Imagination, Augmented: How AI Can Be a Creativity Amplifier

Your Snapshot

A summary of the key insights from this issue

⬩ Research shows Large Language Models (LLMs) like ChatGPT-4 generate diverse ideas faster and with higher quality than humans, benefiting creative problem-solving.

⬩ AI can exhibit types of creativity—combinational, exploratory, transformational—sometimes exceeding human creativity by exploring broader possibilities and taking more risks.

⬩ The future of creativity combines AI and human input. AI enhances creativity, but requires human oversight for idea evaluation. Real-world applications like TextFX, an AI-aided tool for rap writing, exemplify how AI can empower human creativity.


Can artificial intelligence (AI) unearth hidden layers of creativity within us? Have you ever wondered if a machine could help you generate ideas more swiftly, diversely, and effectively?

A burst of innovation often emerges when our minds are sparked by an external stimulus. AI, particularly Large Language Models (LLMs) like ChatGPT, can serve as that catalyst, enhancing our ability to generate ideas and solve problems creatively. This is because AI not only processes information at high speed but also explores a vast universe of possibilities beyond our immediate perception.

Harnessing the power of AI requires some effort, but it can significantly amplify our creative prowess and transform the way we innovate. The future of creativity is not just human or AI, but a blend of both, offering us a unique opportunity to reach new heights of creative potential.

The Power of LLMs for Idea Generation

How do Large Language Models (LLMs) like ChatGPT stack up against humans in generating ideas?

A recent study by researchers from Cornell Tech and the Wharton School tackled this question. They tasked ChatGPT-4 and students from an elite university with generating new product ideas for the college student market, retailing for less than $50.

While it’s no surprise that LLMs like ChatGPT can swiftly produce ideas, the study unearthed some unexpected results regarding AI’s quality.

ChatGPT-4 not only churned out ideas faster than students, but the ideas were also, on average, deemed higher in quality based on purchase-intent surveys. Moreover, they displayed a higher variance in quality. This variance indicates that ChatGPT-4 can produce a broader range of ideas, some excellent and others not as good. This diversity benefits creative problem-solving, raising the likelihood of finding standout solutions.

Interestingly, the paper highlighted that feeding ChatGPT-4, a few highly-rated ideas, further improved its performance. It concluded that, for focused idea generation, a human using ChatGPT-4 is roughly 40 times more productive than a human working alone.

Can AI Be as Creative as Humans?

The debate around whether AI can match human creativity or even surpass it continues. Before we dive into this question, let’s first define creativity.

Margaret Boden, a renowned philosopher and cognitive scientist, defines creativity as the ability to produce something new, valuable, and surprising. She identifies three types of creativity:

  1. Combinational (combining existing ideas in new ways),
  2. Exploratory (exploring the possibilities within a given framework),
  3. Transformational (transforming the framework itself).

According to her, AI can exhibit all three types of creativity, albeit within certain constraints. While she acknowledges that human creativity has nuances that AI has yet to replicate, she believes that human creativity isn’t unique or superior to AI creativity.

Echoing this sentiment, mathematician and author Marcus du Sautoy suggests that AI can exceed human creativity in certain areas. He attributes this to AI’s ability to explore more extensive possibilities, maintain objectivity, and take more risks.

Implications for Innovation

The study by Cornell Tech and the Wharton School suggests that LLMs like ChatGPT can significantly enhance your creative prowess, generating many novel concepts. However, with idea generation becoming quick, cheap, and easy, effective processes for evaluating and filtering the most promising ideas become crucial.

MIT professor Mitchel Resnick views AI systems as a new category of educational resource with unique strengths and limitations. He highlights that while LLMs can inspire human creativity by providing new examples to build upon, they should not replace human ideation.

“encourage learners to use ChatGPT and other generative AI tools not to produce the final result but as a resource throughout their own creative process.”

Mitchel Resnick

How AI Can Collaborate with Humans to Create Multiplicity

Professor of Engineering and artist Ken Goldberg presents a new paradigm of “multiplicity,” where humans and machines collaborate to generate diverse ideas. He argues that multiplicity, defined as “the quality or state of being multiple or various,” is indispensable for creativity.

Goldberg provides examples of multiplicity in practice, such as crowdsourcing platforms like Amazon Mechanical Turk or Wikipedia and collective intelligence systems like Google Search or Netflix Recommendations.

He suggests that diversity can help overcome human and AI creativity challenges, including cognitive biases, information overload, groupthink, or ethical dilemmas.

Even the simple prompt, “What might I be missing?” can shift your perspective and challenge a bias.

AI and the Future of Creativity: A Case Study of TextFX

In practical terms, we can expect to see the convergence of generative AI capabilities into tools specifically designed to bolster elements of the creative process.

A prime example is the collaboration between rapper and professor Lupe Fiasco with Google and the Palm API. They developed a suite of AI-powered tools called TextFX, created to aid in the rap writing process.

TextFX doesn’t generate complete lyrics. Instead, it “explodes” words into multiple phonetic possibilities and explores a vast universe of potential meanings and interpretations. This design is inspired by Fiasco’s technique of dissecting words and phrases into various semantic and phonetic components.

The suite includes ten tools to generate similes, create acronyms, and parse words. It can take any word as input and provide many interpretations, similar to Fiasco’s approach in his songwriting. I can see lots of uses to support young people and their writing or creative thinking.

However, the aim of TextFX isn’t to replace the rapper in the songwriting process. Instead, it’s designed to empower and inform them. Fiasco emphasises that the joy of rapping stems from work and struggle, and these AI tools facilitate that journey.


The promise of AI in the creative landscape is vast. Not as a replacement for human creativity but as a collaborator. AI amplifies our creative process and pushes the boundaries of what’s possible. Do you want to be 40 times more productive?

The future of creativity is not just human or AI but a blend of both, enriching our capacity to innovate and solve problems.


⏭🎯 Your Next Steps

Commit to action and turn words into works

⬩ Explore and Experiment: Start using AI tools like ChatGPT in your creative process, learning their capabilities and your limits through hands-on experimentation.

⬩ Learn and Develop: Invest in AI-related training to understand its potential and ethical implications in your field.

⬩ Collaborate and Share: Share your AI experiences with your team, fostering a collaborative environment for navigating the future of creativity with AI.

🗣💬 Your Talking Points

Lead a team dialogue with these provocations

⬩ What are the potential benefits and challenges we might encounter as we integrate AI into our creative work?

⬩ What might the future look like as we continue to blend human creativity with AI’s capabilities, and how can we prepare ourselves for this future?

⬩ As AI becomes more integrated into our creative processes, what ethical considerations should we keep in mind?

🕳🐇 Down the Rabbit Hole

Still curious? Explore some further readings from my archive

⟶ Time for Creativity in Schools – Tom Barrett (edte.ch) My article explores the challenges and possibilities of fostering creativity in schools, which often operate on rigid timetables and structures that hinder the creative process.

⟶ Can machines be more creative than humans? | Arthur Miller | The Guardian The article explores the implications of AI art for human creativity and knowledge. It suggests that machines may be able to surpass human creativity by making connections across different fields and domains. It also proposes that machines may enhance human creativity and help solve global problems.

 A philosopher argues that an AI can’t be an artist | MIT Technology Review The author argues that creativity is not just novelty or skill, but a vision of the world that changes our understanding of what is good, true, or beautiful. Machines can mimic or assist human creativity, but they cannot produce it on their own.

5 Essential Mental Models for Boosting Your Creativity

Hello there! Welcome to the Dialogic Learning Weekly. It’s Friday, February 20. I’m Tom, writing to you from Melbourne, Australia. Thanks for spending part of your day with me. Reach out with comments, questions and feedback at tom@dialogiclearning.com or on Twitter at @tombarrett. If someone forwarded you this email, subscribe to get the Dialogic Learning Weekly sent straight to your inbox.

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Photo by jet dela cruz on Unsplash

In our last issue, we explored the notion of innate creative thinking. Today, we look at mental models associated with ideas, creativity, and originality.

  1. Divergent Thinking
  2. Convergent Thinking
  3. The Innovation Jolt Model
  4. The Creative Habit Model
  5. The Creative Process Model

Regardless of the model, we use to understand creativity, at its heart is a desire and an intention to be creative. Our focus will be: how we can create the right intention to be more creative.


Divergent Thinking

Divergent thinking involves exploring lots of possible solutions to a problem. At the same time, convergent thinking looks for the correct answer to a specific problem.

Culturally, we are trained to think in ‘right or wrong’ terms and that the only way to be creative is to come up with new ‘right’ answers. When we feel like this, it is impossible to be genuinely innovative.

I often describe Divergent Thinking as a mode when we generate lots of different options. It is an expansive and open mode of thinking.

Convergent Thinking

We narrow down the options in convergent thinking, finding a smaller selection of possibilities.

Convergent thinking is often described as a more analytical and closed mode. Usually, this is done by filtering or voting on collections of ideas or datasets.

When we think in convergent thinking mode, we are not open to new ideas because we attempt to make decisions.

Example questions to encourage convergent thinking:

  • Which five ideas have the most potential?
  • Which of the questions sums up your current challenge?
  • Put a sticker on the three words that resonate with you the most?
  • Of all the places we could start, what feels like the most appropriate?
Sometimes there can be a clash of people thinking in opposite modes. Which explains much of the conflict and idea squashing that can happen. This is a dynamic to look out for and facilitate with care.

The Innovation Jolt Model

The analogy is that the moment you get a great idea is like getting hit with a large jolt of electricity — your mind becomes excited and can’t wait to get started.

When looking for ideas, this is the feeling you want, so if it doesn’t happen right away, don’t worry. Keep asking questions until the jolt happens.

The more you can get in touch with your feelings of excitement about an idea, the closer you are to being creative.

The Creative Habit Model

According to this model, creativity is a habit that requires dedication and effort. This means while great ideas may come naturally to some people, they can also be developed by anybody who knows how to practice regularly.

By practising our creative thinking every day, we gradually retrain our brains to think in new ways, increasing our ability for originality and increasing the number of ideas we can develop.

A simple exercise you can use every day is to ask "What if…" and to follow with any question you feel inspired to ask. Some examples:
> What if I didn't have to work?
> What if we didn't have to travel?
> What if the students chose when to learn?
> What if we could harness energy from the wind?
> What if we create an app that makes it easy for people to water their gardens?

The Creative Process Model

This model suggests that creativity isn’t only about understanding when and how to be creative and learning the correct type of thinking for a given situation.

Thinking of creativity and idea generation as a process also helps us manage and understand what we are doing and where we want to go.

We need to learn how to apply different types of thinking to different situations.


Your Talking Points

  • How can you use these models to bring out greater creativity in yourself and other people you communicate with?
  • What specific practices can you do daily to increase creativity in your life/work/studies, etc.?

🕳🐇 Down the Rabbit Hole

Complement this issue with my Atomic Essays: Solution Siren Call, Walt Disney Creative Strategy, Feedback is Oxygen For Your Ideas, Willful Blindness, Counter Wooden Headedness.


Thanks for taking a moment to join me this week — drop me an email at tom@dialogiclearning.com to connect and say hi. Or you can connect with me on Twitter > @tombarrett