Released in 1993 and considered the first widely used graphic web browser, Mosaic was a window to the brave new world wide web. At the time of Mosaic’s release, I was working at Trinity International University in communications; my buddies in IT and I were enthralled by this fantastic new technology. We spent hours surfing the web, learning basic HTML, marveling at the magic of Flash (don’t judge—it was a thing), and launching rudimentary web pages with page builders like NetObjects Fusion—all with the giddy expectation that we were part of a watershed moment in which our world was being transformed.
And so it was.
Flash forward roughly 30 years and the web is now integral to most of our daily lives. We use it for everything from keeping in touch with friends and family to finding easy weeknight recipes, planning vacations, and ordering smart appliances. The web also powers how we work and learn, allowing us to acquire and share information as well as collaborate in real-time with colleagues down the hall and across the globe. In higher education specifically, most marketing and communications professionals readily point to their institution’s web presence as their most essential and ubiquitous channel for recruitment, retention, fundraising, and friend-raising.
Now, our newest watershed moment: the rise of artificial intelligence. With AI’s sudden popularity, the frenetic pace of evolution, and the sheer volume of information—and misinformation—that appears daily, navigating this incredible technology may seem daunting. We offer three steps to help you on your journey:
- Understand the origins
- Adopt a clear lens through which you view AI
- Experiment liberally but adopt carefully
Step 1: Understand the origins
AI as a concept has existed in our thoughts, fantasies, and popular entertainment seemingly forever, yet AI as a fledgling scientific field of study took shape only in the 1950s. At that time, AI showed more promise and possibility than actual proof of viability. It was only through the tenacity of a handful of researchers from around the world that drove progress, however haltingly, through AI’s earliest, obscure years.
The AI discipline of deep machine learning, upon which large language models like ChatGPT4 and image and art generators like DALL·E 2 are based, developed slowly…at first. Patterned after the human brain, neural networking fell in and out of favor with the scientific community and corporate funding sources for over 50 years.
Then, around 2012, this branch of AI experienced exponential growth both in terms of scientific breakthroughs and dizzying financial capital as tech giants from Google to Microsoft to Chinese-based tech giant Baidu and little-known startup DeepMind raced to acquire the best possible AI technology and talent available.
Demis Hassabis, Co-founder and CEO of DeepMind, describes AI as “the science of making machines smart.” In this simple definition lies the power of AI. When I worked in software development in the early ’90s, we wrote code and tried to anticipate and program for every potential scenario. Basically, we told the software what to do. Deep learning, on the other hand, uses natural language and algorithms to process vast amounts of structured and unstructured data. Smart algorithms, big data, and sheer processing power in the form of specially designed computer chips come together to create machines that learn.
In his 2021 book Genius Makers: The Mavericks Who Brought AI to Google, Facebook, and the World, New York Times reporter and author Cade Metz writes, “The rise of deep learning marked a fundamental change in the way digital technology was built. Rather than carefully defining how a machine was supposed to behave, one rule at a time, one line of code at a time, engineers were beginning to build machines that could learn tasks through their own experiences, and these experiences spanned such enormous amounts of digital information, no human could ever wrap their head around it all.”
In a relatively short amount of time, AI has sprung up all around us. Siri and Alexa? AI. Those incredibly well-targeted ads on Instagram that “just get you?” AI. Full Self-Driving Mode in your Tesla? AI. Auto-complete in Gmail? Grammarly suggestions for tightening up your prose? Yup—AI.
It’s not a matter of whether or even when AI will impact our lives: AI is here to stay. It will only grow in adoption—conscious or not—as the technology continues to evolve and becomes more and more incorporated into the tools that power our personal and professional lives. By understanding AI’s origins, you’ll be better able to develop a context for the technology and anticipate its potential trajectory.
Step 2: Adopt a clear lens through which you view AI
According to Scott Ochander, Partner and Chief Leadership Strategist at Carnegie, “AI is like a car engine without a steering wheel. It’s so helpful, but it requires input and revision. It requires an architect. Quality, form, and function… all require human hands.” Humans created AI, humans train AI, and humans—for better or worse—will deploy these tools in our communities. Placing human innovation, intent, and will at the center of the AI discussion helps focus our thoughts and frame our efforts.
At Carnegie, we constantly come back to three fundamental questions when evaluating AI:
- How can AI foster deeper human connections?
- How can AI enrich our professional lives by making us more efficient and enabling us to focus on the aspects of our work that bring us the most joy and fulfillment?
- How can AI help us tell richer and more authentic stories and create better experiences?
These questions—rooted in our foundational values—drive the decisions we make and the ways in which we harness technology to reach our goals.
Step 3: Experiment liberally but adopt carefully
As impressive as AI is, it also has significant limitations. While ChatGPT returns results to simple prompts with uncommon swagger and incredible speed, it can fail at basic arithmetic. It can return false information. It has less common sense than a housecat. And it reflects the biases of the people who train it. AI is not the solution for every problem we face, and just because AI can do something doesn’t mean it should.
At Carnegie, several incubator teams are actively experimenting with AI pilot projects across our product and service lines, from digital and web to research and creative. We’re evaluating its potential to generate preliminary ideas, streamline production, and increase positive results—consistently and reliably. We’re approaching AI with curiosity, excitement, and a healthy dose of realism, and you should too. Here are five ideas to help get you started:
- Sign up for accounts with ChatGPT and DALL·E 2. Or Jasper. Or you.com. They’re all free. Play around with the tools, have some fun, conduct what we at Carnegie call TATs (tiny AI tests). Ask each of them to complete tasks related to work and to your personal life. Demystify the technology through firsthand experience.
- Take a deep dive into the history of AI. Cade Metz’s book Genius Makers is a great primer and a feat of storytelling as well.
- Choose your trusted sources of information to stay up-to-date. Our shortlist includes The New York Times, The Washington Post, The Atlantic, Forbes, and Wired, all of which have beat reporters for artificial intelligence.
- Familiarize yourself with the discussions around AI and ethics. You’ll find great information at The Future of Life Institute and the Pew Research Center.
- Learn how other professional communicators and marketers are using AI today. The Marketing AI Institute has a bank of resources and education opportunities, and Ann Handley is my personal enduring voice of reason and inspiration in the industry.
Also, follow us. As AI has risen to the forefront of our collective attention, so have the accompanying issues of potential bias, the very real limitations of AI’s capabilities, the huge economic and environmental impact involved in training AI technology, and the dangerous potential for weaponizing these tools. Our goal is to help you navigate this new technology wisely as marketers and communications professionals. Moving forward, we’ll:
- Share with you what we learn through our pilot projects and experiments;
- Bring you into our conversations with colleagues, industry leaders, futurists, students, and subject matter experts focused on AI; and
- Invite you to be partners in our exploration and adoption of new tools.
Like many groundbreaking technologies before it, AI promises to transform our lives. Let’s shape that transformation together for the better.
Tune in to Carnegie’s resource channels for more on the topic of AI, and if you’re craving a conversation about AI on your campus, start one today—we’d love to hear from you!
Voltaire Santos Miran is Executive Vice President of Creative at Carnegie. Voltaire joined the Carnegie team in 2021 when the company acquired mStoner, a web development and technology agency for higher education that he led as CEO and Head of Client Experience. Before co-founding mStoner, he spent the first decade of his career in development and alumni relations, working on print publications, alumni magazines, capital campaigns, and website launches. A natural storyteller, Voltaire enjoys teaching others how to effectively tell their brand story, empowering colleges and universities to forge transformative, memorable, and successful connections with their audiences. His expertise in information architecture, content strategy, and governance moves institutions from a project mindset to a process mindset, with powerful results.