Artificial intelligence technologies transform various domains, and UI/UX design is no exception. Anyone with access to the internet and basic knowledge of English can craft visualizations, mockups, videos, texts, and code regardless of technical proficiency or expertise in design.
The blossoming artificial intelligence technology brings both comfort and threat to the design industry. The dilemma is that AI systems can help you or replace you anytime. As a design agency, Arounda is highly motivated to dig deep into the problem and answer the question, “How does AI affect art design and culture?” In this article, we investigate the opportunities and challenges of AI in UI/UX.
AI is a simulation of human thinking by machines. AI imitates three cognitive skills: learning, reasoning, and self-correction.
When we apply AI algorithms to UI/UX tasks, computers can:
gather, analyze, and arrange data
search for user-centric solutions
produce numerous design modifications
generate wireframes and code from sketches
create text, images, video, and other content
AI implementation into design leads to various opportunities and challenges. The question is, how will AI affect graphic design in detail?
UX designers who stay up-to-date and use AI tools to do the job more effectively have better chances of winning the competition in the rapidly-evolving field of digital design. So let’s first examine the practical perspective of AI in UX.
Personalized labels, banners, and product descriptions are becoming a must in marketing. The task is not difficult but time-consuming. So why not write a program and free designer’s hours for more challenging artwork?
In 2017 Nutella used an algorithm to generate seven million different jar labels for Italian consumers. The brand manifested that every Italian citizen deserves a unique package design. People liked the experiment and the personalized approach, and all seven million jars were sold in a month.
Netflix is also using augmented intelligence to translate banners into multiple languages. Designers only have to approve, reject, or adjust the workpiece. In both cases, AI is a massive time-saver.
AI performs repetitive, detail-oriented tasks much faster and with fewer errors than humans, so we can delegate routines to AI tools. For example, VanceAI turns blurry images into sharp ones. The well-known Removebg tool analyzes an image and allows you to change the background to transparent, white, or customized in no time.
One of our favorite instruments helps check whether our drafts look good in the end product. Uizard assistant automatically transforms sketches into designs for web apps, websites, and software interfaces. The economy of time and effort is the most obvious way AI affects design.
Do you often check the UI to make sure that elements appear in the right color, shape, and size and don’t overlap? We test the front end continuously. Meanwhile, spidering algorithms that are written with the help of machine learning can test your website or app as many times as needed. Spiders crawl your application, take screenshots, download the HTML codes of every page, measure load times, and so forth.
Another group of instruments is the generative AI algorithms, which compile new content from existing data. GPT-4 chat developed by OpenAI is currently in the spotlight. This AI assistant can produce text, prose, and code that is unique, makes sense, and looks human.
Similarly, the DALL-E system can create original images from visual and text prompts, Notion AI works with text, images, and data, and Designs.ai produces logos, videos, banners, and mockups from separate elements.
In the previous section, we pointed out a positive side of AI integration into design. But let’s keep in mind that this technology brings various challenges that we must carefully manage.
AI collects vast amounts of data, including personal user information, to learn. The most powerful algorithms work in healthcare and financial industries and have access to highly sensitive records. Is it possible to eliminate the risk that this data will be misused or stolen?
It is important to inform people how their data can be used. Otherwise, users will feel uncomfortable and unsafe sharing their personal information. This can impede the progress of AI. We already have regulations and laws of Web 3.0, so there is a starting point for this challenge.
AI learns from various sources of information like books, websites, and blogs. If AI consumes biased data based on prejudice or intended discrimination, the automated outcomes will have the imprint of unfair treatment and result in abusive user experiences.
Another challenge is the modification of intellectual property definitions and regulations. If a designer uses an AI assistant to produce visuals for the corporate website, should they sign a contract and credit AI as a co-creator?
Achieving the right balance between automation and user control is difficult. Designers like it when AI crafts dozens of drafts all by itself. On the other hand, they may become frustrated if AI takes over too much control and leaves no place for fine-tuning the output artwork.
AI is becoming more accessible both for individuals and companies. It means everybody can build a front end on top of ready-made AI models like GPT-4. But if solutions are based on the same data from free sources, AI outputs will look similar and fail as a long-lasting advantage. So the real competition will move to training the AI models with exclusive data and tuning them for highly specific tasks.
AI algorithms analyze data, generate original content, propose user-friendly solutions, and complete other cognitive tasks that were the human designers’ prerogative a few years ago. So should we fear the possibility of being replaced by AI tools?
First of all, regarding the most complex parts of the designer's profession, like ideation and building concepts, AI assistants can provide numerous related drafts and data for inspiration. But you still need a human curator who will approve, reject or slightly modify the artwork.
Secondly, AI content is not 100% free of plagiarism and errors. Therefore companies need a responsible human employer to guarantee the accuracy and compliance of the final product.
Another AI weakness is that solutions aren’t unique because AI systems are trained on open-source content.
So, how will AI affect UX design? The scenario when designers lose their jobs looks unlikely. The truth is that they will have to adapt to changes and become more skillful to remain competitive and effective.
AI penetration into UX design opens various opportunities and challenges for designers. Opportunities include personalization, routine and test automation, and content generation. The most distinctive challenges are privacy and security issues, bias concerns, ethical contradictions, sustainability, and MaaS arrival.
Arounda team has been in a rapidly-evolving design field for more than five years. We can recall the boom of Web builders, the rise of Canva and Figma SaaS tools, and fears that new technology will replace human professionals. Concerns and excitement about AI are nothing new. There is no doubt that new technology will move us towards acquiring new skills and improving our UI/UX designs for websites, mobile apps, SaaS, and blockchain.
So if you need human assistance in product design, branding, or business strategy, we are here for you!
AI solutions in UX design still look average and require the curation of a human professional. Therefore, we don’t think that AI tools will replace human designers.
It is crucial to stay up-to-date, follow the latest trends, and investigate new opportunities that AI algorithms offer to UI/UX experts.
Open AI tools will only stay a competitive advantage for a short time. The true race will imply training AI models on exclusive data and offering MaaS products for specific tasks.
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