Towers of power

Wind turbines go to work 16 miles off the Rhode Island coast.

Offshore wind turbines seemed a bit, well, gimmicky to me until a few years ago when I saw a farm calmly spinning its blades as I flew home from Europe. Anything that keeps working in the North Sea is entirely real. Now they have arrived in 600-foot-form off the New England coast, as I saw last month in a trip to Deepwater Wind’s installation off Block Island (thanks, Noelle Swan and the New England Association of Science Writers!). These giant beasts won’t always be easy to maintain, as we saw watching a crew struggling to jump onto one tower from a support vessel in gentle six-foot swells from Hurricane Maria. The 240-foot blades are no favor to offshore birds. But Deepwater Wind seems to have made every reasonable effort to minimize and monitor the overall environmental impact of the turbines, as attested by the National Wildlife Federation scientist onboard our fast ferry. Ocean wind turbine technology is advancing rapidly, one example being the replacement of the traditional gearbox with a GE direct-drive permanent magnet generator, noted Willett Kempton of the University of Delaware’s ocean wind power program. Wind turbines can tap steady winds at sea, where they can be built much larger than on land, and a wealth of projects are planned along the U.S. east coast. Yes, they’re designed to survive hurricanes, although maybe not a problem like Maria. And although offshore wind still can’t produce power here as cheaply as fossil-fuel plants, European wind costs are already below that mark.

Public Spectacle

A beacon of hope in a changing climate.

kid Spectacle

On a clear hot August day you can take a ferry to Spectacle Island and walk a winding path up to its northern summit, admiring wildflowers and eating blackberries. The summit is the highest point of land on Boston Harbor, with low wooded islands scattered around.

Off to the east you can spot a windmill near the huge sludge-digesting eggs of Deer Island, and a second windmill a few miles south at the tip of the Hull peninsula. These two points of land bracket the entrance from Massachusetts Bay to the harbor’s inner archipelago.

One distant day, Deer Island and Hull also may anchor a massive sea barrier, holding off an ocean that’s now projected to climb as much as eight feet by 2100.

Today it’s hard to imagine how we might start to build such a Big Dike, given our current politics.

But you can also see hopeful signs on this Spectacle for our ability to clean up our own messes.

The first time I sailed past the island it was a garbage dump, with the remnants of a horse-rendering plant buried under many feet of still-smoldering refuse.

Now that’s all taken away and replaced by fill from the Big Dig. The island was reengineered and replanted. Rich ecosystems began to reappear. On summer days like this, children swim a stone’s throw away from the site of the old factories.

In wildness is the preservation of the world, as Thoreau said. But not just in wildness.

Working out

Okay, what really happens down the road to all our jobs?welcomeWe know that automation replaces many human jobs and generates many others, and that artificial intelligence will accelerate this creative destruction. Historically, the default view among business and technology leaders, supported mostly by hand-waving, is that this unstoppable march will bring a wealth of new jobs, if only the masses somehow can receive proper technological education.

It’s hard to assess the recent historical record on job loss versus gain, although today’s New York Times offers an interesting take. And while we can easily spot job losses, new jobs created by machines, “almost by definition, are harder to imagine,” as MIT economist Erik Brynjolfsson pointed out in a session at the American Association for the Advancement of Science (AAAS) annual meeting in Boston on Saturday.

But in the past couple of years the public discussion has grown more worried, with one dark perspective on implications well described in a poorly titled essay by Rutgers historian James Livingston.

At the AAAS session, Harvard computer scientist David Parkes presented some relevant thoughts from the 100 Year Study on Artificial Intelligence project. Here are a few quotes from the study’s report on AI and real life in 2030, published last September:

  • “AI will gradually invade almost all employment sectors, requiring a shift away from human labor that computers are able to take over.”
  • “To date, digital technologies have been affecting workers more in the skilled middle, such as travel agents, rather than the very lowest-skilled or highest skilled work. On the other hand, the spectrum of tasks that digital systems can do is evolving as AI systems improve, which is likely to gradually increase the scope of what is considered routine. AI is also creeping into high end of the spectrum, including professional services not historically performed by machines.”
  • “A spectrum of effects will emerge, ranging from small amounts of replacement or augmentation to complete replacement. For example, although most of a lawyer’s job is not yet automated, AI applied to legal information extraction and topic modeling has automated parts of first-year lawyers’ jobs. In the not too distant future, a diverse array of job-holders, from radiologists to truck drivers to gardeners, may be affected.”
  • “As labor becomes a less important factor in production as compared to owning intellectual capital, a majority of citizens may find the value of their labor insufficient to pay for a socially acceptable standard of living. These changes will require a political, rather than a purely economic, response concerning what kind of social safety nets should be in place to protect people from large, structural shifts in the economy. Absent mitigating policies, the beneficiaries of these shifts may be a small group at the upper stratum of the society.”
  • “Longer term, the current social safety net may need to evolve into better social services for everyone, such as healthcare and education, or a guaranteed basic income. Indeed, countries such as Switzerland and Finland have actively considered such measures. AI may be thought of as a radically different mechanism of wealth creation in which everyone should be entitled to a portion of the world’s AI-produced treasure.”

At another packed AAAS session, Alta Charo, professor of law and bioethics at the University of Wisconsin at Madison, gave a masterful quick summary of the history and findings of the report on human genome editing from the National Academy of Science. Released last week, this report’s recommendations drew plenty of public attention—far more than last fall’s AI in 2030 report, although AI will have much greater impact in the next decade or two or three.

An Engine for solving societal problems

MIT’s accelerator brings an incubator and funding to startups that matter.


“One of my frustrations as an academic is that over the last twelve years we’ve produced a lot of really useful methods and techniques, and almost none of them has been put into practice,” one prominent MIT professor told me earlier this year. “This is not an unusual problem for academics. But it’s frustrating to have things that you know could help and they’re not helping.”

Generating the intellectual property (IP) is only the very first step on the road to the real world. Established companies often are not very interested in IP, even game-changing IP. They are more likely to want prototypes, and people who know how to build the prototypes.

They want, in brief, to work with startups.

That’s one reason why this professor launched a startup. It’s also one reason why MIT actively spreads the entrepreneurial gospel to students and staff who might not have considered it a few years back, and keeps deepening its “environmental ecosystem” of competitions and advisory networks and resources like the Startup Exchange.

And it’s the thinking behind the Engine, the startup accelerator that MIT president L. Rafael Reif announced yesterday. The Engine will combine an incubator with funding for startups focused on real needs.

“When it comes to the most important problems humanity needs to solve — climate change, clean energy, fresh water and food for the world, cancer, and infectious disease, to name a few — there is no app for that,” as Reif explained in the Boston Globe. “We believe the Engine will help deliver important answers for addressing such intractable problems — answers that might otherwise never leave the lab.”

Venture capitalists do a reasonable job of funding many tech companies, but very few VCs are interested in startups that may take more than five years to pay off. The Engine won’t sponsor quick-turnaround firms, or companies that join the thundering herds of marketing middlemen, or oddities like the outfit that claims to deliver wine matched to your DNA.

Instead the funds might go to biotechs, like Oxalys, which do very well if they can even get their drug candidates into first clinical trials within a few years. Or makers of industrial products, like Dropwise’s energy-saving coatings for power plants, which manufacturers probably will adopt quite slowly because that’s how that industry works. Or any number of truly innovative, truly needed products and services.

It will take a decade or more to see how the Engine’s bets turn out. Many will fail. But these are bets we need.

The write stuffing


When I graduated from high school, all I really knew professionally was that I wanted to write on many topics. Last weekend when people at my high school reunion asked politely what I wrote about, I did find myself saying, many topics—in fact, way more now than when I worked as a staff journalist. Okay, I’m not covering the full human condition. Much of the universe is unexplored. But so far this year I’ve done stories about medical hackathons and crowdsourced scientific challenges, global data security and global financial crises (still separate topics so far!), drug development crises, the future of suburbia, steam power, gene therapyagricultural particulates, the challenges of small data in healthcare, chemical sensing on a chip, employee cross-trainingurban carbon dioxide release, jet engines, zebrafish brains, surgery by telemedicine and robotics manufacturing, among others.

Hackathon crowd control


Crowdsourced challenges are now an established part of the medical research ecosystem, especially for data analysis problems such as finding the best genomic analysis techniques or new ways to interpret mammography data. Writing a story about these competitions for Nature, I’ve been struck by the rapid spread of their most intense form: the medical hackathon.

Described today in a Science Translational Medicine review, these hackathons (or “datathons”) take place over a weekend or a few evenings, bringing together some mix of medical scientists and engineers, data scientists, clinicians, patients, medical entrepreneurs, public health advocates and other interested parties. Participants “are encouraged to collaborate, fail fast and iterate.”

Hundreds of medical hackathons have been held. Some encourage multiple groups to study the same clinical problem with the same data and compare conclusions. Other hackathons are all about idea generation. The events may target specific threats such as the Zika epidemic, or more general topics such as improved intensive care, or a free-for-all of unsolved medical problems.

Like software hackathons, the medical hackathon “integrates collaboration, idea generation, and group learning by joining various stakeholders in a mutually supportive setting for a limited period of time,” the STM authors say.

Key is the face-to-face mashup of expertise and views, which doesn’t come easily on the outside. “It is difficult to establish a platform for the realtime, respectful, and effective exchange of ideas among specialists who are usually separated by time, space, methods, attitudes, and terminology,” they point out.

This difficulty holds even for global crises like Zika. But hackathons around the world are addressing the rapidly spreading virus, among them one held at Massachusetts General Hospital earlier this month. Among the resulting proposals:

  • An app for crowdsourced mosquito surveillance data collection, with games
  • Larvicide automatic dispensers
  • A public health online rumor-squashing campaign
  • Hairnet-like nets to cover open water containers
  • Applying new diagnostic technology to detect the virus in pregnant women
  • A mosquito larva finder, with a microscope add-on to a smart phone that samples standing water, analyzes for type of larva and adds GPS location data.

As often with more established crowdsourcing competitions like the Dream Challenges, we don’t know which if any of these early results will be driven all the way into the clinic. But the promise is real.

The Seoul of a new innovation machine


South Korea’s spending on research and development is climbing up to 5% of its gross domestic product. That’s the highest rate in the world, almost twice that of the United States.

Writing a quick snapshot of Korean science for Nature, I keep coming across such striking contrasts.

Heightened R&D spending is one foundation for the push for a “creative economy” that President Park Geun-hye launched when she took office two years ago. A centerpiece of her agenda, this initiative aims to boost the creation of innovative products and services, especially by the smaller firms that often struggle for air in an economy dominated by giants such as Hyundai and Samsung.

The quest for a creative economy builds on many multi-year, multi-billion-US-dollar projects, among them the International Science and Business Belt. This hub for science, technology and business is now rising in Daejon, a city an hour south of Seoul by high-speed train that is already crammed with both government and industry research centers.

How well will these grand governmental top-down innovation programs pay off?

Well, who knows?

But I’m impressed by not just the scale but the speed of some of these bets.

One example comes from the Korea Advanced Institute of Science and Technology (KAIST), seen above. Launched in the 1970s as a kind of Korean version of the Massachusetts Institute of Technology, KAIST enrolls about the same number of students as MIT with a third the budget.

Like MIT, KAIST is investigating “flipped classrooms,” in which students watch lectures online and then go back and forth with professors and each other in the classroom—a more interactive alternative that seems to work well for fairly obvious reasons.

MIT has come up with quite wonderful technology for such teaching (supplying the platform for edX online courses). It’s going ahead with a few great courses and thoughtful research about optimizing the benefits thereof. But KAIST is adopting flipped classrooms much more quickly, planning to deliver no fewer than 800 such classes two years from now.