In the age of AI, why do we need UX designers?
Taking stock of designers’ remaining value and new opportunities and challenges
Technology without human interaction is meaningless
Compared to humans, AI is not good at emotions and humanized experience. The system often makes decisions based on large amounts of data and algorithms, without truly understanding human needs. Therefore, the purpose of technology is to solve problems and meet the needs of human life, and make our lives more comfortable and convenient. Only in this way can technology truly bring improvement and progress to people’s lives. For example, ChatGPT itself is just a large language model that guesses possible word combinations through a similar game of “shiritori”. Therefore, the value of UX designers lies in creating humanized designs to ensure user experience, enabling better interaction between humans and AI systems, and enabling the integration of various fields of AI for synergistic effects. After all, as it stands, most AI systems cannot effectively collaborate without sharing data or parameters, especially when their model goals conflict with each other.
The soaring demand for trust design
With the prevalence of artificial intelligence (AI) technology, designing a system or product that can establish people’s trust in AI is crucial, just as ChatGPT is about to replace human-generated rumors. Therefore, UX designers play a critical role in building trust in AI. They not only need to ensure that the system or product design is easy to understand and use, but also to enable users to clearly understand how AI technology is being used and how it works in the product or system, and to avoid users feeling uneasy or distrustful. In addition, AI applications should conform to ethical and social values, and the use of the system should be controlled and responsible.
Given this, Explainable Artificial Intelligence (XAI) is a rising research field in recent years, aiming to develop methods and techniques that can understand and interpret the decision-making process of artificial intelligence. The rise of XAI is because traditional artificial intelligence algorithms are often black box models. These models can handle a large amount of data, but the internal decision-making process of the model is not explainable. After all, the operation of AI systems is usually very complex and difficult for ordinary users to understand. UX designers can create user interfaces that are easy to understand and designs that educate users on how to interact with AI systems to enhance user understanding and trust in the system.
The XAI framework proposed by IBM research team in 2020 indicates that the model can be explained more clearly to users, stakeholders, and even government regulators through the following dimensions:
Producing higher quality user research and design
The emergence of AI technology has led to the generation of a large amount of data and comprehensive tool upgrades. In addition to improving design efficiency, UX designers may also have breakthroughs in user research tools. Researchers can focus more on thinking about the essence of problems rather than conducting research, so we can consider AI as an invisible research partner. Especially for many startups, solo designers or researchers, they can conduct user research at minimal cost, which is actually an opportunity for teams that lack research resources and foundations in the past. For example, cross-border research usually requires a large amount of funding and manpower investment, but through ChatGPT, we can initially understand the religious taboos and cultural habits that may be encountered when designing localized products or services in different markets worldwide. UX is a rapidly growing industry in the past decade, and many companies have gradually recognized its importance, actively incorporating user experience into their business processes. However, the actual methods used have not been updated: including user interviews, journey maps, personas, affinity diagrams, usability testing, diary studies, etc. These methods have become conventions, and most of them follow existing processes and methods, thus limiting creativity and creating blind spots for observations. However, the advancement of AI systems helps UX designers to understand user needs more comprehensively, objectively, and accurately, optimizing products and services and providing better user experiences. And these quantified data often need further interpretation and ensure authenticity, and integrating qualitative research results into product design is precisely where the value of UX designers lies and is something that AI systems cannot replace in the short term.
