Will AI eliminate jobs? Yes, but it’s likely to also create them. Students need to prepare for what’s next | Opinion

The relationship between artificial intelligence (AI) and employment is like the thought experiment known as Schrödinger’s cat: until we see the future, AI’s impact on work is both “alive” with opportunity and “dead” with risk. AI could boost productivity and free workers for creative tasks, or it could cause unemployment and widen inequality. The outcome remains unknowable until it unfolds.

The fear of the “dead cat” scenario has resurfaced in recent months. With over 1 million job cuts so far this year, recent announcements from Amazon, UPS, and Target to lay off a combined 60,000 employees have intensified public anxiety over AI’s impact on employments. While some executives explicitly cite automation and AI implementation as reasons for the reductions, others deny direct AI involvement. Critics have accused companies that cite AI of “AI-washing” their layoffs: blaming AI for broader restructuring or cost-cutting. Either way, for many workers, the message is the same: AI is coming for their jobs.

I’m an assistant professor of information science, and at the beginning of this semester one of my students asked me whether I thought AI would replace workers. I don’t recall my full response, but I likely echoed the popular statement: “AI won’t take your job, but someone who knows how to use AI will.” It’s a neat, comforting phrase. It argues that adaptability and skill development can outpace technological change. But as I read about the layoffs and the shifting rhetoric around AI, I found myself revisiting that question with new unease. What if the issue isn’t just about learning new tools, but about navigating a future where the rules of work are uncertain?

The honest answer is that no one truly knows how AI will reshape employment. During my doctoral studies in engineering and public policy at Carnegie Mellon University, one of our departmental mantras was, “My only certainty is uncertainty.” We even had the phrase printed on our departmental t-shirt! It was a reminder that even the most rigorous analyses and models come with caveats, assumptions, and blind spots. That statement rings truer than ever in the age of AI.

For those of us in higher education, this uncertainty presents a profound challenge. As educators, we are tasked with preparing students for careers that may not yet exist, using tools that are still evolving, in industries that could transform overnight. I teach my students to collaborate with AI, while developing new methods of assessment that cannot be circumvented with AI. Teaching and learning in an era of AI-induced uncertainty requires acknowledging that, beyond transferring knowledge, cultivating resilience, adaptability, and critical inquiry is more essential than ever.

To be clear, uncertainty around technological change is not new. Every industrial revolution has triggered both optimism and panic. At the dawn of the 19th century, Luddites feared that mechanized weaving looms would take their jobs; instead, it transformed labor and productivity. In the 1980s, personal computers were expected to eliminate white-collar jobs; instead, they created new products, services, millions of jobs, and an entire digital economy. Time and again, we’ve misjudged how technology would affect work, both in the direction and scope. That said, the rapid evolution of generative and agentic AI feels distinct. Unlike prior technologies that automated routine, physical, or clerical work, AI now encroaches on cognitive and creative domains once considered uniquely human: writing, analysis, decision-making, even teaching.

To be sure, experts across the spectrum are voicing concern. Geoffrey Hinton, often called the “Godfather of AI,” has warned that the technology could lead to widespread job displacement. But even Hinton’s caution hinges on the emergence of superintelligent systems—a level of capability we have not yet reached, and don’t know if we will reach. Between the hype and the doomsday scenarios lies a more nuanced truth: the future of work will depend less on AI itself and more on how societies, institutions, and educators choose to adapt.

In the classroom, this means teaching students not just to use AI, but to question it, to examine its biases, its limitations, and its social implications. It means designing curricula that balance technical fluency with ethical reasoning and critical thinking. And it means admitting, as educators, that we too are learning as we go.

If “my only certainty is uncertainty,” then perhaps the goal is not to eliminate ambiguity, but to prepare for it. The paradox of AI and employment may remain unresolved for years to come, but our responsibility is to stay curious and critical in the face of the unknown. The future, after all, isn’t waiting for us to open the box. We are building it, one uncertain decision at a time.

Dr. Erezi Ogbo-Gebhardt is an assistant professor of information science at North Carolina Central University’s School of Library and Information Sciences, and a Public Voices Fellow of The OpEd Project.

This story was originally published November 25, 2025 at 5:30 AM.