The Future of Artificial Intelligence in Graphic Design

Artificial intelligence (AI) has become an over-hyped buzzword across many industries these days. And the design world hasn’t been spared its powerful influence. Why do we emphasize the design realm? Because without good design, you won’t be able to engage the audience with your content. Just to be sure, follow the link and see for yourself.

Now, we’d like to go deeper with the artificial aspects of modern art. But let’s make a short stop to clarify what AI means in its essence.

Artificial intelligence makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks. Although AI is progressing rapidly, at this point, it’s just starting to take off.

AI: Expectation Vs. Reality

Most AI examples that you hear about today – from SIRI to self-driving cars – are properly known as narrow AI (or weak AI). They were designed to perform a narrow task. For instance, only facial recognition or only internet searches. They can outperform humans at whatever their specific task is. It’s enough to recall when IBM’s Deep Blue defeated previously unbeaten chess grandmaster Gary Kasparov. But their weakness is that they’re limited to that single task – afterwards, they can’t do much else.

Despite the fact that we have computers able to beat chess champions, the scientists are still questing for general intelligence. Thus, the long-term goal of AI is to create general AI (AGI or strong AI), or intelligence that can be applied to diverse and unrelated situational problems.

In attempts to get closer to the abovementioned cyber-dream, IT specialists started playing around with artificial neural networks. The human generally intelligent brain is made up of biological neural networks. These networks can make connections based on our perceptions and outside stimulus.

Artificial neural networks try to recreate such a learning system on computers. They construct a simple framework program to respond to a problem and receive feedback on how it does. By varying the problems and the number of approaches to solving them, computer scientists can teach a computer to be a generalist.

What is the buzz all about among designers?

There are ongoing discussions among designers and developers around the future impact of AI, Machine Learning (ML), Deep Learning, VR, AR, and MR (virtual, augmented, and mixed realities). All of them realize that their jobs may be changing over time. Some of them even have second thoughts that they’d have to start looking for a new profession. Is this scenario the most likely to happen? Let us recap the past history of graphic design tools in a nutshell.

A brief history of graphic design technology

Graphic design used to require physical labour. In order to compose letterheads, business cards, brochures, magazines, books, and posters, one had to hunch over a desk or a light table. He would cut and past paper or assemble metal type on a printing press. He would process 35mm film by hand, developing pictures in a darkroom with chemicals.

What happened in 1984 is now called ‘the desktop publishing revolution’. Who was the main revolutionist? Small wonder that the company with a rather revolutionary image took the credit. Apple’s Macintosh with its layout software (Aldus PageMaker) and its successors enabled designers to make changes with a click.

That is how graphic design moved from the workbench to the computer screen. The laborious world of hands-on creativity was replaced by more abstract digital realm. The new opportunities gave more freedom to the creators. They could see the results of their choices instantly. Meanwhile, the weight of each decision got less. As you could undo it with a single command.

AI invasion into the graphic design realm

Obviously, Macintosh empowered designers to work faster. Anyway, Jon Gold, a designer and technologist whose interest focus is on the intersection of Artificial Intelligence & the creative process, believes that we’ve been stuck on the same semantic level of interaction since 1984: “Decades later it feels like we’re breaking through to another era. The most exciting and intellectually stimulating years in the history of our industry; the cusp of real designer-computer symbiosis.”

As you all can see, today we’re on the verge of another revolution. It’s been almost three decades since the First International Conference on Artificial Intelligence in Design was held at Edinburgh (June 1991). Machine learning is trying to make the quantum leap in the graphic design field.

There’re already commercial projects aiming to create “websites that just make themselves.” Smart soft will collect and process your text content, business field, and imagery. At the end, you’ll have ready-to-go website pages, ideally, without your having to lift a finger. Print design will face changes as well. Given that design-software makers inject ML into their layout tools and apps.

How far have AI tools come until now?

Considering all the noise about AI-driven graphic design, today’s reality is rather far from the grand vision. Online tools can already generate logos based on a series of criteria and preferences. But those who expect miraculous results from AI genies might get disappointed. It’s not as if the modern tools are useless. But the hype over their superpower to replace humans in creating great custom designs got users expectations too high. After all, let’s have a look at the modern designer tools empowered by AI.

So, as for the “self-made websites”, the most popular resources are:

The Grid (thegrid.io)

One of the earliest entries into the artificial intelligence web design marketplace. And, probably, the most disappointing on this list.

The Grid has been promoting “AI websites that design themselves” since its crowdfunding campaign in 2014. The Grid was asking its “founding members” to donate $96 but then it took years to deliver a product.

As a result, an AI named Molly might be an AI breakthrough, but at the moment, her role is mostly cut down to generating colour palettes and auto-cropping photos. No wonder that many users are dissatisfied. Lots of reviews bottom line is that you end up with a look-alike website that is difficult or impossible to customize.

Wix (wix.com)

In contrast to the previous one, this website builder has had a much higher level of success. It also offers an AI solution — Wix ADI (Artificial Design Intelligence). Traditionally, Wix ADI is claimed to be able to create a website all by itself. Using the content you provide, it suggests “billions of beautiful design options”. The user’s job is to pick a preferred option. The reformatting burden lies on the program’s shoulders.

For sure, it facilitates the routine and speeds up the design process, especially for non-designers. Nevertheless, it doesn’t seem to be a breakthrough tool for auto-generating websites.

Firedrop (firedrop.ai)

At first, it was launched as a drag-and-drop website builder in March 2015. Thereafter, at the end of 2015, Firedrop evolved into a design tool using AI. It was almost at the same time when The Grid gained momentum.

Firedrop’s AI is presented by Sacha. It’s an AI bot meant to replicate the experience of working with a professional web designer. This chatbot walks a user through the site-building process. Its recommendations are based on your answers to the series of standard questions regarding the style preferences etc.

As you can see, this tool, just like the previous ones, still require hands-on use. But nonetheless, it comes in helpful, especially for the novice designers or small business owners. Probably, that’s the reason why small businesses are Firedrop’s target market.

DesignScape (designscape-inc.com)

The University of Toronto presented its project in 2015. Unlike The Grid’s Molly or Firedrop’s Sacha, DesignScape doesn’t promise to do all the work for you. Its role is more like a teacher than an assistant. It gives you hints toward alternate and better solutions.

Hence, you may see that new AI-based tools are still far from generating websites that don’t feel like cookie-cutter lookalikes. Unfortunately, the results too often feel like they’ve been punched out of preset templates.

But, glass half full, template selectors and drag-and-drop interfaces have already lightened the burden on small and medium businesses’ efforts to get online. Now, let’s check out the other design-related resources that’ve been empowered by AI.

Adobe Sensei (adobe.com/sensei)

Adobe is the essential software toolmaker for professionals in the sphere of media and design. Thus, it’s not surprising that Adobe isn’t lagging behind the others in the AI race.

So, the company has collected its data and experience in the super high-end of the market over the years. In the end, it managed to build the resulting expertise into Adobe Sensei — an artificial intelligence and machine-learning framework. Basically, it’s an AI-driven face recognition that lets users select and edit human faces in photos. Currently, you can see it operating behind the scenes in Adobe’s tools. It relates to both Photoshop Creative Cloud and Photoshop Fix.

Google Deep Dream (deepdreamgenerator.com)

Google Deep Dream creates stunning colour-saturated images that help it learn. It’s a set of tools enable exploration of different AI algorithms such as a deep neural network. These tools are divided for visual content generation that merge image styles and content.

ColourMind (colormind.io)

ColormMind is a deep-learning colour palette generator. It can generate pleasing colour suggestions from scratch or based on your input.

Designers often use media as inspiration – films, photography, classical art. ColorMind does this in a single click, by training on separate datasets of millions of images and videos.

Let’s Enhance (letsenhance.io)

Let’s Enhance uses machine learning to enhance images of low quality. This way, the website is learning on its own, memorizing the ways one or another photo can be improved.

AutoDraw (autodraw.com)

AutoDraw is a new kind of drawing tool. Users can draw anything they want on their desktops/tablets/smartphones. They shouldn’t bother if their ‘masterpiece’ looks like a childish abstraction. Why? Because the machine learning combines these ‘masterpieces’ with the drawings by talented artists. So, you can create anything visual really fast.

Prisma (prisma-ai.com)

An application for photo and video that transforms user’s content into works of famous artists. This is achieved by using photo and video filters. Thanks to the AI, this app makes your visual content look as if it was created by Van Gogh, Edvard Munch and so on.

So, let’s ask the Oracle…

Should we prepare for ‘The Matrix’ scenario?

Stephen Hawking, Steve Wozniak, Bill Gates, and many others have recently expressed concern in the media and via open letters about the risks posed by AI. The warning basically comes down to the idea that a super-intelligent AI will be extremely good at accomplishing its goals, and if those goals aren’t aligned with ours, we are in a big trouble.

While Hollywood movies and science fiction novels depict AI as human-like robots that take over the world, we have already seen that the current evolution of AI technologies isn’t that scary – or quite that smart.

Will Digital Designers replace humans?

Well, AI does intend to take lots of routine work off designers shoulders. Designers are faced with tedious day-to-day tasks. The examples may be product localization or creating the same graphics in multiple languages.

Actually, Netflix is already using augmented intelligence systems to translate artwork personalization and localization of show banners into multiple languages. An AI algorithm has also been used to generate millions of unique packaging designs for Nutella. The designs were pulled from a database of dozens of patterns and colors. Each and every jar unique, they splashed across Italy. Just to notice, all seven million jars were sold out in a month.

However, designers shouldn’t sound the alarm and search for retraining courses for another profession. At least in the nearest future, bots won’t be able to make independent decisions on how the final product shall look like.

According to Paula Scher, one of the most influential graphic designers in the world, AI and ML assistance won’t stop professional graphic designers from wanting and needing to “make aesthetic decisions about the retouching and the typography.” At the same time, Scher recognized that “entry-level jobs may be lost” with the software becoming more widespread and sophisticated.

Consequently, people will not be the users of technology anymore. At the same time, it doesn’t mean that technology will dislodge us. Instead, we may become mentors. Humans can coach their tools and guide them through the tasks needed. In this world, design work will become more like curation and management. The tools will propose designs, the designers will decide what works.

The Most Likely Prophecy

AI is an extension of what humans can already do. It may be complex inside. However, it’s simply a tool that makes things a little better. It can work faster, consider more complex systems, and evaluate many more variables. So, the prediction is that AI is going to be mostly about optimization and speed. Designers can then cherry-pick and approve adjustments. Theoretically, this would free up their time for more creative tasks.

Designers will gain more time for creativity. Simultaneously, they are advised to be embedded in engineering and coding teams. As it would help to keep the AI and ML efforts real and keep them part of the world. Obviously, all designers should always move with the times not only on the latest technological innovations but also on the current and forthcoming design trends. Check our article on 2018 – 2019 mainstreams in graphic design. Stay up to date with us!

While we are on the topic of developments… With the artificial intelligence evolution, designers will be able to create forms that would be impossible for a lone human to construct. It will make their work better by suggesting incremental improvements based on a profound understanding of their inspirations and influences, as well as on the ability to A/B test ad nauseam.

Previous experience shows that generative technologies have already changed other industries significantly. Architecture and video game design are good examples. But the changes didn’t mean job loss for creatives. Instead, a new era of technologically-enhanced creativity has begun.

SOURCES

techopedia.com/2/27888/programming/what-is-the-difference-between-artificial-intelligence-and-neural-networks
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