Matthew Griffin, described as “The Adviser behind the Advisers” and a “Young Kurzweil,” is the founder and CEO of the World Futures Forum and the 311 Institute, a global Futures and Deep Futures consultancy working between the dates of 2020 to 2070, and is an award winning futurist, and author of “Codex of the Future” series. Regularly featured in the global media, including AP, BBC, Bloomberg, CNBC, Discovery, RT, Viacom, and WIRED, Matthew’s ability to identify, track, and explain the impacts of hundreds of revolutionary emerging technologies on global culture, industry and society, is unparalleled. Recognised for the past six years as one of the world’s foremost futurists, innovation and strategy experts Matthew is an international speaker who helps governments, investors, multi-nationals and regulators around the world envision, build and lead an inclusive, sustainable future. A rare talent Matthew’s recent work includes mentoring Lunar XPrize teams, re-envisioning global education and training with the G20, and helping the world’s largest organisations envision and ideate the future of their products and services, industries, and countries. Matthew's clients include three Prime Ministers and several governments, including the G7, Accenture, Aon, Bain & Co, BCG, Credit Suisse, Dell EMC, Dentons, Deloitte, E&Y, GEMS, Huawei, JPMorgan Chase, KPMG, Lego, McKinsey, PWC, Qualcomm, SAP, Samsung, Sopra Steria, T-Mobile, and many more.
WHY THIS MATTERS IN BRIEF
I have said for almost a decade that AI can be creative and original because they are ironically a process that can often be mimicked, and now studies are starting to back that up.
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Of all the forms of human intellect that one might expect Artificial Intelligence (AI) to emulate, few people would likely place creativity at the top of their list, but as I’ve been telling audiences for years when you really boil it down creativity is just a process – albeit a complex one – and like any process it too can be automated and emulated by AI.
Creativity is wonderfully mysterious and frustratingly fleeting. It defines us as human beings and seemingly defies the cold logic that lies behind the silicon curtain of machines. Yet, the use of AI for creative endeavours is now growing.
New AI tools like DALL-E and Midjourney are increasingly part of creative production, and some have started to win awards for their creative output. The growing impact is both social and economic – as just one example, the potential of AI to generate new, creative content is a defining flashpoint behind the Hollywood writers strike.
The Future of Synthetic Content, by keynote Matthew Griffin
And if a recent study published in DOI into the “striking originality of AI” is any indication, the emergence of AI-based creativity – along with examples of both its promise and peril – is likely just beginning.
When people are at their most creative, they’re responding to a need, goal, or problem by generating something new – a product or solution that didn’t previously exist, and that sometimes might be the combination of two or more other ideas or concepts.
In this sense, creativity is an act of combining existing resources – ideas, materials, knowledge – in a novel way that’s useful or gratifying. Quite often, the result of creative thinking is also surprising, leading to something the creator did not – and perhaps could not – foresee.
It might involve an invention, an unexpected punchline to a joke, or a groundbreaking theory in physics. It might be a unique arrangement of notes, tempo, sounds, and lyrics that results in a new song, so when a pair of researchers saw something interesting about the content generated by the latest versions of AI, including GPT-4 they dug in.
When prompted with tasks requiring creative thinking the novelty and usefulness of GPT-4’s output apparently reminded them of the creative types of ideas submitted by students and colleagues that they had worked with in the past.
The ideas were different and surprising – yet relevant and useful. And, when required, quite imaginative.
Consider the following prompt offered to GPT-4: “Suppose all children became giants for one day out of the week. What would happen?” The subsequent ideas generated by GPT-4 touched on culture, economics, psychology, politics, interpersonal communication, transportation, recreation, and much more – many surprising and unique in terms of the novel connections generated.
This combination of novelty and utility is difficult to pull off, as most scientists, artists, writers, musicians, poets, chefs, founders, engineers, and academics can attest.
Yet AI seemed to be doing it – and doing it well – so researchers in creativity and entrepreneurship Christian Byrge and Christian Gilde decided to put AI’s creative abilities to the test by having it take the Torrance Tests of Creative Thinking, or TTCT.
The TTCT prompts the test-taker to engage in the kinds of creativity required for real-life tasks: asking questions, how to be more resourceful or efficient, guessing cause and effect, or improving a product. It might ask a test-taker to suggest ways to improve a children’s toy or imagine the consequences of a hypothetical situation, as the above example demonstrates.
The tests are not designed to measure historical creativity, which is what some researchers use to describe the transformative brilliance of figures like Mozart and Einstein. Rather, it assesses the general creative abilities of individuals, often referred to as psychological or personal creativity.
In addition to running the TTCT through GPT-4 eight times the researchers also administered the test to 24 of their undergraduate students.
All of the results were evaluated by trained reviewers at Scholastic Testing Service, a private testing company that provides scoring for the TTCT. They didn’t know in advance that some of the tests they’d be scoring had been completed by AI.
Since Scholastic Testing Service is a private company, it does not share its prompts with the public. This ensured that GPT-4 would not have been able to scrape the internet for past prompts and their responses. In addition, the company has a database of thousands of tests completed by college students and adults, providing a large, additional control group with which to compare AI scores.
The results? GPT-4 scored in the top 1 percent of test-takers for the originality of its ideas, and from their research the team went on to believe that this marks one of the first examples of AI meeting or exceeding the human ability for original thinking.
In short, they believed that AI models like GPT-4 are capable of producing ideas that people see as unexpected, novel, and unique. And other researchers are arriving at similar conclusions in their research of AI and creativity.
The emerging creative ability of AI is surprising for a number of reasons. For one, many outside of the research community continue to believe that creativity cannot be defined, let alone scored. Yet products of human novelty and ingenuity have been prized – and bought and sold – for thousands of years. And creative work has been defined and scored in fields like psychology since at least the 1950s.
The “person, product, process, and press” model of creativity, which researcher Mel Rhodes introduced in 1961, was an attempt to categorize the myriad ways in which creativity had been understood and evaluated until that point. Since then, the understanding of creativity has only grown.
Still others are surprised that the term “creativity” might be applied to nonhuman entities like computers. On this point, we tend to agree with cognitive scientist Margaret Boden, who has argued that the question of whether the term creativity should be applied to AI is a philosophical rather than scientific question.
It’s worth noting that the team studied only the output of AI in their research, they didn’t study its creative process, which is likely very different from human thinking processes, or the environment in which the ideas were generated. And had they defined creativity as requiring a human person, then we would have had to conclude, by definition, that AI cannot possibly be creative.
But regardless of the debate over definitions of creativity and the creative process, the products generated by the latest versions of AI are novel and useful. They believe this satisfies the definition of creativity that is now dominant in the fields of psychology and science.
Furthermore, the creative abilities of AI’s current iterations are not entirely unexpected.
In their now famous proposal for the 1956 Dartmouth Summer Research Project on Artificial Intelligence, the founders of AI highlighted their desire to simulate “every aspect of learning or any other feature of intelligence” – including creativity.
In this same proposal, computer scientist Nathaniel Rochester revealed his motivation: “How can I make a machine which will exhibit originality in its solution of problems?”
Apparently, AI’s founders believed that creativity, including the originality of ideas, was among the specific forms of human intelligence that machines could emulate.
To the researchers though the surprising creativity scores of GPT-4 and other AI models highlighted a more pressing concern: Within US schools, very few official programs and curricula have been implemented to date that specifically target human creativity and cultivate its development.
In this sense, the creative abilities now realized by AI may provide a “Sputnik moment” for educators and others interested in furthering human creative abilities, including those who see creativity as an essential condition of individual, social, and economic growth.