Great Machinations

The next big thing in machine intelligence is already here. Multimodal foundation models, or large neural networks trained on vast data sets, are creating deep-learning systems at scale that allow transferability to myriad downstream tasks. AI systems built using these flexible models, such as DALL-E 2, Midjourney, Stable Diffusion and GPT-3, can turn concepts into art or prose into poems by identifying patterns based on a single text prompt.

Creators across disciplines are adopting these auto-generation tools into their workflows at a staggering rate (OpenAI recently granted access to more than a million users in just a few weeks), sparking important and thorny questions about copyright and plagiarism. It’s not a matter of if but when modern industries will adapt to these developments. Meanwhile, the field of design is entering a period of uncharted transformation. And the time for questioning is now, while there’s still time to influence its trajectory.

As a creative director focused on innovation, I wonder how AI will impact our craft and our livelihoods. Will it be our collaborator or our competition — and why would it matter?

What we know for sure is that foundation models can mimic creativity in a way that is completely indistinguishable from human output. The results can be strikingly emotional in nature, and it’s this characteristic that foreshadows our future. We’re standing at the edge of a technology-fueled creative revolution. The question is: Will we lead it?

The Influence of Emotion

Emotion is deeply embedded into the creative process, influencing how ideas are hatched, leading to great creative thinking that is derived from a mix of complex nuances of the human condition. With AI, we’re witnessing a level of sophisticated intelligence so advanced that it appears to embody these qualities. The ability to be expressive and conjure emotion in an audience brings AI much closer to replicating human creativity.

AIs are trained to recognize patterns, make connections and produce results, but we’re often surprised when the results seem subjective — appearing human in a way that is freakishly convincing. But subjective biases like humor or aesthetic taste are actually derived from human intelligence: the capacity for learning, reasoning and understanding. For instance, you have developed a specific sense of humor because you’ve been “trained” to cognitively process comedy. Theoretically, if a machine were trained with heaps of humorous data, it’s conceivable that it could develop a funny bone that rivals the best comedy writers in the industry.

“The best AI can make bold statements and take risks your average writer would never consider. It can come up with ideas that are downright provocative, too. And it doesn't just do all this for fun — it does it because sometimes you need to be told something in a way that makes you sit up and pay attention.”

— Text generated in collaboration with Copy.ai

Instinctively, the human experience of viewing art involves making connections based on an individual’s interpretation. Designating an artist’s role to AI is acting as a kind of catalyst for this experience. What happens next is entirely up to humans.

At the Forefront

A growing number of prolific artists, creators and brands have already harnessed the power of AI, embracing the technology for its potential. They are becoming real-time pioneers.

Digital media artist Refik Anadol explores the subject of “what it means to be a human in the age of AI,” partnering with brands like Google, Microsoft and IBM to apply the latest developments to his work. With data as a central element, Anadol likens algorithms to an essential tool of the craft. As he told NFT Now, “I see AI becoming this extension of the human mind. When I did Wind of Boston, I was [telling people that] the data is here becoming pigments and the algorithm can become a kind of a brush. Data is still the pigment — but now, the brush can think.”

Los Angeles–based film director Paul Trillo has been experimenting with DALL-E 2 to showcase its ability to flow with fashion trends. Using a method called inpainting, Trillo created a mesmerizing, 30-second composite of a fashion show featuring hundreds of unique, AI-generated outfits on a model via live-action video. Not only is the work striking and imaginative, it inspires creators looking to iterate rapidly. Trillo described the power of AI as “limitless and overwhelming” to Fast Company, saying that it “opened the door to some pretty wild designs that I would have never come to on my own.”

Features like inpainting and the highly anticipated release of DALL-E 2’s outpainting provide creators with the tools to stitch ideas together seamlessly with high-quality extensions to the canvas.

Meanwhile, the very popular experience design app Figma has emerged as a leader on the bleeding edge of efficiencies, particularly with AI features. Recent plug-ins like Ando and Magestic allow UI/UX designers the ability to generate in-app ideas, and optimize the end-to-end design process through simple text prompts, shapes and images. Recently acquired by Adobe for an eye-watering $20 billion, Figma’s AI features are in the hands of more users than ever, bringing the immediacy of innovation into the design process — and on a massive scale.

This, coupled with the current deluge of news in this space suggests machine learning has already gone mainstream.

Exponential Efficiency

The speed at which a trained AI can generate a high volume of outcomes — or predictions, in AI speak — is remarkable. In seconds, it can assemble sophisticated words and images, drawing from a vast data set while constantly learning from it. Having access to deep data will always be AI’s competitive advantage. No matter how hard we work, humans will never be able to outperform machine efficiency at scale. Shall we concede this fact and embrace a partnership with AI to advance our profession? All signs point to yes.

Creatives are constantly angling for more time and space to practice their craft. We’re often inundated with mundane tasks that take us away from the real juicy stuff — the big, scope-for-imagination thinking everyone hopes for. Enter the machine: AI offers up a ready-made assistant to help tackle the grunt work. Suddenly, the human is the true visionary, while the machine is left to the execution. This dynamic already describes the artist-ex-machina relationship experienced by many of today’s generative artists, and will continue to evolve.

In a recent report, the research firm Gartner predicts: “By 2026, generative design AI will automate 60% of the design effort for new websites and mobile apps. Generative design AI reduces the human effort required for design exploration and production design. It allows designers to focus on user research, product strategy and solution evaluation, rather than detailed screen design tasks.”¹

AI can amplify the creative process by sketching dozens of design iterations for us. It can auto-complete our ramblings into coherence. But what could an ongoing collaboration with AI look like? An exciting benefit of this new tool is the ability to volley concepts with it — and receive unexpected results. It even has a playful quality to it, which is quickly winning over many of my colleagues.

“Having a tool that helps juice the system of creation is going to be invaluable. This new type of creativity is going to force people to learn how to use language to express outcomes, and I think that’s going to be a skill they’ll teach in school. The better you are at describing your desired outcome, the more successfully you’re going to operate in this new world of generative art,” says Steve Croll, group vice president of technology at Huge.

The potential here is to expand original thinking. To break us away from derivative ideas and designs, AI can spark concepts that humans wouldn’t arrive at immediately — or ever. Ideally, AI can help shake us from stale or rote habits and push us into fresh territory, helping us deliver work that is unexpected and novel. Bring on the revolution.

A recent article in The Economist, titled “Artificial Intelligence’s new frontier,” put it this way: “AI can be used as a software sidekick to enhance productivity. This machine intelligence does not resemble the human kind, but offers something entirely different. Handled well, it is more likely to complement humanity than usurp it.”

1. Gartner®, Predicts 2022: Generative AI Is Poised to Revolutionize Digital Product. Development, January 11, 2022.

Unintended Consequences

With all the bright promises of AI comes a dark potential: the long-term loss of craft excellence. The efficiency gained from automation might also threaten to render humans too reliant on machine intelligence, dulling our skills — and our own potential to develop true grit — in the process.

Learning how to design, write or ideate is an important part of every creative’s discovery process. What happens when the journey becomes too easy? Will we lose our edge? Worse yet — will companies prefer the work produced by AI to our best human efforts? According to Forrester research, “Large creative agencies will lose 11% of jobs to automation by 2023.”

That stat serves as a real warning sign. But it doesn’t tell us anything about the secondary effects of such a shift. And it doesn’t give any credence to our human capacity to adapt, either.

“The AI revolution promises creative growth in many areas and while some jobs and processes will change or disappear, others should emerge, and people will develop new ways of working in symbiotic relationships with AI. The positive vision for AI is one of co-creativity, where AI will assist creative professionals, not replace them,” writes Julian Watkiss for FE News.

For now, we are still the arbiters of quality. AI’s current output — whether it’s copy, conceptual imagery, creative code or product layouts — is mediocre at best without the guidance of humans. For some companies, generic AI-output might suffice. But for the impassioned creators looking to move the world forward, we’ll need to actively delineate the “good enough” from the “great” in each collaboration that leverages machines.

Text generated in collaboration with Copy.ai