How can you use AI to boost your creativity and problem-solving?

I've used both ChatGPT and Bard as valuable tools for diverse design requirements. I utilized them to conduct broad research on potential competitors for one of the companies I work with. Additionally, I employed these tools to distill findings from user interviews into the values and interests of a design persona. They have proven invaluable as aids in crafting compelling Call To Actions and generating alternatives for AB testing, including Titles, Subtitles, and Body copies.

Using AI today as a designer is adding another set of tools to the arsenal of tools that are currently used by designers. The merit of AI is its speed and repetitive abilities in helping designers iterate ideas at a rapid pace. It is by no means a tool that designers should come to rely on completely and trust for fidelity of rendering, accuracy of text generation, or consistency of output. Having said that with all those considerations in mind, it offers so many possibilities and uses worth exploring.

Generative AI can be used for much more than simply automating repetitive tasks. Problem solving is about building a model of the world based on a priori frameworks and data from the problem, and identifying within this model a set of solutions. LLMs are incredibly good at selecting appropriate frameworks for a problem, either from their default training or from a provided list through RAG, and at applying them to a given dataset. Try to give ChatGTP a problem like "How might we identify new ways to expand our market share for steel bars in Japan". Ask it to pick a framework to analyze the problem: it will probably do a good job at picking something like the growth/share matrix. Then give it a dataset and ask it to provide the analysis.

For designers, AI is best as a co-designer. During research, it helps with data processing, recognizing patterns, organizing user feedback, tracking user behavior, insight generation, marketing research, competitive analysis, interview scripts, and personas. During ideation, it helps you find inspiration through image or text generation models. For prototyping, it helps by generating mockups, design automations, producing color palettes, generating UI, creating high fidelity prototypes, and even iconography. It not only helps speed up the process, but it enhances my abilities and helps me reach a final product that is complete and more refined.

Using AI in design these days is like getting an extra set of tools. It's great for speeding up repetitive tasks and helping you brainstorm ideas quickly. However, it’s not something to fully rely on for perfect details, spot-on text, or consistent output. Even so, AI brings a lot of exciting possibilities that are definitely worth checking out.

I have found that using AI tools like ChatGPT, Adobe Firefly, and Leonardo.AI requires not only a problem to solve but also an idea of how the solution will look visually. AI can be a better painter or artist than I am, but it can't know what I want and how it looks in my head. I have to, like a paintbrush or pencil, tease the visual solution out of the tool.

AI tools can be a great source of inspiration, but I remind myself to never forget to use my critical thinking after each answers generated by an AI.

In my creative endeavors, I've combined ChatGPT and Midjourney, two AI giants, for a unique exploration of ideation. By training ChatGPT to craft Midjourney prompts, I've merged abstract thought with tangible visual output. For today's professionals, here's why this matters: Ideation Boost: ChatGPT offers a burst of innovative ideas. Visual Transition: Midjourney brings those concepts to life visually. Infinite Combinations: Together, they craft diverse creative vistas. This approach highlights the expansive canvas AI offers, blending tech with a renewed sense of creativity. Embrace this AI-fueled creative wave and let artificial intelligence amplify your vision.

I tried ChatGPT, Midjourney, copilot, and various figma plugins to explore if AI can replace a designer or not? I found AI is really very helpful in all design stages specially in ideation and brainstorming. It has ability to analyze vast amount of data and identify patterns and trends which might inspire innovative ideas. AI can work as collaborator to do brainstorming, can give real time feedback and evaluate the ideas based on available data. AI can give mind maps, visual representation. AI can use predictive analysis to forecast potential success of an idea based on historical data and current market trends. It can help in eliminating human biased idea evaluation. The result of check-in different tools was AI can't replace a designer

Every time I use AI for ideation and brainstorming it opens up a whole new world of inspiration and expands my creativity, I find it very useful and fun to be able to complement my creative process with these tools.

To have a effective research, we need to be concerned about the source and reliability of data. Therefore, asking the AI directly what you need to understand may not be the best approach. Focusing in a safe use of GenAI, some of the possibilities are: Synthesizing articles, websites, documents: Try choosing sources and asking the AI to find what you need, so you know the research references. Documenting interviews and ideation processes: Always try to record or have a transcription of conversations, so you can unfold the content as needed, whether it's raising insights, finding pain points, or even creating personas.

AI is in some cases a research and analysis enhancer. It scours various sources, collects relevant info, and breaks down complex data (so much faster than a researcher could do). It can become a super-smart assistant that not only finds what you need but also summarizes and compares information from different angles. There are of course risks, AI is still in development, usually the findings are broad and generic, if not prompted in the right way and refined multiple times. It can broaden your understanding, simplify findings, and back your decisions with solid data. At the moment it still needs human control, in the form of fact-checks, analysis of the sources and of the synthesis that it can make/create.

AI can streamline research by quickly gathering and organizing data, spotting patterns, and analyzing large amounts of text. It can predict trends, create visualizations, and even summarize key insights in reports. With AI, you can discover new content, analyze sentiment, and continuously refine your research, making the whole process faster and more effective.

It is crucial to always use critical thinking and whatever output from an AI tool as food for brainstorming with your team. The magic happens in collaboration. I use different AI tools for research and analysis; to explore the problem space of a design challenge, for data processing and to define a problem statement

In the process of problem-centered research with AI, I identified skills to develop and tools to use that will help me obtain more assertive results. At ChatGPT, my initial challenge was to be specific to create more assertive prompts. It is an exercise in trial and error that requires detachment and focus on what is relevant. Critical thinking comes in as metacognition for me to organize my own path of reasoning. I made progress after using the Board Innovation AI ToolBox because I exercised objectivity. If you don't have the clarity to narrow down the scope, I suggest trying the Board Innovation AI ToolBox before going to ChatGPT. The layout helps you to organize the ideas. Also, to filter options to explore them assertively.

I have used AI once to try and create wireframes for a component (magicpatterns.com). I tested it on a simple article card component. Based on my text prompts, the tool generated 4 different options for me to pick from. I was then able to refine my prompts until I was satisfied. I found it a fun process to go through, but it took a long time to reach a desired outcome. Moreover, the technology and the design system used were already selected (with little options to choose from). A UX/UI designer can definitely achieve the same outcome in much less time. It would be interesting to see how far can AI be pushed, maybe with more complex components, or even nested ones.

I use AI to quickly create user flows that I can adapt and iterate more rapidly. From these user flows and other documents, I can create interactive prototypes with Axure RP. Recently, I have started testing the AI "text to design" beta function of the Visily tool. Unfortunately, this feature still needs significant improvements before it can quickly create wireframes or high-fidelity interfaces that don't look generic. Another drawback is the current 500-character limit for prompts, requiring them to be concise yet detailed enough to generate the expected results. For testing, I use AI to help create usability test protocols, compile feedback questions for users, and analyze test results.

AI can make prototyping and testing smoother by whipping up design ideas fast and checking for problems automatically. It can look at user feedback to see what needs fixing, predict how your design might do, and suggest improvements. Plus, it can test your prototype in different scenarios to find any issues before you roll it out. It’s all about speeding things up and making sure everything works right.

AI can play a crucial role in collaboration and communication. Firstly, it can be used as a connector, linking you with potential collaborators based on skills and interests. This expands your professional network and creates opportunities for collaboration. Secondly, AI is very helpful at overcoming communication barriers. It effortlessly translates languages and adapts to different formats and channels, ensuring effective communication regardless of linguistic or stylistic differences. In summary, AI can enhance collaboration and communication by simplify connections, breaking down language barriers, and infusing emotional intelligence into interactions.

AI can make working together and communicating a lot easier. It can instantly translate messages so people from different countries can understand each other, help schedule meetings by finding the best times for everyone, and summarize what happened in meetings so you don’t miss anything. AI can also manage tasks, handle simple questions with chatbots, and suggest useful documents or ideas. Plus, it can analyze feedback to spot common issues and improve how you work together.

Highlighting the importance of an interdisciplinary approach in AI content creation and visuals is key, especially when we blend sociological, cultural, and ethical perspectives with technological insights. This comprehensive approach offers a broader lens to identify and address inherent biases within the system, ensuring that advancements are in harmony with the intricacies of human society, values, and culture. Recognizing how specific genders, races, sexual orientations, age groups, socioeconomic statuses, disabilities, religious beliefs, and geographical regions are portrayed is foundational. From this understanding, we can work towards creating content that is holistic and resonates profoundly across diverse audiences.