How universities can best prepare for the generative AI tech revolution

Artificial Intelligence machine learning. [Getty Images]

Every major technological revolution sets in motion a concurrent revolution in work. With the development of organised agriculture thousands of years ago, foragers settled on farms. During the Industrial Revolution, steam engines drove those farmers into factories. In the late 20th century, the arrival of the personal computer swapped machines for monitors, and lathes for laptops.

Now, with the appearance of the latest wave of generative artificial intelligence (AI), humanity is about to embark on an entirely new working order.

Last year, the OECD predicted that AI would “radically transform” 1.1 billion jobs in the next 10 years. Given the impressive new technologies that have arrived since, this now seems like an almost bashfully conservative estimate. Systems such as GPT-4 and Midjourney can create poetry, code, research papers, interior design plans, websites, and book reviews. They can model protein structures, evaluate insurance claims, and explain abstruse scientific concepts in layman’s terms. These systems are so impressive that professionals in law, finance, and even the arts are nervously tugging at their white collars. Within days of the arrival of GPT-4, Goldman Sachs issued a report warning that the latest AI systems could automate a quarter of all the work done in the US and the eurozone, costing some 300 million jobs.

Yet while previous technological revolutions also transformed work, this time it’s different – because AI is transforming it at an altogether different speed. As the race to make these systems even more powerful accelerates, AI will soon emerge in everything, everywhere, all at once. From the development of drug therapies to the content on our entertainment apps, these systems are reinventing entire sectors. To adapt to this reinvented economy, people will need to reinvent their skills, careers – and, indeed, agency over their lives.

Traditionally, people have turned to higher education to acquire the knowledge and skills to succeed in the world as it exists. The challenge today is that because of AI, the world will exist in a radically different way tomorrow, and again the day after. Therefore, educating people for reinvention in this fluid context will require the reinvention of higher education itself. We can do this through three fundamental reforms to the model.

Create a curriculum for the AI economy

Higher education needs to orient the curriculum to account for the prevalence of AI going forward. Grounded in what I call “humanics,” such a curriculum should include technological literacy, or understanding how machines work and how to work with them; data literacy, which is the fluency to interpret and utilise the information on which technology operates, and which is generated by it; and especially human literacy, which cultivates our edge over AI in distinctly human traits such as entrepreneurship, ethics, leadership, and understanding of intercultural contexts.

The World Economic Forum’s own “Education 4.0” initiative has also produced a helpful taxonomy that emphasises developing skills and attributes less prone to automation. These include cognitive skills such as creativity, social skills like socio-emotional awareness, intra-personal skills such as curiosity, and societal skills such as civic responsibility. Educators should take note of the need to help students develop these skills as well.

Design experiential programmes for the AI workplace

Colleges and universities should do more to expose students to the changes AI brings about in real-time – particularly how it changes workplaces. As AI continues to be integrated into different sectors, it will lead to the automation of jobs and tasks most likely to be performed by entry-level or junior employees. Copywriting, legal research, simple graphic design, administrative functions – work that used to occupy early career employees will be done by fewer people, or none at all.

Thus, one of the consequences of more AI will be the evaporation of opportunities for young people to learn foundational skills and climb the first rungs of the career ladder. Universities, therefore, need to give them a step up.

They can do this by integrating abstract knowledge with lived experiences. Experiential learning programmes develop meaningful connections between learners, other people, and the changing world, giving them an advantage over machines. What’s more, by immersing learners in the AI workplace, we allow them to acquire foundational skills and industry knowledge – even as AI narrows the main portal for entry, experiential programmes open a professional side door.

Reinvent the university for lifelong learning

Two days after Goldman Sachs published its ominous report, an open letter from the Future of Life Institute called for an immediate halt in the training of AI systems more powerful than GPT-4.

Signatories included luminaries such as Elon Musk and Apple co-founder Steve Wozniak. But the CEOs and head researchers at the leading companies investing in the race to accelerate AI were notably absent.

Despite the threats of mass automation and disinformation, the power and reach of generative AI will continue to grow. As a result, AI’s reinvention of the workplace will be ongoing, too. People will have to reinvent their roles to keep ahead of these evolving technologies, make the best use of their strengths, accommodate their weaknesses, and work with them productively. We will have to upskill and reskill on an ongoing basis.

This has immense implications for our education system, to say nothing of how we approach apprenticeships, corporate training programmes, and educational technology. For universities, this means a fundamental change in priorities. Instead of sidelining lifelong learning to the periphery of its operations, higher education will have to place it at the forefront of its mission, serving nontraditional learners with customised programmes tailored to changing professional needs.

There’s no avoiding the reality that AI is reinventing the workplace and, with it reinventing the work that people do. Universities’ foremost obligation is to serve our students by helping them adapt to this mercurial, bewildering, but an immensely exciting reality. We can do it – but it’s going to take some reinvention.