Is there a clear distinction between imagination and creativity?
Imagination is what helps reimagine the world. Creativity helps apply the ideas by turning them into tangible constructs. In other words, creativity is the process of imagining and turning the imaginary into new being, as Rollo May puts it in “The courage to create”.
Clearly, creativity demands more than just a set of naturally given qualities: a framework, “passion and commitment” (May 1994). Creativity is the cornerstone of the “conceptual age”, as per Daniel Pink, ruled by creators and empathizers (Pink 2006). So, can it be taught — more importantly, can creativity be understood by artificial intelligence?
First, it’s important to understand that people naturally talk a lot about the importance of being creative, but in reality often have “decidedly mixed feelings about creativity” (Roberto 2019). At the same time, studies demonstrate the effectiveness of creativity training.
Well‐designed creativity training programs typically induce gains in performance with these effects generalizing across criteria, settings, and target populations (Scott, Leritz, Mumford 2004).
In his talks on computational creativity, Simon Colton’s talks about artificial intelligence progressing rapidly, and being able to improve the quality of works it produces rapidly — so much so that he admits to feeling as he if he was in the room with an artist.
While people actively unlearn to be creative, the IA learns to apply creativity — which seems to be possible, to a certain extent, although Ramon Mantaras disagrees with that approach, stating that artificial intellect lacks intentionality — “computer programs can only perform syntactic manipulation of symbols but are unable to give them any semantics” (Mantaras 2017).
It is doubtful that the machines will ever be able to truly replace creative thinkers. Automation of routine tasks only helps speed up the process — a fast, more “intelligent” background cropping tool in Photoshop, “smart” filters, recommendations, quick actions — machines can do anything except give things meaning. We should not really consider machines as our competitors.
What we should, however, do — and what I feel this course should tackle at some point in the future — is the ethics of the “creative machines” and the implications of employing “smart” technologies in a creative fashion to improve the quality of lives. If we take the ability to ideate and bring to fruition the imagined ideas as the definition of creativity, and assume that machines are smart enough to be “creative”, how might we ensure we are protected from what they might perceive as creative and efficient, but is mortally dangerous for the humanity?
I have worked with “smart” machinery before, but have not yet explored the topic close enough to comprehend the idea from a more theoretical standpoint. It is exciting to learn that artificial intelligence is changing the very nature of creative process, but I, personally, seem to be prone to what Ramon Mantaras explains in his concluding remarks.
The reasons why we are so reluctant to accept that nonbiological agents can be creative is that they do not have a natural place in our society of human beings and a decision to accept them would have important social implications (Mantaras 2017).
As part of the learning process, I should embrace a more open and less biased approach: accepting that machines may not have consciousness (hence, are not able to comprehend their accomplishments, cannot learn from their past, cannot understand the concept of ethics) should not deny “the potential for creativity or even the potential for intelligence”.
If creation demands a visionary creator, then how does blind evolution manage to build such splendid new things as ourselves? (Gould 1996)
References
MAY, Rollo. 1994. The Courage to Create. Revised ed. edition. New York: W. W. Norton & Company.
PINK, Daniel H. 2006. A Whole New Mind: Why Right-Brainers Will Rule the Future. Annotated edition. New York, NY: Riverhead Books.
ROBERTO, Michael A. 2019. Unlocking Creativity: How to Solve Any Problem and Make the Best Decisions by Shifting Creative Mindsets. 1st edition. Hoboken, New Jersey: Wiley.
SCOTT, Ginamarie, Lyle E. LERITZ and Michael D. MUMFORD. 2004. ‘The Effectiveness of Creativity Training: A Quantitative Review’. Creativity Research Journal 16(4), 361–88.
MÁNTARAS, Ramón López de. n.d. ‘Artificial Intelligence and the Arts: Toward Computational Creativity’. 2017. OpenMind [online]. Available at: https://www.bbvaopenmind.com/en/articles/artificial-intelligence-and-the-arts-toward-computational-creativity/ [accessed 27 Sep 2021].
GREY, Aubrey De and Johnathan ROSSITER. 2017. The Next Step: Exponential Life. Madrid: BBVA-Open Mind.
GOULD, S. J. 1996. ‘Creating the creators.’ Discover Magazine October: 42–54.