IXDC2023 Summit R2 — The Revelation and Practice of AIGC Design Productivity Year
The content was assisted by AIGC in the form of a confession.
In 2023, AGI and AIGC were a beam of light, not too bright but in the pitch dark of night, offering hope.
Two months ago, I received a TOPIC collection from my team, so I used a Large Language Model to create today’s theme, “The Revelation and Practice of AIGC’s Design Productivity Year One.” I’ve thought about how to start today’s sharing session to make myself feel relaxed. Let’s start with a video. I quite like this video; it was completed this week by several open-source Text To Video solutions, with the overall synthesis process taking about 30 minutes.
The Era of Virtual Transformation_IXDC2023（视频）
The core creativity of this video will be interpreted in detail at the end, where everyone will feel the reflection of its ideas. At this moment, I will join everyone, from an observer’s perspective, to scrutinize the content, focusing on the interpretation of the core of AIGC design.
Currently, we can affirm that as the singularity of AGI and AIGC approaches, most designers do not need a grand narrative; because the basic principles and methods obtained in related design fields have already constituted the foundation in the era of AGI and AIGC; thus clarifying designers’ productivity in the era of AIGC, returning to and focusing on imagination.
How big can the imagination of AIGC design be?
This is a recent favorite analogy of mine. We’re only a beautiful fungus away from breaking through the ceiling of imagination. Huge mushrooms, a giant cat, and little people dancing under the mushroom cap. But probably after this page, there won’t be beautiful pictures anymore :)
The need for unlimited imagination and creativity is the AIGC design we are facing now. Design based on “Prompts.”
This is a very popular definition of the value of Prompts by Sam Altman on Twitter, now called X, in February 2023. Being able to write outstanding Prompts and converse with chatbots is a high-leverage skill that can dazzle. So, in the following content, I will not expand too much on cases and images. I look forward to everyone experiencing through text, “Based on thinking and expressing through Prompts,” which is an extremely important capability for designers in this era.
We are facing the uncertainty of AIGC as a wicked problem, meaning there are no definite conditions or constraints in design problems. There’s no clear architectural definition, no stopping rules, no exhaustive execution lists, always multiple possible explanations, and the explanations depend entirely on the designer’s worldview and philosophy; every “wicked problem” is a sign or part of another “higher-level” problem; in practice, designers start with topics that should be called “quasi-themes.” So today’s productization and commercialization process of AGI and AIGC, I would consider there are four design topics worth discussing.
These two concepts have been focusing on the pattern of impact on designers since entering the field of AI design in 2017. In traditional design, users might not know how to interact with new technologies or features. If the affordance of the interface is not clear, users might feel confused and lost. Moreover, without AI Native design for AI feature integration, it could lead to difficulties for users to understand and utilize these features, reducing user experience. Affordance: Refers to the external characteristics of objects or interfaces, indicating how they can be used or interacted with. It was introduced by American psychologist James J. Gibson in the 1960s, mainly to describe the interaction between humans and their environment. In interface design, affordance refers to the appearance and interaction features of design elements that can suggest to users how they should be used. AI Native design is a design pattern aimed at seamlessly integrating AI technology into user interfaces and experiences. It means AI features and interactions are not just simply added to existing designs but interact with users in a natural, seamless, intuitive way, making AI feel like a part of the experience rather than an external add-on. This allows designers, creators, and users to fully leverage the potential of AIGC technology, making it a natural extension of design creativity and productivity, rather than just an add-on feature. It promotes the effective application of AIGC technology, thereby enhancing design productivity and creativity.
These two design patterns can lead users to understand and use new features more easily by reducing learning costs, increasing user engagement, and enhancing brand value. We are more focused on the application techniques on the right, how to clarify affordance, natural language interaction (not a new concept, including tactile/spatial interaction design twenty years ago, we used to think of voice interaction as a natural form of natural interaction), user engagement and feedback (different from past data-driven, with user’s unconscious operation as the model of feedback data, to encourage user participation in the improvement and co-creation of AI features), and building trust (how to build a trust process, smart enough to argue untrustworthiness).
Although AIGC can efficiently generate a large amount of content, the lack of emotional and storytelling elements in product design or content may lead to monotonous and uninteresting content, hard to capture users’ attention and interest. Storytelling is a traditional part of humanity, through which we have shared experiences, passed down knowledge, expressed emotions, and conveyed values since ancient times. It is a powerful and universal way of communicating and transmitting information. By skillfully applying storytelling techniques, designers can better convey the value and potential of AIGC technology in enhancing design productivity. By integrating AIGC application scenarios into stories, designers can attract audiences, evoke emotional resonance, and transform complex technological concepts into vivid, easily understandable stories, thereby enhancing people’s recognition and acceptance of AIGC in design.
In terms of results, we can pay more attention to applications. “Design, like science, is a tool for understanding and action.” One of the important functions of designers is to transform general concepts into tangible realities, give form to innovative concepts, and show what constitutes user value, so that more accurate testing can be conducted in the early stages of any development process. The strategy of narrative significance, with technology and market as cross dimensions. Digging-type narrative facing old markets and old technologies, user-centered narrative facing old technologies and new markets, technology-type narrative facing old markets and new technologies, and exploratory narrative facing new markets and new technologies. It is important to note that although AIGC can enhance storytelling techniques and effects, it is necessary to carefully handle user privacy and ethical issues during application. At the same time, it is important to avoid over-reliance on AIGC, maintaining the importance of human creativity and judgment, to ensure that storytelling remains humanized and deep.
People usually understand the meaning contained in objects according to their expectations. Whether it’s individual natural language, Prompts used for model interaction, or model output works, they cannot accurately and faultlessly convey to each other. (Mutual black boxes) The Prompt model refers to a type of model based on natural language prompts, which guides the model to generate specific outputs by using specific contexts or prompts. Generative design is a method of using machine learning technology to automatically generate designs, which can generate corresponding design results based on given input data. Confession is an expression of design works, and the Prompt used for interaction is a pursuit of exploration. The output and results are not for communication to the user, but for confession and questioning, making the model and generative creation tools meaningful in two ways, which is also the purpose of design.
The problems we encounter with Prompt-based models and generative design on the left side, current generative design technology, although very powerful, still faces issues of unstable generation quality, overfitting, etc. Continuous improvement and optimization are needed. When using generative design, designers need to be aware of copyright and intellectual property issues, ensuring the legality and usage rights of generated works. Generative design may not fully replace the creativity and judgment of human designers in design tasks with high professionalism and creative demands. Some design projects require deeper understanding and creativity, which models may struggle to achieve. Over-reliance on Prompt models and generative design may lead to a reduction in designers’ dependence on personal creativity, thereby lowering designers’ skill levels and creative capabilities. Control towards limitations requires recognizing their limitations and potential pain points, reasonably applying and combining human creativity and judgment to achieve the best design effect. On the right side of the application, generative design can help designers obtain more creativity and inspiration. By providing specific contexts or prompts, the model can generate diverse, unique design works, offering possibilities for creation. Efficiently auto-generating design results, saving designers time and effort. Quickly generating multiple design options (initial sketches and prototypes), rapidly exploring and iterating, thus quickly validating and adjusting design solutions. Generative design can be used for artistic creation, allowing artists to gain inspiration and creative stimulation through interaction with the model.
Technological advancement is not directly proportional to the improvement of human welfare. With the great increase in productivity, we are reappreciating things people can do that technology cannot. Technology is exciting and enjoyable, but it often increases people’s anxiety and loss of control. In the design process, we need to consider “happiness,” using design and technology to enhance human happiness, and develop human potential. Issues of bias and discrimination, AIGC algorithms may be influenced by training data, leading to bias and discrimination issues. If not controlled and corrected, the generated content may have an unfair impact on different groups; when using AIGC to generate content and design services, it is necessary to pay attention to ethical and privacy issues, especially when involving user emotions and psychological states, it is necessary to protect user privacy and personal data security; AIGC may lead to a reduction in real social and emotional exchanges, if people rely too much on technology to satisfy emotional needs, it may lead to increased social isolation and loneliness.
In general, combining positive computing and service design methods, the future of AIGC can achieve more humanized, emotional, and personalized content generation, improving user experience and engagement, and creating more valuable content services. In future development, positive computing and service design can be combined to achieve more positive, humanized service design. This combination can help enterprises improve user experience, increase user loyalty, and enhance service efficiency. For example, through positive computing technology, user emotions and behaviors can be analyzed, thereby providing more personalized services to users. At the same time, service design can commercialize this personalized service by integrating design and business models, thereby achieving enterprise profit goals. Positive computing and service design are important directions for the future development of digital services, their combined application can bring better user experience and service efficiency, and also provide new business opportunities and growth points for enterprises.
If human creativity provides endless possibilities for the generation of new ideas, it must be emphasized that ideas themselves are not innovation, although this misunderstanding is very common. Many designers try to make the design process more systematic, scientific, easier to predict, and more compatible with computers through various regulations, taxonomies, induction, etc. Among them, the procedural design system is one of the most typical practices, trying to place design within a respectable scientific background, giving design a reasonable theoretical framework. In their view, if design has a theoretical structure, it has a scientific style. These methods represent rationality, logic, and wisdom but overuse may also lead to simplification, making design vague and inevitably suffering from the malady of high-technology functionalism, sacrificing basic human needs, namely the pursuit of so-called clarity of form. Only when an idea is embodied in design, appearing in a form that is related to user life, easy to understand, useful, accessible, affordable, or pleasurable, does the idea truly represent innovation, creating new value. THESE VIOLENT DELIGHTS HAVE VIOLENT ENDS.
Everyone should appreciate their patience, in this era, to think and meditate quietly. Finally, the content of the video is explained, from Jean Baudrillard, a French philosopher and sociologist, whose theory explores the characteristics of consumerism in modern society and culture, arguing that modern society has transcended material reality, becoming a virtual world, influencing people’s cognition and behavior. Baudrillard believes that in postmodern society, we live increasingly in a fake reality of simulation and imitation. In modern society, symbols and signs do not reflect reality but create a fictional world, gradually replacing reality itself. In Baudrillard’s view, the boundary between the virtual and real worlds in postmodern society is increasingly blurred, even disappearing. This makes it difficult for us to distinguish what is real and what is fictional.
The Era of Virtual Transformation_IXDC2023（视频）
