The robots are coming, and some of them are charming. That was my reaction on a recent visit to Singularity University, when I met two robots named Pris and Pepper. Even though her “brain” was turned off when I met Pris, she was still able to sit on the floor, cock her head, blink, and follow my words and my body with her head. At times, she would even blink with a tinge of pink in her eyes. The effect was uncanny, engaging, and almost flirtatious.
Pepper—approximately four feet tall—was much larger than Pris and just as endearing. He danced, tried to talk with me and my colleagues from Southern New Hampshire University and follow our commands but mostly made a lot of errors. As a result, we were able to watch his programmer correct him. Their interaction was striking. When Pepper couldn’t quite follow the right cues, his programmer would gently caress his head and try to get him to listen to the correct command. He kept touching his head like a father might do to his young toddler. It didn’t strike me as weird or inappropriate but rather relatable: I might have done the same thing.
My job at Southern New Hampshire University is to lead an R&D innovation lab called Sandbox ColLABorative. My colleagues and I were visiting Singularity University as part of our ongoing efforts to scan the horizon for new ideas, products and services to help inform our thinking about future and alternative business models for the university. At Sandbox, we help create Design Days and workshops for our faculty and staff to develop design-thinking mindsets to tackle any challenge with which they may be dealing. The challenge with orienting toward the future and galvanizing teams in that work, however, is that the future can often seem ominous, daunting, and full of despair.
When those of us in higher education talk about the future of education, we tend to jump quickly to forecasts that reveal our fears, pessimism and anxiety about what seem like tectonic shifts in the sector. Much of this negativity is tied directly to the increasing role of technology.
Experts talk about Moore’s law, which states that computing memory power doubles every two years. Since the 1890s, we have seen a trillion-fold increase in power—one billionfold of that increase just since the creation of mainframe computers. At the same time, the price of new technologies continues to fall, which leads to faster and more market penetration. To date, 75 percent of the global population has access to a mobile phone. In the US, it took 76 years for the telephone to reach half the population; the smartphone did it in less than 10 years. PwC explains that the cost of DNA sequencing per genome has fallen from $96 million in 2001 to less than $6,000 in 2013. Today, we can purchase a 23andMe kit for $20 for a personal genetic test. This is what futurists mean when they talk about exponential futures, and exponential futures are no joke.
The pace of change can feel exhausting. There is palpable ‘innovation fatigue’ across college campuses. Faculty, staff, and administrators are tired of being told to adapt or die. People are sick of hearing about innovation and how they’re not doing enough of it. We freeze up when we hear statistics that project that by 2025, 50 percent of an undergraduate degree will become obsolete. We don’t want to believe it because what in the world are we supposed to do about it?
Perceiving newness as danger, it turns out, is hard-wired in our brain’s limbic system. Our amygdala, which has helped us survive since the Neanderthals, triggers our fight or flight response. The future and the new translate into feelings of fear, stress, and anxiousness just as though we’re responding to a tiger in the bush. It’s no wonder, therefore, that we immediately retreat into a defensive posture and see the future as threatening and something dangerous to resist.
So how do we equip ourselves with better tools? One thing I learned about from the futurists at Singularity University is to orient around a theory of abundance rather than scarcity. SU relies on co-founder Peter Diamandis’s theory of abundance, which imagines a world of increased access and availability. By shifting our mindsets to 25 years out, we can begin to imagine scenarios of abundance that provide hope for our world’s grand challenges. Diamandis describes a future in which a projected nine billion people in the world will have “clean water, nutritious food, affordable housing, personalized education, top-tier medical care, and non-polluting, ubiquitous energy.” The futurists from Singularity University discuss the future with great optimism because they believe that technology has the ability to drive down costs in such dramatic ways that exponential futures are imaginable.
Looking farther out empowers us to move beyond linear thinking. If we are always in a reactive mindset, our instincts will always be on heightened alert, and our tendency to resist change will be stronger. We don’t have to always feel like the future is happening to us. An exponential mindset helps us imagine our way out of all the things that look like barriers today—things like governance, regulatory bodies, infrastructure, and systems that are not ready for that exponential future of abundance.
As a discrete example, think about our growing gig economy. It may be hard to imagine, but soon enough, major companies and organizations will soon house large networks of people but few employees. Traditional org charts and our linear tax structure won’t be able to account for what the experts at the Institute for the Future call “the digital coordination economy,” which is filled with tasks/micro-contributions—not jobs. If we extrapolate out from current platforms like UpWork, TaskRabbit, and Amazon Mechanical Turk, we can see how our system of higher education will perhaps not fit this future well in which students are no longer preparing for jobs but instead learning how to monetize their assets.
If we continue to avoid change, the exponential future will not let up. We cannot simply will it to let up. Rather, we will see innovation blossom in other places, even though we ourselves may resist it. One striking example that the folks at SU mentioned was the work on gene editing that our laws in the U.S. prohibit, but that scientists in China are moving forward on full throttle. By opting out of the innovation, even in an area with plenty of thorny ethical issues, we cannot help steer the exponential transformation toward a better future.
The same goes for thinking about an exponential future of artificial intelligence. Recently, Google DeepMind's AlphaGo computer program beat the world’s best player in a game of Go. Ke Jie, its human contender, remarked: “Last year, it was still quite human-like when it played… But this year, it became like a god of Go.” In a linear mindset, we might dismiss the rapid evolution of AI. We might look at Alexa, Siri or chatbots and not be able to imagine how any of these innovations would ever replace a human-to-human interaction in a learning experience.
And here is where we return to Pepper and Pris. These two robots—two signals of the future—help us extrapolate into an exponential mindset in which artificial intelligence gets so good and integrates so well with robotics, that we can acknowledge the possibility of learning from a robot even though the technology is not quite there yet. We can at least perceive a drastically different future and not be filled with dread, scorn, or skepticism.
Rather, we can open ourselves up differently to the possibilities without confirming our negativity bias: What impact will this have on the future of teaching and learning? What will face-to-face mean in a robot-filled world? How will we build learning experiences that provide our students skills for a future that we can’t yet fathom?
