I was moderating a discussion among media leaders and young scientists at the World Economic Forum’s China meeting this year, when the Forum’s founder, Professor Klaus Schwab, made a surprise appearance. What he said was short and to the point: if science was important 30 years ago because it improved certain aspects of our lives, it is important now because it is changing who we are.
His message stuck with me. We need to understand science and technology like never before, because it has powers like never before. As I took in the many sessions at the meeting in Tianjin, four lessons about modern-day science and technology stood out. Here they are:
1. Genomics is changing how we fight disease
The Ebola outbreak is first and foremost a tragedy, but it is also a remarkable indication of how far genomics has come. In a session on recoding disease, Pardis Sabeti was able to show genetic mutations in the Ebola virus day by day, and to build a family tree of the virus showing which branches were infecting which regions of West Africa. The tree showed that most strains of the current outbreak separated from each other only 10 years ago, and that many of the current strains made their first appearance only in May. Sabeti’s team is able to move from frontline testing to a complete gene sequence within 10 days, using Illumina sequencing machines in Cambridge, MA. This information can then be relayed back to healthcare workers. Her data shows how long a virus has circulated in a population, even before becoming symptomatic, and can distinguish between Ebola and other viruses, such as Lassa fever.
Listening to her speak, I couldn’t help but feel that the curtain is being drawn back on the once-secret machinations of disease. Sabeti gave us a grand objective at the end of her talk: she wants Ebola to be “the last great outbreak in our history”. If her tools prove to be scalable, and the data well understood, they will help realize, not just this vision, but a new type of medical care, one that begins with data and analytics.
2. Healthcare is going to increasingly revolve around IT
Yonatan Adiri calls it the “democratization of healthcare” – giving the billions of people who don’t currently have access to basic healthcare services a chance to get it. His example is telling: a urinalysis dipstick costs $0.20 to buy, but the lab test costs $80 in the US. Instead of sending it to a lab, though, it’s possible to take a picture of the dipstick with a cell phone, and send the image to the cloud to be analysed. The approach would work wonders for healthcare in the developing world, where $80 is completely prohibitive. But assuming regulators and consumers accept it, might the same approach save the developed world a fortune too?
Adiri was pointing out a powerful feature of our technology landscape: the co-existence of highly sophisticated, widely distributed and very cheap technologies like those that are found in cell phones, with also sophisticated but restricted and expensive technologies like those often found in medical care. Combining these technology sets would do more than save money, it would enable healthcare consumers to own and interpret more of their own data. The dipstick is just one of many devices on the horizon that might be a part of this transformation. So too might ingestible sensor pills, home heart-attack monitors, glucose-sensing contact lenses, and the bandwidth and cloud-computing power to process all of the data these produce. As Sabeti’s talk suggested, in the future, a visit to the doctor may well revolve around data as much as symptoms.
3. Modern researchers must negotiate between pure and applied science
At the Tianjin meeting, multiple researchers in both private and public settings expressed their discomfort with needing to present or invent short-term applications of their research in order to obtain funding. One researcher told a crowded room that he needs to copy and paste buzzwords from granting agency documents into his proposals for them to be approved. Another researcher said the modern-day emphasis on applied research and short-term results tends to create hype; also that the best device applications usually appear on their own, and are often not what was expected. (I couldn’t help but think of the classic example of the laser, which just after its invention was dismissed as a solution to a problem that did not exist.) Participants at the meeting also referenced evidence that research output supported by open-ended grants (with less focus on application) produces twice as many high-impact papers as application-focused grants.
This was half of the equation. I got a sense of the other half while listening to executives and administrators from Singapore, China, Japan and the EU describe the economic importance of science for their countries and institutions. They explained that an increasing portion of science funding came from the private sector, which surely must strengthen the applied focus of research dollars. Surprisingly, in China, over 70% of R&D is conducted in the private sector.
The question then, is how do we ensure that fundamental, open-ended research maintains its independent role in a funding environment where leaders expect reliable economic returns? Is there the political will to defend expensive, long-term science with no clear economic motivation?
4. Let robots make mistakes
We often think of robots as instruments of precision, operating in environments – like factories – where the ideal error rate is zero. But we also expect robots to (eventually) be able to perform much more complex tasks. Manuela Veloso, professor of Robotics at Carnegie Mellon University, described the moment she realized that her robots needed to be allowed to make mistakes and get stuck. Instead of yet another sensor array or CPU, she decided to give them the flexibility of not knowing what to do. This struck me as a kind of research-derived wisdom. After all, making mistakes is eminently human, and so is negotiating complex situations. Shouldn’t a robot be given the same latitude as we give ourselves?
The result is Veloso’s so-called CoBot robots, which roam around the CMU campus and ask for help when they get stuck, whether from a passerby (“Can you please press the elevator button?”) or from a member of her lab, whom they can email. She has also programmed them to perform web searches. Veloso calls this “symbiotic autonomy”. So far, CoBots have travelled more than 1,000km around the halls of CMU.
While these were the particular points from Forum sessions that stayed with me most strongly, I was also left with a broader and more general impression from the conference. What a remarkable, energetic and engaged group of people the Forum had assembled in Tianjin. More than any idea or development I heard at the conference, it is the people I met – from students to leaders of government research bodies – that give me optimism that we can understand and steer our accelerating technological pace.
Author: Michael Segal is editor-in-chief of Nautilus, USA, and acted as a Topic Champion at the 2014 Annual Meeting of the New Champions in Tianjin, China
Image: A robot from Android FC, a three-robot soccer team from the School of Infomatics at the University of Edinburgh, shows off its skills during a photocall for their upcoming show in the Edinburgh International Science Festival in Edinburgh, Scotland April 1, 2010. REUTERS/David Moir