How collaboration and A.I. are transforming creative jobs in 2018

The creative industry has always been faced with a rapidly changing landscape, but in 2018 we face some of the largest, and most unknown challenges yet. The way people interact with computers, how we go about doing our jobs, and the fundamental nature of ‘creative work’ is shifting faster than ever before.

This is a look at the state of the creative world and where I think it’s headed from here — a compendium for the next big things in the industry, and the forces that are driving these shifts.

It’s an incredibly exciting time to be in our industry, and as a writer, I can’t wait to see where we’re headed next, but at the same moment it’s a period of anxiety as we’re faced with the realities of a changing landscape, and the impact of automation.

Throwing the doors of the idea creation open

For years, clients and managers have believed that creative work is, essentially, about the fancy website or product you deliver at the end of a months-long project. That misunderstanding has been pervasive and gives too much weight to the wrong part of the creative equation: output rather than the way you got there.

As modern creative processes, such as Agile, Google’s Sprints and other techniques have become widely accepted thanks to the startup industry, we’re seeing a new perspective from our clients: a willingness to work together on the process — from both sides.

Collaborating on a branding project in Milanote

The ideation phase is finally opening up. Rather than agreeing on a project, and each discipline going away to their own rabbit hole to work on their part of the problem, new tools are opening up this process to include almost every stakeholder.

Instead of endless meetings, over-communication of priorities and other nonsense busywork, creatives are able to get work done in a structure that permits experimentation, and iteration, by working together closely throughout the entirety of a project, rather than through arbitrary check in sessions.

“Working together in a sprint, you can shortcut the endless-debate cycle and compress months of time into a single week. Instead of waiting to launch a minimal product to understand if an idea is any good, you’ll get clear data from a realistic prototype. “

— Sprint (GV)

A shift away from single-user tools

This shift has been supported by modernizing tooling for creative work.

For almost two decades, Adobe and Microsoft created tools that had us work in a linear fashion: one task at a time, by one person at a time. Newer tools for creatives like Jira, Basecamp and Asana improved that process, but focused in too much on task management, priorities and deadlines, rather than jotting your ideas down.

Nothing gets your creative juices flowing like opening a ticket for tweaking an icon.

Creatives, it seemed, were doomed to squish their process inside those square boxes for a long time. In the last few years, however, there was a renaissance of new ways to tackling these challenges that developed alongside process improvements and changing attitudes. Designers, clients, writers and everyone else in the process realized that they needed a place to plan, ideate and collaborate — without being forced into ticket numbers, delivery dates and priorities.

Emerging tools take these concepts to a new level, enabling these ways of working across agencies and startups of all sizes. At a high level, I believe this process started with Slack killing email at millions of companies, which threw the doors open. These tools created a direct line to the most important people in a company, where before it might have seemed off-limits to reach out to the CTO directly over email — now they’re engaging on a daily basis across the company. These same principles are quickly moving beyond just chat.

These new tools improve that dynamic by opening up the process, enabling ideation in a new way:

Timely, which gets out of the way of tracking billable hours, and focus on just getting the work done, are making strides in killing off time-tracking headaches — it even features an AI-tool that just figures out those hours for you.

Figma, which brings the design process to the web, puts designers in the web browser rather than a desktop app like Sketch or Photoshop. This allows designs to be shared with anyone, no installation required, instilling a ‘test ideas regularly’ approach I’ve not seen elsewhere.

Milanote, a home for your creative team’s ideas, doesn’t restrict you to a document or page. It helps organize ideas, notes and rich media however you like, across boards with drag and drop, and add structure over time as it all comes together — but offers freedom beyond just a page.

For agencies, which have struggled especially with the shift to open processes, these tools promise to open up the pipeline entirely. By doing this, these “idea-factories” are able to spend time on coming up with genuine solutions to client problems, and executing on good creative work, rather than just the tedium in-between.

Collaborative tools, and a more open process, are throwing the doors wide open to a new way of working that was closed to clients in the past. Stakeholders are tired of long-winded projects, convoluted time-sheets and closed doors — and modern tooling encourages them to engage with creatives much earlier in the process without it seeming intimidating.

Perspective from everyone is important; no ‘design solution’ can be perfect in a vacuum. By adding the context of experts earlier in the process, we’re able to solve our own blind spots, and ultimately create a better unit of work than before.

Are creativity and automation compatible?

From sketch, to wireframe, to usable product

For years we’ve been hearing about the dawn of artificial intelligence, and how machine learning is poised to redefine many jobs as we know them. Over the last few years, machine learning has skyrocketed from scientific project to applicable to everyday life: computers are now able to hear us, speak, see the world, and, are beginning to understand it.

The first place you might have seen this revolution is your photo library. Gone are the days of meticulous tagging: now a computer sifts through everything in your camera roll, deducing what it is, and adding the appropriate metadata so that you can search terms like ‘dog’ or ‘beach photos’ and pull up every single image of a dog you’ve ever taken.

“The most remarkable thing about neural nets is that no human being has programmed a computer to perform any of the stunts described above. In fact, no human could.

Programmers have, rather, fed the computer a learning algorithm, exposed it to terabytes of data — hundreds of thousands of images or years’ worth of speech samples — to train it, and have then allowed the computer to figure out for itself how to recognize the desired objects, words, or sentences. In short, such computers can now teach themselves.”

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This shift in attitudes will be a core change to the way creatives work for years to come.

By combining this trend with artificial intelligence, we’ll gain access to a wealth of data that previously wouldn’t have been obtainable without massive amounts of research, testing, or exploration. In other words, the scale of data (and insights) we have access to will exponentially increase.

For a direct example of how this will change the creative process in the near future, look to Airbnb. In 2017, the company’s technologists unveiled that they have figured out how to turn sketches of wire-frames into code and usable interfaces with no human intervention.

All the user needs to do is show the computer a rough sketch through a camera, and it outputs its interpretation in real-time — a task that might have taken hours before, shrunken down into mere seconds.

“We’ve experimented using the same technology to live-code prototypes from whiteboard drawings, to translate high fidelity mocks into component specifications for our engineers, and to translate production code into design files for iteration by our designers.”

AirBnb’s Design Technologists

On the surface these changes can seem concerning, particularly if you’re someone who does exactly these types of tasks, but I believe it’s an exciting development that frees us up dramatically. Computers have always been great for augmenting human intellect and these technologies will allow creatives to shift their focus from busy work, like creating time-consuming prototypes by hand just to prove a theory, to the ideation phase itself.

Some people call this new human-computer meld augmented creativity. This is the act of bridging our own creative blind-spots by using a computer to enhance our output and solve creative problems together, rather than alone. I believe it sets the stage for a new level of work that we simply could never have achieved alone.

As Smashing Magazine said, 2018 will be the dawn of creative collaboration with algorithms. With that comes new challenges: how can we ethically design AI systems that are inclusive? How do we work alongside these new technologies to create something better than we could have alone?

Let’s embrace our new roles

2018 is exciting, because it promises to redefine the creative practice as you know it. Advances in technology and how we work together, as makers, will lead this change by opening the doors for participation.

As automation of processes, such as wireframing, website creation or artboard building quickly takes hold, we’ll see a shift away from focusing on execution and outputs and a move toward the process itself. If we can automate the creation of tedious wireframes in order to validate an assumption faster, it’s a win for everyone — we can focus on what matters.

These changes allow us, as creatives, to step back from the everyday, and work on solving the problem at hand in the best way possible, the first time. With modern tooling’s shift to open the doors to other stakeholders, we’ll be able to create things that are more inclusive than ever, with more information than ever, to remove blind spots in the process at scale.

Automation is inevitable, but it need not be scary. It allows us to focus in on what we are best at: imagining solutions to problems and the creative process.

By embracing these machine learning as one of the tools in our tool-belt, and participating in the creative process opening up, we’re in for a wild ride: it won’t be easy, but I believe that it’s for the better.

More by Owen Williams

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