The Role of UX Design in the Age of Artificial Intelligence
In the world of UX design, designers have developed over time a set of paradigms to shape digital interfaces. However, with the emergence of technologies like artificial intelligence, designers are now questioning which conceptions will remain and which ones will become obsolete. It is clear that artificial intelligence is here to stay, and it is our job as designers to adapt to the challenges and advantages this new technology brings to our design processes.
Adapting UX to New User Behaviors
UX design focuses on understanding user pain points and creating solutions for them. The ultimate goal of user experience is to provide users a comfortable and seamless experience when interacting with a product. In this new era of AI, we face the challenge of designing for technology that relies on users telling the computer system what they want, rather than instructing it on what to do. Unlike previous technologies, AI-powered tools only require users to focus on the output they receive, without focusing all the attention on the background processes. For example, users used to carefully format slides, choose fonts and colors, and search for relevant images when using presentation tools like PowerPoint. They had control over the execution process by telling the machine what to do. With a simple instruction, users can now get instant results for image and content creation, as well as ideas for presentation layouts. This shift demonstrates that users are giving more control and trust to AI-powered systems. Nevertheless this control can be humanly empowered by settings and parameters . As designers, we must consider specific perspectives when designing for these systems across various topics.
User education:
It is clear that users have different needs and challenges depending on the user persona group that they belong to, but with a new category of technology, such as generative AI, nearly every user needs some level of training on how to use these new tools. One big part of providing a good UX to users in all digital products is to develop relevant tutorials and other materials for onboarding. Users of AI-powered products particularly need to understand how to interact with them, and addressing this requires UX designers to consider user maturity. The process of generative AI can be complex, especially for those who are not familiar with concepts related to artificial intelligence. As designers, it is our responsibility to create user journeys that are seamless and user-friendly, allowing users to achieve their objectives in a straightforward manner.
Task automation:
As the use of generative AI becomes more widespread in different industries, the basic idea of UX is still there: the development of digital products should help users to fulfill their needs. In the case of generative AI, the main goal is to make things easier for users, help them get their work done faster. At Lengoo, we set up an internal task force in early 2023 to validate our assumptions about the use of generative AI in different industries and positions. What we found is that people often struggle with generative tasks like creating content, keeping consistency among assets, and centralizing all their information in one place. All of our findings are grouped under the "task automation" umbrella. By automating tasks, users can increase their productivity, leaving more room for them to innovate and generate fresh ideas.
Trust:
Today’s users are leaving AI systems more in charge than ever before. This change in how people behave when using these tools highlights the need for clear and open communication in the interfaces. While it's true that product designers can't hand over complete control of every little thing to users, giving them a peek into how the system comes up with its output can be very helpful.
So, by being transparent about the inner workings, Lengoo’s UX designers allow users to have a better grasp of what's happening. It's like a behind-the-scenes look that not only shows how things are generated but also builds the user’s trust of the underlying AI. When users have a handle on how accurate the results are and why they're coming out the way they are, it makes the whole interaction more solid. Users feel more sure of themselves, and the relationship between the user and the tech becomes smoother. This transparency thing isn't just a buzzword; it actually makes using AI a better experience, in which everyone's on the same page.
Ethical thinking:
In these kinds of tools, the generation of content is performed by large language models that run in the background. They will output based on the data that they were trained on, which can lead to biased output or privacy problems. This is a topic that cannot be solved exclusively through UX, since this needs to be addressed from the moment of setting the parameters for training, in coordination with the machine learning team. Nevertheless, we can deal with these edge cases from a designer perspective and consider them in the creative process. Some examples of addressing them are adding disclaimers about the output provided by the tool or designing alert messages to be displayed when the particular criteria are met that indicate that the output could be biased, offensive, or objectionable in some other way.
At Lengoo, we believe that artificial intelligence is here to improve processes while enhancing human well-being from all perspectives. For this reason, we also created an AI ethics board to set up guidelines and create discussions around ensuring that our AI does no harm.
Data privacy:
Acknowledging the significance of trust in user interactions with generative AI tools, it becomes crucial to recognize the important role that data privacy plays in shaping the overall user experience. Fundamentally, data privacy stands as an inherent right of every individual, in all aspects of life. This becomes particularly relevant in the context of AI systems, which rely entirely on data that is fed into and processed by large language models.
In essence, users should possess a clear understanding of how their data is handled within these generative AI tools, giving them the information required to determine when and whether to use such technologies. The safe use and storage of data is crucial for delivering a positive user experience. The assurance of transparent practices in handling user data not only fosters trust but also empowers users to make informed decisions about using these tools.
Humans in the loop and customization:
Even though generative AI is a handy tool for automating tasks, it's essential to remember that it still needs the human touch. When we tell the system what to do, the results can sometimes be a bit off or even completely wrong. That's where feedback and customization come into play.
For feedback, a good user experience means letting users share their thoughts on the results, such as "thumbs up" or "thumbs down" buttons that help the system learn and do better next time.
Additional training of the language language models can be done when sufficient amounts of new high-quality material have been collected, as through user feedback or the human correction of generative AI output. The changes users make can be used to teach the system, allowing it to produce even better results in the future. It's like a virtuous cycle that leads to a smoother and more satisfying user experience.
In a world buzzing with artificial intelligence, the way we design digital experiences is changing. Designers are tweaking their approaches, wondering what old tricks will still work and what needs a fresh perspective. Artificial intelligence is not just a passing trend; it's here to stay. As designers, our job is to roll with the changes, juggling the challenges and perks this new tech brings to the design table.
Imagine telling your computer what you want, and poof, it gets things done. That's the shift happening in how we interact with technology. No more focusing over tiny details; instead, users focus on what they will get. We're seeing this especially in areas like content creation and knowledge discovery, where AI is lending a helping hand. But the potential of these tools is much broader and will be used in a vast range of industries and professions.
With that said, we're not handing over the reins completely. Users still have a say, giving feedback and tweaking outputs to fit their needs. It's like a never ending conversation between humans and tech, making sure things get better each time. And in this flow, trust and transparency are the key moves, ensuring everyone's on the same page. Whether it's about learning the basics of AI or keeping data safe, the goal is to make this AI journey a smooth and satisfying ride for everyone involved.
