism may be adduced from
various past philosophers. We need to tread carefully, however, since
most of the figures we are about to consider were writing long before
the rise of the relevant sciences, so they could not have made any
explicit claim either way as to whether creativity could be explained
by those sciences. Nevertheless, some of them did make claims which
entail, or seem to entail, that creativity simply isn't the kind
of thing that could be explained through scientific inquiry as we
understand it today.



The classic expression of such a view comes from Plato. In his
dialogues, Plato features his teacher Socrates as a spokesperson for
his own views, and in the *Ion* he has Socrates argue that
poets do not produce poetry through knowledge or skill. When you
exercise a skill (*techne*), you apply techniques, rules,
or methods to perform a given activity, like charioteering, fishing,
or commanding an army. In principle, one could explain these
activities by identifying the techniques they involve, and a student
or apprentice could learn these activities by applying and practicing
those techniques. But poetry is not like that, in Socrates'
view. A poet can only imitate the application of rules or techniques,
mimicking the surface appearance of skill. Voicing an idea that was
familiar in Ancient Greek culture, Socrates suggests that poetry
emerges instead through divine inspiration, whereby a human being is
*inspired*--literally "filled with a spirit",
with a god or goddess, with a muse:



> 
> 
> You know, none of the epic [or lyric] poets, if they're good,
> are masters of their subject; they are inspired, possessed, and that
> is how they utter all those beautiful poems. ... [They] are not
> in their right minds when they make those beautiful lyrics, but as
> soon as they sail into harmony and rhythm they are possessed by
> Bacchic frenzy. [...] For a poet is an airy thing, winged and
> holy, and he is not able to make poetry until he becomes inspired and
> goes out of his mind and his intellect is no longer in him. As long as
> a human being has his intellect in his possession he will always lack
> the power to make poetry or sing prophecy. [...] You see,
> it's not mastery [*techne*] that enables them to
> speak those verses, but a divine power. That's why the god takes
> their intellect away from them when he uses them as his servants, as
> he does prophets and godly diviners, so that we who hear should know
> that *they* are not the ones who speak those verses that are of
> such high value, for their intellect is not in them: the god himself
> is the one who speaks, and he gives voice through them to us. In this
> more than anything, then, I think, the god is showing us, so that we
> should be in no doubt about it, that these beautiful poems are not
> human, not even *from* human beings, but are divine and from
> gods; that poets are nothing but representatives of the gods,
> possessed by whoever possesses them. (*Ion* 534a-d)
> 
> 
> 



Socrates repeats this view in the *Phaedrus*: "Some of
the greatest blessings come by way of madness, indeed madness that is
heaven-sent" (244a). He adds that while a poet may have some
kind of skill, anyone who aspires to make poetry purely by skill,
without the madness or the muse, will fail (245a).



It's important to note that "madness", for Plato, is
a supernatural affair. From the vantage of contemporary behavioral
science, we think of madness--or rather, mental illness--as
a pathology arising from some combination of genetic and environmental
factors, and those factors can be studied scientifically. So even if
creativity is linked to mental illness--a highly controversial
proposition--it could still be entirely within the scope of
science. However, Plato's talk of "madness" does not
refer to any naturally occurring pathology, but rather to the result
of divine intervention: the poet is taken over or
"possessed" by the muse and that is precisely why he is
"out of his mind". Plato's poet suffers
*divine* madness.



According to this story, then, the person we call a poet isn't
really a creator of poetry, but is merely the vessel through which a
divine being delivers poetry. If it is literally true that the source
of poetry is supernatural, then poetic creativity could never be
explained by science, which is limited to the investigation of natural
causes. (For more on Plato, see Asmis 1992.)



This kind of supernaturalism has enjoyed a long afterlife in Western
thought. In ancient Rome, the Latin term "*genius*"
referred to a guiding spirit that was thought to accompany each person
throughout their lives. The *genius* of an artist would
occasionally deliver art through that person in the manner of Platonic
inspiration.



Conceptions of the artist take a new turn when the idea of genius is
transformed in the eighteenth century. As we saw above, Immanuel Kant
defines *genius* as a natural capacity that a certain kind of
artist possesses innately and which partly constitutes that
artist's identity. So rather than saying that a gifted artist
"has a genius", Kant says that such a person "is a
genius". What distinguishes the genius is fundamentally an
imaginative capacity--an ability to engage in a "free
play" of imagination to produce artworks of "exemplary
originality". These works are exemplary not only in the sense
that they have artistic or aesthetic value, unlike "original
nonsense"; they are also exemplary in the more radical sense of
providing an exemplar--a new paradigm and precedent--for
lesser artists to follow. A work of genius sets a new standard of
artistic value, and, looking to that exemplar, lesser artists may then
extract techniques or rules for their own craft. The genius therefore
"gives the rule to art". In creating such works, the
genius does not follow any rules or methods. Instead the genius
creates art through a "free play of
imagination"--where the terms "free" and
"play" characterize the nature of an activity
unconstrained by any pre-established methods or rules:



> 
> 
> [G]enius ... is a *talent* for producing that for which no
> determinate rule can be given, not a predisposition of skill for that
> which can be learned in accordance with some rule .... (1790:
> SS46 5:307-8; 2000 trans., 186)
> 
> 
> 



Kant thought that genius, so conceived, is limited to the fine arts,
poetry being chief among them. Meanwhile, in Kant's view, there
is no room for genius in science, for example, where good theories and
hypotheses must emerge from the careful application of scientific
method, and so he said that even Isaac Newton, "that great man
of science", was not a genius. We'll soon consider why
this view might seem to entail that creativity is inexplicable, but
first it will be helpful to bring another figure, Arthur Schopenhauer,
who was deeply influenced both by Kant and by Plato.



Like Kant, Schopenhauer thought of genius as a natural capacity that
is limited to the fine arts. He also echoes Plato's sentiments
about madness, famously stating that "genius and madness have a
side where they touch and even pass over into each other"
(*The World as Will and Representation*, 1859, WWV I: 190), and
that "Genius lives only one storey above madness"
(*Parerga and Paralipomena*, SW 2:53, PP 2:49). In a state of
madness, Schopenhauer's genius is like Plato's poet in
experiencing a momentary loss of self, but what displaces the self is
not any divine being but rather a pure *Idea* which seizes the
author's being and becomes the object of both his fascination
and his artistic expression:



> 
> 
> We *lose* ourselves entirely in this object, to use a pregnant
> expression; in other words, we forget our individuality, our will, and
> continue to exist only as pure subject, as clear mirror of the object,
> so that it is as though the object alone existed without anyone to
> perceive it, and thus we are no longer able to separate the perceiver
> from the perception, but the two have become one, since the entire
> consciousness is filled and occupied by a single image of perception.
> (*World* WWV I: 178-179, SS34).
> 
>  
> 



With their focus on genius construed as a natural capacity, figures
like Kant and Schopenhauer abandon the supernaturalism of the Platonic
muse. Nevertheless, they retain the idea that
creativity--specifically genius-level creativity in the fine
arts--is not a matter of exercising a skill or applying given
rules, methods, or techniques.



As we noted earlier, these figures did not and could not have
explicitly denied that creativity could be explained by the sciences
of the twentieth and twenty-first centuries, but they are commonly
taken to represent such a denial (Kronfeldner 2018). Why?



Perhaps figures like Kant and Schopenhauer seem to make creativity, or
at least creative genius, inexplicable insofar they suppose it to be
innate and as they have no story to tell about how one came to acquire
an innate capacity except to say that it was either an accident of
chance (which is no explanation at all) or a gift from God (which
again is not a scientific explanation). But while these figures seemed
to think of artistic genius as being endowed entirely by nature with
no contribution from nurture, modern genetic theory rejects that
dichotomy. Instead of positing all-or-nothing natural abilities,
behavioral scientists today think in terms of genetically inherited
predispositions. In order for a genetic predisposition to develop into
a trait with an observable phenotype, it needs to be triggered and
shaped through a complex interaction between an organism's genes
and certain kinds of stimuli or environmental conditions. There are
still open questions about exactly how, and how much, genes and
environment feed into the development of any given trait, but
it's misguided to pose the binary nature-versus-nurture question
as if the two were mutually exclusive (see Tabery 2014). Many
researchers agree that some people have a stronger natural
predisposition toward creativity than others, and that genius-level
creativity partly stems from such a predisposition. Even so, the
predisposition itself can be understood scientifically in terms of
genetic heritability. (For a sampling of the relevant studies, see the
essays collected in S.B. Kaufman 2013.)



Perhaps creativity seems inexplicable according to these accounts
because it doesn't follow rules or methods. In order to explain
*how to* do something--how to build a boat or lead an army
etc.--perhaps I need to be able to identify the rules or methods
you should follow in order to practice and apply those skills.
*How-to* explanations are instructions. But scientific
explanations needn't be instructions. A lot of good science
explains *how* something happens--e.g., how heat melts ice
or how a bat navigates its environment by echolocation--without
explaining *how to* do it yourself.



Perhaps creativity seems inexplicable according to these accounts
because creators themselves do not know how they create. But a
scientific explanation needn't be available through
introspection. Most people cannot explain how their own digestive,
circulatory, or perceptual systems work, but scientists who study
those systems can.



Another line of thought is perhaps implicit in Kant but comes to the
fore in Schopenhauer, who says that "the nature of genius
consists precisely in the preeminent ability" to



> 
> 
> consider things independently of *the principle of sufficient
> reason*, in contrast to the way of considering which proceeds in
> exact accordance with this principle, and is the way of science and
> experience. (*World* WWV: I: 192, SS36)
> 
> 
> 



The principle of sufficient reason says that for every fact there is a
cause which completely explains that fact. So the defining ability of
genius is to see things in a way that transcends the causal order and
defies all explanation.



A version of this view is defended more recently by Carl Hausman (1975
[1984], 1979, 1985) who frames it in terms of novelty that creativity
involves. Hausman asserts that if a product is creative, it must be
*metaphysically novel* (or in his terms, "genuinely
novel") in the sense that it cannot be predicted from, or
explained by, prior events--not even in principle. Creativity is
therefore incompatible with causal determination and causal
explanation: "A causal view of explanation sets a framework for
ways of denying that there is anything new under the sun"
(Hausman 1984: ix). If something can be explained by prior causes, it
is not metaphysically novel, and is therefore, in Hausman's
view, not truly creative.



Against Hausman's skeptical charge, Maria Kronfeldner (2009)
argues that creativity is compatible with causal determination. First,
causal determinism does not preclude novelty or change. Determinism
says the emergence of new kinds of things can at least in principle be
predicted in advance. Importantly, though, when this prediction
becomes true, then something new is added to the world. Of course, not
all novelty instantiates creativity. The question is whether the kind
of novelty involved in creativity must be metaphysical novelty, which
is by definition incompatible with causal determination. This is
doubtful. Notice that, by definition, metaphysical novelty defies
natural laws. The production of something metaphysically novel would
therefore require supernatural powers. Traditional Western religions
conceive of *God* as performing the miracle of creation *ex
nihilo*. But are we positing a miracle every time we describe a
human artifact or achievement as creative? Surely not. As noted above,
human creativity is manifest in things that are novel relative to the
agent producing them or new to human history, but both of those kinds
of novelty (psychological and historical) are perfectly compatible
with causal determination. As Kronfeldner explains, creativity does
not preclude causes in general; it only precludes certain
*kinds* of causes. A creative product, she argues, must be
*original*--which means that it cannot be produced through
a process of copying something prior. And it must be
*spontaneous* (not produced through a routine or mechanical
procedure)--which means that it is to some extent independent of
the agent's intentional control and previously acquired
knowledge. (For more on originality and spontaneity, recall
 SS2.2
 above). Intuitively, the causes of something creative cannot simply
be a matter of copying or following a routine. But it may have causes
nonetheless, and cognitive science can investigate those causes, at
least in principle. Indeed, as we'll see next, it is doing so in
practice.


## 5. The Cognitive Science of Creativity



Although creativity has been relatively understudied by contemporary
philosophers, as we noted in
 SS1,
 it has been receiving a great deal of attention from psychologists
over the past few decades. In 1950, J. P. Guilford gave a presidential
address at the American Psychological Association calling for research
on the topic, and the field soon took off with waves of research
investigating the traits and dispositions of creative personalities;
the cognitive and neurological mechanisms at play in creative thought;
the motivational determinants of creative achievement; the range of
institutional, educational, and environmental factors that enhance or
inhibit creativity; and more. Today, the blossoming of this field can
be seen in the flurry of popular writing on its results; an official
division of the American Psychological Association for the psychology
of aesthetics, creativity, and the arts (Division 10); numerous
academic conferences; dedicated peer-reviewed journals (*Psychology
of Aesthetics*, *Creativity and the Arts*; *Creativity
Research Journal*; *Journal of Creative Behavior*;
*International Journal of Creativity and Problem Solving*);
special issues of journals (*Current Opinion in Behavioral
Sciences*, Takeuchi & Jung 2019); literature surveys
(Hennessey & Amabile 2010; Runco & Albert 2010; Runco 2017;
Glaveanu 2014; Williams et al. 2016); textbooks (J.C. Kaufman 2009;
Sawyer 2012; R. W. Weisberg 1986, 2006); and a comprehensive
encyclopedia (Runco & Pritzker 2020). According to one overview,
creativity has been studied by nearly all of the most eminent
psychologists of the twentieth century, and "the field can only
be described as explosive" (Albert & Runco 1999: 17). There
is also a groundswell of new work on creativity in the fields of
computer science, artificial intelligence (AI), and robotics.



The present section surveys empirical work in psychology along with
some related work in neuroscience, while the next section
 (SS6)
 covers research in computing, AI, and robotics. Throughout,
we'll see that philosophers are actively in dialogue with these
fields under the broad, interdisciplinary umbrella of cognitive
science.



The vast body of empirical research of creativity can be seen as
addressing a variety of issues, but the central question that concerns
us here is the one we identified above as the challenge for explaining
creativity: *How are people creative?* This question is
analogous to a number of other questions in cognitive science: How do
people perceive through sense modalities such as vision? How do they
form concepts? How do they acquire a language? How do they make
inferences? Just as psychologists investigate the psychological and
neurological processes, systems, and mechanisms at work in these other
mental operations, as well as the internal and external factors that
either enhance or hinder these operations, they are doing the same for
creativity. There is no pretension to achieving a *complete*
explanation which would include each and every causal factor, and
provide the basis for perfectly predicting creative outcomes in
advance. But to the extent that we identify some of the relevant
causal factors involved in creativity we thereby make progress in
explaining creativity, just as we do with other features of the
mind.



As we noted in
 SS2,
 the standard definition of creativity in psychology says that a
product (idea or artefact) is creative to the extent that it is both
new and valuable ("effective", "useful" or
"appropriate"), and, in turn, people and processes are
creative to the extent that they produce new and valuable things. As
we also noted, many psychologists do not actually employ this, or any,
definition of creativity in conducting their research. In one sampling
of studies of creativity published in peer-reviewed psychology
journals, only 38% of them included an explicit definition of
creativity (Plucker, Beghetto, & Dow 2004), as they rely in one
way or another on the assumption that we know it when we see it. For
example, many studies use the Consensual Assessment Technique (CAT),
whereby experimental subjects produce things that are then rated for
how creative they are by a panel of experts in the relevant field; so
paintings are rated by professional painters, stories by published
authors, etc. Many other research methodologies are used, as
we'll see below.



Empirical research on creativity departs in several ways from the
traditional approaches that seemed to place creativity outside the
scope of science. For starters, in stark contrast to Plato's
supernaturalism, empirical psychologists take creativity to be a
completely natural phenomenon. Creative people may of course be
"inspired" in the sense of feeling energized or filled
with ideas, but rather than being literally "breathed
into" by some god or muse, their thoughts and behaviors are
presumed to have causes that are perfectly natural. While it is
difficult in practice to identify these causes, they are not *in
principle* beyond the reach of science.



Further, the range of phenomena that contemporary researchers
countenance within the ambit of creativity is far broader and more
diverse than the traditional focus on poetry and the fine arts, as
creativity can be manifest in any kind of art or craft, as well as in
the sciences, technology, entrepreneurship, cooking, humor, or indeed
in any domain where people come up with ideas or things that are novel
and valuable in some way or another. Departing from Kant, genius, the
highest echelon of creativity, may be acknowledged in virtually any of
these domains, not just in the fine arts. And while a few researchers
(e.g., Simonton 1984, 1994, 1997, 2009; Root-Bernstein &
Root-Bernstein 1999) venture to examine genius (so-called
"Big-C" creativity), most of them focus instead on
relatively ordinary creative feats ("little-c" creativity)
including the kinds of story-making, drawing, and problem-solving that
can be elicited on command from regular people in experimental
settings. Some researchers propose that in order to understand how the
mind generates new ideas, we should begin with even more rudimentary
phenomena. For example, philosopher Jesse Prinz and psychologist
Lawrence Barsalou focus on how we form new concepts to categorize the
things we perceive, a process which they claim is creative, albeit in
a "mundane" rather than "exceptional" way
(Prinz & Barsalou 2002; Barsalou & Prinz 1997; cf. Child
2018).



Of course, many feats of human creativity, and the ones that are most
interesting, go far beyond the basic formation of concepts. A major
step toward explaining those feats is to recognize that what we call
"the creative process", as if it were a single, homogenous
phenomenon, is in fact an assembly of multiple stages or operations.
The simplest recognition of this fact is the *Geneplore* model
which distinguishes just two stages: *generating* ideas and
*exploring* ideas (Finke 1996; Smith, Ward, & Finke 1995).
This distinction may be seen as echoing one made by philosophers of
science in the early twentieth century, between the *context of
discovery* and the *context of justification* (Popper
1934). Other theorists posit up to eight stages of creativity (for a
summary of proposals, see Sawyer 2012: 89). But the most influential
stage-theory traces back to Henri Poincare's lecture,
"Mathematical Creation" (1908 [1913: 383-394]), in
which he identifies four phases in his own innovative work as a
mathematician:


1. conscious hard work or *preparation*,
2. unconscious *incubation*,
3. *illumination*, and
4. *verification*.



In his book, *The Art of Thought* (1926), the psychologist
Graham Wallas endorses Poincare's four stages with
corroborating evidence from the personal reports of other eminent
scientists like Hermann von Helmholtz. Wallas's scheme, as a
development of Poincare's, is still the one that is most
widely cited, and we employ a version of it here with some slightly
different terminology and with two more substantive alterations:
instead of "incubation", we identify the second operation
more generally as the "generation" of ideas, which may
include unconscious incubation but may also occur in conscious,
deliberate thought; and we add "externalization" for a
total of five operations:


1. *Preparation*--You invest a great deal of effort
learning and practicing in order to acquire the knowledge, skills, and
expertise required for work in a given domain.
2. *Generation*--You produce new ideas, whether through
conscious reflection or unconscious incubation.
3. *Insight*--You consciously experience the emergence of
a new idea, which would strike you with a feeling of surprise:
"Aha!", "Eureka!"
4. *Evaluation -* You assess the idea to determine
whether it should be discarded, retained, revised, or amended.
5. *Externalization*--You express your idea in a
concrete, observable form.



Artists provide compelling examples (though not the only ones) of each
of these five operations. Such examples can be especially illustrative
since they come straight from the artists' mouths, as they
reflect upon, and share, their creative process. The twentieth century
painter Jacob Lawrence was known for painting in the style of visual
narratives. Lawrence developed a system, much like a filmmaker's
storyboard, for the preparation of these paintings. He would lay as
many as 60 wood panels on the studio floor, each with individual
scenes and sometimes with captions. From these storyboards, Lawrence
would generate and evaluate ideas and insights for a visual narrative,
culminating in the paintings such as those in his *Migration
Series* (see Whitney Museum, 2002, in
 Other Internet Resources).
 Toni Morrison, the Nobel prize winning novelist, remarks on the
labors and sustained effort required at the preparation, generation,
evaluation, and externalization stages of a creative writing process.
Commenting on her novel *Jazz*, she says,



> 
> 
> I thought of myself as like the jazz musician--someone who
> practices and practices and practices in order to be able to invent
> and to make his art look effortless and graceful. I was always
> conscious of the constructed aspect of the writing process, and that
> art appears natural and elegant only as a result of constant practice
> and awareness of its formal structures.
> 
> 
> 



She further notes that insight does not always come in a flash,



> 
> 
> [I]t's a sustained thing I have to play with. I always start out
> with an idea, even a boring idea, that becomes a question I
> don't have any answers to. (T. Morrison 1993)
> 
> 
> 



Writer Ishmael Reed claims that insight can come unexpectedly and in
various contexts:



> 
> 
> One can find inspiration from many sources. The idea of *Japanese
> by Spring* originated in a news item that claimed the endowment to
> a major university was traced to Japanese mob, the Yakuza. *Flight
> to Canada* began as a poem. *The Terrible* series began
> when I heard someone at party mention that there was a black figure,
> Black Peter, in the Dutch Christmas, and by coincidence I was invited
> to the Netherlands shortly afterwards, where I witnessed the arrival
> of Saint Nicholas and Peter on a barge that floated into Amsterdam
> with crowds looking on. I took photos of the ceremony ....
> (Howell 2020: 91)
> 
> 
> 



And with signature profundity, James Baldwin suggested that all
elements of the creative artistic process, from preparation to
externalization, require a basic enabling condition: being (and
willing to be) alone (Baldwin 1962).



As Wallas recognized (1926: 81), and as the above examples suggest,
the "stages" of the creative process are not necessarily
discrete steps that follow one another in a tidy sequence. Creative
work is messy: over time you have numerous ideas, keeping some and
abandoning others in multiple rounds of trial-and-error; you incubate
new ideas for one problem while you're busy externalizing your
ideas for another; and your moments of insight, evaluation, and
externalization trigger further generative processes that send you
cycling through these operations many times over. It's still
important to distinguish these operations, however, because, as
researchers are confirming, they are enabled and influenced by
different causal factors.



Among the additional stages that researchers have posited, one of the
most widely discussed is known as *problem-finding.*
Psychologists often conceptualize creative thought in terms of
problem-solving: the ideas generated within the creative process are
seen as candidate solutions to a given problem--where
"problems" are broadly construed to include any creative
aim, like that of producing a particular kind of artwork or proving a
particular theorem, etc. (Flavell & Draguns 1957: 201; Newell,
Shaw, & Simon 1962). But following some early work by Mihalyi
Csikszentmihalyi (1965), many researchers came to appreciate that a
lot of creative work is done not just in solving problems but in
*finding* the right problem to begin with (Abdulla et al. 2020;
Csikszentmihalyi & Getzels 1970; Getzels 1965; Getzels &
Csikszentmihalyi 1975). While we agree that problem-finding often
plays a key role in creativity, we have not assigned it to a separate
stage, for the following reasons. Consider that you might settle on a
problem to work on in either of two ways. On one hand, you might
choose a problem to work on from a pre-existing menu of options. In
that case, your choice would fall under the *evaluation* phase;
it's just that the idea you select is a problem that calls for
the pursuit of further ideas. If, on the other hand, you develop a
*new* problem, you would thereby be engaging in the
*generation* of a new idea--the new problem--which
may emerge in a moment of *insight*. Einstein and his colleague
celebrated the novelty in such problem-finding:



> 
> 
> The formulation of a problem is often more essential than its
> solution, which may be merely a matter of mathematical or experimental
> skill. To raise new questions, new possibilities, to regard old
> problems from a new angle, requires creative imagination and marks
> real advance in science. (Einstein & Infeld 1938: 92)
> 
> 
> 



Either way--whether you "find" a problem by picking a
pre-existing one or by coming up with a new one
yourself--problem-finding, though important, does not need to be
seen as an additional operation beyond the five listed above;
it's just a special case of generation, insight, or
evaluation.



The next five sub-sections will respectively examine the five
operations of creative work. Notice that three of
them--preparation, evaluation, and externalization--are
uncontroversially ordinary activities that involve no apparent
mystery; it's a challenge to explain them but no one is tempted
to regard them as inexplicable or as violating the laws of nature. As
we saw in
 SS4,
 traditional skepticism about the possibility of explaining creativity
is really focused on the two remaining phenomena: the
*generation* of new ideas
 (SS5.2)
 and the experience of *insight* whereby an idea seems to come
out of the blue, as if from a god
 (SS5.3).


### 5.1 Preparation



It's myth that outsiders are more creative. To put yourself in a
position to create anything of value, you have to spend a great deal
of time and effort acquiring the relevant knowledge, skills, and
expertise. In what has come to be called "the ten-year
rule", Howard Gardner (1993) found that, on average, people
spend about 10 years learning and being immersed in a domain before
they make any significant creative contribution to it.



Though a certain amount of rote learning is required, gaining mastery
in a field is not simply a matter of passively absorbing information.
Much of it involves what Anders Ericsson calls *deliberate
practice,* where you focus on tasks which are a little beyond your
current abilities, but which you eventually conquer through feedback
and repetition. Across a variety of domains--including physics,
medicine, programming, dance, and music--Ericsson found that, on
average, world-class performance becomes possible for people only
after 10,000 hours of deliberate practice in their chosen activity.
This finding also converges on the ten-year rule, because if you
engage in deliberate practice four hours a day, five days a week, that
would add up to 10,000 hours in ten years (Ericsson, Krampe, &
Tesch-Romer 1993; Ericsson et al. 2006).



However, there seems to be a point at which too much formal training
can dampen creativity. Simonton (1984: 70-73) has reported that
the relationship between creativity and education level is an
inverted-U, as too much schooling can reinforce familiar,
pre-established styles of thought. Even so, the point remains that,
before you run into diminishing returns, years of preparatory learning
and practice are required for exceptional creativity.


### 5.2 Generation



In this section we discuss four kinds of mental capacities or
processes that researchers have posited for generating new ideas.


#### 5.2.1 Blind Variation



Psychologist Donald T. Campbell (1960, 1965) proposed that creative
thought proceeds through "blind variation and selective
retention (BVSR)". The "variations" he refers to are
the various ideas that might occur to a creator, and the process of
generating them is "blind" to the extent that it is not
guided or directed by prior knowledge of how valuable or useful they
will be: "Real gains must have been the products of explorations
going beyond the limits of *foresight* or *prescience*,
and in this sense blind" (Campbell 1960: 92, emphasis added).
Once ideas have been generated, however, there is a subsequent stage
where the creator selectively retains some of those ideas while
discarding others, and Campbell says this stage is
"sighted" rather than blind since it *is* guided by
the creator's judgments as to which ideas are valuable. While
there is little debate that selective retention is sighted in this
sense, there has been more controversy over whether the initial
production of ideas is, by contrast, blind.



In his prolific body of work, Dean Keith Simonton has extended and
refined Campbell's proposal. His work nicely illustrates the
interdisciplinary nature of creativity research as he, like Campbell,
is a psychologist who engages with philosophers, some of whom are
broadly sympathetic to the BVSR theory (Briskman, 2009; Nickles,
2003), while others are skeptical (Kronfeldner 2010, 2011, 2018). In
earlier writings Simonton suggested, in a way Campbell did not, that
BVSR is to be understood on the model of Darwinian evolution (Simonton
1999a, 1999b). But Simonton (forthcoming: 2-3) has come to
rescind the Darwinian framing of BVSR, conceding that it is
misleading. Reprising Campbell's core idea, he says that a
process of generating an idea is blind to the extent that it is not
guided by "the creator's prior knowledge of the
variation's utility" (Simonton forthcoming: 5; cf.
Simonton 2011, 2012a, 2012b, 2018). He stresses that blindness is not
all-or-nothing; it comes in degrees. An example of a highly sighted
process is that of using the quadratic formula to find the roots of a
quadratic equation: you know in advance that if you apply the formula
correctly, it will yield the correct answer. Examples of relatively
blind processes include remote association and mind wandering.


#### 5.2.2 The Default-Mode Network



Despite the foregoing criticism of BVSR, recent neuroscientific
studies suggest a network of brain activity that may serve the blind
variation role. Brain activity doesn't cease when one is not
focusing on a task, when one is at rest, daydreaming, and so on.
Following this insight, researchers have used neuroimaging methods to
identify what is now called the *default mode network* (DMN).
The precise anatomy of this network is still a matter of
investigation, but it is supposed to be less active when one is
focused on an external task (say a problem in the real world or in the
lab) and more active when one is not so focused (Raichle et al. 2001;
Buckner & DiNicola 2019). Notice then, that while this network is
not creativity-specific--it is supposed to be active during
memory recall, imagining future events, daydreaming, and so
on--it does seem especially well-suited for creativity, and
particularly for the random idea generation hypothesized by the BVSR
(Jung et al. 2013). Creativity researchers in these fields often refer
to this more "free" production of ideas as
"divergent thinking", and some argue on the basis of
neuroimaging studies that creative thought requires cooperation
between this mode of thought as well as that under "executive
control". As one team puts the point,



> 
> 
> In general, we contend that the default network influences the
> generation of candidate ideas, but that the control network can
> constrain and direct this process to meet task-specific goals via
> top-down monitoring and executive control.. (Beaty, Benedek, et al.
> 2016; see also Mayseless, Eran, & Shamay-Tsoory 2015; Beaty, Seli,
> & Schacter 2019; Chrysikou 2019)
> 
> 
> 



Notice how well this comports with both the Geneplore and the BVSR
frameworks, perhaps identifying a way to keep some of the insights of
both without commitment to a special creativity mechanism after
all.


#### 5.2.3 Imagination



At least since Kant, theorists have identified an important link
between creativity and imagination; indeed, the two are sometimes
unfortunately conflated. Construed broadly, imagination can take
various forms: sensory imagery, propositional imagination,
supposition, free association. Berys Gaut (2003, 2009, 2010) and
Stokes (2014, 2016) have both recently argued that, although
imagination and creativity are distinct, imagination is especially
well-suited to creative thought because of its characteristic
flexibility. They both agree that imagination is decoupled from action
(Gaut 2003) and "non-truthbound" (Stokes 2014) in the
sense that, unlike belief, imagination is not limited by the proper
function of accurately representing (some part of) the world. This
freedom or playfulness of imagination is crucial to generating new
ideas, since it allows one to safely "try out" hypotheses,
conceptual combinations, strategies for solutions, and so on, without
epistemic or behavioral commitment.



A series of studies illustrates both the need for non-truthbound
capacities in creative thought, as well as the difficulty of employing
them. When people--children and adults alike--are asked to
imagine and draw non-existent houses, people, or animals, they depict
things that are strikingly similar to their familiar counterparts in
the real world: imagined people, for example, were generally drawn
with some version of a head, limbs, eyes, and so forth.
(Karmiloff-Smith 1990, 1992: 155-61; Cacciari et. al 1997; Ward
1994, 1995). This suggests that we are highly constrained in our
creativity by the concepts we already have. Concepts of existing
things are truth-bound: your concept of an animal, for example, has
the proper function of accurately representing the range of things
that are in fact animals. When you try to envision a new, fictional
kind of animal, you begin with a mental image that exemplifies your
existing concept of animal, which is why you are constrained by that
concept. You then have to *manipulate* your initial image,
varying its features in ways that abandon the aim of accuracy, using a
capacity that isn't truthbound. Generalizing this point yields
the *c**ognitive manipulation thesis*, according to
which creative thought requires cognitive manipulation, which involves
thinking in ways that are not bound to the truth (Stokes 2014: 167).
Plausibly, imagination is the mental capacity which is best suited to
serve in this cognitive manipulation role. In the studies just cited,
subjects must use their imagination to manipulate their existing
concepts so as to form new ideas.



Recent empirical research on visual imagery seems to corroborate this
claim. Various studies have identified positive correlations between
creative problem solving and visual image generation, image
transformation, and vividness of imagery (Finke 1990, 1996; Zemore
1995; R. Morrison & Wallace 2001; Perez-Fabello and Campos
2007). A more recent study highlights the importance of image
transformation ability--the ability to mentally manipulate a
given image--and the ability to achieve high degrees of visual
creativity. Further, the results of this study suggest that although
vividness negatively correlates with the practicality of images
created, vividness positively correlates with novel idea generation
(Palmiero et al. 2015). The novelty involved is minimal, but again it
appears that imagination, here in the form of imagery, well serves the
role of cognitive manipulation.



Stokes observes further that we can voluntarily control imaginative
states (in contrast with other non-truthbound states, like desires and
wishes). And because imagination connects in important ways with
inferential systems, as well as affective systems, the thoughts it
produces can often be integrated with knowledge and skills to
formulate an innovative strategy or solution to a problem. Finally,
this role for imagination in creativity is not exclusive to the rich
creativity of artists and scientists, but indeed seems to characterize
the minimally creative behavior that we all enjoy. This claim is
partly motivated by the empirical research just discussed. Here, as in
the more radical cases, instances of novel achievement or learning by
subjects requires more than rote memorization; it requires cognitive
manipulation of the information in the relevant conceptual space
(e.g., combining concepts about houses and persons). This kind of
cognitive activity is best done by using the imagination.



Peter Carruthers has argued that imagination is important to
creativity on evolutionary grounds (2002, 2006; see also Picciuto
& Carruthers 2014). Like the above analyses, he focuses on the
playfulness of imagination. Pretend play typically develops early in
childhood in humans. And imagination in adults provides the right
mechanisms for generating and exploring ideas (just as required by the
Geneplore model). Carruthers argues that imagination evolves under
adaptive advantage as a kind of practice for adult
creativity--and may have been accordingly selected for, aligning
with the putative creativity explosion of 40,000 years ago (Mithen
1996, 1998; Harris 2000). This, he argues, is the most parsimonious
explanation of both the emergence and the ubiquity of creativity in
the human species. See B. Gaut (2009) for a critique of
Carruthers' analysis.


#### 5.2.4 Incubation



While we may generate ideas consciously in imagination, we may also do
so during a period of unconscious incubation, when we are focused on
something else. This point is illustrated by any number of famous
stories, though some are probably embellished after years of
retelling. Isaac Newton witnessed an apple fall from a tree (on some
accounts, falling upon Newton's head) and thereby found the
insight for his laws of gravity. August Kekule is reported to
have discovered the structure of the benzene molecule while
daydreaming of a serpent circling upon and seizing its own tail. Henri
Poincare alleged that, while boarding a bus, he enjoyed a
needed flash of insight that led to his discovery of non-Euclidian
geometry. Richard Feynman, the Nobel prize winning physicist, claimed
to find inspiration while sipping soda and doodling at adult clubs.
And Einstein reported:



> 
> 
> I was sitting in a chair in the patent office at Bern when all of a
> sudden a thought occurred to me. "If a person falls freely he
> will not feel his own weight". I was startled. This simple
> thought made a deep impression on me. It impelled me toward a theory
> of gravitation. (Einstein, "Kyoto Lecture", translated and
> quoted in Pais 1982: 179)
> 
> 
> 



In each case, someone is suddenly struck with a flash of insight about
one thing while engaged with something else entirely. The
empirically-minded theorist rejects the notion that such ideas arise
*ex nihilo* or through divine possession. So how are they
explained in terms of natural mental phenomena?



Arthur Koestler, partly inspired by the work of Henri Poincare
(1908 [1913]), hypothesized that during creative thought processing,
ideas are combined in novel ways, and this combination is performed
largely *unconsciously*, by what Poincare called the
subliminal self (Koestler 1964: 164-5). For Poincare
there are only two ways we might think of the unconscious. One, we
might think of the unconscious in Freudian terms, as a self capable of
careful and fine discernment and, importantly, distinctions and
combinations that the conscious self fails to make. Alternatively (and
this is the option favored by both Poincare and Koestler), we
can think of the unconscious as a sub-personal automaton that
mechanically runs through various combinations of ideas. Importantly,
this unconscious process (or, if one likes, automaton) generates
random conceptual associations and ideas. And these can then be
further considered, examined, explored, and revised.



These behavioral methods can be combined with contemporary
understanding of neural plasticity and the effects of cognitive effort
and attention. Neuroscientists have long recognized that the human
brain is *plastic*--stable in genetic material but
constantly undergoing functional change and development in neural
networking in response to external stimuli, with the work of Donald
Hebb in the middle of the twentieth century being one important early
precedent. As Hebb put it, neural cells that "fire together,
wire together". *Cell assemblies* thus form as a result
of the synchrony and proximity of the firing of individual cells.



> 
> 
> [A]ny two cells or systems of cells that are repeatedly active at the
> same time will tend to become "associated", so that
> activity in one facilitates activity in the other. (Hebb 1949 [2002:
> 70])
> 
> 
> 



And continued attention to a problem, what some have called
*cerebral effort*, causes changes in the networking of the
brain's cortex (Donald 2001: 175-8). Importantly, these
changes can continue to take place, to "reverberate" even
after one has removed attention from that problem. This motivates a
simple (and somewhat unsurprising) hypothesis: attending to and
performing cognitive tasks affects neural networking (Posner et al.
1997; Posner & Raichle 1994; see also Kami et al. 1995), and those
changes can involve strengthening of synaptic connectivity (which
correlate with conceptual connections and associations). These
changes, again, can occur both when one is attending to a task and
after one has diverted attention elsewhere. And, finally, the latter
goes some way to explain a moment of insight after incubation (the
so-called incubation effect): when one returns attention to the target
problem, new or newly strengthened neural connectivity (as a result of
previous cognitive effort) can give rise to a new idea. And because
that neural process is not in any sense *done by* you, the
emergence of the new idea can feel like a burst of insight (see Stokes
2007; Thagard & Stewart 2011; Ritter & Dijksterhuis 2014; and
Heilman 2016).



There are also various recent studies on closely related topics: on
mindwandering and spontaneous thought (Christoff et al. 2016; Irving
& Thompson 2018; Murray et al. forthcoming), on so-called
"divergent thinking" (Mekern et al. 2019), and more on the
neural basis of insight (Jung-Beeman et al. 2004; Bowden et al. 2005;
Limb & Braun 2008; Dietrich & Kanso 2010; Kounios & Beeman
2014).


### 5.3 Insight



It should be intuitive that creativity often involves solving problems
and doing so in interesting or surprising ways. In exceptional cases,
the individual identifies a problem solution that perhaps no one
(including the creator) anticipated. But there are countless examples
of more mundane instances of problem solving, where the solution may
be surprising (or especially interesting) to only a few individuals,
perhaps even only to the problem solver. One broad, standard
experimental method used by researchers thus focuses on
*insight* in problem solving. Some problems (thankfully!) can
be solved by straightforward appeal to memory, or by applying some
technique or method of calculation in a mechanical way. Solving the
problem may still take time and effort, but the solution will come so
long as one executes the appropriate strategy or applies the relevant
knowledge from memory. An insight problem, by contrast, typically
requires something new on the part of the individual, and one must
often "change views" of the structure of the very problem.
Predictably, there are a variety of definitions or characterizations
of "insight" in the literature. Here are two recent,
representative examples. Bowden et al. suggest that insight occurs



> 
> 
> when a solver breaks free of unwarranted assumptions, or forms novel,
> task-related connections between existing concepts or skills. (Bowden
> et al. 2005: 322)
> 
> 
> 



More recently, Kounios and Beeman write,



> 
> 
> we define insight as any sudden comprehension, realization, or problem
> solution that involves a reorganization of the elements of a
> person's mental representation of a stimulus, situation, or
> event to yield a nonobvious or nondominant interpretation. (2014:
> 74)
> 
> 
> 



Some early studies on these phenomena centered around a familiar
observation. Consider the tip-of the-tongue phenomenon, when you know
that you know some bit of information (an actor's name or the
title of a song) but, try as you may, you just can't recall it.
It often helps to give up for a moment and allow the memory to surface
without effort. Researchers found that the same
approach--forgetting about a problem--works well to overcome
fixation on ineffective ideas so as to allow the actual solution to
pop up. Smith and Blankenship primed two groups of subjects with
inappropriate or misleading solutions to problems. They left one group
to continue struggling with the same problem, while they distracted
the second group with a distinct but cognitively demanding task. The
second group thereby overcame fixation and outperformed the first
group when returning attention to the original target problem (Smith
& Blankenship 1989, 1991; see also Smith, Ward, & Finke
1995).



In the context of creativity in particular, there is precedent, or at
least overlap, in Colin Martindale's cortical arousal theory.
This theory centers around the nature of focuses of attention
(Martindale 1977, 1981, 1995, 1999; Martindale & Armstrong 1974;
Martindale & Hines 1975). Martindale proposes a multi-stage model
of problem solving, which if the right mechanism is possessed, leads
to creative thought. In the initial stages, information is gathered,
various approaches are taken to the problem, and there is a high level
of cortical arousal with a narrow focus of attention. As information
increases and the problem remains unsolved, two kinds of responses may
occur. The first kind of response is to keep attempting the same
solutions to the problem such that the arousal and attention focus
stay high and narrow, respectively. Alternatively, some persons
experience a decrease in cortical arousal coupled with a wider range
of attention focus. Information then enters what Martindale calls
primary processing: a kind of subconscious cognition not under the
complete control of the agent. It is this kind of processing, and the
arousal mechanisms that enable it, that distinguish creative insight
or achievement from non-creative ones. The first kind of response
typically results in frustration and failure (fixation), while the
second often results in creative insight.



There are at least two, separable components of insight thus
understood. First, an insight problem requires non-mechanical or
non-algorithmic solution, and this in turn requires some kind of
conceptual reorganization. A hackneyed phrase may come to mind here:
one has to "think outside the box".



The second element of insight as understood here is subjective or
phenomenological. An insightful problem solution is often described as
occurring suddenly and with little or no apparent effort. It is an aha
moment, even if less dramatic than the traditionally romanticized
Eureka moment. One way researchers have tested for this subjective
feature is to ask subjects to report nearness or "warmth"
relative to solving a problem. They find that for insight problems, by
contrast to non-insight problems, subjects report that as they near
solution they experience abrupt changes in the sense of warmth for
solving the problem (Metcalfe & Wiebe 1987; see also Dominowski
1995; Laukkonen & Tangen 2018). More recently, researchers have
begun to employ neuroimaging techniques to study insight and
insightful problem solving (Luo & Niki 2003; Mai et al. 2004).



First, researchers have developed methods for using subjective report,
where subjects rate whether they felt that they used insight in
solving a designated problem (Bowden et al. 2005). And second, and
coupled with those report methods, researchers have developed simple
problems that can be solved with insight. One such example is the
"Compound remote associates problem" (CRA). Here is an
example of a CRA problem:



> 
> 
> Each of the three words in (a) and (b) below can form a compound word
> or two-word phrase with the solution word. The solution word can come
> before or after any of the problem words.
> 
> 
> 1. french, car, shoe
> 2. boot, summer,
>  ground[1]
> 
> 
> 
> (Bowden et al. 2005: 324)
> 
> 
> 



Because of their simplicity, these problems can be solved
unambiguously and quickly, and with this speed comes better potential
for neuroimaging study. In instances where subjects report insight
solutions to these kinds of problems,



> 
> 
> EEG shows a burst of high-frequency (gamma-band) EEG activity over the
> right temporal lobe, and fMRI shows a corresponding change in blood
> flow in the medial aspect of the right anterior superior temporal
> gyrus (Jung-Beeman et al. 2004). (Kounios & Beeman 2014: 78)
> 
> 
> 



The question for neuroscientists is whether this convergence of
evidence is sufficient to establish neural correlates of insight.


### 5.4 Evaluation



A moment of "insight" can be misleading, as what initially
strikes you as a promising idea may ultimately turn out to be a dead
end. You may have countless ideas in the course of undertaking a
complex creative project, while only a few of them will make the final
cut. A crucial part of your creative work therefore consists in
evaluating your ideas. For any idea that occurs to you, you might have
to ask: Will this work? Is it new? How does it fit in with other parts
of your project? Do you have the resources and abilities to bring it
to fruition? Is it worth the time and effort?



Much of the research on this phase of the creative process is
concerned to identify and categorize the range of factors that people
take into consider as they evaluate their ideas (Blair & Mumford
2007; Dailey & Mumford, 2006). Unsurprisingly, those factors vary
from one domain to another. New culinary dishes are judged by factors
like aroma, taste, texture, color, presentation (Horng & Lin
2009), whereas improved musical performances are judged according to
their complexity, originality, and technical virtuosity (Eisenberg
& Thompson 2003), and so on. Your understanding of the relevant
factors is part of your internalized model of the domain (Bink &
Marsh, 2000; Csikszentmihalyi & Sawyer 1995). And since you
acquired and refined that model through years of preparation, your
capacity for evaluation is largely a consequence of your efforts from
that initial stage.



Somewhat more surprisingly, there is some evidence that people who are
good at evaluating ideas are also good at generating them (Runco 1991;
Runco & Dow 2004; Runco & Chand 1994; Runco & Vega
1990).



Other studies support what Sawyer calls Sawyer (2012: 131) calls the
*productivity theory,* which says that the best way to get good
ideas is to have lots of ideas and just throw away the bad ones. In
historiometric studies, Simonton found that creators who yielded the
greatest number of works over their lifetimes were mostly likely to
produce works that were significant and stood the test of time. Even
more striking, he discovered that, from year to year, the periods when
creators were most productive were also the ones in which they were
most likely to do exceptional work (Simonton 1988a, 1988b). Linus
Pauling, who won the Nobel Prize in Chemistry in 1954 as well as the
Nobel Peace Prize in 1962, summed up the productivity theory in a
famous remark:



> 
> 
> If you want to have good ideas you must have many ideas. Most of them
> will be wrong, and what you have to learn is which ones to throw away.
> (quoted by Crick 1995 [time 34:57])
> 
> 
> 


### 5.5 Externalization



The final operation of the creative process--externalizing
ideas--may involve any number of disparate activities, which
Keith Sawyer sums up as follows:



> 
> 
> Creativity research has tended to focus on the early stages of the
> eight-stage creative process--particularly on the idea-generating
> stage. But a lot has to happen to make any idea a reality. Successful
> creators are skilled at executing their ideas, predicting how others
> might react to them and being prepared to respond, identifying the
> necessary resources to make them successful, forming plans for
> implementing the ideas, and improvising to adjust their plans as new
> information arrives. These activities are important in all creativity,
> but are likely to be even more important in practical domains such as
> technological invention and entrepreneurship (Mumford, 2003;
> Policastro & Gardner, 1999). (Sawyer 2012: 133-4)
> 
> 
> 



It may be tempting to assume that the real creative work is finished
once a new idea emerges in the moment of insight, and that
externalization is just the uncreative, mechanical chore of making the
idea public. But a closer look at the phenomenon reveals that
externalization is often integral to creativity itself.



Vera John-Steiner (1985) interviewed, and examined the notebooks of,
over 70 exceptional creators (ranging from author Anais Nin to
composer Aaron Copland), and consulted the notebook of another 50
eminent historical creators such as Leo Tolstoy and Marie Curie. A
recurring theme throughout was that at the beginning of each creative
endeavor and continually throughout its development, creators
manipulate and build upon their impressions, inklings, and tentative
hunches using sketches, outlines, and other external
representations.



Perkins (1981) corroborated this finding by analyzing the 61 sketches
Picasso made en route to painting his famous work, *Guernica*,
as well as Beethoven's musical drafts and Darwin's
notebooks. In each case, the artist progressed by engaging with
external representations.



Other studies found that people discovered and solved more problem
when they used sketches during a task (Verstijnen 1997), and that
people come up with better ideas for improving inventions when they
work with visual diagrams (Mayer 1989).



One reason externalization is so vital to substantial creative work is
because of our limited capacity to consciously hold and manipulate
information in our minds. It helps to offload ideas and store them in
the form of physical symbols and expressions in order to free up space
for the mind to examine those ideas at arm's length while
entertaining new ones. Thus research shows that internal strategies
like mental visualization can help with relatively simple tasks, but
for more complex projects externalization is key (Finke et al. 1992:
60).


### 5.6 Worries and future directions



We close our survey of the cognitive science of creativity with a
brief discussion of some general worries about current work, and some
prescriptions for future research.



Some have worried about the validity of the psychometric measures
employed in neuroimaging studies. One such concern regards the
confidence that we should have that the tests employed are really
tracking creative behavior. This is of course a general problem,
partly symptomatic of the challenges that come with defining
creativity (like other phenomena) and with the special challenges that
attach to features such as insight and incubation. But there are
particular challenges that come with using neuroimaging technologies
such as fMRI scanning to attempt to study naturally occurring
phenomena. Use of this technology is almost invariably ecologically
invalid--one cannot run an fMRI in the artist's studio. And
because of the cost and sensitivity of these imaging systems, the
correlative behavioral tests are often significantly abbreviated. This
may impose constraints on space for occurrence of the target
phenomena--novel thinking and insight--during the imaging
session. As one researcher worries,



> 
> 
> Too often single tests are used--or even single items! This is
> contrary of psychometric theory in general (where longer tests allow
> errors to cancel themselves out and are thus more reliable) and true
> of the research on creativity assessment in particular, where
> differences among items and even tests are common (Richards, 1976;
> Runco, Mohamad, & Paek, 2016 [sic should be Runco, Abdulla et al.
> 2016). Results from any one test will not generalize to other tests.
> Results from a single item of course have even less generalizability.
> (Runco 2017: 309-310; see also Abraham 2013)
> 
> 
> 



Another empirical researcher criticizes what he sees as "the
wild goose chase" in the neuroscience of creativity. Arne
Dietrich (2019) recapitulates the above worries about validity of
psychometric measures and their abbreviated and piecemeal application.
He further worries about the now dominant emphasis on divergent
thinking, and the default mode network (as well as the now mostly
abandoned emphasis on notions such as madness, the right brain, and
REM sleep). Dietrich's concern in each case is that the research
emphasis is unhelpfully myopic, and that while the imaging methods are
sound and state of the art, the characterization of creativity is not.
He decries the temptation to identify what may be a *feature*
of creativity with the whole of the phenomenon. Divergent thinking, he
suggests, is likely a cluster of various mental phenomena rather than
a singular one, and



> 
> 
> there is no effort underway to dissect divergent thinking and link it
> to the kinds of cognitive processes we use to operationalize all other
> psychological phenomena, such as working memory, cognitive control,
> semantic memory, perceptual processes, or executive attention. (2019:
> 37)
> 
> 
> 



Notice, then, that the "wild goose" for Dietrich is to
hastily conclude and then center studies around a singular, special
creativity mechanism.



Dietrich also offers various prescriptions for remedy. To combat
myopia, he suggests (as some have in other disciplines, e.g., Boden
2004) a plurality of types of creativity (and/or features of
creativity). He cautions,



> 
> 
> Since different types of creativity contain opposing brain
> mechanisms--focused versus defocused attention, for
> instance--any all-encompassing claim about creativity in the
> brain will almost certainly qualify as phrenology. (2019: 39)
> 
> 
> 



He pairs this with a prescription for a more interdisciplinary
approach to the topic. Others in the field have made the same
prescription, advocating a "systems" approach sensitive
both to the multi-faceted nature of creativity and the value of
theorizing at multiple levels of explanation (Hennessy & Amabile
2010).



These directives for future research seem hard to resist. At the very
least, it would seem advantageous to ensure that the full range of
empirical method across the behavioral and brain sciences is
communicated across the relevant sub-disciplines. This would ideally
lead to better collaboration amongst such researchers. What's
interesting is that a cousin to this prescription is not well heeded
by the same researchers advancing it here. However little crossover
there is between, say, behavioral psychologists and neuroscientists in
studies of creativity, there is comparatively even less crossover
(almost none) between the psychological sciences and computational
approaches to creativity. The next section thus begins by highlighting
this "gap", and identifying some of the potentially
fruitful areas for interdisciplinary work on that front. It then
continues with a discussion, generally, of research on creativity in
the fields of computing science, artificial intelligence, and
robotics.


## 6. Creativity and Artificial Intelligence



Just as we find in psychology and neuroscience, there is a rich
research literature on creativity in artificial intelligence and
computer science, with devoted journals, special issues, and
conferences (*The Journal of Artificial Creativity*, *The
Journal of Creative Music Systems*, *Digital Creativity*,
*Minds and Machines* special issue on Computational Creativity
[Gervas et al. 2010], *The International Conference on
Computational Creativity*). The question we focus on here is
whether a computer could *be creative*. As background, it is
worth considering how theorists approached the analogous question as
to whether a computer could *think*.



Although theorists of various kinds have asked whether machines can
think since at least the early modern period, the most important
conceptual innovations on the topic came from Alan Turing, centering
around his 1950 paper "Computing machinery and
intelligence". Here Turing provided a number of groundbreaking
insights. Perhaps most familiar is Turing's "imitation
game", now commonly known as "the Turing Test". In
brief, the test involved an unknowing interrogator who could ask an
open-ended series of questions of both a human and a computer. If the
interrogator could not distinguish computer from human, Turing
postulated that this would suffice to illustrate genuine intelligence.
There is no shortage of controversy regarding the aptness of the test
for intelligence, and arguably no computer has yet passed it. (For
more thorough discussion of Turing and the Turing test see entries on
 Alan Turing,
 Turing machines, and
 the Turing test).



Successful performance in Turing's game would require remarkable
behavioral flexibility. And it is highly operational: specify a
threshold for imitation, and then simply allow the interrogator to ask
questions, then assess performance. If the behavior is sufficiently
flexible to fool the interrogator, Turing claimed, the behavior was
intelligent and, therefore, the computer intelligent.



With this background in mind, what are some of the cases in AI
research lauded as success cases, and how do they align with some of
Turing's criteria?



Many of the familiar success cases are highly specialized. *Deep
Blue* defeated chess master Garry Kasparov (Kasparov &
Greengard 2017); some language processing systems managed to navigate
social contexts such as ordering from a menu at a restaurant (Schank
& Abelson 1977); *AlphaGo* more recently defeated the world
champion Go player. This specialization is both a virtue and a
limitation. On the one hand, achievement in such a specialized domain
implies an exceptional amount of detailed memory and skill. On the
other hand, this knowledge and skill does not generalize. Neither
*Deep Blue* nor *Alpha Go* could successfully order from
a menu, along with countless other basic human tasks. Put in terms of
Turing's imitation game, these systems would fail miserably to
fool a human, or even remotely imitate one (except for their
performance in a very narrow domain). What about systems such as
IBM's *Watson*, which famously won (against humans) on
the television game show *Jeopardy!* This performance is more
general, since topics on the show vary widely, and seemed to require
both language comprehension and some minimal reasoning skills (see
entry on
 artificial intelligence
 for extended discussion). Even so, Watson's capabilities are
still quite limited: it cannot make fluid conversation "in real
time" and is largely insensitive to temporal and other factors
that come with context.



There are many, many more examples of computational systems that
display sophisticated behavior, from the highly specialized to the
more general. On the language processing front, very recent AI systems
such as
 OpenAI's ChatGPT
 and
 Google's LaMDA
 significantly outperform the systems described above. To be clear,
these are remarkable achievements that display substantial complexity
and, it appears in some cases, significant flexibility--features
Turing highlighted in characteristically human behaviors. But this
also underscores a distinction, often invoked by critics of artificial
intelligence research. There is a difference between a
computer's displaying or merely imitating an intelligent
behavior, and a computer's instantiating intelligence through
such behavior. And the critic will say, even if a computer behaves
*as if* it is intelligent, this is just modeling or simulating
intelligence. The greater ambition, though, is "genuine
artificial intelligence", a system that *actually
thinks.* John Searle refers to this as the distinction between
"weak AI" and "strong AI", respectively.



* **Weak AI**: Could a computer *behave* *as
if* it thinks?
* **Strong AI:** Could a computer genuinely think?




The general worry here is that however sophisticated a system's
behavior may appear "from the outside", for all we know it
may just be a "hollow shell" (Haugeland 1981 [1997]; Clark
2001). The worry has then been fleshed out in various ways by
specifying what is missing from the shell, as it were. Here are three
standard such candidates. And, again, in each case however
sophisticated the computer's behavior may appear it still may be
lacking in any or all of the following. First, the computer may lack
*consciousness*. Second, the computer may lack any
*understanding* of the symbols over which it computes (Searle
1980). Finally, the computer may operate without *caring* about
its own behavior or, as John Haugeland colorfully puts it, without
"giving a damn". In each case, any kind of response from
the ambitious AI researcher encounters the substantial challenges that
come with theorizing mental phenomena such as consciousness,
understanding, linguistic competence, and emotion. (Turing 1950, for
instance, recognized but largely eschewed these kinds of topics).



It's one thing to ask whether computers could think, and another
to ask whether they could be creative. And just as the prospect of
artificial intelligence or thinking divides into two
questions--of weak AI and strong AI--we may distinguish two
analogous questions about artificial creativity, which we'll
refer to as the questions of "weak AC" and "strong
AC", respectively. To begin with the former:



* **Weak AC**: Could a computer *behave* *as
if* it's creative?




Something behaves as if it's creative if it produces things
which are *psychologically new* (new to that thing) and
*valuable*. Arguably, a number of computers have already done
that.



In the 1970s, Harold Cohen began using computational technologies to
produce new drawings and paintings. The work of his computer painter,
Aaron, has exhibited at galleries such as the Tate and the Victoria
and Albert Museum in London. David Cope's "EMI"
(Experiments in Musical Intelligence) has composed musical works in
the style of various known composers and styles, even a full-length
opera. Some of these works have been recorded and produced by bona
fide record labels. Just search "Emily Howell" on Spotify
or Apple Music and give it a listen (Cope 1996, 2006). Simon
Colton's *The Painting Fool* is an ongoing project,
involving a software that abstracts phrases, images, and other items
from newspaper articles and creates collage-style pieces. It has also
produced portraits, based on images of film characters, of the same
individual in different emotional states (see *Painting Fool*
in
 Other Internet Resources;
 see Colton 2012 for theoretical discussion). Even more recently,
there have been explosive developments in generative art systems like
DALL*E, Midjourney, Stable Diffusion, VQGAN+CLIP. (For discussion
see Paul & Stokes 2021). In all of these cases, the relevant
outputs of the computer program are new relative to its past
productions--so they are psychologically (or behaviorally) novel,
which again is all the novelty that creativity requires. And although
historical novelty isn't required for creativity, it's
worth noting that these products appear to be to be new in all of
history as well.



What about value? As noted above in
 SS2.1,
 some theorists reject the value condition, but even if value
*is* required for creativity, that too is a condition these
computer artworks seem to meet. Assessments of value can be
controversial, but that is no less true for the outputs of human
creativity. The fact that these works are critically acclaimed,
showcased in prestigious galleries, and commissioned by selective
record labels testifies to their artistic merit, and viewers find them
pleasing, interesting, and appealing, even before being apprised of
their unusual origin. So it is reasonable to conclude computer
programs like the ones just described exhibit at least weak AC insofar
as they produce works of valuable novelty, and one could cite many
more examples in the same vein.



Some theorists have noted that, whether or not the original Turing
test is a good test for intelligence or thinking, we might adopt an
analogous test for creativity: If a computer can fool human observers
into thinking that it is a human creator, then it is in fact creative
(Pease & Colton 2011; see also Chen 2020 for useful discussion of
artificial creativity, including many additional examples of
particular cases, and so-called Dartmouth-based Turing tests). If we
employ this test, we might find ourselves with an unexpected
conclusion: computers can be creative; in fact, some of them already
are. But one might reasonably worry that the test is inadequate and
the conclusion is too quick (Berrar & Schuster 2014; Bringsjord et
al. 2001). From the fact that a computer operates *as if*
it's creative, one might argue, it doesn't follow that it
really is. Which brings us to our next question:



* **Strong AC**: Could a computer genuinely be
creative?




This obviously returns us to the question of what conditions something
must meet in order to count as being genuinely creative. And here we
need go beyond the outwardly observable product-features of novelty
and value to consider the underlying processes of genuine creativity.
As we saw in
 SS2.2,
 theorists have variously proposed that in order for a process to
count as creative, it must be *surprising, original,
spontaneous,* and/or *agential.* There is no consensus to
appeal to here, but *if* any one of these conditions is indeed
required for genuine creativity, then a computer could be genuinely
creative only to the extent that it executes processes which satisfy
that condition.



The classic statement of skepticism regarding the possibility of
computer creativity is due to Lady Ada Lovelace who had this to say
while remarking on "the Analytical Engine" designed by her
friend Charles Babbage:



> 
> 
> It is desirable to guard against the possibility of exaggerated ideas
> that might arise as to the powers of the Analytical Engine. The
> Analytical Engine has no pretensions whatever to *originate*
> anything. (Lovelace 1843, italics added)
> 
> 
> 



Though Lovelace does not frame her comments in terms of
"creativity" as such, she explicitly denied that a
computer could satisfy at least one condition that is plausibly
required for creativity, namely *originality*. A computer
cannot be the originator, the author, or the creator of anything new,
she contends; it can only do what it is programmed to do. We cannot
get anything out of a computer that has not already been programmed
into it. Further, Lovelace may also be interpreted as expressing or
implying doubt about whether a computer could satisfy the three other
proposed requirements for genuine creativity. Insofar as a
computer's outputs cannot be original, one might also suspect
that they cannot be *surprising*. The image of a machine
strictly following rules invokes precisely the kind of mechanical
procedure that is the antithesis of *spontaneity*. And it may
seem that such a machine could not be a genuine *agent* either.
The problem isn't just that a computer can't produce
anything original; it's that it deserves no credit for whatever
it does produce. Any praise or blame for the outputs of a computer
rightly go to the engineers and programmers who made the machine, not
to the machine itself. While these points may be intuitive, at least
some of them are being challenged by modern technologies, which have
come a long way since Babbage's invention.



Consider AlphaGo again. This is a "deep learning" system,
which involves two neural networks: a Policy network and a Value
network. Very briefly: The system is trained using a vast number of
legitimate moves made in actual games of Go played by professional
human players (28.4 million moves from 160,000 games, to be precise;
see Silver et al. 2016 and Halina 2021). The network is further
trained, again using learning algorithms, by playing many games (some
100 million) against previous versions of itself (in the sense of a
differently weighted neural network). The weights of nodes in the
network are then adjusted by a learning algorithm that favors moves
made in winning games. The value network is trained over a subset of
these many games, with node weighting adjustments resulting in
reliable probability assignments to moves vis-a-vis their
potential to contribute to a win. Finally, the system employs a
*Monte Carlo search tree* (MCT). Generally, this kind of
algorithm is designed to simulate a decision process to optimize
success given chosen parameters. In this case, the search algorithm
selects a given path of moves, then adds some valid moves to this
path, and then if this process does not terminate (end in win/loss),
the system performs a "rollout". A rollout essentially
plays the game out for both players (using samples of possible moves)
to its conclusion. The information that results from the MCT and
processing by the value network are then fed back (back propagated)
into the system. This entire process (once the system is trained) is
rapid and determines how AlphaGo "decides" to move in any
given game.



Here are some things to note. AlphaGo's style of play is
*surprising*. As commentators have noted, it is starkly
unconventional relative to standards of human play (Halina cites Baker
and Hui 2017
 [Other Internet Resources]).
 Indeed, Lee Sodol, the world champion Go player defeated by AlphaGo
in 2016, remarked that AlphaGo's play revealed that much of
human play is, contrary to prior common opinion, not creative after
all--intimating that at least some of the play of AlphaGo
*is*. Note further that this system is flexible. While there
are learning algorithms and rules that adjust network weights, the
system is not mechanical or predictable in the same fashion as
earlier, classical systems (including *Deep Blue*, for
example). In a recent paper, Marta Halina has made this argument
(Halina 2021). She explicitly invokes Boden's characterization,
which requires novelty, value, and surprise of creativity. Again, the
novelty and value should be plausibly attributed in this case.
Regarding surprise, Halina suggests that it is AlphaGo's
employment of MCT that enables a kind of "insight",
flexibility, and unpredictable results. She writes,



> 
> 
> It is the exploration parameter that allows AlphaGo to go beyond its
> training, encouraging it to simulate moves outside of those
> recommended by the policy network. As the search tree is constructed,
> the system starts choosing moves with the highest "action
> value" to simulate, where the action value indicates how good a
> move is based on the outcome of rollouts and value-network
> evaluations. (Halina 2021: 324)
> 
> 
> 



Halina grants that given its domain-specificity, as we have already
noted, this system's particular abilities do not generalize in a
way that may be required to properly attribute genuine intelligence.
But she suggests that the complex use of the MCT search may amount to
"mental scenario building" or, we might say, a kind of
imagination. And insofar as this search algorithm technology can be
applied to other systems in other domains, and imagination is a
general component of intelligence, perhaps here lies space for
generalizability. AlphaGo also affords at least some reply to the
traditional Lovelace worry.



> 
> 
> Artificial systems do not act only according to preprogrammed rules
> hand-coded by engineers. Moreover, current deep-learning methods are
> capable of producing systems that are superhuman in their abilities to
> discover novel and valuable solutions to problems within specific
> domains. (Halina 2021: 327)
> 
> 
> 



If this is right, then AlphaGo exhibits *originality*. Finally,
the flexibility with which this system operates may also satisfy
Kronfeldner's *spontaneity* requirement.



Some of these same features are found in a related approach in AI,
namely research in evolutionary robotics. These systems also involve
various forms of machine learning but in this case the learning is
distributed, as it were, across a population of individuals rather
than one individual. This approach can be understood, albeit
imperfectly, as analogous to natural evolution. One begins, typically
in computer simulation, with a population of agents. These agents are
typically identified with individual neural networks, the connections
and weightings of which are random to start. Relative to some
task--for instance, avoiding obstacles, collecting objects,
performing photo or phonotaxis--a *genetic algorithm*
assigns a fitness value to each individual agent after a certain
period of time or number of trials. Fitter agents are typically
favored and used to generate the next population of agents. Also
included in this generation are *random mutation* and
*genetic crossover* (digital breeding!). Although it can take
hundreds of generations, this is a discovery approach to engineering
or constructing a system that successfully performs a task; it is
"gradient descent learning" (Clark 1996). In this
bottom-up approach, no single individual, nor even an entire
population, are in any strict sense programmed. Rather, successful
agents have "learned" as a result of generations of
randomness, crossover, and small fitness improvements (and lots and
lots of failures). Early success cases evolved robots that can follow
trails (Koza 1992), locomote in insect-fashion (Beer & Gallagher
1992), guide themselves visually (Cliff, Husbands, & Harvey 1993),
and collect garbage (Nolfi & Floreana 2000). See Bird and Stokes
(2006, 2007) and Stokes and Bird (2008) for analysis and study of
creativity in the context of evolutionary robotics.



These systems most certainly produce novelty. Later, fit individuals
achieve novelty at their aimed task relative to whole generations and
populations of previous agents. And this novelty is often surprising
to the engineers and programmers that build them, indeed sometimes
even unpredictably independent of any relevant task for individuals in
the population. There are many examples in the literature. Indeed
Lehman and others (2020) catalog a large range of cases where digital
evolution surprises its creators, categorizing them in four
representative groups: "mis-specified fitness functions",
"unintended debugging", "exceeded experimenter
expectations", and "convergence with biology". Here
is one now relatively famous example of the first type of case. In
early research in artificial life (A-Life), Karl Sims (1994) designed
virtual creatures that were supposed to learn to walk (as well as swim
and jump) in a simulated environment. The fitness function assessed
individual agents on their average ground velocity across 10 seconds.
Some of the fittest individuals to evolve were surprising: they grew
tall and rigid and when they would fall over they would achieve high
ground velocity, thus maximizing fitness given the (mis)specified
parameters in unpredicted ways.



This is but one example of how systems like these can evolve in
unpredictable or *surprising* ways. This unpredictability has
occurred not just in simulated robotics, but in embodied robotics as
well. In using a genetic algorithm to attempt to evolve oscillating
sensors, researchers unintentionally evolved a radio antenna (Bird
& Layzell 2002). This unexpected result arose from a combination
of the particular algorithm used (which was intended) and various
physical features of the space such as proximity to a PC monitor
(which the researchers had presumably deemed irrelevant but which the
evolved system, in a sense, did not). And one might be further
inclined to describe some of these achievements as creative (and not
just in the trivial sense that they are original instances of robotic
success), since they also produce value, at least insofar as they are
useful at performing a task, whether it is locomoting or locating a
source of light or sensing radio waves.



Some theorists in this domain might argue that these systems achieve
*spontaneity* as well. Given the substantial inclusion of
randomness in the system's development--both at the outset
when the individual's neural networks are randomized and more
importantly with random mutation across populations--it is
intuitive to describe the system's as *not* following a
mechanical procedure. Indeed, the way in which systems exploit fitness
functions and data patterns further underscores this point. (Again,
see the rich catalog of cases offered by Lehman et al. 2020).



On the face of it, then, recent technologies in AI, evolutionary
robotics, and artificial life, seem to fulfill many of the conditions
proposed for genuine creativity. These systems produce things that are
novel and valuable, and do so through computational processes that are
plausibly surprising, original, and spontaneous. The one requirement
we have yet to address, however, is *agency*. Recall the
suggestion, implicit in Lovelace's remarks, that whatever a
computer produces is to the credit of the programmer, not the
computer. Notice that as sophisticated as current technologies in
artificial creativity may be, presumably they are still not subject to
praise or blame for what they do. If any beings are responsible for
the work of these programs, it still seems to be the programmers and
engineers who make them, not the programs themselves. The programs
themselves do not seem to "give a damn". So, if the
creative process requires agency, arguably we have not yet created,
programmed, or evolved a computational system that is really creative,
however much they might appear to be. In the pursuit of strong AC,
agency might be the final frontier (Paul & Stokes 2021).


## 7. Conclusion



It should be clear from the above discussions that there are rich and
lively research programs, across a range of scientific disciplines,
studying human creativity. These approaches substantiate the view
that, contrary to the romantic tradition, creativity can be explained.
Psychological functions and neural correlates have been identified,
and remarkable advances are being made with computational and robotics
technologies. What may be less clear is that, despite these advances,
the distinct research programs in question are largely disjoint or
siloed.



In a recent paper, Geraint Wiggins and Joydeep Bhattacharya (2014)
highlight this "gap" between scientific studies of
creativity. Their particular emphasis is on the gaps between research
in neuroscience and research in computer science, and they advocate a
bridge in the form of a neurocomputational approach. This kind of
bridging may be called for even beyond what these authors prescribe,
since there are gaps not just between these disciplines, but also
between these and behavioral psychology, AI and A-Life research, and
philosophical analysis. Creativity is a deeply complex and deeply
important phenomenon. Fully understanding it will require us to
integrate a variety of theoretical perspectives, and, as this survey
reveals, philosophy has a vital role to play in that endeavor.