How Can MIT xPRO’s Generative AI Course Benefit You? An AI Expert Shares His Experience

Ready or not, AI is here to stay, and it’s reshaping the workforce. 

Since ChatGPT disrupted the scene in 2022, the demand for generative AI knowledge has skyrocketed. Businesses are racing to figure out how to use it, and professionals across industries are eager to keep up. In response, MIT xPRO launched a course called Driving Innovation with Generative AI to help learners explore generative AI’s capabilities, applications, and ethical considerations.

Wondering what to expect from the course? 

We spoke with Grant Harvey, a writer for The Neuron, a website recently acquired by TechnologyAdvice that covers AI trends and tools and publishes The Neuron Daily newsletter—and a graduate of the first cohort of our generative AI course. 

In this Q&A, Grant shares his experience with the course: what surprised him, how it changed his perspective on AI, and why professionals from a range of industries can benefit from it.

What Was Your Path to Covering AI at The Neuron? 

“I have always loved writing,” says Grant. He studied screenwriting in college and spent time in content marketing, PR, and advertising before landing a role at You Exec, where he wrote a newsletter covering emerging trends.

Through that work, Grant closely followed AI’s capabilities in the years leading up to ChatGPT’s explosive impact. Like many writers, he experienced some existential panic when he saw what generative AI could do. “I think a lot of people had that moment—you see it generating text, and you think, ‘Oh wow, this can do what I do. Is it coming for my job?’” he says.

Instead of shying away from AI, Grant leaned in. “I wanted to understand how generative AI worked and find ways to use it for my own purposes—before someone else replaced me with it,” he explains.

That curiosity put him on the path to The Neuron. “By the time the opportunity to write for The Neuron came around, I had already been following AI and using AI tools in my own writing for a couple of years,” Grant says.

“What I love about The Neuron is that we take an entertaining approach to AI news,” he explains. AI can feel intimidating—like an unstoppable force disrupting careers and industries. Covering it in a way that is engaging, accessible, and even funny helps demystify it.

What Makes MIT xPRO’s Generative AI Course Valuable for Professionals?

For Grant, one of the standout aspects of the generative AI course was how it took complex AI concepts and made them accessible—something that aligned with his goal at The Neuron. “The course gives you videos from actual MIT professors explaining these technical topics in a really digestible way,” he says. “For such a technical subject, it was surprisingly easy to understand.”

The course assignments follow a consistent three-part structure: identify a real-world challenge in your field, design an AI solution (conceptual, not technical), and reflect on broader implications. 

For example, one assignment had Grant designing an AI agent with specific functions and ethical considerations, while another required creating an entire framework to integrate AI into industry workflows. 

What makes these assignments so effective is their practical focus—learners immediately apply concepts to their specific industry—and the peer review process, which exposes learners to how professionals across different fields are implementing similar principles.

“You get to see the kinds of projects people are working on, and it’s clear that many are using the course to solve real challenges in their jobs at companies you'd recognize the name of,” Grant says. 

What Takeaways Can You Apply to Your Work as a Journalist?

At The Neuron, Grant’s use of AI is primarily hands-on and prompt-based. “I typically work with Claude, which is the tool we prefer, and use it for things like refining my drafts, making content easier to understand, or cutting down word count,” he explains. “Basically, all the things a writer would want quick help with here and there.”

MIT xPRO’s course encouraged him to think bigger about AI’s potential in journalism, and he began mapping out how he could automate his entire workflow using AI.

“It’s actually a great exercise for anyone—especially if you’re worried about AI replacing your job,” Grant says. “Write down every single thing you do that a robot would have to replicate, and you’ll realize just how complex that list really is. Imagine trying to write an algorithm to do all of those things!” 

The course also inspired Grant to create “The Decider,” an AI tool that helps prioritize tasks by ranking goals, asking targeted questions, and applying importance weights. It serves as a practical example of how AI can augment decision-making without replacing human judgment. 

How Did the Course Change Your Perspective on Generative AI? 

Even as someone who follows AI news daily, Grant was surprised by how much he learned in MIT xPRO’s course. “Despite covering this space every day, I still came across things that genuinely surprised me,” he says.

One moment that stood out was learning about an algorithm developed by MIT researchers that can generate a working 3D printed robot from a simple prompt. “It’s not building you R2-D2 or C-3PO, but it can print a flexible robot that moves and accomplishes small tasks,” he says. “I had no idea something like that existed.”

AI extends far beyond chatbots and large language models (LLMs). “The course covered AI applications in generative art, biology, and even developing language models for things beyond human language,” Grant recalls.

Another key takeaway? The importance of ethics. “In hindsight, one of the most valuable parts of the course was how much time it spent on the ethics of AI,” Grant says. “They don’t just ask you to think about how to build something useful for your job—they push you to think about how to do it in a responsible and ethical way.”

He highlights one assignment that focused on designing AI for educational spaces. “They gave us interesting examples of AI being tested with kids—how it can be a great tool for learning, but also how kids can form attachments to robots,” he explains. “It made me realize that when building AI, you have to consider how to make something work in a way that’s maximally beneficial and minimally harmful.”

How Do You See AI Impacting the Workforce?

At The Neuron, there’s a saying: A robot isn’t going to steal your job, but someone who knows how to use AI probably will. “Obviously, that’s a little tongue-in-cheek,” Grant says, “but there’s truth to it. AI isn’t going away, so the challenge is learning to work alongside it.”

Grant sees AI as a tool that amplifies human capabilities rather than replacing them outright. “Even if you don’t use AI yourself, understanding what it can and can’t do is essential,” he says. “That way, you can focus on the aspects of your job that only you can do while using AI to enhance your efficiency.” 

For professionals who do embrace AI, the advantages can be enormous. “Whatever you’re already great at, AI can help you do it ten times better—if you know how to use it effectively.”

What Role Does Training Play in Helping Companies Implement AI Effectively? 

While AI is impacting the workforce in immeasurable ways, many companies are still figuring out how to integrate it effectively. Some organizations take an unstructured approach, simply telling employees something akin to, “Use ChatGPT and be faster.” Others, particularly large corporations, might do the opposite—strictly limiting AI use to minimize risk and protect sensitive data.

Grant notes that neither approach is ideal. “When companies ban AI outright, employees often just use it in secret,” he says, referencing a report that showed that 52% of people who use AI at work are reluctant to admit that they use it. People aren’t sharing what they learn—meaning organizations are missing out on collective knowledge that could make everyone more efficient.

The solution? Taking a deliberate approach to AI training. “It’s imperative for organizations to identify the best strategies and tools for AI, then share that knowledge internally so everyone benefits,” Grant says. “If you don’t, you end up with an uneven system where some employees are far more efficient than others—just because they figured it out on their own.”

What Excites You Most About the Future of AI?

For someone who spends so much time analyzing AI’s trajectory, Grant admits he doesn’t often stop to think about what excites him most. He’s usually focused on predicting what’s likely to happen rather than what he hopes will happen. But when pressed, two key ideas stand out.

“The first thing that comes to mind is the actual personal AI assistant we’ve been promised,” he says. “I mean one that’s fully local to your device—that remembers everything about you and functions as a true second brain.” This kind of AI assistant could be a game-changer for productivity, though Grant acknowledges the potential downsides of people offloading their thinking to AI.

The other area he’s watching closely? Robotics. “I do love robots,” Grant says with a laugh. “And I feel like we’re on the cusp of seeing truly capable humanoid robots. Companies like Figure and 1X Technologies are making incredible progress in this space.”

But as with any transformative technology, the implications matter just as much as the advancements.

That’s something Grant has learned from covering technology for the past five years: There’s always a tradeoff. “The real challenge is figuring out whether the benefits outweigh the costs—and, to bring it back to the MIT xPRO course, how we can minimize the downsides while maximizing the upsides,” he says. 

That’s what will ultimately determine how AI shapes our future.

Ready to take the next step in using generative AI to its fullest potential? Enroll in Driving Innovation with Generative AI today!