Automating creativity: How AI makes us more creative

Generative AIs are capable of being creative, which is a core irony since they were initially designed to be all logic and no imagination.

They can make up information, engage in emotional discussions, and generate new ideas but are generally not regarded as being creative.

However recent experimental papers have shown that AI can in fact be creative in real-world settings, a fact that makes some people uncomfortable.

Yes, AI is creative in practice (really)

Three recent experimental papers have directly compared AI-powered creativity with human creative effort in controlled experiments. The first paper, conducted by researchers at Wharton, staged an idea generation contest between ChatGPT-4 and students in a popular innovation class.

The researchers used human judges to assess idea quality and found that ChatGPT-4 generated more, cheaper, and better ideas than the students. Even more impressive was that the purchase intent from outside judges was higher for the AI-generated ideas.

The second paper conducted a crowdsourcing contest, asking people to come up with business ideas based on reusing, recycling, or sharing products as part of the circular economy.

The researchers then had judges rate those ideas and compared them to the ones generated by GPT-4. The overall quality level of the AI and human-generated ideas were similar, but the AI was judged to be better on feasibility and impact, while the humans generated more novel ideas.

The final paper focused on creative writing ideas, comparing humans working alone to write short stories to humans who used AI to suggest 3-5 possible topics.

The AI proved helpful: humans with AI help created stories that were judged as significantly more novel and more interesting than those written by humans alone. However, the most creative people were helped least by the AI, and AI ideas were generally judged to be more similar to each other than ideas generated by people.

So what does this mean?

Reading these studies, it seems like there are a few clear conclusions:

• AI can generate creative ideas in real-life, practical situations. It can also help people generate better ideas.
• The ideas AI generates are better than what most people can come up with, but very creative people will beat the AI (at least for now), and may benefit less from using AI to generate ideas
• There is more underlying similarity in the ideas that the current generation of AIs produce than among ideas generated by a large number of humans.

All of this suggests that humans still have a large role to play in innovation… but that they would be foolish not to include AI in that process, especially if they don’t consider themselves highly creative.?

Prompting for ideas

In the context of idea generation, people often believe that specific wording is necessary to prompt AIs to accomplish tasks. However, this is not the case. In a paper comparing AI to crowdsourcing, the authors tested three kinds of prompts:

• basic ones that stated the problem,
• more advanced ones that gave the AI a persona to be more like a human solver, and
• very advanced ones that asked the AI to take the perspective of particular famous experts.

Simple prompts seemed to work fine.

Researchers also experimented with few-shot prompting and found that, while few-shot learning is easy to do, and the AI generated more and better ideas with few-shot approaches, the difference was not statistically significant.

Key takeaways from these studies

AI language models work better with constraints (just like humans do!)

Force it to give you less likely answers, and you are going to find more original combinations, which may solve the originality problem.

Generative AI has altered the landscape of human creativity, making it less limited by ideas than ever before.

Even people who do not consider themselves creative now have access to a machine that will generate innovative concepts that beat those of most humans. However, the most creative individuals are still able to come up with better ideas than AI. The future of creativity will be distinguished by execution, not raw creativity.

Practical tips

Here are some practical tips on how to use AI for idea generation based on the results of these experimental papers

• Use constraints when prompting AI to generate more original combinations of ideas.
• Use simple prompts that state the problem.
• Consider using few-shot learning to generate more and better ideas.
• Use AI's ability to hallucinate plausible but interesting material as a seed of creativity.
• Experiment with different prompt techniques to find what works best for you.

In conclusion, generative AI has the potential to augment human creativity and democratize innovation, but it also poses threats and challenges that need to be addressed through human-centric capabilities such as creativity, curiosity, and compassion.

Happy prompting!

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Hi there! I am a seasoned digital marketer with a wealth of experience across a range of marketing activities, from SEO and social media to email automation and ecommerce, with a love for oil painting and mountain biking.