The Future of Graphic Designers in the Machine Learning Age

 2 years ago
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The Future of Graphic Designers in the Machine Learning Age

If your grandfather was a graphic designer, he would be creating posters and pamphlets with a pen, paper, scissors, and glue. Every mistake he made would be a huge setback.

If your father was a graphic designer, he would be creating posters and pamphlets with a mouse, keyboard, and computer. Mistakes were not a problem since the invention of ctrl + z.

If you’re a graphic designer today, the tools to create graphic designs are plentiful, and they’re even dread-inducing. When you use cutting edge tools available today, questions will arise.

Questions like, will computers and algorithms replace my job? Did I waste my life training to become a designer only to lose my job to some code? Did a program create 20 variations of a design that would take me a week to do?

It’s tough being a professional human today with the looming presence of machines and algorithms. Every day there are sensationalized headlines about the future of technology and how it will change what it means to have a skill.

Not even creative skills are safe from the algorithms, yet the demand for skilled workers is high and companies aren’t looking to hire robots just yet.

But artificial intelligence and algorithms are already here and they’re making their presence felt in the advanced tools of the present.

As a graphic designer, you need to become aware of the future trends of technology and how they’re going to disrupt the way we view tools and skills.

What is machine learning?

One of the most pressing debates in the realm of graphic design is machine learning and how it will affect the future of graphic designers. So let’s start by understanding what machine learning is.

Material.io describes machine learning as: “Machine learning (ML) gives computers the ability to make predictions and perform tasks without specific instructions.”

In other words, semi-autonomous computers which produce desired outputs. If your ML algorithm is designed to make predictions about the stock market, then the output will be predictions about the stock market.

Machine learning in design products today

ML algorithms aren’t going to infiltrate the day to day processes of our work in the future, they’re already here.

Many large companies such as Adobe, Google, Netflix, Wix and more are embracing AI technology and adding its capabilities into their own products.

One company that rode the hype wave of ML and AI was thegrid.io. This company created an AI service that generated website designs. Web designers were not pleased with this tool but despite the hype, the product and designs were unimpressive and the company fell off the map completely.

Web design is difficult to master and many humans spend years of their life training to be great at it. Web design isn’t the only area of graphic design though, there are also presentation slide designers and logo design companies like Logo Design aiming to automate with AI and ML.

Haikudeck.com is one of those companies selling presentation slides created by AI. Their website claims: “Professional design, without the designer.” This company has created millions of slides and seems to be doing well.


Logos and presentation slides are less complex than websites, and those outputs are more suited for the capabilities of ML and AI algorithms today. In 5 to 10 years this may be different and website designs created by AI may be different entirely.

These service-based companies are just one area where AI and ML will continue to grow into.

Machine learning helping graphic designers work

Other than entirely replacing our skill sets by creating designs without any human intervention, ML algorithms can help augment our skills.


Image credit: Adobe Sensei

Adobe is one of the leading companies servicing graphic designers today. They are aware of the threat that ML and AI pose to graphic designer jobs and so their path in creating an AI tool is to create one which enables humans to work better.

Adobe Sensei is the main ML tool by Adobe which powers many features across their platform stack. They have three main focus areas for Sensei: content understanding, computational creativity, and experience intelligence.

The main goal of Adobe Sensei is to empower humans using the tool by doing hard and tedious work with ML and AI. Tasks like understanding large quantities of content are carried out by AI rather than your own effort. The AI will take the content and provide you an executive summary of the content.

This is just one example of the many ways Adobe Sensei helps users free their time to do creative work rather than repetitive and time-consuming work.

Designing the bridge from algorithm to user

Algorithms and computers are already here but they aren’t knocking on designer’s windows at night asking them to play. There still needs to be a bridge to close the gap between what’s already invented, and what people are using every day.

Here lies a new opportunity where human input is required-in designing and building interfaces for humans to use the AI products that exist and are being developed.


Image credit. Material.io

As more ML features are added, it is important for designers to enable a smooth transition from cutting edge features to a usable product.

Google has anticipated this issue and created a design guideline for adding ML features to its material design products. In this guideline, you will see how Google recommends you to design interfaces so that users will be able to use and understand the full capabilities of the ML features.

At the moment there are three: live camera object detection, static image object detection, and barcode scanning. Each section has subsections of: usage, components, experience, and theming.

They are quite specific about the entire experience of the application. From what the intended usage is, to what functionalities there are, to the specific positioning of the components of the interface, this guideline is thorough and doesn’t leave much room for experimentation.

The future of machine learning

There seems to be an overarching theme when the topic of ML and AI is brought up: the end of everything we know. Humans have been the dominant intelligent species in our entire modern existence. We are so smart that we have started building something that can replace us.

The experts seem divided on this issue, though. There are two experts in particular with a history of making accurate predictions about the future: Ray Kurzweil and Kevin Kelly.

Ray Kurzweil is Google’s Director of Engineering and he is well known for his singularity prediction. The singularity is when technology and AI become smarter and more capable than humans, then all human minds merge with technology to transform into a new kind of consciousness. Ray predicts that this will happen by 2047.

Kevin Kelly is the co-founder of Wired magazine and he is well known as a futurist. His views on the future of AI is less world ending and more world enhancing.

Kevin’s view is that AI will not be human-like, it will be highly specific. The fear coming from AI is that computers will eventually become replicates of humans except much stronger and smarter. Kevin says that rather than replacing human intelligence, AI will augment human thinking with its own unique intelligence.

Take the example of the nowadays cheap website builders which offer templates for you to set up ecommerce websites at the drop of a hat. Humans can design limitless designs but they will not be as fast as AI and its ability to learn and predict the behavior of business owners on the go. Humans can see the analysis the computers provide and extract meaning and insights to help design better websites. This is an example of the harmonious nature that AI and human intelligence will have in Kevin Kelly’s future.

Whether or not AI is coming to destroy us, take our jobs, end human existence, or usher us into a new utopia, bills still need to be paid today. Graphic designers aren’t going to lose their jobs to AI and ML algorithms just yet but the future is uncertain.

Chances are the existing tools will become better, more useful and may even replace some human tasks. The timeline for this happening is unknown but being adaptive and prepared for what’s coming may be your most important skill.

Using machine learning to your advantage

When advanced ML tools arrive, they can either replace you or enhance you. It’s important to position yourself as a person who can take technology and use it to your advantage rather than a person who views technology as a threat.

One way to have ML to your advantage is by teaching it to understand your workflow and optimize it. If you work in Photoshop every day and you train an ML tool to learn your workflow, the tool can analyze how you work and make suggestions on improvements to the way you work. For example, if you always use a few tools in Photoshop, the ML tool can suggest shortcuts or more efficient ways to go about your Photoshop routine which may make you more productive.

This scenario is an example of the personalization that ML algorithms enable. Netflix, Amazon, and Youtube already use personalization algorithms for your home page feed. These companies detect what you watch or search for and make suggestions based on your history.

In the world of professional creatives, personalization may be the next big trend that makes waves.

My take on the future of machine learning and AI

My belief is that AI and machine learning will resemble Kevin Kelly’s vision of the future. Highly specialized intelligent tools that enhance a human’s daily life rather than deadly humanoid robots.

Autonomous cars is an example of the highly specialized intelligent tool that ML and AI can become. The car knows how to drive like a human does and can deliver you to your destination without you driving. However, without you, the car won’t have a destination or the reason to drive in the first place.

Author Bio

Tarif Kahn is Head of Design at Logo Design who loves sharing his diversified pool of knowledge in graphic design, web design and development, and print design. He enjoys experimenting with new technologies and has a knack for photography. Connect with him on Twitter or LinkedIn.

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