2023 is the year of artificial intelligence. ChatGPT, Midjourney, DALL-E 2 and GitHub Copilot are AI tools that radically change how many designers and developers are working today. This rapid change in the tech landscape is impacting how creatives organize their routines. We’re entering the era of co-creation with AI. In this article, we will discuss a few notable changes that this era will likely bring about.
What Will AI Do to Creative Work?
Artificial intelligence is unlikely to replace humans who work in creative fields anytime soon, but it is rapidly changing the landscape. Designers, developers, and copywriters who embrace AI the use of AI tools in their work will gain a competitive edge in their careers.
AI as Co-Creator
Co-creation with AI refers to the practice of humans and machines working together to create something new or to solve a problem. AI tools can generate art (Midjourney, DALL-E 2), music (MusicLM), and even entire stories (ChatGPT).
You may wonder whether AI tools can completely replace humans. The answer is no, at least not right now. If you take a closer look at modern AI tools, you’ll notice one thing that they all have in common — they require human moderation.
Let’s take ChatGPT, a sophisticated chatbot that can generate text responses to questions, as an example. ChatGPT users say that the output that the tool generates requires fact-checking. The tool rarely says that it doesn’t know something and can easily make up answers to produce incorrect responses to a specific question. In January 2023, the NewsGuard team fed 100 prompts into ChatGPT relating to U.S. politics and health care. In 80 percent of its responses, ChatGPT produced false and/or misleading claims. Without fact-checking, the chance of an incorrect response skyrockets.
The same is true for the Midjourney, a text-to-image generator. Humans must validate the imagery this tool generates, and it often requires fine-tuning by graphic designers. For example, when Midjourney generates a silhouette of a human, it usually adds extra fingers to the hands or even an extra leg to the body.
AI can be a great co-creator, improving the efficiency of designers and developers, but it still requires a human moderator to review its output. The moderator should have relevant experience in the field to evaluate and refine the result.
How to Use AI Tools for Design Ideation
The ideation phase is one of the most critical steps in the design process. During this step, product teams explore various solutions to the problem they’re solving in design and try to find the optimal one. The speed of exploration plays a tremendous role during the ideation phase. The faster the team can explore potential solutions, the more effective the ideation phase will be.
AI tools can streamline the ideation process. For example, ChatGPT can suggest possible ideas for a particular problem. You can write a prompt like “Suggest 10 ideas for how to solve the cart abandonment,” and the tool will generate a list of ideas you can explore. ChatGPT’s most appealing feature is that the tool can answer follow-up questions. So once you receive a response from ChatGPT, you can ask clarifying questions such as “Explain the cart abandonment solution in more detail.”
Text-to-image tools like Midjourney or DALL-E 2 can replace moodboards. Designers often create moodboards, arrangements of images intended to evoke or project a particular style or concept, when they explore various visual styles they want to use in a product. Instead, designers can use plain words to communicate to AI tools what sort of images they want to see. This method of exploration is excellent because designers might not foresee what ideas the tool will generate for them. The tool can often create pictures that designers didn’t even think of. That’s why creatives should see AI tools as an opportunity to push the boundaries of what is possible.
The Human in the Loop
A prompt is an input text that the user provides to an AI tool so it can perform a specific task. An example of a prompt for ChatGPT is the text string "Generate ten ideas for local business in Nebraska." Modern AI tools are very sensitive to prompts. That’s why clearly formulated prompts can significantly impact co-creation with AI. The better a user specifies what they want to achieve, the higher the chance that an AI tool will generate the right thing. But the challenge of finding the right prompt is that it might be hard to predict how the system will react to particular words. So, the only way to find out is to experiment with different input signals and see how the system reacts to them.
As AI tools become increasingly sophisticated, they will depend less on prompts. The systems will rely on past user interactions to predict what a particular user wants to achieve when they provide a specific input. So, the process of co-creation with AI will be less about choosing specific keywords for the prompt and more about explaining the idea the same way you explain it to other humans.
Will AI Replace Creative Jobs?
AI tools require human moderation, and they won’t replace human professionals any time soon. But that doesn't mean designers’, developers’, and writers’ jobs are safe. The tech world is rapidly changing, and job requirements for each of these roles will change. AI won’t replace a human professional, but a human professional who masters AI can replace another designer that doesn’t have experience working with AI tools. That’s why AI is not the kind of thing you can ignore. Embrace AI tools and embed them in your design process to make your work more efficient and yourself more versatile.
AI Is Here to Stay, So Make It Your Colleague
AI is transforming the way we approach problem-solving, creativity, and innovation. In the co-creation model, machines are not just tools to be used by humans but are active participants in the creative process. One of the most significant benefits of co-creation with AI is drawing on the strengths of both humans and machines. Humans bring creativity, intuition, and contextual understanding to the table, while machines bring large-scale data analysis. By combining these strengths, co-creation can lead to breakthrough solutions.
