Artificial intelligence is perhaps the hottest trend of our time. It seems to be even more popular now than blockchain was at one time. Both technologies have huge potential to change the world for the better, but AI looks more attractive and exciting due to its accessibility to literally everyone.
No one expected computers to start doing creativity, everyone just thought the opposite. Creativity was considered to be the prerogative of man, his ability to create something new and original. Computers were perceived as machines that could only follow instructions and operate with logic. However, with the development of AI, everything has changed. Now computers can generate amazing works of art, music, literature and design.
Artificial intelligence is showing amazing results, but this is just the beginning of a long journey and a lot of designers, especially beginners, are anxious about it. This anxiety is certainly understandable, but at the moment it is not well founded. Designers are afraid that AI will take away their work, destroy their creativity and make them redundant. However, these fears are not yet supported by facts.
Sources of fears
One of the main fears of designers is that technology may take away their jobs or reduce the demand for their services. This fear is reinforced by the fact that computers are already capable of generating high quality graphics from given parameters or from examples of other work. Online services such as Canva, Khroma or Visme allow you to create logos, banners, posters and illustrations in minutes.
The value of visualization is dropping because now anyone can generate what they want. Designers are afraid of losing their relevance, they fear that businesses will stop needing their services. Yes, businesses strive to minimize costs, but there’s nothing new or surprising about that – it’s their basic nature. But designers should remember that their work is not limited to visualization, but includes analysis, strategy, communication with the client and the team, and other global aspects that neural networks cannot handle yet.
We have already gone through a similar process when machines replaced some professions in England during the Industrial Revolution (this is how Luddism emerged – a movement of English craftsmen in the early 19th century who destroyed the machines that replaced their labor). Some professions did disappear then, but centuries have passed and it is still impossible to completely abandon man in production. Technology does not destroy work, but transforms it. Now, despite the hype around AI, there is no noticeable process of designers’ dismissal. On the contrary, the demand for design is growing as it becomes an integral part of any product or service.
According to my observations, it is mainly those designers who are afraid of losing their jobs who are not familiar with modern AI tools and have not tried them themselves, which is a classic fear of the unknown. But there is nothing to fear here: a computer cannot replace human creativity, empathy and intuition anyway. It can only offer options, but the choice is always up to the designer.
As an example, Adobe FireFly is a plug-in for Photoshop, in which, based on text queries, you can change images and create new ones literally in a couple of seconds. Although the technology is available to literally everyone, the tool will be really useful only in the hands of a professional, allowing you to save him a lot of time on routine operations. But it takes experience and professional flair to know what kind of operations are needed.
Another fear is genericization, the lack of the new, the repetition of hackneyed patterns. Many even experienced designers fear that AI can make design monotonous and dull because it relies on existing data and examples. Of course, no one wants to see a future where there will be recycling from recycling and no room for original ideas. But this is what is happening now: Dribbble is filled with the same type of work, only a small percentage of designers set trends, the rest just copy them, this phenomenon appeared long before the current hype. Neural networks are not just a tool for imitation, the main thing is how you apply it. AI can become your assistant in overcoming stereotypes and limitations, in exploring new forms and combinations, in searching for unusual ideas.
Challenges of current creative processes
Design is as much about creativity as it is about technique. In the game industry there is an interesting description for good games: “Easy to learn, hard to master”. It seems to me that this aphorism fits very well with the description of the path of becoming a designer.
To achieve impressive results, you need skills in a multitude of related areas such as 3D modeling, copywriting, typography and style, illustration, and the ability to work with animation. You need to be confident with Photoshop, Illustrator, Figma, Blender, After Effects, etc. The process of mastering them can take months, and for high-end results, years. I’m not even talking about the fact that it takes years of proper observation and minimal theory to do something that looks at least professional in each of the tools. All of these barriers are significant impediments to the rapid growth of designers, despite the seemingly generally low threshold for entry into the industry.
Even if you have mastered all of this perfectly, the process of visualizing your ideas will take some significant time. Often even a lot of time, if we are talking about some complex and complex graphics. Yes, being an experienced specialist you may know how to cut corners, have your own ready-made developments and templates, but all these are micro-improvements, which if they speed up, then not so much, or do not give the final idea of the design solution.
You end up spending a lot of time visualizing ideas that may end up being discarded for one reason or another. While this kind of phenomenon is common in the workflow, it can not only be tedious, but it can also affect your efficiency. The speed of idea generation and rejection is key to a successful business: whoever experiments more often will hit the target more often. It’s hard to achieve a high frequency if you have to spend a lot of time on each layout.