How AI is Changing Creativity: Beyond the Hype

There is way too much scaremongering going on when it comes to AI. While acknowledging the real existential threats (or opportunities), I'm definitely in the camp that says the benefits AI can bring to our world currently outweigh the challenges. I particularly think that Human x AI partnerships will help us become more efficient, impactful and, perhaps most surprisingly, more creative. (By the way, a caveat before we even get started: I am perhaps most worried about what we will do with the time that AI will save us. No one needs more time for emails, work or to take on an extra side hustle! What we do with this gained time really needs thinking about carefully, not least in education.)

Let’s talk then about how AI can make us more not less creative.

This pragmatic perspective is perfectly illustrated by Foster + Partners' Lusail Towers project in Qatar. Their use of AI-powered generative design, optimising both aesthetics and energy efficiency, highlights something far more profound: how artificial intelligence is reshaping creative problem-solving across every sector of society. This transformation echoes philosopher Martin Heidegger's concept of 'techne' - where technology isn't merely a tool, but a way of revealing new possibilities in the world.

At Imperial College London, researchers are demonstrating this broader creative potential, using AI to develop new materials for solar panels. Here, machine learning combines with human intuition to solve complex engineering challenges. Meanwhile, London-based DeepMind's AlphaFold has revolutionised how scientists visualise protein structures, turning abstract data into actionable insights for real-world problems.

Creativity in 2024 (and even further into the future) stretches far beyond traditional artistic domains. From scientific research to education, from healthcare to urban planning, creative problem-solving shapes our future in ways we're only beginning to understand. This evolution raises fundamental questions about the nature of creativity itself - questions that philosophers like Margaret Boden at Sussex University have grappled with for decades.

Yet beneath these advances lies a deeper tension. The philosopher Gilbert Ryle's distinction between 'knowing how' and 'knowing that' becomes particularly relevant as we consider AI's role in creative processes (more on that later). Are we witnessing a fundamental shift in what it means to be creative, or simply expanding our creative toolkit?

At UCL's Knowledge Lab, Professor Rose Luckin frames this question precisely: 

“I think the future will be one where we work alongside artificially intelligent partners." -Rose Luckin

This isn't about adapting to new tools - it's about understanding how these tools are transforming the very nature of human ingenuity and innovation.

How AI is Changing What We Traditionally Perceive as ‘Creative’

When Abbey Road Studios explored adaptive music and automated composition as part of its music tech incubation programme, Abbey Road Red, it crystallised a pivotal moment in British creative history. In November 2022, AI music composition platform DAACI joined their programme. In June 2024, in that same music sector, Universal Music signed a deal to train artificial intelligence to make "ultra-high fidelity vocal models" of its artists. These weren't AI replacing musicians - it was the world's most famous recording studio and record label finding new ways to amplify human creativity. The tools that once seemed like science fiction are now as commonplace in British studios as coffee cups, computer screens and an AMS Neve console from Burnley (look them up - mental!).

In the UK's £108 billion creative arts sector, AI tools are reshaping how we work. At the Royal College of Art, students have been integrating Midjourney and DALL-E into their creative processes for years. The Serpentine Galleries in London launched a dedicated AI art programme. Even the BBC (that stalwart of British tradition!) is experimenting with AI in production, while maintaining strict guidelines about transparency and human oversight.

Lurking below this rapid adoption lies a deeper question for me: Is AI fundamentally changing what it means to be creative?

The creative industries stand at a crossroads. It's not the apocalyptic scenario some predicted - AI hasn't replaced human creativity. Instead, we're seeing something more nuanced: a reformation of creative practice. The above examples show this perfectly - AI isn't replacing the magic of Abbey Road or the wonder of Dylan’s lyric writing; it's making that magic more accessible to creators worldwide.

Jake Elwes, whose AI-driven artwork The Zizi Show explores questions of identity and performance art, demonstrates this evolution. His work, featured at the Zabludowicz Collection in London, doesn't replace human creativity - it extends it into new territories. AI then is another medium to work with, not a replacement for human creativity.

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This transformation brings legitimate concerns. When Abba launched their Voyage show in London, using AI and digital technology to create virtual performances, it sparked debate about authenticity in creative work. These discussions aren't just academic - they have real implications for our creative workforce.

The question isn't whether AI will replace human creativity. Instead, we should ask: How can we harness this technology to enhance rather than diminish human creative potential? What new forms of expression might emerge from this partnership? And how do we ensure that as AI capabilities expand, we maintain the essentially human elements that make creativity meaningful?

This isn't just about adapting to new tools. It's about understanding how these tools are transforming creative practice at its core. The stakes couldn't be higher - or the opportunities more exciting.

The Nature of Creativity: Beyond Arts and Entertainment 

We often suffer from a peculiarly narrow view of creativity. While the examples from Abbey Road Studios and the UK's creative sectors show how AI is transforming traditional creative industries, this barely scratches the surface of creativity's true scope. 

Creativity isn't a special sauce reserved for artists and musicians - it's fundamental to how humans solve problems and envision new possibilities. When a teacher designs a lesson that finally makes a concept click for struggling students, that's creativity. When a nurse develops a better way to manage ward rotations, that's creativity. When an engineer finds a novel solution to reduce carbon emissions, that's creativity too.

This broader understanding becomes crucial when we consider AI's role. Consider how Britain's Met Office uses creative applications of AI to improve weather forecasting accuracy. Their work combines vast amounts of data with innovative modeling approaches - a perfect example of how creativity in scientific domains often means seeing connections others have missed.

What's particularly interesting is how AI is helping us rediscover this broader definition of creativity. When we see an AI system generate art or compose music, we're forced to question our assumptions about what creativity actually is. This connects directly again to Margaret Boden's pioneering work on computational creativity - she argued that understanding how machines can be creative helps us better understand human creativity itself.

“Creativity isn't magical. It's an aspect of normal human intelligence, not a special faculty granted to a tiny elite. There are three forms: combinational, exploratory, and transformational. All three can be modeled by AI—in some cases, with impressive results. AI techniques underlie various types of computer art. Whether computers could “really” be creative isn't a scientific question but a philosophical one, to which there's no clear answer. But we do have the beginnings of a scientific understanding of creativity.” Margaret Boden

But perhaps most importantly, this expanded view of creativity helps us move beyond the tired narrative of 'AI versus human creativity' towards something more nuanced: how different forms of intelligence might complement each other in solving complex problems.

AI as Intelligence Amplification: Partners Not Replacements

The term "Intelligence Amplification" was coined by British psychiatrist W. Ross Ashby in his 1956 book An Introduction to Cybernetics. Unlike artificial intelligence, which aims to create autonomous thinking machines, intelligence amplification focuses on how technology can enhance human cognitive capabilities. This distinction is crucial for understanding AI's role in creativity.

Take the renewable energy sector. At the University of Sheffield, researchers are using AI to optimise wind farm performance. The AI doesn't independently solve energy distribution problems - instead, it helps human engineers visualise complex data patterns, enabling them to make better-informed creative decisions about turbine placement and grid management. The machine and the human dance together. 

Similarly, Cambridge-based AstraZeneca's drug discovery teams (don’t just pigeonhole them into COVID vaccines!) use AI to identify promising molecular compounds. AI doesn't replace the scientists' creativity; it expands their ability to explore possible solutions. As detailed in their recent research publications, this partnership has accelerated the early stages of drug development by helping researchers see patterns they might otherwise miss.

The philosophical implications here are significant. Ryle's concept of 'knowing how' versus 'knowing that', documented in his 1949 work The Concept of Mind, is pertinent. AI systems excel at 'knowing that' - processing vast amounts of data and identifying patterns. But humans retain the crucial 'knowing how' - the ability to contextualise these insights and apply them creatively to real-world problems. 

This human-AI partnership is exemplified by the UK's National Air Traffic Control. Their controllers use AI-enhanced systems not to automate decision-making, but to better visualise complex air spaces. The creativity required for managing unexpected situations remains firmly human, while AI amplifies their capacity to process information quickly.

The Human Element: Beyond Amplification

Having established how AI amplifies our creative capabilities, we must confront another crucial question: what remains distinctly human in this partnership? This isn't just about dividing tasks between human and machine - it's about understanding the unique value we bring to creative processes.

At DeepMind's London headquarters, researchers working with AlphaFold that we linked to earlier have discovered something telling: their most successful projects aren't those where AI works autonomously, but where it enhances human understanding and decision-making. This builds directly on what we've seen in sectors from architecture to music production - AI excels at processing and pattern recognition, but humans provide the crucial contextual understanding that gives these patterns meaning.

This dynamic is reshaping how we think about creative partnerships. At Manchester University's School of Computer Science, researchers are finding that the most effective systems are those that help humans understand why decisions are being made. It's this transparency that allows for genuine creative collaboration rather than blind reliance on AI outputs.

As our creative partnership with AI deepens, thorny questions emerge about authenticity and originality. When Abbey Road Studios' AI music platform generates a composition, or when architects use generative design for buildings, who owns the creative spark? More importantly, does it matter?

This isn't purely academic. The UK's Intellectual Property Office is actively grappling with questions about AI-assisted creative works. When Universal Music signed their deal to create AI voice models of artists, it raised fundamental questions about consent and creative control. While the technology offers exciting possibilities, it also challenges our traditional understanding of artistic authenticity.

The implications stretch further still. When NHS trusts use AI to design treatment plans, or when civil engineers employ it for infrastructure projects, we face similar questions about human agency and responsibility. A bridge designed with AI assistance is still ultimately a human creation - but where exactly do we draw that line? If this bridge collapses, who is to blame? 

These questions become particularly acute in education. UK schools incorporating AI tools like ChatGPT into creative writing or problem-solving exercises face a delicate balance. How do we foster genuine creativity while acknowledging AI's role in the creative process? How do we assess originality in an age of AI assistance?

Students using AI tools like Midjourney aren't just creating art - they're actively questioning what artistic authenticity means in a digital age. Their work suggests that perhaps we need to move beyond traditional notions of originality toward a more nuanced understanding of creative collaboration. In the same way that we use word processors and don’t call that cheating, perhaps the cyborg nature of human + AI in content creation is the next natural step.

The challenge isn't just philosophical - it has real implications for how we value and protect creative work. As AI tools become more sophisticated, we need frameworks that recognise both human and machine contributions while preserving what makes human creativity unique: our ability to understand context, make ethical judgments, and connect with human experience.

Future Horizons: Crystal Ball Not Included

Predicting the future of AI and creativity is about as reliable as British weather forecasting - which, ironically, is now significantly improved by AI! Nevertheless, some trends are emerging that hint at where this partnership might be heading.

Remember when we thought AI would replace creatives? That prediction aged about as well as my 1990s shell suit. Instead, we're seeing the emergence of what might be called 'creative symbiosis'. At Cambridge's Judge Business School, researchers are tracking how industries from advertising to engineering are developing workflows that seamlessly blend human insight with AI capability. Though given how quickly things change in tech, by the time you read this, we might all be telepathically communicating with our AI assistants.

The UK's creative arts sector is likely to transform further as AI tools become more sophisticated. But rather than displacement, we're seeing signs of augmentation. The BBC's R&D department is already experimenting with AI tools that help producers identify emerging storytelling trends while leaving the crucial human elements - empathy, cultural understanding, humour - firmly in human hands.

Education will likely see some of the most profound changes. Schools across the world are already grappling with how to prepare students for a world where AI is a creative partner rather than just a tool. The challenge isn't teaching kids to use AI - they're probably better at it than us already - but helping them understand when and how to leverage it effectively. On a side note, I have heard lots of educators and parents say that things like ChatGPT are going to make our students lazy. I hear the concern but respectfully and wholeheartedly disagree! The reality is that in a world of quantum computing and potentially instantaneous access to information through developments like Neuralink, the traditional model of ‘learning’ may well be a redundant concept within our lifetime! Imagine that. 

Most excitingly though, we might see entirely new forms of creative expression emerge. Just as the invention of photography didn't kill painting but gave birth to new art forms, AI might enable creative possibilities we haven't yet imagined. Though I draw the line at AI-generated crisp flavours - some experiments are better left unpursued.

Takeaways: Making AI Work For Your Creativity 

Like any good creative project, let's finish with some practical insights. After all, theory's brilliant, but as any teacher marking coursework knows, it's the application that counts.

The first key to making AI your creative partner is to think in terms of amplification rather than replacement. Use AI to handle the heavy lifting of data processing and pattern recognition, while focusing your human creativity on what matters: context, nuance, and meaning. Think of AI as your creative sat-nav, not your chauffeur.

Next, embrace a broader view of creativity. Look beyond traditional 'creative' sectors and recognise that problem-solving itself is creative work. This mindset shift allows you to apply creative thinking to how you use AI itself, finding innovative ways to leverage its capabilities across different domains.

Ethics must remain at the forefront of your approach. Consider the implications of AI use in your field, be transparent about AI assistance, and keep human judgment at the core of decision-making. This isn't just about following rules - it's about ensuring AI enhances rather than diminishes human creative agency.

Adaptability is crucial. Keep learning as tools evolve, experiment with different AI applications, and be prepared to change your approach as technology develops. The landscape is shifting rapidly, and flexibility will be key to making the most of new opportunities.

Finally, maintain perspective. Remember that AI is a tool, not a magic wand. Value your human insights and expertise, and focus on outcomes rather than just capabilities. The future of creativity isn't about humans versus AI - it's about humans and AI working together to solve problems and generate new possibilities.

Just remember to keep your sense of humour about it all. After all, at least AI doesn't make dad jokes... yet. Though if it does start making dad jokes, I'm definitely writing another article about that.