Wednesday, June 12, 2013

A tech arms race is pitting states against their citizens

http://www.ft.com/cms/s/0/877ae448-d283-11e2-88ed-00144feab7de.html#ixzz2W1Sj4jW3

A tech arms race is pitting states against their citizens

Communications revolution empowers the people; big data protects authorities, says Ian Bremmer

A generation ago, autocrats could still hope to maintain control of information within their countries and to limit the ability of citizens to communicate with one another and the outside world. Today, people carry gadgetry that allows them to send ideas hurtling across borders, to connect with one another as never before.

Satellite television, mobile phones with cameras, Facebook, YouTube and Twitter have empowered the individual. Recent headlines remind us that the state is developing new tools of its own. But the decision by former US Central Intelligence Agency employee Edward Snowden to expose the National Security Agency’s data dragnets demonstrates that state-sponsored surveillance may prove as difficult a secret to keep as any other in an open society.

A battle has now been joined. China still uses its “great firewall”, a system designed to monitor and filter internet traffic, but even the hardest of hardliners knows that China’s online conversation is expanding much faster than Beijing’s ability to manage it. Russian, Saudi and Iranian officials try to censor but they cannot return to the day when most messages with political content were broadcast from a regime-run radio or TV tower.

So states are learning that management of communications traffic need not depend only on censorship. It is more effective to use the flow of information than to block it, and governments are countering the revolution in communication technology with a “data revolution” that allows officials to move from defence to offence in their battle with perceived threats.

In short, the traffic data and content produced by the world’s emails, online searches and purchases, and the electronic signatures from all those texts and tweets, can be aggregated in real time. Those with access to that data – and the technology to use it – have captured something valuable.

Our use of online technology – whether for storage, communications or commerce – reveals more of who we are, what we think and what we want. Providing those who treat us as consumers with so much data can compromise our privacy. As the 2012 US presidential election proved, when both sides used it to identify potential voters, big data has now become an essential element of sophisticated political campaigns.

But it is a different matter when that information is passed to states, to those who think of us as voters, opinion-makers or troublemakers.

There is nothing inherently evil about big-data analysis. It can help bureaucrats meet the needs of citizens. It can help with the design of systems that improve public health, help street traffic flow more freely, target infrastructure investment, fight crime and protect national security. But who draws the line between activists and criminals? Or terrorists? Or potential terrorists?

Each government will use this material in its own way. There will be differences of opinion on how this information should be used, but all are vulnerable to abuses of power. As states become more deeply involved in data collection, officials will want maximum control of everything they think might be relevant for (what they consider) national security, in particular.

Google has endured multiple attacks on the Gmail accounts of suspected dissidents inside China, attacks engineered (or, at least, condoned) by Chinese authorities. But, as the NSA surveillance disclosures remind us, all governments are analysing data to protect against all sorts of threats.

Around the world, the race is on between a communications revolution that empowers the individual and a data revolution designed to protect the state. This contest will play out in different countries in different ways. Not all will prove effective in harvesting data; some will perform as poorly here as in other areas of governance.

But larger and more efficiently run governments will have much more success. We can’t yet know how this race will end, but it is a mistake to assume the state can’t hold its own for years to come. We can say with complete confidence that this competition has only just begun.

The writer is president of Eurasia Group and author of ‘Every Nation for Itself: Winners and Losers in a G-Zero World’

 

WSJ: A Revolution in the Making

  • JOURNAL REPORTS
  • Updated June 10, 2013, 1:15 p.m. ET

A Revolution in the Making

Digital technology is transforming manufacturing, making it leaner and smarter—and raising the prospect of an American industrial revival

By JOHN KOTEN

On a dark and stormy night two weeks ago in Schenectady, N.Y., Ken Hislop was relaxing at home when his cellphone suddenly began buzzing in his pocket. It was an urgent text message—from the General Electric Co. factory where he works.

Soon, a second message arrived. And then another, and another. The texts were being sent by tiny sensors embedded inside a series of machines, some of which look like enormous upside-down cement mixers. A violent thunderstorm passing through the area had caused something to go wrong.

"I knew right away we'd lost power at the plant," says Mr. Hislop, a manufacturing engineer. He quickly switched on his iPad and accessed animated schematic maps that signaled everything happening at the $170 million facility, which makes massive batteries for things like cellphone towers and power plants. Though the outage had been momentary, much of the equipment at the factory had to, in effect, reboot, and any blip could mean costly lost production time.

 

Ryan Etter

"I was getting a first-person, real-time account," says Mr. Hislop, who also could watch video of the storm from the plant's roof. The information allowed him to ensure that the machinery restarted in proper sequence and that the sensitive battery material hadn't been damaged.

Welcome to the New Industrial Revolution—a wave of technologies and ideas that are creating a computer-driven manufacturing environment that bears little resemblance to the gritty and grimy shop floors of the past. The revolution threatens to shatter long-standing business models, upend global trade patterns and revive American industry.

Impacts Big and Small

For big companies, it means a swath of new tools to build smarter, leaner factories and explore innovative new products, materials and techniques that weren't possible before. And thanks to plummeting prices, small companies have access to better, cheaper manufacturing equipment and design tools—giving even one-person startups the chance to create market-shaking innovations. Many people liken the era we're in to the early days of computing, where upstart hobbyists in their garages came up with huge advances that changed the industry. (See "Build a Better Mousetrap—Fast."

"Manufacturing is undergoing a change that is every bit as significant as the introduction of interchangeable parts or the production line, maybe even more so," says Michael Idelchik, who heads up advanced technologies at GE's global research lab, located about 15 minutes away from the battery plant. "The future is not going to be about stretched-out global supply chains connected to a web of distant giant factories. It's about small, nimble manufacturing operations using highly sophisticated new tools and new materials."

There's no question that a coinage like the New Industrial Revolution sounds magisterial, given the profound impact that the original Industrial Revolution had not just on business but on living standards around the world. And there's also no question that for all the big talk and big forecasts, many things will go on being produced using techniques that were all but perfected long ago.

But the big label is far from unwarranted. The upheaval, still in an early stage, is accelerating now thanks to the convergence of a number of trends: the low cost and accessibility of Big Data associated with cloud computing; the plummeting cost of electronic sensors, microprocessors and other components that can be used to make machines more adept; and advances in software and communications technology that make it possible to manage manufacturing with a whole new level of precision and enable new forms of collaboration.

A new wave of supercheap electronic sensors, microprocessors and other components means that facilities like Mr. Hislop's need almost no human help to do their jobs and can collect huge amounts of data along the way. Managers can get instant alerts about potential problems or study the numbers to find ways to boost efficiency and improve performance.

Related Video

The 3Doodler is a 3-D printer attached to a pen that quite literally lets you make three-dimensional doodles. Designed as a toy, it is being sought after by everyone from architects to the sight-impaired community.

Flexible Fabricating

At the same time, technological advances now allow manufacturers to invent new ways of fabricating things that represent an extreme departure from the classic production-line model. By far the most significant of these steps forward is additive manufacturing—a process of making a three-dimensional object of virtually any shape from a digital model.

These exotic machines can use a range of materials—everything from wood pulp to cobalt—and create things as varied as sneakers, fuel nozzles for airplanes and, ultimately, even human organs. And a single piece of manufacturing equipment, rather than being custom-designed to perform a single function, can be programed to fabricate a virtually limitless array of objects.

And, of course, that includes making more machines. On a tour of a laboratory of advanced manufacturing equipment that Autodesk Inc. is building on a pier in downtown San Francisco, Chief Executive Carl Bass points to some masking tape on the ground that marks the spot where a sophisticated computer-controlled milling machine will be housed.

"The Japanese company Mori Seiki is making that in Sacramento in an automated factory," says Mr. Bass, whose company creates computer-aided-design software. "The factory is so advanced that you almost don't need to turn on the lights because the machines are doing everything, and what they are making is other machines." In fact, a 3-D printer has replicated itself at a university in England.

Still, manufacturers will have to navigate big new challenges in this era, too. For one thing, because additive manufacturing works from digital models of objects, companies are much more vulnerable to intellectual-property theft—the same way that easily copied music and movies have shaken the entertainment business.

The Sole of a New Machine

To get an up-close look at how the new technologies are already disrupting the old ways of doing things, consider Nike Inc.'s Flyknit shoe.

 

Nike

An upper for Nike's Flyknit shoe.

As high tech as some sneakers may be in materials and appearance, almost all of them are still made on assembly lines that put a shockingly heavy emphasis on human labor. Workers sit side by side in enormous facilities, cutting material and stitching and gluing shoe components together. But, starting last year, Nike began making the Flyknit a whole new way.

The company's engineers modified a machine used to make sweaters into a shoe-making contraption that knits the entire upper portion of the shoe in a single cocoon-like piece that is then attached to the tongue and to the sole. As the shoe is stitched, proprietary software instructs the machine to alter the materials being used—a bit more polyester thread here, a bit more there—to add strength or flexibility where needed.

 

Bespoke Products

A Bespoke Products leg.

Most important, it makes all these refinements at no added cost. The technology allowed Nike to make a shoe with just a few parts instead of dozens and with up to 80% less waste. "The Nike Flyknit is the world's first mass-produced consumer product made using additive manufacturing," says Maurice Conti, director of strategic innovation at Autodesk, which worked with Nike on the Flyknit project. "It's a hugely significant advance, not the least because, once you start doing things this way it obviously takes a lot of the labor cost out of the equation."

The implications for this are as obvious as they are profound: Almost seemingly out of the blue, the reason for making shoes in low-wage countries begins to evaporate and the advantages of locating the machine closer to the customer—in part for faster delivery—begin to loom much larger. Already, Adidas AG is knitting a shoe, the Primeknit, in its home country, Germany.

Last year, Boston Consulting Group published a report predicting that as much as 30% of America's exports from China could be domestically produced by 2020. President Obama gave a nod to this hope in his State of the Union address in February when he said that the popular additive-manufacturing technique called 3-D printing "has the potential to revolutionize the way we make just about everything."

Last year the president proposed a $1 billion addition to his fiscal 2013 budget to create a network of as many as 15 manufacturing-innovation institutes around the country. One is already up and running in Youngstown, Ohio, the setting of the Bruce Springsteen song about the rise and fall of the steel industry. Three more are in the works under the supervision of the Department of Energy and the Defense Department. Congress has yet to approve spending for the others.

Not So Fast

But the jury is out on whether a boost in manufacturing will create a resurgence in U.S. manufacturing employment, which peaked at around 19.5 million in 1979 and today totals around 12 million, according to the Bureau of Labor Statistics. (Economists attribute the recent modest increase in U.S. manufacturing employment to a rebound in the business cycle, and have found no evidence yet of an employment rebound connected to advanced manufacturing or the return of jobs from overseas.)

Almost certainly, it won't mean creating jobs the old way—building large factories that employ thousands of people. The real opportunity is in the growth of highly specialized, highly advanced microfactories and in legions of small entrepreneurial ventures making old things in new ways, as well as producing new products and custom-made items. An important sign of the times: the largest U.S. maker of 3-D printers, 3D Systems Corp., introduced a slick push-button model for $1,299 last year—putting it within range of the smallest businesses and home users. Kits to make a printer powered by software from the open-source RepRap project run as low as $400.

Experts envision bike shops that print custom frames and assemble bikes on demand; made-to-order shops or websites that offer one-off or personally designed jewelry; and more sophisticated production shops that crank out all manner of high-end products. Already, a company called Bespoke Products, a unit of 3D Systems, is making artificial limbs. Another, Organovo Holdings Inc., is using 3-D printing to create human tissue for use in medical labs. At a recent conference, the company showed off a piece of raw meat it had made in a printer. Over time, this "democratization of manufacturing," as some refer to it, is expected to accelerate, and one day could mean that your local auto dealer or maybe even your neighbor (or you) will be able print out a replacement part for your car or make you a new cup holder sized perfectly for that enormous thermos you carry around.

New Ways of Making

Additive manufacturing may bring other changes that are just as dramatic as "factories" run out of somebody's garage. Additive manufacturing makes it possible to create designs or structures that weren't feasible using the two traditional ways of making things: milling (sculpting material out of a solid block) and casting (pouring liquid material that hardens into a mold). Both of these techniques are greatly enhanced by mass production because quality typically rises and costs fall as volume increases. Making a lot of something also means it's not so painful to discard defective units.

Advanced Architecture with Joris Laarman Lab

Mataerial, a prototype 3-D printer that can make curved objects.

But additive manufacturing enables the creation of materials with multiple parts and moving components without assembly. And because the process is entirely controlled by computers, following precise digital instructions, the very first piece that's manufactured is just as good as the last one. The incremental cost of producing a part becomes strictly a function of time and materials.

All of which means manufacturers can scan further afield for inspiration. Designers and engineers at General Electric have begun looking at ancient objects and prehistoric bird skeletons, and delving anew into topology, for inspiration on new forms of design. Their thinking: Centuries of making things under the constraints of old methods may have caused their predecessors to discard innovative structures simply because there was no practical way to produce them through milling or casting. But what was impractical in the past may be quite feasible today.

There's another big change playing out that isn't so obvious but could have a huge impact on the world of manufacturing. The rise of the 3-D printer has coincided with the digitization of the physical world through the use of 3-D scanners and, increasingly, two-dimensional photos that can be stitched together digitally using software to create precise 3-D renditions of anything made of atoms.

That affects everyone who works with manufacturers and who participates in the creative process: designers, engineers, materials specialists, machine makers and supply managers, among others. It's much easier to collaborate on a model if it is stored on a computer, because lots of digital hands can be working on it at the same time.

"The big untold story in all of this is the way the digitization of manufacturing compresses everything—from the early design of a product to its final assembly," says Ping Fu, who founded a company called Geomagic that makes 3-D modeling software and is now in charge of strategy at 3D Systems. "Everyone can now work together simultaneously. The software makes it possible, and you get much better results than when all of these activities were being done in different silos."

Still, this new environment leaves manufacturers facing big new challenges, as digital files of physical objects show up in huge numbers on websites like Thingiverse and Physibles, and manufacturing instructions appear online, too.

"I give a lot of speeches about this topic to manufacturing groups, and people are usually quiet during the Q&A," says Christine Furstoss, who oversees a staff of 450 engineers and scientists working on materials, energy strategy and processing technology at GE's research center. "But afterward, they come up to me in private and want to talk about how frightened they are. People get a glimpse of how this could change the game in their business, and they are just not sure what to do about it."

The Road Forward

For an idea of how the New Industrial Revolution might play out on a large scale, look at GE. Its footprints are everywhere in the advanced-manufacturing community. It is a highly visible participant in the federal government's efforts to boost additive manufacturing, as well as university programs focusing on the topic. Partners include the Massachusetts Institute of Technology, Amazon.com's Web-services department and the Defense Advanced Research Projects Agency, which are collaborating with GE on a new crowdsourcing platform for product design and development.

General Electric

High-tech batteries from GE.

The company also is latching onto the technique in-house. For instance, it is making a big bet on additive manufacturing as a way to create engine parts that weigh less, cost less and employ more intricate designs. Last year, it bought one of the largest additive manufacturers in the U.S., Morris Technologies, and plans to use the company to make the sophisticated fuel nozzle for its next-generation jet engine, the LEAP. (The Morris family has a long industrial pedigree: It once supplied steel tubing to the Wright Brothers' bicycle shop.)

The new nozzle will be 3-D printed as a single part rather than assembled from 18 pieces, and it will be up to five times more durable. GE is also running its own 3-D metal printers, testing the procedure out on as many parts as possible for both the LEAP and the GE 9x, its next-generation 777 engine. This week, GE plans to announce a major investment in an another new additive-manufacturing factory that will mass-produce ceramic engine shrouds.

All told, the company projects it will spend $3.5 billion on aviation-related advanced manufacturing in the next five years and will produce 100,000 end-use parts for its engines annually by 2020 using additive techniques.

One of GE's most creative initiatives is an arrangement that will begin to make its more than 30,000 patents available to inventors and entrepreneurs who use the website Quirky—which employs crowdsourcing to evaluate ideas for products. "It's a whole new paradigm for innovation," says Ben Kaufman, the founder of Quirky, an industrial-design company in New York.

Starting this month, inventors and their ilk will be able to sift through the first 200 of GE's patents posted on Quirky, with more than 1,000 expected to be available by the end of the year. People who think they can use the technology without infringing on GE's own use will be able to click a button and begin a process enabling them to license use of the patent for whatever application they've dreamed up.

GE's efforts also offer a look at how data can be leveraged in this new era. One of the take-aways from a visit to GE's battery plant back in Schenectady, located adjacent to a parcel that housed Thomas Edison's machine works, is the sheer volume of data it generates—information that allows plant engineers to continually improve the production process and head off problems before they become serious.

The company can trace a product's entire genealogy, from containers of dirt, sand and salt to a bank of high-tech batteries supporting a nation's electric grid. The data not only improve quality control—if a defect shows up at any point, GE can trace it back to its original source—but in the end give GE a powerful competitive weapon that's virtually impossible to duplicate.

The Schenectady plant, nestled in a valley alongside the Mohawk River, is so extensively networked and connected, in fact, that it might just as easily be thought of as a single machine rather than a collection of them. And, of course, because it is so automated, it doesn't require a whole lot of human assistance. GE's Schenectady campus once had so many employees it was given its own ZIP Code, 12345. Yet even when it reaches full production—GE expects its output to exceed $1 billion in annual sales by 2020—the showcase battery plant won't employ more than 450 people.

Mr. Hislop, who confesses to using his iPad to check in on the factory during a recent camping trip, describes his experience on the night of the storm in the tones of an anxious parent. Yet in the midst of the howling winds and thunderclaps, the technology meant he could remain intimately in touch with everything that was happening across town. Despite the beating the plant was taking, he says he felt "reassured."

Mr. Koten is a columnist for WSJ.Money magazine in New York. He can be reached at reports@wsj.com.

A version of this article appeared June 11, 2013, on page R1 in the U.S. edition of The Wall Street Journal, with the headline: A Revolution In the Making.

 

Tuesday, June 11, 2013

Big Data Is Not Our Master

Big Data Is Not Our Master

Humans create technology. Humans can control it.

http://www.newrepublic.com/node/113436/print

We’ve known for a long time that big companies can stalk our every digital move and customize our every Web interaction. Our movements are tracked by credit cards, Gmail, and tollbooths, and we haven’t seemed to care all that much. 

That is, until this week’s news of government eavesdropping, with the help of these very same big companies—Verizon, Facebook, and Google, among others. For the first time, America is waking up to the realities of what all this information—known in the business as “big data”—enables governments and corporations to do. 

Whether it requires a subpoena or a warrant, if government truly wants to identify your physical location, which friends you talk to, or what you have recently purchased, the revealing data is all readily available. The NSA’s overly broad interpretation of the Patriot Act suggests that government agencies will interpret the law as aggressively as necessary to get their job done.

We are suddenly wondering, Can the rise of enormous data systems that enable this surveillance be stopped or controlled? Is it possible to turn back the clock?

Technologists see the rise of big data as the inevitable march of history, impossible to prevent or alter. Viktor Mayer-Schönberger and Kenneth Cukier’s recent book Big Data is emblematic of this argument: They say that we must cope with the consequences of these changes, but they never really consider the role we play in creating and supporting these technologies themselves.

Larry Page just last week shrugged off concerns about Google Glass—a set of eyeglasses that can deploy facial identification or silently take pictures of everyone around you—as inevitable. "Obviously, there are cameras everywhere," Page said at his shareholder meeting, implying that because iPhone cameras exist, the next technology that enables silent, surreptitious photography is the inevitable next step.

But these well-meaning technological advocates have forgotten that as a society, we determine our own future and set our own standards, norms, and policy. Talking about technological advancements as if they are pre-ordained science erases the role of human autonomy and decision-making in inventing our own future. Big data is not a Leviathan that must be coped with, but a technological trend that we have made possible and support through social and political policy.

Unfortunately, this teleological approach to technology isn’t just a recent phenomenon. The clearest example of Silicon Valley mistaking scientific law for sociological trend dates from a 1965 paper discovering Moore’s “law.” According to its author Gordon Moore, co-founder of Intel, the number of transistors on integrated circuits doubles approximately every 18 months. 

Or is it every two years? Moore corrected his initial prediction in 1975, revising it to claim doubling every two years. Or is it even longer? A 2010 update to the law predicts it will slow to every three years beginning at the end of 2013. 

Among academics, there is consensus that the word “law” is a misnomer, since it isn’t clear if the advancement is driven by economics, corporate policy, or some other factor. To posit that the growth is driven by the nature of technology itself would ignore the economic, social, and political backdrop on which the innovation occurs. Craig Barrett, the former CEO of Intel, said in a talk earlier this year that Moore’s law was more of a strategic plan for Intel than a scientific law.

The “laws” of Silicon Valley are, in fact, not laws at all, but breakthroughs that we make possible. Europe is in the midst of debating its own approach to privacy and is considering a fundamental “right to be forgotten” law. Technology may continue to grow and become more complex, but that need not preclude debate—and potentially legislation—about how it can and should be used.

The security and privacy crises that have unfolded over the past week are the perfect moment for us to ask ourselves what public policy we should adopt not only to limit the government’s ability to mine data, but the ability of technological systems to store and process this data in the first place.

We do not need to live in a society where photos can be silently taken by a pair of eyeglasses or conversations can be overheard by a stranger across the room. We don’t need to live in a world where government or commercial satellites might peer into our homes at any moment without request. These are still hypothetical advancements, but for how long?

Source URL: http://www.newrepublic.com//article/113436/chris-hughes-nsa-leaks

Friday, June 7, 2013

Washington Post: The next big national intelligence debate

 

http://www.washingtonpost.com/blogs/innovations/wp/2013/06/07/silicon-valley-through-the-nsa-prism/


The next big national intelligence debate

By Vivek Wadhwa, Updated: June 7, 2013

My iPhone keeps track of everywhere I go and everyone that I call. It knows when I sleep, when I wake, and how active I am. It has the names and numbers of all of my friends and access to all of my emails, social networks, and even to the health information collected by apps that I’ve installed.

Google has a one-up on my iPhone. It reads my emails before I do and knows what I am thinking by analyzing what I search for on the Internet and which Web sites I visit. It “knows” what other people think about me. If my friend and noted futurist Ray Kurzweil succeeds in his mission at Google, it will also understand my wants and needs. It will be able to predict what I want to search for, where I want to go, and what I want to eat. It will understand how my brain thinks and know me better than my wife does.

Apple and Google would make Big Brother jealous. Yet we voluntarily offer these companies, and others, our deeply personal information because it makes our lives better.

We can debate whether government access to our phone records and web data is making us safer or obliterating our civil liberties.  But the reality is that in the tech era, which we have already entered, what we used to think of as privacy is becoming a relic.

Before we know it, products like Google Glass will record everything we see and hear. Expect cameras and sensors to be everywhere in public places and office buildings and on drones. Face recognition technology will identify and track us.

Even our appliances will be connected to the Internet and “talk” to each other. Speaking at and In-Q-Tel event last year, CIA Director David Petraeus said:

 

Items of interest will be located, identified, monitored, and remotely controlled through technologies such as radio-frequency identification, sensor networks, tiny embedded servers, and energy harvesters—all connected to the next-generation Internet using abundant, low cost, and high-power computing—the latter now going to cloud computing, in many areas greater and greater supercomputing, and, ultimately, heading to quantum computing. In practice, these technologies could lead to rapid integration of data from closed societies and provide near-continuous, persistent monitoring of virtually anywhere we choose.

In other words, there will be nowhere to hide. There will be all sorts of data collected about us from many sources.

The real debate we need to have centers around what is being done with these data. We will readily allow Google to track our searches, learn our likes and dislikes, and incorporate the advice of our friends so that it can recommend where we travel or what restaurants we choose. But should these data also be used to market to us? Should Google be allowed to share our data with third parties—and governments? And then the bigger question: how do we reign in government? We can’t stop the gathering of data, but we can surely limit its use. We can also put limits on the time that tech companies and governments are allowed to keep these data.

That is the real battle that needs to be fought.

I personally worry less about data that I know is being collected than what is being collected surreptitiously. Hackers, for example, who have the ability to turn on the camera and microphone on our computers without our knowing it. The Chinese government is hacking into government and corporate networks to download every piece of information that it can. The data that the U.S. government is gathering is likely being used to protect the public and many tragedies may have been prevented. But the Chinese are using our data to give their companies a competitive edge and find ways to disable the U.S. infrastructure. Organized crime is reaping billions by hacking banks and robbing from individuals. That is what terrifies me more than U.S. government snooping.

Vivek Wadhwa is Vice President of Innovation and Research at Singularity University and Arthur & Toni Rembe Rock Center for Corporate Governance at Stanford University. His other academic appointments include Harvard, Duke and Emory Universities as well as the University of California Berkeley.

READ: Files show U.S. mining Internet data; firms deny giving access

 

Saturday, June 1, 2013

NYT: Techs and the City

Techs and the City

By ALEC APPELBAUM
http://www.nytimes.com/2013/06/02/opinion/sunday/the-limits-of-big-data-in-the-big-city.html?pagewanted=print
 

THIS spring New York City is rolling out its much-ballyhooed bike-sharing program, which relies on a sophisticated set of smartphone apps and other digital tools to manage it. The city isn’t alone: across the country, municipalities are buying ever more complicated technological “solutions” for urban life.

But higher tech is not always essential tech. Cities could instead be making savvier investments in cheaper technology that may work better to stoke civic involvement than the more complicated, expensive products being peddled by information-technology developers.

Of course, you’d never hear such an idea from the likes of I.B.M., which has plastered airports with ads about how its consultants help municipalities cut costs with its “Smarter Cities” analytics platform, or Cisco, which has teamed with Toyota and other companies to sponsor annual conferences about how to automate cars and gather information on urban activity through streetlight-mounted sensors. For these companies, the more complicated the technology, the more cities can save — aside, of course, from the eye-popping price tags of the technology itself.

To be sure, big tech can zap some city weaknesses. According to I.B.M., its predictive-analysis technology, which examines historical data to estimate the next crime hot spots, has helped Memphis lower its violent crime rate by 30 percent.

But many problems require a decidedly different approach. Take the seven-acre site in Lower Manhattan called the Seward Park Urban Renewal Area, where 1,000 mixed-income apartments are set to rise. A working-class neighborhood that fell to bulldozers in 1969, it stayed bare as co-ops nearby filled with affluent families, including my own.

In 2010, with the city ready to invite developers to bid for the site, long-simmering tensions between nearby public-housing tenants and wealthier dwellers like me turned suddenly — well, civil.

What changed? Was it some multimillion-dollar “open democracy” platform from Cisco, or a Big Data program to suss out the community’s real priorities? Nope. According to Dominic Pisciotta Berg, then the chairman of the local community board, it was plain old e-mail, and the dialogue it facilitated. “We simply set up an e-mail box dedicated to receiving e-mail comments” on the renewal project, and organizers would then “pull them together by comment type and then consolidate them for display during the meetings,” he said. “So those who couldn’t be there had their voices considered and those who were there could see them up on a screen and adopted, modified or rejected.”

Through e-mail conversations, neighbors articulated priorities — permanently affordable homes, a movie theater, protections for small merchants — that even a supercomputer wouldn’t necessarily have identified in the data.

The point is not that software is useless. But like anything else in a city, it’s only as useful as its ability to facilitate the messy clash of real human beings and their myriad interests and opinions. And often, it’s the simpler software, the technology that merely puts people in contact and steps out of the way, that works best.

Even San Francisco, one of the most technophilic towns in America, understands the limits of “smart city” technology. It has a chief information officer, Jay Nath, and sponsors “hackathons” to develop software to, say, bring more fresh produce to the underserved Central Market area. But Mr. Nath talks proudly of how San Franciscans helped retool taxi-dispatch systems by meeting in person. “We decided to do an ‘unhackathon,’ ” he told me. “And we had about 100 people from our community” at the meeting.

“Technology doesn’t walk into a room and take over everything,” San Francisco’s mayor, Edwin M. Lee, said last year. “It has to be combined with a spirit that people from all skill sets can solve problems that government over the years has kind of done in silos.”

Indeed, some high-tech solutions being offered to cities run roughshod over urban values. Cisco is marketing cafe-like spaces in residential neighborhoods where creative workers can telecommute to their offices, using powerful communications technologies unavailable to the average home. Take that logic to its limit, and only low-wage workers whose employers can’t afford the jazzed-up satellite sites will actually show up, physically, for work.

That’s because the answers that make cities run more smoothly only inadvertently end up being the ones that make cities run more equitably. Deep data can learn and display policy cues that used to flow from guesswork. What it can do less reliably is reflect democratic action.

For that, you need more people discussing issues with more equal information and franchise. And that can most easily come from decidedly low-tech, but widely accessible, technologies like Facebook pages and e-mail chains. After all, cities don’t have to buy “smart” software to get smarter.

Alec Appelbaum, who teaches at Pratt Institute, writes frequently on urban planning and design.

 

The Dictatorship of Data

From MIT Technology Review

The Dictatorship of Data

Robert McNamara epitomizes the hyper-rational executive led astray by numbers.

Why It Matters

Data can mislead as well as inform.

Part of our Business Report:

Big Data Gets Personal

Data science and personal information are converging to shape the Internet’s most powerful and surprising consumer products.

 

Big data is poised to transform society, from how we diagnose illness to how we educate children, even making it possible for a car to drive itself. Information is emerging as a new economic input, a vital resource. Companies, governments, and even individuals will be measuring and optimizing everything possible.

But there is a dark side. Big data erodes privacy. And when it is used to make predictions about what we are likely to do but haven’t yet done, it threatens freedom as well. Yet big data also exacerbates a very old problem: relying on the numbers when they are far more fallible than we think. Nothing underscores the consequences of data analysis gone awry more than the story of Robert McNamara.

McNamara was a numbers guy. Appointed the U.S. secretary of defense when tensions in Vietnam rose in the early 1960s, he insisted on getting data on everything he could. Only by applying statistical rigor, he believed, could decision makers understand a complex situation and make the right choices. The world in his view was a mass of unruly information that—if delineated, denoted, demarcated, and quantified—could be tamed by human hand and fall under human will. McNamara sought Truth, and that Truth could be found in data. Among the numbers that came back to him was the “body count.”

McNamara developed his love of numbers as a student at Harvard Business School and then as its youngest assistant professor at age 24. He applied this rigor during the Second World War as part of an elite Pentagon team called Statistical Control, which brought data-driven decision making to one of the world’s largest bureaucracies. Before this, the military was blind. It didn’t know, for instance, the type, quantity, or location of spare airplane parts. Data came to the rescue. Just making armament procurement more efficient saved $3.6 billion in 1943. Modern war demanded the efficient allocation of resources; the team’s work was a stunning success.

At war’s end, the members of this group offered their skills to corporate America. The Ford Motor Company was floundering, and a desperate Henry Ford II handed them the reins. Just as they knew nothing about the military when they helped win the war, so too were they clueless about making cars. Still, the so-called “Whiz Kids” turned the company around.

McNamara rose swiftly up the ranks, trotting out a data point for every situation. Harried factory managers produced the figures he demanded—whether they were correct or not. When an edict came down that all inventory from one car model must be used before a new model could begin production, exasperated line managers simply dumped excess parts into a nearby river. The joke at the factory was that a fellow could walk on water—atop rusted pieces of 1950 and 1951 cars.

McNamara epitomized the hyper-rational executive who relied on numbers rather than sentiments, and who could apply his quantitative skills to any industry he turned them to. In 1960 he was named president of Ford, a position he held for only a few weeks before being tapped to join President Kennedy’s cabinet as secretary of defense.

As the Vietnam conflict escalated and the United States sent more troops, it became clear that this was a war of wills, not of territory. America’s strategy was to pound the Viet Cong to the negotiation table. The way to measure progress, therefore, was by the number of enemy killed. The body count was published daily in the newspapers. To the war’s supporters it was proof of progress; to critics, evidence of its immorality. The body count was the data point that defined an era.

McNamara relied on the figures, fetishized them. With his perfectly combed-back hair and his flawlessly knotted tie, McNamara felt he could comprehend what was happening on the ground only by staring at a spreadsheet—at all those orderly rows and columns, calculations and charts, whose mastery seemed to bring him one standard deviation closer to God.

In 1977, two years after the last helicopter lifted off the rooftop of the U.S. embassy in Saigon, a retired Army general, Douglas Kinnard, published a landmark survey called The War Managers that revealed the quagmire of quantification. A mere 2 percent of America’s generals considered the body count a valid way to measure progress. “A fake—totally worthless,” wrote one general in his comments. “Often blatant lies,” wrote another. “They were grossly exaggerated by many units primarily because of the incredible interest shown by people like McNamara,” said a third.

The use, abuse, and misuse of data by the U.S. military during the Vietnam War is a troubling lesson about the limitations of information as the world hurls toward the big-data era. The underlying data can be of poor quality. It can be biased. It can be misanalyzed or used misleadingly. And even more damning, data can fail to capture what it purports to quantify.

We are more susceptible than we may think to the “dictatorship of data”—that is, to letting the data govern us in ways that may do as much harm as good. The threat is that we will let ourselves be mindlessly bound by the output of our analyses even when we have reasonable grounds for suspecting that something is amiss. Education seems on the skids? Push standardized tests to measure performance and penalize teachers or schools. Want to prevent terrorism? Create layers of watch lists and no-fly lists in order to police the skies. Want to lose weight? Buy an app to count every calorie but eschew actual exercise.

The dictatorship of data ensnares even the best of them. Google runs everything according to data. That strategy has led to much of its success. But it also trips up the company from time to time. Its cofounders, Larry Page and Sergey Brin, long insisted on knowing all job candidates’ SAT scores and their grade point averages when they graduated from college. In their thinking, the first number measured potential and the second measured achievement. Accomplished managers in their 40s were hounded for the scores, to their outright bafflement. The company even continued to demand the numbers long after its internal studies showed no correlation between the scores and job performance.

Google ought to know better, to resist being seduced by data’s false charms. The measure leaves little room for change in a person’s life. It counts book smarts at the expense of knowledge. And it may not reflect the qualifications of people from the humanities, where know-how may be less quantifiable than in science and engineering. Google’s obsession with such data for HR purposes is especially queer considering that the company’s founders are products of Montessori schools, which emphasize learning, not grades. By Google’s standards, neither Bill Gates nor Mark Zuckerberg nor Steve Jobs would have been hired, since they lack college degrees.

Google’s deference to data has been taken to extremes. To determine the best color of a toolbar on the website, Marissa Mayer, when she was one of Google’s top executives before going to Yahoo, once ordered staff to test 41 gradations of blue to see which ones people used more. In 2009, Google’s top designer, Douglas Bowman, quit in a huff because he couldn’t stand the constant quantification of everything. “I had a recent debate over whether a border should be 3, 4 or 5 pixels wide, and was asked to prove my case. I can’t operate in an environment like that,” he wrote on a blog announcing his resignation. “When a company is filled with engineers, it turns to engineering to solve problems. Reduce each decision to a simple logic problem. That data eventually becomes a crutch for every decision, paralyzing the company.”

This is the dictatorship of data. And it recalls the thinking that led the United States to escalate the Vietnam War partly on the basis of body counts, rather than basing decisions on more meaningful metrics. “It is true enough that not every conceivable complex human situation can be fully reduced to the lines on a graph, or to percentage points on a chart, or to figures on a balance sheet,” said McNamara in a speech in 1967, as domestic protests were growing. “But all reality can be reasoned about. And not to quantify what can be quantified is only to be content with something less than the full range of reason.” If only the right data were used in the right way, not respected for data’s sake.

Robert Strange McNamara went on to run the World Bank throughout the 1970s, then painted himself as a dove in the 1980s. He became an outspoken critic of nuclear weapons and a proponent of environmental protection. Later in life he produced a memoir, In Retrospect, that criticized the thinking behind the war and his own decisions as secretary of defense. “We were wrong, terribly wrong,” he famously wrote. But McNamara, who died in 2009 at age 93, was referring to the war’s broad strategy. On the question of data, and of body counts in particular, he remained unrepentant. He admitted that many of the statistics were “misleading or erroneous.” “But things you can count, you ought to count. Loss of life is one.”

Big data will be a foundation for improving the drugs we take, the way we learn, and the actions of individuals. However, the risk is that its extraordinary powers may lure us to commit the sin of McNamara: to become so fixated on the data, and so obsessed with the power and promise it offers, that we fail to appreciate its inherent ability to mislead.

Kenneth Cukier is the data editor of The Economist. Viktor Mayer-Schönberger is a professor of Internet governance and regulation at the Oxford Internet Institute in the U.K. They are the authors of Big Data: A Revolution That Will Transform How We Live, Work, and Think (Houghton Mifflin Harcourt, 2013), from which this article was adapted.




 

New Tools Beget Revolutions: Big Data and the 21st Century Information-based Society

New Tools Beget Revolutions: Big Data and the 21st Century Information-based Society

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Irving Wladawsky-Berger

Guest Contributor

 

http://blogs.wsj.com/cio/2013/05/31/new-tools-beget-revolutions-big-data-and-the-21st-century-information-based-society/?mod=google_news_blog

 

On May 22 I attended the 2013 MIT Sloan CIO Symposium. This year's theme was The Transformational CIO: Architecting the Enterprise of the Future. "The enterprise of the future will be very different from the one we know," wrote the organizers in the event's website. "It will be complex, develop hitherto unforeseen forms, and will have to respond to unforeseen challenges…There will not only be the need to be agile and adapt to changes as they occur, but to be proactive in shaping the next generation enterprise to be ready for the future." 

The Symposium included a number of talks and panels on the key issues facing CIOs in our post-digital world, that is, in an era when digital technologies permeate just about every nook and cranny of the business, and where every business is a digital business–the title of one of the talks at the event. While a number of transformative technologies were discussed, Big Data was the most prominent.

MIT professor Erik Brynjolfsson led an all-MIT academic panel of experts on The Reality of Big Data. In a brief introductory talk, Mr. Brynjolfsson pointed out that throughout history new tools beget revolutions. Scientific revolutions are launched when new tools make possible all kinds of new measurements and observations. In 1676, for example, Antonie van Leeuwenhoek used a microscope, a relatively recent and rare tool, to discover the existence of microorganisms in a drop of water. Thus was microbiology born, leading to major discoveries in biology, medicine, public health and food production in subsequent decades and centuries.

Big Data is such a measurement revolution made possible by the new digital tools all around us, including location data transmitted by our mobile phones; searches, Web links and social media interactions; payments and transactions; the myriads of smart sensors keeping track of the physical world; and so on. As one of the panelists, Media Lab professor Sandy Pentland recently put it in this online conversation:

"This is the first time in human history that we have the ability to see enough about ourselves that we can hope to actually build social systems that work qualitatively better than the systems we've always had. . . .  That's a remarkable change. It's like the phase transition that happened when writing was developed or when education became ubiquitous, or perhaps when people began being tied together via the Internet."

Continuing with his talk, Mr. Brynjolfsson added that beyond being a technology and scientific revolution, Big Data should be viewed as a management revolution. We have mostly been managing by gut, intuition and hunches because we've lacked the appropriately analyzed data to do otherwise. Key business and strategic decisions are frequently made by what he called the HiPPO or Highest Paid Person with an Opinion. "We need to change from opinions and hunches and go with facts and data," he said. By feeding data to the HiPPOs we can turn them into geeks.

Mr. Brynjolfsson and Andy McAfee elaborated on this in a recent Harvard Business Review article: Big Data: The Management Revolution. "[The] Big Data of this revolution is far more powerful than the analytics that were used in the past. We can measure and therefore manage more precisely than ever before. We can make better predictions and smarter decisions. We can target more-effective interventions, and can do so in areas that so far have been dominated by gut and intuition rather than by data and rigor. As the tools and philosophies of big data spread, they will change long-standing ideas about the value of experience, the nature of expertise, and the practice of management. Smart leaders across industries will see using big data for what it is: a management revolution."

In his panel introduction, Mr. Brynjolfsson cited insurance underwriting, housing sales, and even wine ratings as some of the industries where Big Data is already having an impact. He referenced a 2011 research paper which he co-authored that found that those companies that have embraced data-driven decision making enjoyed 5%  higher productivity and 6% higher profits that what would be expected given their other investments and IT usage. In addition, data-driven decision making also improved other performance measures in these companies, including asset utilization, return on equity and market value.

Professor Dimitris Bertsimas, another member of the panel, talked about his research analyzing decades of cancer treatment data in the hope of improving the life expectancy and quality of life of cancer patients at reasonable costs. Along with three of his students, he developed models for predicting survival and toxicity using patients' demographic data as well as data on the chemotherapy drugs and dosages they were given. Their results show that it's possible to predict future clinical trial outcomes based on past data, even if the exact combination of drugs being predicted has never been tested in a clinical trial before.

Mr. Bertsimas told us that his research was motivated by the cancer treatment his own father went through. In 2012, he published a paper with his students, An Analytics Approach to Designing Clinical Trials for Cancer, which he dedicated to the memory of his father.

"We believe that our approach to apply analytics to the design of clinical trials has the potential to significantly advance the state of the art in meta-analysis of cancer chemotherapy trials and fundamentally changing the design process for new chemotherapy clinical trials," they wrote in the concluding remarks. "This approach can help medical researchers identify the most promising drug combinations for treating different forms of cancer by drawing on previously published clinical trials. This would save researchers' time and effort by identifying proposed clinical trials that are unlikely to succeed and, most importantly, save and improve the quality of patients' lives by improving the quality of available chemotherapy regimens."

The third panelist, Professor of Finance Andrew Lo, is looking at data from banks, hedge funds, insurance companies, sovereign funds and other financial institutions to see if he can detect patterns that could alerts us to the potential for another financial crisis. This is a particularly difficult task because financial service companies have largely kept their data segregated, hampering our ability to analyze the financial system as the highly interconnected, interdependent, holistic system it actually is. In fact, in the five years since the crisis, our global financial system has become even more interconnected than it was in the years preceding the crisis.

"We're only now at the beginning of understanding how to map the financial system," Mr. Lo said.  "I'm optimistic that over the next five or 10 years we're going to be building a much more advanced financial system. But over the shorter term, in the next one to five years, I think it's going to be Moore's Law versus Murphy's Law." His use of Moore's Law versus Murphy's Law is explained in this recently published paper of the same title.

The panel strongly believed that privacy is a major area of concern for Big Data applications, especially in regulated industries like healthcare and financial services. But, there are a number of things we can do to ameliorate these concerns. According to Mr. Lo, part of the answer lies in the use of secure multi-party computation, a sub-field of cryptography that enables statistics and other functions to be calculated and shared while keeping the individual inputs used in the calculations totally anonymous.

Mr. Pentland advocates that individuals should have the final say about the use of the data collected about them, including the ability to put the data in circulation and turn it into a personal asset by giving permission to share it for value in return. In 2011, he founded the Institute for Data Driven Design – ID3, a research and educational nonprofit to help define the kind of principles, contracts and rules needed to empower individuals to assert greater control over their data and digital identities and authentication. ID3 is developing software mechanisms and an open software platform to implement and enforce these principles.

Our new Big Data tools have the potential to usher an information-based scientific revolution in healthcare, finance, management and a number of other human endeavors. We need to learn how to best leverage our tools – their benefits as well as their limits – and how to surmount major obstacles, including the serious privacy concerns discussed in the panel. Like all scientific revolutions, this will take time, as we learn how to architect not only the enterprise of the future but our future information-based society.

Irving Wladawsky-Berger is a former vice-president of technical strategy and innovation at IBM. He is a strategic advisor to Citigroup and is a regular contributor to CIO Journal.

 

Thursday, May 30, 2013

Todd Park: A Data-Powered Revolution in Health Care

A Data-Powered Revolution in Health Care


Todd Park

May 28, 2013
12:40 PM EDT

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Thomas Friedman’s New York Times column, Obamacare’s Other Surprise, highlights a rising tide of innovation that has been unleashed by the Affordable Care Act and the Administration’s health IT and data initiatives. Supported by digital data, new data-driven tools, and payment policies that reward improving the quality and value of care, doctors, hospitals, patients, and entrepreneurs across the nation are demonstrating that smarter, better, more accessible, and more proactive care is the best way to improve quality and control health care costs.   

We are witnessing the emergence of a data-powered revolution in health care. Catalyzed by the Recovery Act, adoption of electronic health records is increasing dramatically. More than half of all doctors and other eligible providers and nearly 80 percent of hospitals are using electronic health records to improve care, an increase of more than 200 percent since 2008. In addition, the Administration’s Health Data Initiative is making a growing supply of key government data on everything from hospital charges and quality to regional health care system performance statistics freely available in computer-readable, downloadable form, as fuel for innovation, entrepreneurship, and discovery.

As Friedman describes, these trends, combined with efforts under the Affordable Care Act to change how we pay health care providers to better reward improving the quality and value of care, are creating a “new marketplace and platform for innovation.” Entrepreneurs and innovators across the country are developing and deploying new data-powered IT tools to help clinicians succeed at delivering better care at lower cost.

These tools are giving clinicians the ability to measure how they are doing, compare how they are doing relative to others, and set and meet goals. They are enabling clinicians to analyze their patient population, understand who needs help (including and especially patients who haven’t been able to come into their office), and proactively reach out and give those patients the care they need. They are helping clinicians and patients get the latest and greatest evidence-based, life-saving best practices at their fingertips. And much more.

Many of the entrepreneurs and innovators who are driving this revolution will be joining us and leaders from across the health care system next week at the fourth annual Health Datapalooza, a national celebration of data-powered innovation in health care.

We are beginning to see what happens when you unleash the power of American innovators and data to transform health care for the better from the ground up.  It’s no surprise to the doctors, hospitals, patients and entrepreneurs who have been working so hard to improve health care. But it is, indeed, great news for the nation.


Read more:

 

Tuesday, May 28, 2013

Technology executives could be the next public enemies

http://www.ft.com/cms/s/0/b4d11650-c45b-11e2-bc94-00144feab7de.html#ixzz2Ub2SWALy

Technology executives could be the next public enemies

About a year ago I was in San Francisco’s Pacific Heights, gazing down at the Golden Gate Bridge from one of Larry Ellison’s many spectacular homes. The Oracle chief executive wasn’t there – he had lent the house out for a reception. In any case, he would be the last person to apologise for enjoying the fruits of his success. But the view from technology executives’ balconies is getting stormier. After banks and bankers, could they be next to feel the sting of a populist backlash?

It sounds unlikely. For the tablet-toting, smartphone-stroking, Amazon-and-Googling masses – you and me, in other words – to attack companies that provide the products and services we love would be a case of biting the data feed they hand us.

But consider these rumbles: politicians on both sides of the Atlantic attack Apple, Google and Amazon for their tax arrangements; commentators take Silicon Valley’s wealthy to task for the growing economic inequality in northern California; activists worry about ill-protected privacy, dirt-cheap labour and energy-inefficient server farms; antitrust regulators circle closer.

Like banking, technology is ubiquitous and its benefits often taken for granted. Executives and engineers are highly paid and unafraid to reinvest their wealth in real estate, cars and luxury goods. Forget Wall Street – “after decades in which [the US] has become less and less equal, Silicon Valley is one of the most unequal places in America”, wrote George Packer in a withering recent analysis in The New Yorker. Like big banks, tech companies are protected by a bubble of their own making – literally in the case of Amazon, which is planning a trio of biospheres for its new Seattle headquarters – and their representatives often exude a sense of entitlement and an overconfidence that technology can solve the world’s problems.

Technology companies do have some clear advantages over banks. They start with what Laurence Evans, who oversees Edelman’s annual Global Trust Barometer, calls a brand “halo”. Technology regularly tops the list of the most trusted industries and has done since the survey started 13 years ago. Even before the financial crisis, banks never rose above the middle of the ranking. Users have an intimate involvement with their iPhones and Samsung Galaxys they will never have with their current accounts or mutual funds. Crucially, technology companies do not stand accused of bringing down the global economy.

One Silicon Valley entrepreneur I contacted last week said it was “a stretch” even to imagine a backlash. I’m not so sure. Technology executives could shrug off the first gentle jabs at their superiority, as financiers did in the years before the credit crunch bit in 2007-08. But they would do better to act now.

Instead of doing as the banks did – closing ranks and deploying battalions of lobbyists to crush dissent – their first priority should be to ensure their products continue to serve customers’ needs. The challenge from new competitors and innovations is a big incentive for technology companies, unlike the banking oligopolies, to go on improving. But still, the temptation to take users for granted, or exploit them – say, for their personal information – is high.

So they must also share their wealth and react early to any perception of excess. Some founder-billionaires, having sweated to build a technology business, may justifiably claim they have no obligation to direct their earnings to good causes. (Others, such as Mr Ellison himself, have made pledges to give away much of their wealth to charity.) But the populist wave of anger at banks and bankers was, and is, fuelled in part by envy. It makes sense not to aggravate that.

Technology executives should keep listening, and keep talking. Tim Cook may not have satisfied critics when he was grilled by the US Congress last week about Apple’s tax affairs but he was a model of calm and reasonableness.

Finally, stay clean. The risk is that technology titans’ undoubted success will breed complacency, which begets arrogance, and can lead to actual wrongdoing. Big Tech has huge advantages over High Finance when it comes to defending its reputation. So its leaders should adopt a new slogan, borrowed from Yahoo chief executive Marissa Mayer’s declaration to fans of Tumblr, the blogging platform her company has just bought: “We promise not to screw it up.”

 

Saturday, May 25, 2013

Tom Friedman on Health Information: Obamacare’s Other Surprise

May 25, 2013

Obamacare's Other Surprise

By THOMAS L. FRIEDMAN
http://www.nytimes.com/2013/05/26/opinion/sunday/friedman-obamacares-other-surprise.html?ref=opinion&pagewanted=print#h[]

LISTENING to the debate about President Obama's health care plan, some critics argue that Obamacare is going to need Obamacare — because it's going to be a "train wreck." Obama officials insist they're wrong. We'll just have to wait and see whether the Affordable Care Act, as the health care law is officially known, surprises us on the downside. But there is one area where the law already appears to be surprising on the upside. And that is the number of health care information start-ups it's spurring. This is a big deal.

The combination of Obamacare regulations, incentives in the recovery act for doctors and hospitals to shift to electronic records and the releasing of mountains of data held by the Department of Health and Human Services is creating a new marketplace and platform for innovation — a health care Silicon Valley — that has the potential to create better outcomes at lower costs by changing how health data are stored, shared and mined. It's a new industry.

Obamacare is based on the notion that a main reason we pay so much more than any other industrial nation for health care, without better results, is because the incentive structure in our system is wrong. Doctors and hospitals are paid primarily for procedures and tests, not health outcomes. The goal of the health care law is to flip this fee-for-services system (which some insurance companies are emulating) to one where the government pays doctors and hospitals to keep Medicare patients healthy and the services they do render are reimbursed more for their value than volume.

To do this, though, doctors and hospitals need instant access to data about patients — diagnoses, medications, test results, procedures and potential gaps in care that need to be addressed. As long as this information was stuffed into manila folders in doctors' offices and hospitals, and not turned into electronic records, it was difficult to execute these kinds of analyses. That is changing. According to the Obama administration, thanks to incentives in the recovery act there has been nearly a tripling since 2008 of electronic records installed by office-based physicians, and a quadrupling by hospitals.

The Health and Human Services Department connected me with some start-ups and doctors who've benefited from all this, including Dr. Jen Brull, a family medicine specialist in Plainville, Kan., who said that she was certain she had been alerting her relevant patients to have colorectal cancer screening — until she looked at the data in her new electronic health care system and discovered that only 43 percent of those who should be getting the screening had done so. She improved it to 90 percent by installing alerts in her electronic health records, and this led to the early detection of cancer in three patients — and early surgery that saved these patients' lives and also substantial health care expense.

Todd Park, the White House's chief technology officer, said many new apps being developed have been further fueled by the decision by Health and Human Services to make available massive amounts data that it had gathered over the years but had largely not been accessible in computer readable forms that could be used to improve health care. 

It started in March 2010 when Health and Human Services met with "45 rather skeptical entrepreneurs," said Park, "and rather meekly put an initial pile of H.H.S. data in front of them — aggregate data on hospital quality, nursing home patient satisfaction and regional health care system performance. We asked the entrepreneurs what, if anything, they might be able to do with this data, if we made it supereasy to find, download and use." They were told that in 90 days the department would hold a "Health Datapalooza," — a public event to showcase innovators who harnessed the power of this data to improve health and care.

Ninety days later, entrepreneurs showed up and demonstrated more than 20 new or upgraded apps they had built that leveraged open data to do everything from helping patients find the best health care providers to enabling health care leaders to better understand patterns of health care system performance across communities, said Park. In 2012, another "Health Datapalooza" was held, and this time, he added, "1,600 entrepreneurs and innovators packed into rooms at the Washington Convention Center, hearing presentations from about 100 companies who were selected from a field of over 230 companies who had applied to present." Most had been started in the last 24 months.

Among the start-ups I met with are Eviti, which uses technology to help cancer patients get the right combination of drugs or radiation from Day 1, which can lower costs and improve outcomes; Teladoc, which takes unused slices of doctors' time and makes use of it by connecting them with remote patients, reducing visits to emergency wards; Humedica, which helps health care providers analyze their electronic patient records, tracking what was done to a patient, and did they actually get better; and Lumeris, which does health care analytics that uses real-time data about every aspect of a patient's care, to improve medical decision-making, collaboration and cost-saving.

Obamacare will be a success only if it can deliver improved health care for more people at affordable prices. That remains to be seen. But at least it is already spurring the innovation necessary to make that happen.