2018 Design and Artificial Intelligence Report: Optimism and Criticism

Members of the "Design Artificial Intelligence Network" of the 2018 Design Artificial Intelligence Report volunteered.

"Designing Artificial Intelligence Network" is a globally oriented open network dedicated to bringing together ideas and thoughts on design intelligence and machine intelligence to stimulate widespread discussion. The network has gathered scholars and opinion leaders from well-known universities at home and abroad, such as MIT, Stanford, Cornell, New York University, Carnegie Mellon, Milan Polytechnic, Central Academy of Fine Arts, and sounds from different fields and backgrounds. Intensive discussion in the context of artificial intelligence has inspired a diverse perspective.

Complex System with Diversified Values

The arrival of technological singularity and the optimism of index development simplifies the complexity of solving the problem itself. In the process of solving a problem, it will also bring new problems.

The understanding of design and artificial intelligence should evolve from “things” to “things”, from the generation of big data research and design to the process of unstructured data research and design.

Unstructured Data

There are significant differences between the design of computational intelligence and the classic design, including: number of users, implementation cycle, result orientation, production data, result presentation, ROI/KPI, etc. Companies such as Alibaba have been redefining the career path of designers.

The design of computational intelligence has transformed the design from a functional department that is difficult to quantify to a department that can directly be responsible for the KPI of the enterprise, and a large-scale personalization and other business strategies in the data intelligence scenario, which have increased the design requirements exponentially. Multiple scenes designed by people and machines.

Although designers have a long history of using digital tools, design has not yet become part of the data economy, and process data for design is a resource that has not been tapped.

89% of design related data is unstructured data. The mapping migration of design logic and business logic has deep potential, and design and artificial intelligence laboratories have made a lot of efforts and attempts in this regard.

Brain Machine Ratio 2.0

Brain-computers are more abstract than the synergy between people and machines in design work. The brain-computer ratio in 2018 increases the dimension of people's willingness to use machines. For example, looking for data, although the machine can do a high proportion, but designers still tend to spend a lot of time doing it themselves, because this process is not a simple mechanical process, but is constantly inspiring while looking for information.

Artificial intelligence has had an impact on design practices in areas such as graphics, smart products, UI/UX, and urban space. Smart products are new design types that arise because of artificial intelligence, while graphic design and urban space are artificial intelligence that will challenge the original design paradigm.

Designing Machine EQ

Relevant capabilities such as artificial intelligence and data analysis are the most demanding skills that companies need to design students in the short and long term.

The value and limitations of artificial intelligence allow us to rethink the intelligence of design. Many design schools in China, the United States, and Europe have added artificial intelligence-related courses and balanced object-oriented design and system-oriented design.

The intelligent design of the design involves the interface between the society and the individual, and artificial intelligence helps the society design to find a path to data acquisition and ethics.

Emotional intelligence distinguishes between people and machines, and how to design the emotional intelligence of a machine becomes the next challenge of design.