Being creative in an age of genAI | by Jasper Kense | Jan, 2024


Large language models are getting better at mimicking human creativity. That doesn’t mean they’re actually being creative, though.

Creative industries can benefit from AI-assisted creativity — But I don’t think they will replace the creative
Creative industries can benefit from AI-assisted creativity — But I don’t think they will replace the creative

As the AI boom is crystallizing we are seeing the first strengths emerge, along with its fair share of weaknesses. Generative AI has proven to be an amazing technology with the potential to impact many industries — But is our early fear of creativity justifiable?

The reason I wanted to share this post is an article I came across, titled ‘AI just beat a test for human creativity, but what does that even mean?’ I think that exact question is something that the creative world, and specifically designers, rightfully worry about.

The impact that genAI does have

The business impact of generative algorithms on industries is slowly materializing itself. We can see companies with a strong connection to AI peak on our public exchanges, a sign of real value being produced. These companies are at the forefront of (generative) AI and are betting on being number one in new industries.

Recent advancements in technical capabilities, as highlighted in a McKinsey report, suggest that the impact could be profound. According to their research, the estimated annual addition to global economic value ranges from an impressive $2.6 trillion to $4.4 trillion across 63 analyzed use cases. To put this into perspective, it surpasses the entire GDP of the United Kingdom in 2021, which stood at $3.1 trillion.

However, it’s essential to approach these figures with cautious optimism, acknowledging that the potential value is yet to be fully realized. While the nascent stages of generative AI’s influence on the global industry are becoming apparent, the true extent of its impact is still unfolding. As we navigate this era of genAI, questions persist about the nature of creativity in the face of artificial intelligence and whether the early apprehensions surrounding it are justified.

The strengths and weaknesses of generative algorithms

As we continue to see the crystallization and true value of generative capabilities on creative industries, we realize that certain applications are becoming less and less relevant. Sometimes it is too easy to say: “Let’s use AI!” — Just like your manage might. We need to find the right tools at the right time.

One example is the use of LLMs to write articles. While LLMs are good at writing lots of articles, the articles just feel bland. There is little out-of-the-box thinking found and the creative twist is almost always lost. For that reason you’ll find that a Midjourney picture feels like a Midjourney picture.

This picture from Flickr just screams Midjourney. And indeed, it is.
This picture from Flickr just screams Midjourney. And indeed, it is.

What we can learn from that example is that, while good at diverging, generative algorithms tend to uphold to historic patterns. Out-of-the-box facts do not adhere to patterns, but rather break patterns.

It is logical once you realize that generative algorithms, not just LLMs, are trained by historic data. The output generated is a generalized version of that training data. You’d rarely see an albino tiger when asking Midjourney for a picture of a tiger. Generative algorithms inherently adhere to patterns.

What is the place for creatives in AI powered industries?

While it might be good to find patterns for certain industries, like data science, for creative industries it is but a tool. While it might be helpful for a designer to find 100s of variations of a toothbrush design, having one creative designer will give you the most unique design.

A designer can put the generative capability to their advantage, leveraging on visualization tools like Dalle2 and Midjourney. They can explore what the world has to offer. But to truly be creative, one would need to mostly explore their own ideas and experience.

To refer back to the article I mentioned earlier, an algorithm might be able to mimic creativity to a certain extend. It might be able to function as a sparring partner for the design community. But to be disruptive, to be out-of-the-box, companies should look to up their design maturity.

Another point I want to make is more extreme. Imagine we would have a world where all creative work is done by genAI. GenAI builds on its training data, creating nothing new in the process. We would then train newer versions with output generated by older versions. Would we then see new disruptive technologies and design? If you ask me, I think it is very unlikely.

This future where innovation is non-existent makes creates a rather dystopian future. We would lose out-of-the-box ideas, meaning innovation comes to a halt. That is a future I don’t believe will ever exist.

The last year has made clear that we, as a design community, should not feel feared by the developments. We should rather feel empowered by the new shortcuts in our workflow. But creativity will always stay with humans.

As we witness the evolution of AI in creative industries, it becomes evident that these technologies can serve as powerful aids rather than replacements for human ingenuity. The key lies in understanding the symbiotic relationship between human intuition and AI assistance. While generative algorithms excel at data-driven tasks and pattern recognition, they lack the emotional depth and nuanced understanding that humans bring to the creative process.

How we should make ourselves ready

The synergy between human creativity and generative algorithms can lead to unprecedented innovations. While AI may excel in pattern recognition and optimization, it lacks the intuitive, experiential depth that human designers bring to the creative process. A human touch is essential for understanding emotions, cultural nuances, and a profound understanding of societal trends into artistic endeavors.

AI is simply a data-driven solution. We should not fully rely on creative output from generative algorithms, for the same reason that designers do not solely rely on analytics and heatmaps. Creativity, at its core, is a deeply human attribute that goes beyond the replication of existing patterns. That means that nuance, context and emotions are to be fully understood to output creatively.

The coexistence of human creativity and generative AI holds potential to unlock new workflows in creative processes. The fear of AI replacing human creativity, or the blue sky question ‘how do we actually use this to our advantage’ should be replaced with a proactive, positive mindset. We’ll be able, and already are in some degree, to leverage AI as a tool to boost our human capabilities.

As the design community navigates this evolving landscape, it is crucial to recognize that while AI can mimic certain aspects of creativity, it cannot replace the authentic, groundbreaking ideas that stem from the rich tapestry of human experience. The future is not a dichotomy between humans and AI but a collaboration that propels creativity.


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