From its inclusion in our phone assistants to now being a part of editing tools like Canva and Grammarly, artificial intelligence is everywhere.
Adobe wants you to use it in Photoshop, and software developers can use Copilot to help create code faster. Marketing professionals can use AI tools to schedule posts and A/B test content for different audiences. As digital-minded individuals, I don't think the question is whether or not we should use AI. The better question is: if we are to use AI, how can we use it in a way that benefits and empowers creatives while also keeping the human elements of curiosity, wonder, and creativity that our careers demand of us?
In this piece, I want to outline a few strategies for using AI — and technology in general — for those uncertain about how to integrate it healthily into their practice. I want to quickly outline some examples of a healthier approach to AI in a few different fields and aspects of industries. In a brief:
One of the interesting things you'll learn as a new graduate is that in the real world, the rules are slightly different from those of a student. Being a student meant trying to come up with original work and answers: being an employee often may mean using tools other employees have created or copying templates that others have provided online (whether in company wikis, knowledge bases, or places like Stack Overflow). At its best, AI is a tool to help facilitate this and help you work smarter and faster, but as with academia, the takeaway from this is not to help you cheat through your employment. With that in mind…
AI is a tool for helping one create good work, not a shortcut for robbing them of creative thinking. Whether the digital marketer, the content creator, the strategist, the developer, or the designer, it's crucial to begin with things that are our own. Beginning with one's work is important because AI is only as good as the work we provide it with. While ChatGPT can generate code on the fly or text prompts that we can take to our meetings, the real learning comes when we begin with what we know instead of what the machine gives us based on a prompt. Knowing how fast-paced agency work can be, I understand that others may say, "We use templates and tools to make work more efficient: isn't having AI generate the starters the same thing?" It is, and it isn't: while there is value in creating based on others' work and not reinventing the wheel (after all, time is money!), an overreliance on these assets stunts the creative's inventiveness. Treat AI as a tool for increasing creative output, not as a crutch to lean on. I use the word crutch because while crutches help support injured individuals, overuse of them can prevent a person from healing correctly, and this is a perfect analogy for over-reliance on AI to do the initial thinking for us. When AI tools augment your work, they can help you create work at greater volume; when they become a crutch that you reach for too often, they rob you of the opportunity to stretch your creative muscles and showcase the unique skillset your employers hired you for.
Creative minds should strive for mastery in the fundamentals of their fields rather than overreliance on AI tooling because there could be a world where this sort of technology is frowned upon — or worse, banned. Governments and regulatory bodies are trying to put the cap back on the toothpaste mess that can be AI technology: while it seems farfetched now, there is a possibility of a world where AI usage is all but banned — or at least, only left in the hands of specific individuals. Rather than trying to collect all the AI tools like Infinity Stones, you should ensure your field's fundamentals are always on point. Doing this will mean you'll always have a place in the workforce, regardless of where AI goes. Try to take a platform-agnostic approach to AI — know the tools and how to use them, but make sure your fundamentals are up-to-date and transferrable in the software of the day. No matter what stance your industry takes on these technologies — whether embracing it or banning it — you'll always be able to leverage your skillset in the field.
While design tools have changed through the 2000s from Dreamweaver to Balsamiq to Photoshop to Figma, young designers still learn the fundamentals of form, type, shape, colours, and size. Though print design isn't my area of practice, I still use the principles of typography, visual hierarchy, spacing, and balance/proportion in my web design work. Academics taught me how to use Photoshop for layouts, but working professionally in a marketing role meant using Canva to do the same things. Tools change, systems change, software changes: as long as the fundamentals are always sound, designers will be adaptable no matter the technology.
Spend enough time with a software developer, and you'll hear about the rubber-ducky approach to debugging code. In this approach, one explains their code to a rubber ducky that sits on their desk. [If you live with a developer, you may be entitled to financial compensation for being their rubber duck of choice.] The point of this approach is to talk through the code aloud — doing so reminds the developer that underneath the code and abstraction, software is about communication: code is for communicating with the computer and telling it what to do, and comments are for communicating with other developers to guide them in what you're trying to do. There's an old aphorism from Arthur Bloch: "A computer program does what you tell it to do, not what you want it to do." If you don't know what you're telling the computer, then it's safe to say you don't know where to begin when the program inevitably raises a bug. While one can spit their code into their AI tool of choice, doing so robs them of the learning and growth that comes from understanding their code. You probably don't understand your bug if you can't communicate your problem to another individual [or a hapless duck]. If you can't articulate the issue to a rubber duck (or another human), you shouldn't immediately reach for an AI tool to help you solve it because doing so robs you of the learning potential. Instead, an engineer should take the time to describe their situation to artificial intelligence and strive to have the code help them understand what's being done (rather than having AI generate the code for them). This approach treats AI like the digital equivalent of a senior developer: a great senior developer doesn't give you the answers; instead, they help you understand the flaws in your thinking and guide you to fill the gaps in your learning.
Content writers and marketers may need help competing with the ever-present sea of promptgeneration guides and AI strategies to create novel ideas and concepts for marketing content, blog posts, and social media captions. While it's tempting to use AI to do the heavy lifting in creating content, it may be better to step away from the computer first to make a good old-fashioned communications outline. Whether using pen and paper, a blank Word document, or a whiteboard and markers, taking the time to do a brain dump of what the messaging goal is, what your company's values are, and what the metrics of success look like helps create a more unique and creative content piece — one that hits the business needs and goals, but also provides value to the audience you've built up over the years. Remember: though your readers may not be in the room with you, they can spot when a caption or post uses too much AI generation. Taking the time to make sure the content you're putting together is your own at the start can create something interesting that stands out in your audience's memory. After all, AI doesn't know your company's unique selling points like you do!
Whether it's Google's Gemini, Microsoft's Cortana, ChatGPT, or Apple's Siri, our AI tools will evolve in capability, share information, and ultimately strive to compete to make our lives easier. What doesn't change, however, is that what we make with these tools is to be used by other people. The most important thing to remember is that technology is a tool for communication with each other. If we keep each other in mind when doing creative work — whether for ourselves, clients, or our employers — then the tool of choice and its popularity becomes secondary: we'll naturally reach for the tool that takes an idea from conceptual to reality. It's this mindfulness, I think, that makes human intelligence far more hopeful than artificial intelligence.