Published: 02/06/2024
By: Moozhan Shakeri
Claiming, that we humans are the only ones who can be creative has been historically our first line of defence against the rise of machines. Reflections on creativity beyond the fields of psychology and neuroscience, which have an inherent interest in the concept, typically peak when artificial intelligence is advancing. No claim on creativity is free of bias, whether it aims to prove that humans are the only creatures capable of creativity or that machines will eventually surpass humans in creativity.
The sudden burst of interest in creativity, though, who the prominent voices in these discussions are, and the shifting definitions of creativity during these heated moments reveal much about our perceptions of problem-solving, the role we assign to technology within them, and our expectations of ourselves as humans.
Before delving into these narratives, let’s first identify where our tools, processes, and frameworks of creativity come from. At the highest level of abstraction, there are philosophers of mind, psychologists, and neuroscientists who conduct fundamental research on the nature of the mind and its relation to the body and the external world. They primarily aim to understand how humans think, whether their mental processes can be replicated and whether we can ever truly know how humans think. Then, there are those who build on these foundational inquiries to theorize about specific human activities such as decision-making, problem-solving, and belonging.
Next, there are those, usually computer scientists or human-computer interaction designers, who take these insights and operationalize them. They design processes, tools, and frameworks to make these high-level conceptual ideals accessible to others. Then we have those who adopt these frameworks or tools, such as urban planners and environmental designers. They may tweak certain features of these tools, processes, and frameworks to better fit their needs, but they rarely delve into the core assumptions behind them. There are also those who are interested in understanding the impacts of the resultant frameworks, tools or processes. This group usually have to track back to core assumptions involved in these practices to speculate about their impact.
To translate high-level theoretical ideas into practical frameworks, numerous interpretations, subjective selections, communications, and translations are required, making the process highly susceptible to misinterpretation, misunderstanding, and sometimes intentional misreading of ideas 1. In effect, as you move down this hierarchy of abstraction, the set of theories and ideas available becomes increasingly limited.
An urban planner, for instance, is more likely to be familiar with rational decision-making or design thinking frameworks than with the more nuanced and uncertain ideas circulating in the philosophy of mind. While this may seem obvious, as social scientists, we often forget how limited and sometimes misunderstood the ideas we engage with are. Our efforts to address the limitations of our tools, frameworks, and processes often focus on finding alternative practices rather than questioning the core assumptions underlying them.
There was a time when the boundaries between disciplines were not so rigid, and interdisciplinarity was an inherent aspect of scholars' works and interests, rather than a forced idea. More people used to translate high-level concepts into practical frameworks themselves, achieving a cohesive and comprehensive view of the process that we rarely manage today. Herbert Simon, for example, was a social scientist trained by economists and mathematicians. He conducted studies on administrative behaviour, delved into problem-solving processes, designed computer programs to understand how people solve problems, and theorized about creative processes. There are still many individuals who move seamlessly between high-level and practical levels, connecting them effectively.
So it’s important to keep in mind that the concept of creativity used in social science has undergone the same process over the past 70 years. Many notions of creativity have been dismissed to make creativity operational in today’s society. Political economy today is a popular lens for examining creative and experimental practices. For some, ‘the creative economy’ is seen as an extension of a neo-liberal economic agenda, an attempt to exploit the creative industry and the public for the benefit of a few. Some even oppose all attempts to operationalize creativity and urge us to work against them all in all. Others see creativity as valuable but believe it needs to be more democratic and accessible. For others, design thinking, creative practices and institutions of creativity, like living labs, would be our best shot at overcoming the challenges we face today.
Despite their differences, these approaches share more commonalities than one might expect. They all build and refine the same understanding of creativity, as collective, replicable and systematic. All touch upon the impacts of creativity, yet none really are interested in creativity itself as a concept. Partly, this is because we have never been interested in creativity in any other way when it comes to dealing with social issues.
Our Initial Interest in Creativity was Related to AI
The very first instance of reactionary interest in creativity as a concept happened in the late 1950s. In 1950, J. P. Guilford, the president of the American Psychology Association called for more formal theoretical research on creativity in the field of psychology. In 1956, Allan Newell and Herbert Simon released The Logic Theorist computer program (arguably the first automated reasoning program), in 1957 The General Problem Solver program and in 1959, a report in RAND on the process of creative thinking 2! All this happened in the context of the Cold War and when military decision-making methods were being adapted to deal with social issues – an era characterized by high trust in scientific methods for addressing social problems.
In their writing, Newell and Simon noted that much of the works on processes of human thinking are ignored in the field of psychology with the excuse that they are too hard to measure or simulate and that their goal is to show that techniques of psychological inquiry have become adequate, at least to some degree, to study thinking and problem-solving processes in one’s mind. From the outset, they assumed that one can indeed study human thinking and that made most of the claims about creativity being mysterious and unknown, inaccessible to today’s social scientists.
Today’s understanding of creativity and experimental urban planning has, in one way or another, roots in design thinking (an extension of Herbert Simon’s work) – a collective and iterative process with a motto of failing fast and often. We often justify the adoption of such experimental approaches by presenting them as an alternative to positivist approaches – a new way of embracing the complexity of the urban phenomenon. The argument is that these approaches are more human-centred and sensitive to nuances of human experience. Well! Herbert Simon’s work couldn’t be more positivist in its core assumption and it would be surprising if it was anything other than that within the context of its time, being the 1950s, and within the institution where these studies were carried out, being RAND.
Creativity could only be packaged as a framework if scholars could prove that creative thinking processes can be studied and modelled - that was exactly what Simon and his colleagues did. Some psychologists were quick to point out the problems with such an approach. The back-and-forth responses between Mihaly Csikszentmihalyi and Herbert Simon are by far the most interesting documented debates in this regard.
Csikszentmihalyi’s main discontent was with the fact that Simon and his colleagues had excluded personal characteristics, motivations, emotions and curiosity from their study. They had explicitly mentioned in their report, and later in their book. They emphasized that they are mostly interested in how one solves problems and how within the problem-solving process one understands the problem in a more refined way. To Csikszentmihalyi, motivation, curiosity and emotions were the core human qualities in creative problem-solving that made explaining creativity in its totality challenging, if not impossible. To him, Simon and his colleagues did not succeed in explaining the creative process, they reduced it to rational explainable components.
Simon accused Csikszentmihalyi of “glorifying unreason”. Csikszentmihalyi responded: “To point out the variety of dimensions of human thought in no sense implies a “glorification” of non-rational elements. Ignoring them, however, leads to an unrealistic feeling of security about what we do and do not understand.”
These lines aptly describe our current condition. Much of the efforts to render creativity systematic and rational, and to claim that machines can indeed be creative, is an attempt to maintain that unrealistic feeling of security. You might think that social scientists would work against this, that they would be more prone to argue against such rationalisation and objectification. But over the past year, I found out that even social scientists find Csikszentmihalyi’s claims about unexplainable qualities of creativity unacceptable and unreasonable.
“To point out the variety of dimensions of human thought in no sense implies a “glorification” of non-rational elements. Ignoring them, however, leads to an unrealistic feeling of security about what we do and do not understand.”
Social Scientists’ Complex with AI
Here is the complex social scientists have, especially those, like urban planners, whose work in some way has a direct impact on society. For years, they have sought legitimacy by adopting scientific methods– scientific methods, in their eyes, lend social science robustness, credibility and a set of coherent methodologies. Legitimacy, accountability and transparency are the main lines of justification for social scientists in adopting scientific methods. Why rationality and an objective view of human experience persist in fields like urban planning has been of interest to many scholars. Baum 3 might be the only one who has explicitly linked this to the psychological need to rely on scientific methods in urban planning.
Social scientists also want to have their academic trench – for their works to be teachable, researchable and expandable. Establishing frameworks, packaging their ideas to apply to various contexts, and aiming to devise ‘standard’ practices, would help them consolidate their work as a field of study. Many works claiming against this, including much of the pragmatic theories in planning, are labelled useless for the works and education of planning. Even efforts to escape systematic and rational treatment of social phenomena themselves fall into this trap; participatory planning, for example, rationalizes and models communication and consensus building, or the storytelling paradigm, creates reusable tools and frameworks for story collection and analysis.
Social scientists themselves reduce their work to rational parts, systemized and modelled. But here is the sad news! Once everything is thought to be systematic and replicable, machines can do them as well. Recognizing this, social scientists often panic and begin emphasizing creativity and irreplaceable human qualities. This interest in creativity is more a self-defence mechanism against machines than an interest in creativity itself. The same goes for art. As Mortensen put it in 1997:
“The increased interest in the arts must be seen as a reaction to the growing prestige of what we would now consider a scientific approach … when empirical and scientific forms of explanation of natural phenomena become predominant, nature, including human nature, becomes objectified, which leads to a break or a form of loss in relation to earlier, more holistic approaches. Those who feel this loss find in the arts a sphere where it can be overcome or compensated”.
Such emotionally-driven interest in creativity rarely results in a deep exploration of alternatives. In urban planning, everyone has some claims over creativity, and how badly it is needed in addressing complex challenges cities face. Yet, there are only a handful of studies that even mention theories of creativity, let alone trying to define what it means for the works of planners. Despite acknowledging the importance of non-rational views in planning, there is not a single course of planning that encourages a more art-led view of planning, one that teaches students to find their style of planning or forms of expression beyond maps and charts. We have neither developed the knowledge nor the terminologies to talk about our practices in a non-systematic, non-rationalized way.
This interest in creativity is more a self-defence mechanism against machines than an interest in creativity itself.
Why This is Not Ideal, Even Though It’s Understandable
The combination of social scientists’ urge for systematic approaches and the thirst of computer scientists to prove that we know more than we do about human beings is a harmful one. It reinforces the temptation to see everything as systematic, understandable, and replicable. Computer scientists make human processes more replicable with the technologies they provide and social scientists push for a systematic approach by taming the development of the technology by imposing regulations or attempting to take control of them by adopting them - by pretending that these technologies’ value lies only in them being adopted. It’s the long-lasting narrative that assumes that it’s we, social scientists, who define when and how these tools should be used in our processes, rather than acknowledging that these technologies have already and will be changing not only our processes but also our psyche even as professionals.
We Might Never Get Over This Tension
If you think there are computer scientists who are pushing technology solutions to society, and there are social scientists who are working against it, you cannot be more wrong! Beyond the immediate impacts, jobs being lost or children being affected by misinformation, etc., both groups are working hand in hand and the ultimate result of their work would be objectification and rationalisation of human experience.
The tension between the desire to understand and explain everything systematically and to preserve our humanistic elements, more than being about the economy and external factors, I would argue, is internal and we might never be able to overcome it. We like to claim that we can understand collective problem-solving, and provide tools for participatory practices, all rooted in ideas that the human mind is indeed understandable.
Yet, as Mays 4 once said, “At least for the unphilosophical person, minds have a certain privacy about them. I can directly inspect the contents of my own mind, but not that of my neighbours, which is, no doubt, all to the good.” Today, many technologies can and do inspect the contents of our mind, yet the mind being understandable and so replicable has a psychological bearing on us. Maybe that is why urban planners, and many other social scientists, put a very definitive boundary between your ‘understandable’ public mind and your ‘private’ individual mind - claiming that to understand and influence behaviour one does not need to know how one's mind works. We can train the public mind to be professional and forget about the needs of the private mind. There are already studies showing how wrong this assumption is and what negative impacts it has on urban planners’ practice.
The machines might end up being creative, yet if that happened I am sure we would come up with another definition of creativity to prove that they aren’t. Perhaps these emotionally heightened points in history where we get interested in creativity are the more fruitful time for us social scientists to become more critical about what we do and don’t realistically know about creativity, about decision-making and problem-solving rather than trying to argue for or against certain narratives around them.
Notes
1 Any interaction with other fields is done through the lens of your field rather than exploring the origins of that idea within its own disciplinary context. A great example of such limits in communication between ideas, which I personally know about, is planning’s communication with game design which I wrote about it here.
2 Check out the report here.
3 Check out the paper here. Baum, H. S. (1996). Why the Rational Paradigm Persists: Tales from the Field. Journal of Planning Education and Research, 15(2), 127-135.
4 Check out the paper here. Mays, W. (1952). Can Machines Think? Philosophy, 27(101), 148–162.