The train slips slyly between valleys and tunnels, with a gentleness that suits the Alpine landscape but hardly matches the importance of the journey. It takes more than four hours to reach Villach from Vienna: many, considering the kilometers, but perfect for deepening a reflection.
I’ve just spent two days alongside a group of Austrian academics, working to convince the local government of the value of a proposal for a new international doctoral school. The subject: geographic information sciences and technologies (GIS)—mainly software enabling the visualization and analysis, on a map, of a landscape, a city, or any other entity with a geographic component.
The mission proved more difficult than we had all hoped. The commission, made up of American and British experts, wasted no time in posing the most basic and challenging questions: How will collaborative work among researchers be fostered? What professional pathways will follow after the doctorate? Why is GIS important for the world, and why is academic research essential for its development?
While the proposal aimed to legitimize the young field of GIS as a new academic discipline, the commission wanted to know how the research project would serve a changing world. In an era when the most impactful innovations are being made available to everyone by Google—think of Google Earth—and a handful of other software multinationals, what added value can the university truly offer in terms of new scientific and technological developments?
Perhaps this is a question that has always existed, across all fields. Yet for engineering disciplines focused on new digital technologies, it holds special significance: good practices are still scarce, while the risk of academia imitating—or futilely chasing—industry is very real. To formulate plausible answers, I believe we must first take a step back and ask ourselves: what is the fundamental relationship linking the world of science to that of technology?
Here is my own limited synthesis of their respective missions. The purpose of science is to understand physical and social phenomena, and its raw material is empirical data. The purpose of technology is to overcome the limits of the physical world, and its raw material is mechanistic processes.
Such a distinction would clarify much conceptual work too freely labeled as “scientific” or “technological” by both academic and industrial researchers. It would also render more transparent one of the fundamental ties between science and technology: new technologies can be used to generate new empirical data useful for understanding physical and social phenomena; in turn, scientific discoveries can be used to overcome the limits of the physical world. Two classic examples: the invention of the microscope (technology) paved the way for a new understanding of physical phenomena (science); the discovery of uranium (science) paved the way for the invention of atomic technologies (technology).
In light of this distinction, should we then conclude that each should stick to its own trade—that universities should deal with science, while industry with technology? Before drawing conclusions, I prefer to take another step back and ask: what fundamental difference distinguishes the university from industry when it comes to innovation? I observe that the industrial approach is largely reactive and oriented: given a problem and a market demand (real or constructed), all work is directed toward finding a solution. By contrast, the academic approach is largely creative and non-oriented: given a discipline, researchers creatively explore certain paths that may lead to new knowledge, paths that are not oriented toward any end beyond pure understanding.
It seems to be industry, more than universities, that allows for the greater number of exceptions: every Google employee, for instance, may devote 20% of their work time to a project of their choice. Such creativity and lack of orientation can lead to the discovery of new paths for the company, keeping it at the forefront of innovation. Conversely, the creation of new start-ups out of academic contexts remains incredibly difficult: the researcher is accustomed to viewing the world through the categorizations of their scientific discipline, rather than as a set of “value chains” that compose different markets. They know that the computer works thanks to this, that, and the other process; but they don’t know who performs this, that, and the other operation so that the computer ends up on the shelf of the local store.
To sum up, we could say: universities deal predominantly with science, industries predominantly with technology; universities are founded on scientific disciplines, industries on markets. I tell myself: if this is the case, there must be good reasons. But I also ask: is all this enough? Can disciplines and markets optimize the alliance between science and technology in an era of global problems of gigantic and unprecedented scale, such as climate change and ecological degradation, cultural uprooting, mass migrations and religious conflicts, extreme poverty and social divides?
My answer is no. We still need universities and industries as we know them, but we also need new entities. We still greatly need faculties of natural sciences, economics, and engineering, just as we need the automotive, IT, and energy markets. Yet we also need a broader alignment and re-orientation of both science and industry toward the world’s most urgent problems.
I imagine a “faculty and industry of climate change,” a “faculty and industry of poverty and social inequalities,” a “faculty and industry of industrial and financial globalization.” I imagine new organizations at the service of the world before being at the service of a discipline or a market—organizations meant to produce new science as well as new technology, composed of mixed teams—university and industry, all disciplines and all markets—brought together to converge on a single, unequivocally defined problem.
In their absence, one discipline or market may “undo” what another has painstakingly achieved: alternative energy technologies gain ground, yet at the same time the telecommunications and computer industries generate astronomical energy consumption (charging electronic devices and powering server farms); psychology embraces the validity of new life models, while economics continues to rely on opposite assumptions.
I believe the future will only surprise us on this matter. Arizona State University is already beginning to think along these lines. The new world is yet to be invented—a world that reconciles opposites: theory and practice, creativity and reactivity, disinterested knowledge and orientation toward real-world problems.