#95 Mastering UX Patterns for AI Products: Essential Design Strategies – Part 1
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Hello friends and welcome back to the Future of UX podcast. We will dive into the evolving world of technology and design. My name is Patricia Reiners, I'm your host and today we are embarking on an exciting journey into the rearm of AI and its impact on user experience design.

Artificial intelligence is everywhere. It's integrated in our daily lives and virtual assistants like Siri and Alexa to recommendation systems to Netflix and Spotify. But how do we as designers ensure that these AI-driven interfaces are intuitive and user-friendly? That's where UX patterns come into play.

And in this two-part series, we will explore what kind of UX patterns for AI products are out there. We'll talk about the significance in AI products and have a very deep dive into specific patterns that are shaping the future of AI design. We will draw insights from different resources that I'm also going to link in the show notes, so make sure to check them all out.

We will go through different areas in this podcast. First of all, we will start with understanding UX patterns in AI and you will talk about some key UX patterns in AI and then we will dive into designing for the future of AI and some ethical and practical considerations.

I already mentioned this is a two-part series. So we will get started with part one now and next week you will be able to listen to the second part. So let's get started with the basics. UX patterns are essentially tried and true solutions to common usability challenges. They serve as templates that designers can apply to create intuitive and efficient user experiences.

I would say like one of the most known UX patterns are the 10 heuristics of user interface design, also kind of like UX patterns from the Niels Norman group. I'm also going to link them in the show notes so you can check them out. And in the context of AI, these patterns become

even more crucial because a lot of things are new, a lot of companies are trying out different things. So there are already different AI/UX patterns evolving. One thing that I definitely want to emphasize is that this is not the master solution. Everyone, also every company, every user experience solution is exploring different things right now. So those are not things that you should follow.

but maybe some inspiration of how other people solved different problems. AI systems especially can be very complex and sometimes also unpredictable. And by implementing consistent UX patterns or UX patterns for AI products,

This really helps users to navigate these systems with confidence and ease. So when you are maybe designing your first AI product or if you want to, then these AI UX patterns are super helpful to get started. Have some kind of like a little guideline. Of course, this is not the master solution, but a little bit of a guideline.

For instance, consider the autocomplete feature in search engines. It's a pattern that predicts what you're typing and offers suggestions in real time. This not only speeds up the search process but also enhances the user experience by reducing effort.

So we talked a little bit about what these patterns are, what our AI UX patterns are. Now let's talk about some key UX patterns in AI. We will dive into some very specific UX patterns that are particularly relevant in AI products. Let's have a look at a few examples. The first one, and you probably all have seen it, is the template pattern.

The template pattern provides users with already pre-structured formats that they can fill in or modify. This is especially useful in AI systems where users might be unsure of how to get started.

So a lot of AI products like JTPT, the typical large language models, starting with a prompt. But sometimes these prompts need to be so complex with different parameters, different information, that for the user it's really difficult to come up with all these different elements. So what

So the concept basically or the idea behind is to provide already some kind of like a template, almost like not a survey, more like a template you can fill out. For example, one template that I find pretty interesting is the GPT for the logo generator where you need to enter certain information. So you can use this GPT to create a logo with ChatGPT.

And to come up with a good logo you need a lot of information. Like what style, the colors, for what it is. So this GPT already provides a template that you need to fill out. For example, what is this logo for? What kind of slogan do you want? Do you need to have text involved? Do you want any visuals created? What is the style? Do you have any references? You basically enter all these background information.

in this template so you already know what to enter. And this really simplifies the user's task and enhances efficiency. This is a very common UX pattern for AI products. If these prompts that you enter are very, very complex, they need a lot of information. Okay, so now let's come to this episode's sponsor, Wix Studio. Web designers, let's talk about the C word, creative burnout.

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That's wixstudio.com. Now let's move to the second topic or the second UX pattern, which are the suggestion patterns. The suggestion patterns involves the AI offering recommendations based on user behavior or input data. Think about streaming services like Netflix, for example. Based on your viewing history, the AI already suggests movies or shows you might enjoy.

and this personalized experience keeps users engaged and satisfied.

Something that you've probably all have seen is, for example, if you enter an AI tool, there are any kind of prompts involved. You have these example prompts basically that you can enter just like OpenChatGPT, for example, or any large language model. And then you will see you have the input field and below or above there are certain prompts already. Right. So how to get started?

Ideally, these prompts are based on your past search history, on the past prompts that you inputted. Unfortunately, ChatGPT, for example, doesn't do it. And I think this would be an amazing pattern to already provide personalized recommendation prompts based on the user behavior and the input data. UX pattern number three is the incognito mode pattern.

The incognito mode pattern allows users to interact with AI systems without leaving data traces addressing privacy concerns. And this is super, super important for a lot of people because in most cases, AI or the data that the user enters while using the AI tool will be trained to, will be used to train the AI model.

and to make sure that if you want to work on something a little bit more like sensitive topic, you can switch to the incognito mode. This is what you or what also web browsers like Chrome offer an incognito mode when your browsing history isn't saved. And similarly, AI systems can provide modes where user interactions aren't recorded, giving users control of that data. It's also what you can do with ChatGPT.

And pattern number four is the KVIT pattern. The KVIT pattern focuses on transparency, informing users about the limitations and uncertainties of AI products. So when using AI-driven translation services, for example, you might see disclaimers like "this translation may not be accurate".

And such Kvids set realistic expectations and build trust. So the next time you open a large language model, you will see that at the bottom usually there's this little line of this large language model and then named "TradGBT", for example, this mistake. Always check the results. This is super important to also help users understand these tools are making mistakes. So,

As designers, our role is evolving alongside AI technologies. We are not just creating interfaces, but we are shaping how humans interact with intelligent systems. Consider the rise of voice assistants. Designing for voice, for example, requires understanding natural language processing and creating conversational flows that feel human-like. It's a shift from traditional visual design to crafting auditory experiences.

Another example is of course also the large language models but also AI in healthcare. Designing interfaces for AI-driven diagnostic tools involves ensuring that complex data is presented clearly and that users trust the AI's recommendation. And with the integration of AI into user experiences, all these ethical considerations become paramount.

Patterns like the incognito mode or COVID are essential in ensuring user privacy and transparency. And for us, it's super important to design AI systems that are not only functional, but also respect user autonomy and the data privacy. So this involved being transparent, right?

and being transparent about data usage and providing users with control over their information. And AI systems learn from user interactions. We must ensure that we don't perpetuate biases. And this requires continuous monitoring and updating our AI algorithms to promote fairness and inclusivity.

So as the AI continues, we weave ourselves into the fabric of our daily lives. Understanding and implementing effective UX AI patterns is essential. And this is still work in progress. Right? Also, these four patterns that I presented are still work in progress. This is a good guideline, a good tip for you to get started if you're currently working on AI products or AI tools.

So these patterns serve as the bridge between complex AI systems and human users, ensuring interactions are intuitive, efficient and also trustworthy. So what were the four AI patterns that we talked about? First of all, the template pattern. If the user needs to input something through a prompt that's very complex with a lot of information, sometimes it's helpful to provide a template that the user just needs to fill out.

We're seeing that for example with the GPT logo generator at ChatGPT or with tools like Jasper AI for example where they are basically crafting you a whole story or a whole copy text and you really need to enter a lot of information.

The second pattern we talked about are the suggestions pattern. Suggesting content, suggesting prompts based on past behavior and input data. Number three is the incognito mode patterns. This is a pattern that allows users to interact with the AI system without leaving traces. So this is addressing privacy concerns. And the cathete pattern that focuses on transparency,

It basically informs the user about the limitations and uncertainties of AI products. This is super important as well. So in our next episode, we will continue this exploration by discussing more UX patterns in AI and how you can apply them in your design projects.

Thank you so much for joining me today on the future of your ex. If you found this episode helpful, insightful, please subscribe and share it with your peers or give it a rating. Stay tuned for more discussions on the evolving landscape of user experience design. Until next time and keep designing the future. Hear you in the future, my friends.