From the Industrial Revolution to AI in a Year

The Struggle in Higher Education is Real.

For decades, we have been told that higher education is facing digital transformation of unfathomable magnitude. But bastions of learning are not easily impressed.

While change in the form of AI may not be welcomed everywhere, the problem with AI is the fundamental incompatibility between a new omnipresent technology, currently gaining exponential traction in society, and an educational model that is built on the logic of the industrial revolution.

In some institutions more than others, the core teaching philosophy has evolved beyond wooden benches and chalkboards, embracing more active learning methods, interdisciplinary studies, and personalized instruction. But the underlying model of class teaching, set curriculums, expert lectures, grading and examinations remains entrenched.

Of course, improvements and adaptations have been made along the way. For example, the Corona crisis moved institutions into digital learning spaces quite forcefully, albeit unwillingly, and some institutions have subsequently retained and expanded digital offerings to increase flexibility for students. Nonetheless, the core of an overheated model for education persists.

From Legacy to Educational Futures

The traditional approach to higher education has been largely successful. The primary goal of education is to produce graduates who are able to create measurable output - whether in the form of grades that allow progression through the education system, research publications, successful startups or other types of output in business or the public sector. Every day, graduates make significant contributions to their fields, and the overwhelming preference for results and output in the education system has been pivotal to driving global innovation and economic growth.

However, when the focus is primarily on producing results, there seems to be a tendency to overlook other meaningful components in the conversation about the purpose of higher education. And this is a conversation that has become highly topical now that we are on the threshold of the greatest technological change for education since the invention of the printed book, Gutenberg’s Bible, more than 500 years ago.

Generative artificial intelligence is already capable of matching and surpassing human ability to solve many of the results-oriented tasks that higher education has monopolized for centuries. While we may be at the very beginning of the Age of Generative AI, AI assistants can already produce high quality output at university level in some subject areas, and the technology's capabilities for idea generation, data analysis and more is frankly extraordinary.

We are also seeing the contours of a future of education in which language technologies and video translation tools can remove friction and barriers, providing seamless interaction between students and teachers in live teaching sessions. AI-driven platforms and teaching systems already enable personalized learning paths with individualized chatbots that assist with motivation and skills in environments with tailored, level-matched feedback.

These tendencies already resonate with corporate business that currently faces a shortage of talent in high-demand areas and dwindling college enrollment amid increasing costs. Right now, Walmart is planning to remove college degree requirements for hundreds of job descriptions within the company. This is but the latest development in a trend where Accenture, IBM, Google and others have introduced similar plans to loosen formal education requirements. Part of the reason has to do with recruitment problems, part of it has to do with the ways in which generative artificial intelligence is transforming jobs, says Lorraine Stomski, Walmart’s senior vice president for associate learning and leadership.

Meanwhile, conventional higher education still concentrates primarily on delivering consistent academic outcomes in the form of research and graduates, minimizing deviations, and streamlining operations. In most institutions, it is what leaders are still encouraged and rewarded to do. With exceedingly long product lifecycles in higher education - think about how long it takes to produce a graduate student, let alone an academic - it remains the prevailing mode of thinking.

The contrasts are building up, and fast.

People | Technology | People

Technology will most likely not dominate human relationships, but AI has already proven to be a potentially democratizing project that enables educational dialogues in new and enriching ways.

These solutions will also create other types of problems. Personalized learning paths can be great, but they also entail a potential abolishment or unintended dissolution of learning communities and belonging. Moreover, developing new skills to change careers is great, but a state of constant transition may lead to excessive trend following rather than depth of learning and pursuing more stable career paths.

At any rate, it is abundantly clear that the technology makes us rethink the future role, purpose, and objectives of education. In doing so, higher education institutions can benefit from using generative AI to help find answers to big and small questions in this transition. Generative AI is a technology that causes strategic and operational headaches in higher education, but it is also a remarkable tool that can be used to achieve strategic benefits over other institutions.

Bold universities can harness AI to make education more daringly imaginative, adaptive, and humane than ever before.

The chalkboard is lit up. Let’s go.