• Posted on 9 May 2024
  • 18-minute read

Artificial intelligence (AI) is reshaping creativity. From crafting narratives, poetry, music, and art to data personalisation, driverless cars, augmented reality, and solving intricate business challenges. The question that's emerging is where human creativity and innovation find their place amidst the growing use of AI. To explore this intersection, we turned to the insights of three experts from the University of Technology Sydney (UTS).

The changing workplace

The workplace is transforming due to the integration of AI tools such as ChatGPT explains Dr Sumati Ahuja, Program Director for the Digital Creative Enterprise major at the UTS Business School. AI tools use machine learning algorithms that can absorb a large amount of existing data and create something new – and it’s all based on a single prompt.

In the creative industries Dr Ahuja says, there is a great deal of apprehension that AI will be used to generate creative inputs that were traditionally provided by humans, and as a result replacing people in many jobs. Driven by these fears, it was one of the reasons Hollywood writers went on strike for 5 months last year concerned that AI would replace them in the interest of efficiency.

Despite the hype that AI will replace humans in many jobs, Dr Ahuja tells us it’s important to remember two things. Firstly, AI is trained on existing data and is not capable of ‘original thought.’ It needs humans to create the data it trains on. Without humans to create the data, even highly intelligent machines can’t ‘create’ anything. Secondly, according to a recent article in The Verge, AI doesn't actually replace work, instead it reshapes how work is organised.

The article points out that processing raw information to train AI models is tedious and repetitive ‘human’ work, generating a vast underclass of low paid workers who often have no idea what the purpose of their job is.

As AI is rolled out across a range of industries, the article also raises important questions about the ethical implications of data shaping (the process of collating, organising, and structuring data). These include:

  • What information (data) is shaping these systems?
  • Who are the people doing the shaping, and at what (human) cost?

A recent Google research paper claims that there are millions of people who work in annotation (the work of ‘tagging’ data for machine learning), mainly in developing countries on very low wages, with the potential for this underclass to be blown out to billions of people.

The definition of creativity

As AI systems become more capable, Dr Ahuja explains it’s entirely possible our definition of creativity will change. The ways in which we express our creativity will need to evolve beyond what machines are capable of. This opens opportunity for entirely new creative methods and practices to emerge, as well as new forms of creative expression that use AI capabilities.

Dr Ahuja envisions a synergistic relationship between human creatives and AI.

“Human creatives bring their original ideas, unique lens, intuition and passion, and AI can be used in ways that augment rather than replace this human creativity.”

As this creative relationship takes shape, Dr Ahuja also highlights the importance of addressing legal and ethical issues to ensure that the rights of humans involved in creative processes are protected.

Teaming up with AI

Dr Antonette Shibani, Senior Lecturer at the TD School at UTS advocates that AI does not replace human creativity and innovation, but instead calls for a different form of engagement from humans to augment our collective intelligence.

According to Dr Shibani, humans bring unique perspectives, emotions, and a nuanced understanding of our world that AI lacks. Rather than seeing AI as a competitor or substitute, she encourages seeing it as a high-tech assistant, working in tandem to accomplish tasks more efficiently.

Adaptability, transdisciplinary thinking, ethical decision making, and critical engagement with AI are crucial to stay actively engaged and continuously learning in an AI-driven future. Educators must also focus on nurturing these skills in learners alongside their disciplinary knowledge, particularly as we advance into an era of more sophisticated artificial general intelligence. Dr Shibani says the best way to work alongside technology to tackle big challenges, is to combine our collective strengths.  

“While AI can come up with 100 creative ideas for your new project, you should be the judge of what is good, practical, and aligns with your values. The combination of AI’s generative capabilities and human judgement gives you the best of both worlds and results in a more robust and well-rounded creative outcome.”

Dr Shibani highlights the productivity improvements brought about by AI, from writing emails to drafting business presentations, which free up human capacity for more complex, abstract, and empathetic problem-solving and innovation.

However, she points out that the true potential of AI extends beyond replicating our already existing ways of working. To fully utilise its power, we need to learn to partner with it to reimagine how these tasks were thought out in the first place.

Dr Shibani uses a metaphor generated by ChatGPT 3.5 to emphasise the untapped potentials of technology:

If a cognitive partnership with AI is not sought, it is akin to owning a high-performance car with numerous gears but only driving it in first gear. You have a vast array of capabilities at your disposal, yet by not exploring the full range, you're essentially cruising in a limited capacity, missing out on the acceleration, efficiency, and the exhilarating journey that the technology can offer!

AI humour

While models like ChatGPT excel in various creative tasks, such as compelling short stories, and essays capable of challenging the foundations of our education system, many believe humour to be a unique challenge for AI models.

Grok is the latest addition of large language models and it’s been deliberately designed to be funny –without much success – revealing a potential limitation of AI models and their creative capabilities.

Professor Adam Berry from the Human Technology Institute at UTS however believes this may not be as clear cut as we once thought.

Professor Berry shared a story of his friend asking DALL-E (an AI system designed to create realistic images/art from a description in natural language) to produce a special holiday t-shirt.  

The idea was simple: design a souvenir t-shirt capturing the likeness of four friends enjoying quality time together in Queenstown. However, things didn’t go to plan when representing a friend who had recently become a father.

Despite successfully including a baby, DALL-E mistakenly gave the new dad a grizzled beard, which was an attribute he did not possess. Several attempts to fix the digital beard failed, leaving the friend forever 'bearded' on his virtual t-shirt. 

On the surface, Professor Berry said it looks like a basic failure, but he argues that it actually shows us something interesting.

“In DALL-E’s world, fed endless images from the internet about what humans are, it picked up on a grand and unifying truth — dads with babies are grizzled, bearded types. No amount of prompting could sway DALL-E from that truth. If you are a man with a baby, you must also have a beard.”

Professor Berry believes this to be a great example of AI wit.

“It’s intuitive to think that generative AI models won’t or can’t be funny, as humour often requires unique perspective, incisive commentary and surprise – qualities that don’t immediately come to mind for systems built on predicting the next word. Yet this t-shirt example suggests otherwise – It offers commentary on how we present ourselves online in a surprising and ultimately humorous way.”  

Beyond the amusement, there's a profound insight here. According to Professor Berry, DALL-E is articulating something from its unique perspective. DALL-E has picked up on a lot about our online selves, and our representations, and whether intentional or not it’s reflecting these back at us.

This DALL-E example highlights the very important need for meticulous, creative and diverse human thought on what data we feed AI models and how that may influence its perspective of the world and the outputs it produces as a result.

What we've learned

AI's impact on creativity and innovation is multifaceted; transforming workplaces, redefining creativity, and presenting challenges related to historical data and our online presentations.  

Despite widespread fear, AI can act as an important collaborator in the creative process. It can help to automate mundane tasks, which gives us more time to get creative. It can use complex data sets to inform design decisions and provide us with some much-needed creative direction. We can explore a thousand more concepts before landing on the right one – opening the door to endless possibility.  

However, the creation of technologies, and the data inputted, and insights generated from AI still need interrogation, meaningful interpretation, creative and critical thinking, as well as emotional intelligence.

Want to learn more about AI? Check out our Curiosities series on YouTube

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Descriptive transcript

Hello, curious people. I'm Professor Adam Berry, Professor of Data Innovation, and I'm here to answer your curious questions about artificial intelligence, or AI. This is AI Curious.

[Upbeat music plays. UTS logo appears on screen.]

Okay, so our social media community has sent in some fairly curly questions to tackle, so let's get started.

Can AI feel emotion? Truth is, we have no idea. So I certainly hope that the answer is no, because we're spinning up artificial intelligence all the time, and unfortunately that means we're also turning it off all the time. And if you think about humans, part of the reason that we feel things is that we've evolved to feel things. So back early in time, if there was a lion or a tiger or something hunting me, it would make sense for me to feel afraid, and then I'd run away. When we design artificial intelligence, we don't need to build that into it. So historically, there would be no purpose for us to build in that feeling. But whether or not there's some kind of emergent property that's come out, we actually don't know, but my hope is the answer is no.

Our next question here is, will AI ever be able to adopt critical thinking skills? In my opinion, the answer is yes, and it's already happening. So if you've ever used ChatGPT from OpenAI or Gemini from Google, you'll notice that when you ask questions, it gives not just the answer, but can also reference materials, it can explain why it came up with a particular solution and so on. So in my opinion, that's already displaying critical thinking skills. More importantly, if you actually deliberately ask one of those models, "Think about this step by step," the answers that you get out the other side are actually improved, and it shows, step by step, the critical thinking skills that large language model has. So the answer here is yes.

Our next question is, could AI ever be used to create companions? What are some of the ethical issues involved in using AI for companionship? Earlier, I mentioned ChatGPT and Gemini. These are large language models, basically things capable of producing language and interacting with humans in natural ways. We're already seeing virtual girlfriends appearing on the large scale, and these technologies have only been out for somewhere around a year or so. So the fact that we're already seeing things like virtual girlfriends emerging suggests, yes, there's definitely going to be an impact here in terms of human relationships and companionship. In my personal opinion, this is, of course, problematic. There's value that companionship can offer, even if it's an automated form, but we need to be really clear about stating that you are engaging in an artificial form of companionship. For anyone that's watched the movie Her, you'll know that if you don't understand that that's what's happening, it can come as quite a surprise.

Our next question is, do we still need a human element in decision-making or overseeing AI algorithms? Yes, absolutely yes. Please make sure that we have humans in the loop across the whole AI cycle. So that's not just when we go to use it, it's when we design it, it's when we develop it, it's when we test it, it's when we maintain it. So artificial intelligence is incredibly powerful, but if we're not including the voices of the people it might impact as we design it and as we test it, then there's very real danger that we'll miss something and we'll end up hurting people. So it's really critical that we include people across the process. And if we do that, I'm hopeful that we end up with solutions that are tailored, not just to the business using the AI, but also to the people that could benefit from it.

Our next question is, what happens to human creativity and innovation and progressive perspectives if we're only using historical data? Most of artificial intelligence, the way it works is we take a lot of historical data, we use that historical data either to predict the future or to understand the context of what our solution should be, but a lot of it is built around history. Now, history is problematic and a lot of that data bakes in stereotypes, cultural norms, social norms, those sorts of things. So if we're relying exclusively on that data to predict or inform the future, then it definitely is the case that it is more difficult to come up with genuinely new ideas or to be progressive, to push beyond what the past has said is possible. Having said that, if you've used any of these new generative AI tools, so things like DALL-E is an example, I can't draw at all, I have no artistic skill whatsoever, and it's amazing that I can now, through language, design artwork that reflects something I'm passionate about or interested in. So in some ways, it opens up creativity to people that otherwise wouldn't have the capacity to do that. So that is absolutely exciting, but there are risks associated with it just because everything that we build is built on history.

Our next question is a really important one, which is, does AI eliminate human bias? One of the appeals and I guess one of the features that people really like about data science and artificial intelligence and data in general is that there is something that feels sterile and objective about data and that it's factual and it will give us facts back as a result. But as I mentioned before, the way most artificial intelligence is built is on historical data. And unfortunately, a huge amount of the historical data that we do have has bias baked into it. So an artificial intelligence model is just going to learn that bias and regurgitate it. As an example of this, Amazon, an amazing leader in the technology space, produced a hiring tool that was going to use artificial intelligence so that they could automate some of the hiring decisions that they were making. And part of the intent here is, hopefully we can get rid of this human bias that's there. Unfortunately, it turns out what part of the model learned was that historically, Amazon hired primarily men. So the consequence of that was that the model re-articulated that, regurgitated that, and so was promoting the idea that men were better fit for positions than women were. So here's an example where the intent was a positive one, but the skew in the data, the bias in the data, those historical practices get baked into the model in a way that's difficult to predict and then actually leads to the exact opposite of the outcome they were hoping for. So bias in AI, absolutely something we should think carefully about and is potentially a real problem. The best way to address it is for people to be involved at every step of the process, including discussing and understanding the data that we're building those models from.

We have a question here on how will AI affect human relationships? I think it's going to affect relationships in pretty profound ways. And part of this is that our modern artificial intelligence algorithms are now so powerful that the interactions that humans have feel a lot like the types of interactions we have with these chatbots that are emerging. And to give you a sense of how this can be potentially problematic and how it can damage relationships, there's a new idea that is emerging called heaven banning. And the idea behind heaven banning is if you're on an online platform and you're starting to spread things like hate speech and the like, then a response a platform could have is to slowly replace your community with chatbots that basically engage with you in a completely authentic way, but that means your hate speech doesn't go to any actual human ears. Now, I can understand the motivation for this, but it's quite an Orwellian outcome that the way we solve some of our problems about how humans interact with humans is to lock them in a room with bots and pretend that that is the real world. So I think human relationships are critical. We need to maintain them to the best extent possible. AI can help, it can break down language barriers. On my new phone, I can do auto-translation now, which means I can talk to people in other languages. That's remarkable for enabling human relationships, but we just need to think very carefully about the best way to do that.

We have a great question here, which is how can AI practically improve our daily lives? One of the things about artificial intelligence, I've heard a definition before, which is artificial intelligence is whatever we can't do yet. So it always feels like artificial intelligence is on the horizon or in the future. Whereas the truth is artificial intelligence is all around us already and does a huge amount of useful stuff for us. So as an example, when I drive home later today, I'll be using Google Maps. Sitting behind that is artificial intelligence that's working out historically how busy has this road been. It knows the route that I need to take because it understands where I should be turning, where I shouldn't be turning. All of that is artificial intelligence. When I ask Siri a question and it sometimes gives me a helpful answer, that's artificial intelligence. It's understanding the words that I use, being able to put that in the context and then sending that out, doing an internet search and then returning back a solution. That's AI all the way down. And now we're seeing increasingly generative AI products that are helpful in all sorts of ways, whether it's I want to write a silly poem, I want to tell a joke, I want to come up with a picture of a dog chasing a Frisbee, and I'm hopeless at drawing. All of that is possible now with AI. So I think tremendously helpful already and will only become more helpful going forward.

Our last question here is, can AI surpass human intelligence? I think in some ways it depends what we mean by surpassing human intelligence. So already I would argue if you look at something like ChatGPT, it's basically a B-level student at every possible discipline you could imagine. So I think you put any human in a room with ChatGPT, the human will be significantly better at some things, but ChatGPT on average will probably beat the human. And to give you an example of that, I don't know of many humans that are great at writing code, that can give you a solution to a complex physics algorithm, that can write a poem, can draw a picture, and so on and so forth. It is remarkable how quickly these systems have become incredibly intelligent, but it's also understandable to some extent. So if you gave me an infinite amount of time to absorb every piece of information digitally available, then I would probably end up at least understanding some of that. And that is the way that we build these models. It's just a huge amount of information.

What's interesting about something like ChatGPT is underneath it, all we're asking that model to do is to predict the next word. That's it. So if I have a sentence, "I like throwing Frisbee with my dog," all ChatGPT is trying to work out is what's the next word that follows "dog"? Maybe it's Fido. But it turns out in order to do that for all sorts of different conversations in all sorts of different domains, ChatGPT basically has to learn about the whole world, about people, about interactions, about disciplines. It does all of that just so it can predict the next word. So already that intelligence is baked in, it's impressive. I suspect it's only going to get stronger and better in the future, particularly as some of these models have the capacity to build the next generation of those models. And you get into these remarkable loops there where the models keep getting better because they're building and improving themselves.

That was all the questions for today. I hope you learned something new and until next time, stay curious.

 

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