By Steven Cohen, Ph.D., Director of the M.S. in Sustainability Management program, School of Professional Studies
Throughout human history, new technologies have impacted the world of work. Agriculture disrupted hunting and gathering. The technology of sailing ships expanded the practice of global trade. The work of trading goods and products expanded, and more people worked in trade than in earlier times. Manufacturing replaced the production of many hand-crafted products, and automation reduced employment in manufacturing. Today, we live in a brain-based economy dominated by service industries. It is more lucrative to design clothing than to manufacture it. There is more money in computer software than hardware. Technology marches on, leaving humans to adapt as the jobs they once trained for and held are eliminated or radically modified. Along comes artificial intelligence, which transforms many of the routine and even analytic tasks of the brain-based economy. The machine can draft the presentation deck and analyze the key performance indicators. Soon, the robots will be commanding us, and we will work for them.
Perhaps, but probably not. We have good reason to fear AI, but hopefully we can control it and use it. The history of technological change is one that enhances economic productivity and makes our lives more interesting, less dangerous, and more fulfilling. The economy that my grandparents escaped from in Europe was dominated by a relentless search for food, clothing, shelter, and safety. My grandparents would have thought the idea of work as a means of self-actualization as ridiculous. That was what the synagogue was about, and what you derived from family and, to a lesser degree, from friends. My grandfather Ben Cohen was a baker. For him, work was literally about bringing home loaves of bread and cash to support his family. My father was a businessman whose aim was, in part, the satisfaction gained by building a company and, more crucially, by making as much money as he could in the process. The technologies of mass production, communication, and global travel enabled his business endeavors. His work and approach to work were radically different from his father’s. I ended up becoming an educator, and I derive satisfaction from applying research about how the world works into professional education that helps people lead organizations that might make the world a better place. I’ve taught thousands of students and written over a dozen books, but can barely screw in a lightbulb. I never got to bring home loaves of fresh bread to my family, but the nature of my work and its meaning are as satisfying to me as they were to my grandfather.
The nature of work changes. Technology changes what we do and how we do it—even within the same profession. I began my career as a policy and management analyst before the internet was invented. In graduate school, I often spent scores of hours a week in libraries. I searched for books through card catalogues, wandering through the “stacks” looking at the books adjacent to the ones that I was searching for and learning the ins and outs of the Dewey Decimal system. During my early days in the School of International and Public Affairs, I became the best customer of the “Government Documents Room” in the depths of the Lehman Library. I devoured green covered committee prints from Congress and tried to understand the debates that created the Clean Water Act and Superfund. Years later, I was the beneficiary of a technological miracle: The World Wide Web and search engines. All those committee prints were digitized and placed on the Library of Congress website named for Thomas Jefferson. I could find what I needed in minutes instead of days. Most of Columbia’s libraries can be accessed online. I haven’t done research work inside a physical library in decades. As a result of Columbia’s online library resources, my productivity as a researcher and educator increased exponentially. My work has been made easier and more comprehensive by technology. How will Artificial Intelligence change the way I work? Naturally, I asked ChatGPT to tell me: How will artificial intelligence impact my work as a researcher and educator? This is how it responded (in seconds):
“AI will likely affect your work in both research and education in ways that are both enabling and challenging.
If we break it down:
1. As a Researcher
AI is becoming a powerful research partner, especially in disciplines where pattern recognition, data analysis, and literature synthesis matter.
- Faster literature reviews – Tools like semantic search and summarization can scan tens of thousands of papers, cluster them by theme, and highlight consensus or gaps. This means you can map a field in hours, not weeks.
- Data processing at scale – Whether it’s environmental data, survey responses, or historical archives, AI can clean, code, and analyze data much faster than traditional methods.
- Hypothesis generation – AI can spot patterns in your field’s literature or data that suggest new angles of inquiry you might not have considered.
- Writing & editing assistance – Drafting grant proposals, research articles, and conference presentations can be sped up by AI-assisted structuring, clarity checks, and language polishing.
- Simulation & modeling – In environmental and policy research especially, AI-driven models can simulate scenarios, stress test policies, or forecast trends with higher accuracy.
Risks / Caveats:
- Over-reliance on AI outputs without verifying methodology can introduce errors.
- AI’s “black box” models may produce results you can’t fully explain to reviewers or funders.
- Ethical and IP issues around AI-generated content are still unsettled.
2. As an Educator
AI is changing how students learn and what skills they need.
- Personalized learning – Adaptive AI tutors can help students at different levels move at their own pace, freeing you to focus on higher-order mentoring and conceptual discussion.
- AI-assisted assignments – Students may use AI to draft, code, or analyze—making it necessary to rethink assessment toward process and critical thinking, not just final output.
- New teaching tools – AI can auto-generate examples, datasets, simulations, and visualizations tailored to your course topics.
- Administrative relief – Automated grading for certain assignments, generating rubrics, or providing formative feedback can reduce routine workload.
Risks / Caveats:
- Academic integrity concerns (plagiarism via AI tools).
- The need to explicitly teach AI literacy—how to use AI critically, not blindly.
- Keeping up with AI capabilities so you remain the guide, not the follower.
3. Strategic Implications for You
To thrive, you might:
- Integrate AI into your research workflow but keep a strong validation process.
- Teach AI literacy as part of your curriculum, even if the course isn’t about AI—students will need it in all fields.
- Rethink assignments to focus on analysis, critique, and application rather than rote production.
- Collaborate across disciplines—AI often enables work that crosses data science, social science, and policy analysis.
- Stay ahead on ethics and governance issues, so you can model responsible use.”
I reviewed ChatGPT’s response to my question, agreed with most of it, and couldn’t help but be impressed with the speed and organization of its response to my inquiry.
Just as I needed to learn how to replace libraries with search engines, I will now need to augment search engines with Artificial Intelligence. This will enable me to do a more thorough and comprehensive job of analyzing the sustainability policy and management issues that are at the heart of my areas of expertise. I need to adapt and raise my game to fully utilize this amazing new tool that is available to me.
At the heart of this, for me and I suspect for everyone, will be the application of human values and the judgment based on my unique life experiences. These values were influenced by teachers, colleagues, friends, and family. The combination of influences and my interpretation of their meaning is a little like DNA. The basic materials that make me who I am are similar to the stuff that makes everyone else, but my DNA is still exclusively mine. That is the value added I bring to my work. My voice remains my own, and that is true of everyone. That is what distinguishes us from AI: humans are unique and imperfect; AI is based on a set of data available to all, and while it strives for perfection, it can never be unique.
What does Artificial Intelligence mean to our economic, political, and cultural life? Just as the transition from rural to urban living and from manufacturing to the service economy disrupted and damaged many forms of employment, jobs, and communities, we will experience massive disruptions from AI. We are already seeing reductions in the entry-level jobs that did the drudgery work that AI does more rapidly and with far less expense. But if every organization now has the benefit of the analysis and knowledge generated by AI, we can expect that the floor and the bar of organizational competition will be raised and the need for creative and rapid introduction of new services and products will grow. Automation generates increased demands by customers for higher levels of service: Why should I wait in a physical line at the Department of Motor Vehicles when I could simply fill out a form online? Now we will ask: Why do I need to fill out the form? Can’t AI generate my information for me to review?
The irony of this change is that many of the technical and engineering skills we thought would guarantee employment, while still needed, will only be the starting point to assure a successful career. Creativity, communication skills, critical thought, innovation, and the ability to pursue relentless experimentation are the best bases for employment going forward. This is not an argument for liberal arts but for interdisciplinary education. ChatGPT was right about the importance of interdisciplinary collaboration. People become experts in one field of knowledge but then learn how to engage in creative group work with people from other fields: Engineers, natural scientists, medical professionals, economists, lawyers, social scientists, and many others work in teams to develop improved products and services. The key skill is the ability to work as both a follower and a leader of a team. Be the person that everyone wants on their team.
The employers who are ecstatic about the prospect of cost savings from AI have decided to eliminate entry-level hiring because the old grinding staff are no longer needed. That is beyond short-sighted and more than a little idiotic. Changing culture and technology cause young people to have radically different life experiences than their elders. The new services and products required due to AI-induced competition will need their input to succeed. Moreover, as middle management ascends, who will replace them a decade from now? Hiring should focus on people who work well in teams, have demonstrated a love of learning, and are self-conscious about the way their own generation thinks the world works.
Artificial Intelligence is a powerful and unpredictable new technology. It will be as transformative as the internet and will change economic and work life. To succeed, workers must learn how to use it to facilitate innovation. Ignoring it or running from it is not a good idea. It must be carefully and thoughtfully embraced, keeping in mind its dangers and limits. Many of the new jobs it will create have yet to be invented. The past several decades of job creation may provide a hint of what might come. In the 21st century, we have seen an explosion of designers, for example, like web designers and fashion designers. We have also seen a high demand for people who can organize events and exhibits. There has been a massive increase in physical and occupational trainers. New careers have developed for social media managers, analysts, and content providers and for podcasters and podcast producers. The list could go on. There is no question that new opportunities and jobs will resemble the past, but will also be impossible to predict today. AI should not be feared, but it should be understood, managed, and regulated.
Views and opinions expressed here are those of the authors, and do not necessarily reflect the official position of Columbia School of Professional Studies or Columbia University.
About the Program
The Columbia University M.S. in Sustainability Management program offered by the School of Professional Studies in partnership with the Climate School provides students cutting-edge policy and management tools they can use to help public and private organizations and governments address environmental impacts and risks, pollution control, and remediation to achieve sustainability. The program is customized for working professionals and is offered as both a full- and part-time course of study.
