There are very serious people today imagining and considering the implications of a “world without work,” with algorithms performing cognitive tasks once thought only humans could perform. Derek Thompson, writing in The Atlantic, observes:

The good news is that, while the pace of change is probably faster than you might imagine, we are still two decades away from pervasive synthetic intelligence.

“In the past few years, even as the United States has pulled itself partway out of the jobs hole created by the Great Recession, some economists and technologists have warned that the economy is near a tipping point. When they peer deeply into labor-market data, they see troubling signs, masked for now by a cyclical recovery. And when they look up from their spreadsheets, they see automation high and low — robots in the operating room and behind the fast-food counter. They imagine self-driving cars snaking through the streets and Amazon drones dotting the sky, replacing millions of drivers, warehouse stockers and retail workers. They observe that the capabilities of machines — already formidable — continue to expand exponentially, while our own remain the same. And they wonder: Is any job truly safe?”

Jerry Kaplan identifies such algorithms as “synthetic intellects.” Synthetic intelligence, in the form of “machine learning, neural networks, big data, cognitive systems or genetic algorithms” will soon supplant human intelligence.  In the same way that machines replaced human — physical — labor during the Industrial Revolution, synthetic intelligence will replace human — cognitive — labor during what Erik Brynjolfsson and Andrew McAfee have termed the Second Machine Age. “The coming wave of synthetic intellects is going to devastate many … professions,” asserts Kaplan. “Automation is blind to the color of your collar.”  

It is commonplace in our contemporary society to say that the purpose of higher education is to prepare young people for work. Sean Gallagher states that, “Today it is well accepted that one of the primary purposes of higher education is to prepare students for and connect them to jobs.” We take it as given that the purpose of higher education is to produce productive workers to fill positions in a complex global economy. Indeed, higher education in the United States since the Morrill Act, or at least since the GI Bill, has been defined as human capital development. But if predictions of a world without work come to pass, then the linkage of higher education and job preparation would be torn apart. What will be “the primary purpose of higher education” when synthetic intelligence has made human employment redundant?

Below are three scenarios, each imagining a future world 25 years hence where synthetic intelligence is widespread and ubiquitous. What role will higher education institutions fulfill in each scenario? How might higher education leaders think strategically to thrive under the conditions described under each scenario? 

Scenario 1: Higher Education is Obsolete

Under conditions of synthetic intelligence, with a waning number of jobs that require human cognitive skills, human capital development is no longer an imperative, and thus higher education has become unnecessary for the bulk of the population. A small number of institutions of higher learning remain, as places where students go to engage their minds, but many institutions have shuttered since a central core of their missions have been eliminated. Higher education returns to its pre-Morrill condition as a leisure activity for the few.  Those who do seek higher learning do so without a specific end goal, and certainly not the promise of employment at the end. Higher education exists only for those interested and curious enough to attain it. Some of the costs of higher learning are somewhat offset by basic minimum income allowances — incomes guaranteed by the stat — but the costs of higher learning are borne largely by individuals, and so most people tend to shy away from formal sites of learning. Those interested in higher learning seek out informal, non-degree bearing, and free sources, such as TED talks and other online resources or visits to public libraries.

Scenario 2: Uniquely Human

At one time, higher education was about the acquisition of information. As information exploded and became easy to access, higher education became focused on skill development. Once synthetic intelligence advanced such that many human skills were rendered unnecessary, higher education shifted its focus to the cultivation of attributes, especially those attributes that cannot be mimicked by machines. Students no longer arrive on campus to study accounting, engineering or information technology, these professions now overrun by algorithms. Students now arrive to develop curiosity, creativity, imagination, play and wonder: attributes no algorithm has yet mastered. There is no set curriculum, no prescribed set of courses that one is required to follow at this university. Rather, students are encouraged to follow their interests, moving from subject to subject as their curiosity determines it. Daniel Pink once observed that right brain attributes — such as play and meaning-making — would triumph in the age of smart machines, left-brain skills having been automated. The Age of the Smart Machine has arrived, and higher education shifts its curricular mission to focus on the cultivation of right-brain attributes. 

Scenario 3: Better Together

Hybrid chess — developed by Garry Kasparov shortly after he lost to the computer Deep Blue — is a form of the game where computers and humans compete together against other human-computer teams. Kasparov described these teams as “centaurs:” hybrids of humans and machines. In this scenario, higher education exists to produce centaurs. Synthetic intelligence carries out many cognitive tasks with greater efficiency than humans. But human intelligence is also necessary to complete many cognitive tasks. In other words, humans and algorithms working together prove more effective than either algorithms or humans alone. The purpose of higher education, then, becomes cultivating the interface between human and synthetic intelligence. The designer Sveta McShane describes how algorithms and designers work together: “No longer required to be the operator of the tool in generative design, the human being is freed to become the curator; choosing the best possible solution and working alongside the computer to co-create the most ideal design. Given various possibilities, we can now choose which design suits our needs the best in terms of structure, weight, shape, etc. … Humans don’t get replaced when the machine begins to design creatively; instead we step into the newly evolved phase of the mentor.”

The purpose of higher education is to educate humans and machines together, with human intellects learning how to mentor their synthetic counterparts. Howard Gardner imagines a future where “those hooked on creative activity will also use computers as intellectual prosthetics … most innovations today — from the architectural designs of Frank Gehry to the decoding of genomes by the company Celera — would not be possible without powerful computers.”  The purpose of higher education becomes the augmentation of human intelligence with synthetic intelligence. 

The good news is that, while the pace of change is probably faster than you might imagine, we are still two decades away from pervasive synthetic intelligence. Nevertheless, higher education leaders need to start preparing today for such a world and determining now how their institutions will align to the new reality. Those who do so will be in a position to thrive in the Age of Synthetic Intelligence. 

David J. Staley, PhD is an Associate Professor in the departments of History, Design and Educational Studies at The Ohio State University, where he leads the “Forum on the University,” which considers the future of higher education. He is the author most recently of Brain, Mind and Internet: A Deep History and Future and writes the monthly futures column “Next” for

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