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Vol. 42 No. 1 — Jan/Feb 2025

OUTSIDE THE BOX

A TIMELINE OF AI

AI is technology that enables computers and machines to simulate human learning, problem solving, comprehension, decision making, creativity, and autonomy, according to IBM. Although it is all the rage in 2024, IBM notes that “human intelligence exhibited by machines” was a concept as early as the 1950s. Machine learning—“AI systems that learn from historical data,” per IBM—dates from the 1980s, followed by deep learning, which IBM describes as “[m]achine learning models that mimic human brain function,” in the 2010s. Today, what most of us are familiar with is generative AI (gen AI)—deep learning models that produce content, including various forms of text, video, audio, and code.

WHERE DO I BEGIN?

I began to wonder where I could get started after years of hiding from AI. As a trained journalist, I, along with many others in my field, feared what it would do to our work, reputation (yes, it could get worse), and the future of media. As much as I love sci-fi and futuristic books (especially Octavia Butler’s) and films (the recent The Creator), as well as everyday tools such as facial recognition on my iPhone, Google Maps’ navigation, and online banking (I live by it), the idea of totally succumbing to an “intelligence” other than my own or that of my higher power’s was not something I was ready for.

That was until a few months ago. As more journalists began to see how some uses of AI could enhance their research, fact-finding, and reporting skills, I realized it was time to take a technological leap of faith. At the 2024 National Association of Black Journalists (NABJ) convention in Chicago in August, a couple of colleague-friends, who dove headfirst into AI many years ago, presented several workshops as part of the Innovation Bubble Powered by Pew Research Center. I listened, and I learned. By the time I left the Midwest, I was sold.

RETHA HILL

Retha Hill is a faculty member at the Walter Cronkite School of Journalism and Mass Communication at Arizona State University–Phoenix and a newly inducted NABJ Hall of Fame honoree. Hill is also the executive director of the New Media Innovation and Entrepreneurship Lab at Arizona State University. She teaches “her students to use AI tools and other technologies to create scenes depicting historical events,” writes Carlett Spike for Quill . Spike quotes Hill as saying the following about AI’s impact on journalism: “The explosion of generative AI has presented even more opportunity.” Hill adds, “What I’m trying to tell my students is that AI won’t take your job, but a person who knows AI will … which is why I’m trying to encourage them to be as flexible as possible.”

MICHELLE JOHNSON

Michelle Johnson is an emerita associate professor of the practice in journalism at Boston University. After retiring from the university in 2022, she taught courses focused on online journalism and multimedia storytelling. Johnson also found the time to delve into the world of AI. “AI can feel overwhelming because it’s evolving so fast and so much hype and misinformation is flying around,” Johnson admitted to me during a recent conversation. “My advice is to not be afraid to experiment. Stay curious, ask questions, and don’t hesitate to push for transparency in how these technologies are being developed and used.” She added, “AI has the potential to revolutionize our lives in countless positive ways, and I’m excited to see what the future holds!” See the sidebar above for more of what Johnson had to share about the “pool” I’m finally swimming in—although I am still in the shallow end.

FIVE QUESTIONS

Michelle Fitzhugh-Craig: To a novice, how would you explain what AI is and how it works?

Michelle Johnson: Imagine a super-smart librarian who has read every book in a massive library and memorized each one. You can have a conversation with this librarian about almost any topic, and they can instantly find connections and patterns across all of the information in these and respond with unique insights really fast. So, essentially, AI is about teaching computers to learn from data and make decisions, similar to humans, but much faster and with access to a vast amount of information. AI isn’t exactly new; Siri and Google Search are like the older siblings of today’s AI. They use AI techniques, but in a more limited way.

What’s new is that AI is becoming more advanced and accessible. For instance, we’re asking chatbots such as ChatGPT, Gemini, and Copilot to write things, generate images, create video, and make audio, and have conversations that approximate human speech. And we’re now seeing AI baked into everything from the tools that we use to write (Google Docs and Word) to our cellphones. These features are being updated very rapidly. And it’s not just about the chatbots. AI-powered humanoid robots are being trained to do repetitive tasks. Breakthroughs are happening in medicine and other fields that benefit from AI-powered systems that can process large amounts of data and find solutions faster than humans can.

Fitzhugh-Craig: I want to learn to use AI. Where should I start?

Johnson: There are tons of free resources available online that explain AI basics without diving too deep into technical stuff. Sites such as Coursera or YouTube have excellent beginner guides. Sign up for a free account at chatgpt.com or gemini.google.com and type in a prompt asking it to teach you about how it works. Ask it how to write a good prompt or to explain what a prompt is. Be sure to tell it you’re a beginner to help it simplify how it responds to you. Don’t treat chatbots like a Google search. It’s a conversational platform. Just speak as if you’re talking to an expert or a smart friend. Ask follow-up questions if you don’t understand something.

Fitzhugh-Craig: Is AI something we should be introducing to our children (more) at this time?

Johnson: Absolutely, but in a way that’s age appropriate. Kids are growing up in a world where AI is everywhere, from their video games to apps that recommend what to watch next. Introducing them to the concepts behind AI helps demystify it. Students are already using AI tools, even when they’ve been told not to. Rather than banning usage, I believe they should be taught to use it appropriately.

Fitzhugh-Craig: How does machine learning differ from traditional programming?

Johnson: Traditional programming is such as giving a computer a set of strict instructions to follow—if X happens, do Y. Machine learning lets the computer figure out its own instructions by learning from examples. Instead of telling a computer how to recognize a cat, for example, you feed it thousands of pictures of cats, and it learns what makes a cat, well, a cat. Machine learning is about teaching a system to learn from data and improve over time. It’s more about guiding the computer to teach itself what the right answers are.

Fitzhugh-Craig: Many believe that AI—via various forms— will take over the world (jobs, homes, how we navigate our day-to-day, etc.). How real is this scenario? Is there a positive outcome in it happening?

Johnson: It’s true that AI will change things, including the job market, but “taking over the world” is a bit Hollywood. AI is a tool, and like any tool, [its impact] depends on how we use it. When it comes to your job, the real challenge will be adapting and learning new skills that complement AI. On the upside, AI can free us from repetitive tasks, create new job opportunities, and maybe even help solve global challenges like climate change.

Michelle Johnson is a former editor for The Boston Globe and Boston.com. She is currently an expert in residence with the BU Spark! program, an experiential learning and innovation lab based in the Center for Computing and Data Science at Boston University. For more of her take on AI, read her newsletter at mijohn.com/aiinsider.