AI is quickly becoming mainstream in many industries, including graphic design. The technology is making the designers giddy with excitement because AI can make the designing process so much faster and easier but — it’s also scary at the same time because we’ve seen what AI systems are capable of.
One of the earliest examples of AI entering the graphic design industry is The Grid, a website which creates modern-looking websites for customers in minutes. Users just need to upload the content and using AI, the Grid will begin setting up the website. The website was launched in 2015. A lot of AI-powered tools for creating websites and generating logos have been introduced ever since, including Tailor Brands, Turbologo, Squarespace, Wix, etc.
Engineering was a job carried out with pencils and paper not all that long ago. Calculations were made by hand and designs on large sheets were sketched out. Physical models will be created from actual blueprints to figure out how the final product should look and be made.
Of course, engineering today is a discipline that is deeply concerned with software and machine tools. Some of the basic techniques that engineers deploy when designing new product designs are computer-assisted design, computational fluid dynamics, and finite-element analysis applications. Prototypes may be printed directly from machine files when physical models need to be checked.
Although these instruments have strengthened the capabilities of engineers, the engineer is still clearly in charge of the design process. That power, however, is now in doubt. Growing interest is being expressed in using emerging artificial intelligence and other innovations to achieve higher levels of product automation and drive new product innovation. Advances in AI, coupled synergistically with other innovations such as cognitive computing, the Internet of Things, 3-D (or even 4-D) printing, advanced robotics, virtual and mixed reality, and interfaces with human machines, are changing what, where and how goods are built, created, manufactured, delivered, serviced, and updated.
Role of AI in Design
This revolution will allow for a new kind of design process, one where, with little human interference, AI-enabled programs iterate and optimize. The resulting designs seem extremely complex, but are no more difficult to print than traditional designs, thanks to advanced printing technology. In commercial aircraft and other vital structures, parts that are the result of this generative design process are already being prepared for use.
The shift from drafting boards to CAD to engineering was disruptive. It is expected that the next transition to generative design will be more disruptive.
Artificial intelligence is a notion that includes a wide variety of technology, and for some time, some kinds of AI have been applied to engineering systems. In the 1980s, many of the mundane activities for engineers were first used to automate knowledge-based systems and AI rule-based expert systems. In the 1990s, the intelligent agent model was introduced and a shared language was given to identify issues and share their solutions. These apps are considered to be “weak” AI.
“Strong” AI, on the other hand, will function more like general intelligence and be able to sense, interpret, learn from and react to the environment and users. Strong AI, also referred to as Artificial General Intelligence (AGI), refers to deep learning and machine intelligence, systems that demonstrate complex behavior similar to living systems such as swarms, colonies of ants, and neural systems. The ability to adjust to most circumstances will be provided to these systems.
In leaps and bounds, artificial intelligence is moving forward (indeed some researchers are now talking about the development of artificial superintelligence-ASI) and much of the AI enthusiasm is targeted at applications where computer systems work with great autonomy. The self-driving car is the poster child for AI, however there are a range of interesting applications, from robotic doctors that can more reliably diagnose diseases than any human doctor to AI-directed businesses that can orchestrate business operations without flesh and blood management.
Existing artificial intelligence has already impacted the product-design process, and AI will change the way we embed connected sensors and use mixed or augmented reality headsets in the future. Based on the current trend, in the next decade, we are likely to see AI influence product design and the development of engineering systems in three distinct phases.
Second, the laborious tasks faced by designers, such as having to continuously search for suitable content, correct mistakes, find optimal solutions, communicate changes, and check for design failure, will be eased by artificially intelligent systems. It would be possible for machine learning to take on certain jobs and do them much quicker.
Next, in generating sophisticated designs, AI would be able to help. At the designer’s elbow, intelligent systems will work, propose alternatives, incorporate sensor-based data, produce design precursors, optimize supply chain processes, and then deliver the designs to smart manufacturing facilities.
Design for Immersion not Interaction
AI is about living systems that are ultimately going to be smart enough to know when, where, and how to engage us. Designing for immersion means that experiences should feel natural. People should be empowered by AI and automation. People should be less hindered, and their interactions should feel frictionless.
To get to this level of immersion, technology on the back end needs to be able to learn from people to become a system that ultimately intuits what people need. And on the front end, designers need to create similarly frictionless interaction. Allow people to speak rather than grab a mouse. Consider immersive experiences that can anticipate and engage in ways that require less effort.
At the same time, when you engage the senses, you want the system to feel “living” and ”real,” not clinical and machine-like. Think about the “EQ” or emotional intelligence of the system, and the human emotions it will impact and interact with. For instance, voice technologies may have a hard time intuiting emotion that could be gleaned from facial expressions. It is incredibly nuanced to understand what people are thinking and how they are feeling. Many tech leaders understand the concept of multi-modal interaction — the same applies here. Make the system come to the people. Don’t make people have to come to the system.
Acting on Intention
During the design and development process, engineering systems that integrate stronger AI would be able to act more like human assistants. True human designers will only be able to design” by communicating intent and curating outcomes, while in order to produce new design iterations for analysis, intelligent systems and machines will act on these intentions.
However, the AI wouldn’t approach the project the way a human designer might. Instead, the computational power will be used to replicate the evolutionary method of Nature, taking the best current solution to a problem and iterating in each setting to maximize efficiency. In this way, beyond what is actually possible using the conventional design process, the AI will explore the variants of a design. This approach is called Generative architecture.
The engineer or industrial designer, along with design criteria and constraints, including material type, manufacturing capacity, and price points, sets high-level design objectives.
The AI generative design framework, such as Autodesk’s Dreamcatcher, explores the permutation of a design solution with the limits of the design problem identified, cycling rapidly through thousands or even millions of design choices and running performance analyses for each design. The device will tap available cloud computing processing resources for the most intensive calculations.
Its machine-learning algorithm is a core component of a generative design method. Without human guidance or interference, the algorithm detects patterns inherent in millions of 3-D models and generates taxonomies. Generative design software may use that skill to learn what all the components of a complex system are, define how they relate to each other and decide what they do. For a particular dimension of a piece, it can then serve up hundreds of different design options and provide them as parts for the next design.
Application in AI in Design Technologies
The use of tools like Tobii Pro Sprint, web-based eye-tracking technology, is used in developing websites. It allows UX designers to record website users’ eye movements, thereby assisting in improving website design.
The Grid is the first company to offer website design within minutes. The websites are custom AI-designed. After Grid, many other companies emerged with the same AI-designed websites. They include Wix and Squarespace.
With AI technology, one only needs to upload the data content; and they can build the website from scratch within minutes.
Turbologo uses the same technology to design logos. One only needs to upload the brand name, colors, and other preferences, and the logo is generated within minutes.
Automation of Manual Design Works
Technology can easily automate most of the designers’ tasks. Activities like cropping images and correcting colors can be automated easily using AI.
Adobe Sensei is a design tool that uses intelligent features to improve the final product’s overall design. It assists designers in performing work more efficiently and faster. Adobe Sensei Stitch is used to identify patterns in images, edit, or even create new scenes.
Another example is Netflix, which uses an augmented intelligence system for artwork personalization. When the need arises to create multiple banners, designers only need to look at the robot’s banners to accept or reject them.
Design Scape is a system that helps in the design process by aiding with suggestions such as changes in position, scale, and elements.
It assists website designers with suggestions to create near-perfect websites. It doesn’t design the website on its own but improves designers’ efficiency. Using Design Scape reduces maintenance efforts and time taken to complete tasks.
Font Joy uses machine learning to generate font combinations. It assists designers in choosing the best font combination. A person can set different fonts and generate font combinations with a click of a button. The page will then load and generate a new font combination.
Benefits of using AI in Design Technology
1.AI can assist designers in creating designs more quickly. It can also suggest alternatives and report how they can improve the design.
2.It helps designers customize and personalize designs more effectively. Different brands can be designed using AI and be distributed to thousands of users based on their preferences and experiences. AI generates millions of unique versions, new sites, and media found on the user profile.
3.It is useful in facial recognition and computer vision. It helps designers have a wide range of characteristics of users like gender, age, location, context, and mood.
4.It is possible to couple AI with voice recognition. This helps UX designers create more convenient and personalized experiences.
5.AI is used when performing data analysis, thereby helping designers have a wide range of information on user metrics.
Will AI Replace Engineers
The answer is NO. The position of the human engineer will in time, be that of a director rather than a producer. Humans may not be the ones carrying out the tasks, but we will select the path we want the system to follow and provide the most important feedback: if we are pleased with the performance.
Most of the technical aspect of engineering will be shifted to the machine-based design method, just as a good engineer today does not need to be able to operate a slide rule or complete an isometric drawing. To some degree, in a working partnership with an artificial intelligence that can find the solution as long as it knows what the problem is the programmer will become someone adept at interpreting the inchoate human desires for goods with a more elegant shape or using less resources or operating more efficiently. Engineering will be altered until computers know how to build, even how to design themselves, but engineers will still be highly trained. AI technologies can augment them cognitively, mentally, and perceptually. And thus, with a different set of skills, they will simply have to develop their abilities, including teaching the AI systems how to innovate and become successful collaborators in potential human-AI organizations.
AI is essential as far as the engineering field is concerned. There has been a concern arising after all the automation, whether AI is replacing engineers. The answer is no, but AI will assist many engineers with a majority of the technical work. AI in systems design is of great importance and will be part of a revolution in the future.
By: Abbas Umrethwala, Adnan Inamdar, Atharva Dasgude, Atharva Gangad, Karen Baldota.