November 30, 2022. That’s the day that academia changed forever. It’s the day that ChatGPT was released and made widely available to the public and artificial intelligence (AI) arrived in a very real way. Like many other organizations, we have seen machine learning increasingly embedded in our tech infrastructure, but that required technical expertise. And sure, we have been teaching machine learning in our computer science and information technology classes for some time, but neither students nor faculty members were actually using it.
ChatGPT, neither the largest nor most powerful large language model (LLM) application of AI out there, has seized the popular imagination, is being adopted by students (and many others), and is causing panic among many academics. There has been a rush to forbid its use, which students are routinely ignoring-that toothpaste is not going back into the tube. Everyone who produces and curates content, from publishers to academics to artists to programmers to search engine companies (Google has declared a “Code Red” because of the threat to its lucrative search business) has existential anxiety.
And we haven’t seen anything yet. The technology, still prone to mind-boggling errors (AI hallucinations, that nevertheless sound convincing), will get exponentially better, especially as tens of millions of users now make it smarter by feeding it more data. Attempts to prohibit its use miss the point. AI will now enter every aspect of our lives, supercharging our cognitive abilities and reach. It raises paradigmatic questions for all of us who lead and work in colleges and universities.
How do we think about knowledge when all knowledge is increasingly within instantaneous reach? Think about ChatGPT as an algorithmic knowledge worker (or cobot, to use a phrase from Lumina’s Jamie Merisotis) always at our side and ready to generate content. I can now use it to create work I might spend hours or days doing (writing a new computer application or creating a script). So do I still need to learn how to code or write a script, or do I now need to know how to assess the quality and efficacy of those products? When my AI coworker can do in minutes what used to take me hours, I now have hours more to spend on higher order questions.
Much of higher education has historically been happy to convey knowledge and infer what a student might do with said knowledge. When knowledge is just a prompt away, what someone can do with that knowledge becomes far more important. A Silicon Valley CFO told me she encourages her teams to use AI to do the monthly close of the budget for their respective business units, using the time now freed up to do more higher order analysis, strategic thinking, and creating the narrative for the nonfinancial stakeholders. AI will run the numbers and produce the monthly results, the knowledge of how a given unit performed financially. But her budget managers must now do more with that knowledge than she had asked of them in the past and they have a lot more time to satisfy that demand. In that sense, AI and LLMs like ChatGPT will likely speed the move to more competency-based learning, which has at its core the question, “What can you do with what you know?” Assessment thus moves to more performance-based methods.
Power skills, often associated with the humanities, will be ever more important in a world where AI does more knowledge work for us and we instead focus on human work. I might ask my AI cobot what I need to know to assess a business opportunity—say, an acquisition—and to run the analysis of their documents and budgets and forecasts for me. However, it will be in my read of the potential business partner, my sense of ways the market is shifting, my assessment of their culture, the possibilities for leveraging the newly acquired across my existing business lines—that combination of critical thinking, emotional intelligence, creativity, and intuition that is distinctly human—in which I perform the most important work.
There is an even more exciting possibility. As AI comes to take on more knowledge work, we may be freed up to do more relational work. My 2022 book, Broken: How Our Social Systems Are Failing Us and How We Can Fix Them (Matt Holt), argues that our large-scale systems of care, those that define a healthy society—preschool care, K-12 and postsecondary education, healthcare, mental health, addiction treatment, care of the elderly, and social work—require relationship and human connection to be effective. A combination of technology, capitalist emphasis on efficiency and cost savings, and a post-Reagan ethos that sacrifices community welfare for individual attainment, fails to recognize the criticality of human relationships in human transformation. We can look at the coming displacement of knowledge work by AI as a workforce disaster or as an opportunity to flood our schools with gifted teachers, provide struggling communities with social workers, rebuild a decimated mental health system, and provide robust counseling to the addicted. None of that is work that an LLM can perform, and no AI system can console a crying child, counsel a deeply depressed patient, inspire a student to dream bigger dreams, or hold the hand of a lonely and aging senior.
Curricula across our academic catalog have been rendered out of date, though many of our people don’t know it yet, and we don’t yet understand how to rethink what we do at the heart of our work. None of this will happen overnight, but I believe that within ten years our lives will be utterly changed. Leaders of institutions need to play with the technology, become active learners, convene their best thinkers, run pilots, and try things. The AI in education conferences, consultants, and critiques will soon abound, but my counsel is not to wait. Nor to rush. We are all in a learning mode now and sometimes we have to go slow at the start—trying some things, making some mistakes, reflecting, and iterating—to go faster later. Our roles as leaders, trustees, and presidents should propel us to ask the big, hard questions, rally the right people, support the learning, and prepare our institutions for the paradigm shift that has begun. If this topic is not on the agenda for your next board meeting and leadership retreat, you’re not paying attention.
Paul LeBlanc, PhD, is the president of Southern New Hampshire University.
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