Wednesday, March 27, 2013

Group Announces New Project To Develop 'Big Data' Cancer Database

Wednesday, March 27, 2013

Group Announces New Project To Develop 'Big Data' Cancer Database

On Wednesday, the American Society of Clinical Oncology announced that it is launching a database that will collect data on hundreds of thousands of individuals with cancer, the Wall Street Journal reports.

ASCO already has developed a prototype of the database, which includes information from the electronic health records of about 100,000 individuals with breast cancer.

Project Details

The database -- called CancerLinQ -- will collect all information that physicians routinely enter into the EHR of a patient with cancer, including:

  • Age;
  • Gender;
  • Cancer diagnosis;
  • Treatment;
  • Medications;
  • Other illnesses; and
  • Date of death.

ASCO says that it has developed software that can accept clinical data from nearly any type of EHR system. According ASCO, researchers still are working on ways to transform the data into useful reports and to overcome patient privacy issues.

The organization says that it likely will be 12 to 18 months before physicians can use the first components of the project.

Project Goals

ASCO hopes that health care providers can use the database as a guide for effective cancer treatment practices.

Allen Lichter -- CEO of ASCO -- said that most of the details of cancer treatments are "locked up in medical records and file drawers or in electronic systems not connected to each other." He added, "There is a treasure trove of information inside those cases if we simply bring them together."

Lynn Etheredge -- a consultant with the Rapid Learning Project at George Washington University in Washington, D.C. -- said that the development of the database signifies a "recognition that big data is an imperative for the future of medicine" (Winslow, Wall Street Journal, 3/26).


Read more: http://www.ihealthbeat.org/articles/2013/3/27/group-announces-new-project-to-develop-big-data-cancer-database.aspx#ixzz2OnaYKFmW

 

Tuesday, March 26, 2013

Todd Park: How to Kick-Start Innovation with Free Data

How to Kick-Start Innovation with Free Data

Weather and GPS information stimulated the economy with new products and services. Todd Park, the U.S. chief technology officer, wants to repeat that success with the rest of the government’s data trove

WASHINGTON, D.C.— Government-funded projects have yielded a wealth of information, but much of this data has historically remained locked up in difficult-to-use form. To get this data to people who might start businesses with them, the Obama administration created the position of chief technology officer.

Todd Park, the nation’s current CTO, has plenty of innovation experience. In 1997, at the age of 24, he co-founded his first start-up, called Athenahealth, which provides online data management for physicians. After momentarily retiring to focus on his family he set up two other start-ups before joining the White House team four years ago.

At a media briefing in February he talked about getting government data into the hands of entrepreneurs to spark innovation and economic growth.

[An edited transcript follows.]

You’re an entrepreneur who helped launch three successful health-tech start-ups. How did you end up working for the U.S. government?

In the summer of 2009 I got an e-mail from the U.S. Department of Health and Human Services (HHS) asking about my becoming its chief technology officer. My first question was: Why are you talking to me? Because I don’t know anything about government. I didn’t serve at any level. But they said, it’s actually your background as someone who’s not in government, who’s been a health-tech entrepreneur.

In March 2012 you became the chief technology officer of the U.S. What do you as the nation’s CTO?

It’s a position the president established for the first time in his first term in office. I’m the second CTO, after Aneesh Chopra.

The gist of the job is that I run an incubator inside the government. It’s not birthing companies; it’s birthing projects that all have the common denominator of unleashing the power of tech to advance the president’s programs, whether that’s job creation, economic growth, improved outcomes in health care, education, public safety or energy.

How does the incubation work?

One category of projects is the Open Data Initiative program. This set of initiatives aims to liberate data from the vaults of the government to spur entrepreneurship, innovation and scientific discovery.

A lot of data has been made public, but in unusable form, like books or pdfs or static Web sites. So the notion is to make them available as bulk downloadable files, as APIs [application protocol interfaces], so that you can actually use this stuff to create value. It was inspired by what the government did in prior eras, when it opened up weather data decades ago, making the data downloadable electronically by anyone, for free.

What happened once U.S. weather data became freely available?

Entrepreneurs picked it up and turned it into the Weather Channel, weather.com, weather apps, weather insurance--all which grew the economy, created jobs and improved our lives all at the same time.

GPS is similar story. Beginning the 1980s Pres. Ronald Reagan began the process of opening the GPS system for civilian and commercial access, which was completed under Pres. Bill Clinton. The access has spawned an incredible array of innovations by American entrepreneurs ranging from navigation systems to precision crop farming to location-based apps. In fact, it’s estimated that last year alone civilian and commercial access to GPS added $90 billion in annual value to the U.S. economy. And the number keeps growing.

So this is a play that gets the president and us very excited. Without legislation, without regulation, without incremental expenditure of taxpayer capital, you’re basically taking data—information resources that taxes have already paid for—and you’re jujitsuing it, if you will, into the public domain as fuel for entrepreneurs to pick up and turn into awesomeness.

How much data is there in the government?

The thing that’s really amazing to me is that weather and GPS are just the tip of the iceberg. The analogy we use is the last scene of Raiders of the Lost Ark, where they are in a giant warehouse wheeling in a box that has the latest treasure. That’s a really good metaphor for the data treasures that are held in the vaults of the government—data which taxpayers have paid for and which we should give back to them.

We’re focusing on six sectors in particular: health, energy, education, public safety, global development and finance.

How do you get innovators and entrepreneurs involved in the process?

We do these “Datapaloozas,” where folks get together to learn more about the data that’s available and to showcase what entrepreneurs have done with them.

Just to show you how fast this can go, we actually started this effort when I was at HHS with something called Healthy Initiative in 2010. We kicked it off by inviting 45 very skeptical entrepreneurs into a room and saying, “Here’s a bunch of data we have. What do you think?” Ninety days later 20-plus new innovations were showcased. It not only inspired entrepreneurs to do innovations of their own but also inspired people who own data inside the government to realize the value of putting it out there.

Two years later in June 2012 we had a Health Datapalooza that drew 1,600 entrepreneurs—and several hundred entrepreneurs who were angry they couldn’t get in.

What were some of the products that were showcased at the Health Datapalooza?

Two hundred and thirty–plus companies had gone through an American Idol–style contest for the right to present. Most of these companies have been founded in the last 18 to 24 months, all leveraging open data to actually do something remarkable in health care.

An example is Pete Hudson, who started a company called iTriage. The mobile app took a bunch of data around where all the doctors are, like GPS for health care providers. As a user, you can punch in your symptoms and it tells you based on the GPS and the data you punched in who the best local providers are that can help you. It’s been downloaded nine million times and has literally saved people’s lives.

Do you keep track of how the data is used?

No. The data is completely free, there are no conditions, there are no agreements to sign, no registration process—you just take it and do amazing things with it.

One example is Google. I remember Bryan Sivak, my successor at as CTO at HHS, called me one day and said, “Go to Google, and type in ‘aspirin.’ It’ll make you really happy.” I did, and then—boom!—it pops up on the right-hand side next to the search results, a whole bunch of government-sourced scientific data about aspirin. Google has done it for every single drug, leveraging our national medical API’s.

Best of all, I had no idea they were doing it. All great innovation ecosystems are chaotic, self-propelled and out of control. And I think we’re getting to that point where open-data ecosystems are at that happy place.

You started another program, called the Presidential Innovation Fellows. What is that about?

It allows us to bring in amazing people from the outside to complement the people on the inside. They operate in start-up mode: small, agile teams to come up with a minimal viable product and then engage with the customer as soon as they can.

What were some of the innovations that have come out of the fellowship program?

One was called Blue Button for America, which is all about enabling Americans to securely download their own heath information wherever they might be. There is also a project called MyUSA, which deals with the fact we have 24,000 Web sites across the U.S. government—our Web presence is organized the way the government is organized, which is to say incomprehensible. So MyUSA has built a prototype platform that helps you access and use the services and information.

Overall, how would you describe the release of data?

It’s an instantiation of one of our favorite laws of the universe, called Joy’s Law. From Bill Joy, co-founder of Sun Microsystems, who famously said, “No matter who you are, most of the smartest people in the world work for somebody else.”

The whole idea behind open data is to say, look, we don’t know anything about the data. We don’t have the money or the expertise to do anything, so why don’t we just open it up to the people who paid for it already, and they will invent all kinds of things.

 

Why 'Big Data' Is a Big Deal

Why 'Big Data' Is a Big Deal

Analysis showed that prematurely born infants with unusually stable vital signs correlates with serious fevers 24 hours later—enabling physicians to take preventive measures.

·         By L. GORDON CROVITZ

http://online.wsj.com/article/SB10001424127887324077704578364632408717740.html

Analog-era minds have a hard time processing a key product of the digital era: the staggering amount of information being created, collected and correlated. What's called "big data" already identifies flu outbreaks and treatments for premature babies, and it predicts apartment overcrowding and airline delays.

Explaining this is the focus of a new book, "Big Data: A Revolution That Will Transform How We Live, Work, and Think," written by Oxford scholar Viktor Mayer-Schonberger and Kenneth Cukier, data editor of The Economist. The book should spur policy makers to rethink how to protect privacy while enabling more access to data. (Disclosure: The publisher is Houghton Mifflin Harcourt, on whose board I serve.)

Big data differs from traditional information in mind-bending ways. For one thing, the authors write, "society will need to shed some of its obsession for causality in exchange for simple correlations: not knowing why but only what. This overturns centuries of established practices and challenges our most basic understanding of how to make decisions and comprehend reality."

Until recently, big data made for interesting anecdotes, but now it has become a major source of new knowledge. Google is better than the Centers for Disease Control at identifying flu outbreaks. Google monitors billions of search terms ("best cough medicine," for example) and adds location details to track outbreaks. When Wal-Mart analyzed correlations using its customer data and weather, it found that before storms, people buy more flashlights but also more Pop-Tarts, even though marketers can't establish a causal relationship between weather and toaster pastries.

Technology researchers in Canada analyzed premature births, tracking more than 1,000 data points per second. They shocked doctors by showing that when vital signs are unusually stable, that correlates with a serious fever 24 hours later. Physicians now prevent fevers through treatment though causation remains a mystery.

Data scientists working for New York City analyzed hundreds of data points to predict where owners were illegally subdividing houses and apartments, which leads to overcrowding and raises the risk of serious fires. By tracking data, including foreclosure proceedings and reports of rodents, inspectors were able to filter complaints so efficiently that they found dangerous conditions 70% of the time they inspected, an increase from 13%.

Air travelers can now figure out which flights are likeliest to be on time, thanks to data scientists who tracked a decade of flight history correlated with weather patterns. Credit scores predict who needs reminders to take medicine. Publishers use data from text analysis and social networks to give readers personalized news.

Using big data to improve health care is one of the biggest opportunities, but current laws make it hard to mine even data aggregated from many patients. If we had electronic records of Americans going back generations, we'd know more about genetic propensities, correlations among symptoms, and how to individualize treatments.

"Instead of focusing on the problems of inadvertent disclosure or misuse, which are admittedly very real," Mr. Cukier said in an interview, "we need to balance those risks with the great potential of making health-care data available to researchers. I'm certain that in the future, we will be aghast if doctors don't turn to big data to aid them in treating patients, just as today we'd be terrified if a pilot tried to land a jumbo jet without computer instrumentation."

Mr. Cukier's book is a surprise best seller in China. "Big data is emerging just as China is now strong, and so it's an area where they may be able to be a global leader, and steal a march on Silicon Valley," he says. China also shows the dark side of big data, with the government monitoring everything from Web usage to mobile-phone locations in order to block protests and arrest dissidents.

In the U.S., much of the privacy debate has focused on targeted online advertising. The authors identify more worrisome issues, such as "penalties based on propensities."

Law enforcement is using data to identify streets, groups and even individuals to track through "predictive policing." This is fine so long as it doesn't extend, as the movie "Minority Report" imagined, to punishing people for crimes the data say they likely will commit. "If we hold people responsible for predicted future acts," the authors warn, "we also deny that humans have a capacity for moral choice." Big data shouldn't "become a tool to collectivize human choice and abandon free will."

The authors compare policy choices arising from big data to how governments responded to the printing press by censoring books and newspapers: "As centuries passed, we opted for more information flows rather than less, and to guard against its excesses not primarily through censorship but through rules that limited the misuse of information."

Wise policy on big data will follow the precedent of the printing press to allow broader access to information, while finding creative ways to limit its misuse. Big data is too big a deal to suppress.

A version of this article appeared March 25, 2013, on page A15 in the U.S. edition of The Wall Street Journal, with the headline: Why 'Big Data' Is a Big Deal.

 

Sunday, March 24, 2013

NYC: The Mayor's Geek Squad

The Mayor’s Geek Squad

By ALAN FEUER
http://www.nytimes.com/2013/03/24/nyregion/mayor-bloombergs-geek-squad.html?hp&_r=0&pagewanted=all&pagewanted=print#h[]

It was a case for a digital Sherlock Holmes. Last fall, the city’s Department of Environmental Protection wanted, finally, to crack down on restaurants that were illegally dumping cooking oil into sewers in their neighborhoods — congealed yellow grease is responsible, the department says, for more than half of New York’s clogged drains. The question, of course, was how to find the culprits?

The antiquated answer would have been to have the health department send inspectors to restaurants on blocks with backed-up sewers and hope by chance to catch a busboy pouring the contents of a deep fryer into the street.

Enter the city’s Office of Policy and Strategic Planning, a geek squad of civic-minded number-crunchers working from a pair of cluttered cubicles across from City Hall in the Municipal Building. They dug up data from the Business Integrity Commission, an obscure city agency that among other tasks certifies that all local restaurants have a carting service to haul away their grease. With a few quick calculations, comparing restaurants that did not have a carter with geo-spatial data on the sewers, the team was able to hand inspectors a list of statistically likely suspects.

The result: a 95 percent success rate in tracking down the dumpers. With nothing grander than public data, the Case of the Grease-Clogged Sewers was solved.

Data — or Big Data, as quantitative analysts will call it — is the tool du jour for tech-savvy companies that have realized that lurking in the vast pools of unprocessed information in their networks are solutions to some of today’s most pressing and convoluted problems. A few years ago, Google, for example, took the 50 million most common keywords that Americans typed in search bars and tried to figure out, by comparing them with federal health statistics, where the H1N1 flu virus was to likely strike next.

According to a new book, “Big Data: A Revolution that Will Transform How We Live, Work and Think,” the enormous quantity of information whirling through the ether can affect and enhance our quality of life. As the authors put it, “The change of scale has led to a change of state.”

Now the city has brought this quantitative method to the exceedingly complicated machine that is New York. For the modest sum of $1 million, and at a moment when decreasing budgets have required increased efficiency, the in-house geek squad has over the last three years leveraged the power of computers to double the city’s hit rate in finding stores selling bootleg cigarettes; sped the removal of trees destroyed by Hurricane Sandy; and helped steer overburdened housing inspectors — working with more than 20,000 options — directly to lawbreaking buildings where catastrophic fires were likeliest to occur.

“I think of us as the Get Stuff Done Folks,” Michael Flowers who oversees the group, said. “All we do is take and process massive amounts of information and use it to do things more effectively.”

Before being hired in 2009 by John Feinblatt, the mayor’s chief policy adviser, Mr. Flowers didn’t know much about computer code — let alone Bayesian statistics. From 1999 to 2003, he worked at the Manhattan district attorney’s office, prosecuting homicides and drug crimes. When he left law enforcement, he moved to Washington, where he joined the power law firm Williams & Connolly and later took a job with the Senate Permanent Subcommittee on Investigations. Disenchanted by the smug homogeneity of Washington, Mr. Flowers leapt at the chance in 2005 to travel to Iraq with a team from the Justice Department to work on issues concerning mass graves and on Saddam Hussein’s trial.

While serving in the Green Zone, Mr. Flowers was responsible for sending investigators to grave sites in the countryside and transporting witnesses against Mr. Hussein to his office — without getting either group blown up by roadside bombs. It came to his attention that military officers were using predictive informational techniques to determine where and when the bombs were likely to explode.

He borrowed those techniques when he returned to New York and went to work for Mr. Feinblatt with the initial, limited task of trying to understand in the early months of the recession what was causing mortgage fraud.

“We eventually realized there was enormous value in using all our data — together and proactively,” Mr. Feinblatt said. “We’d already done the retroactive act of looking back for accountability’s sake. So we tried to use the data prescriptively to figure out what might be coming next.”

These days, Mr. Flowers, a relative amateur in data analytics, is the geek squad’s chief tactician and resident asker of questions.

He allows the half-dozen post-collegiate techies working under him to ferret out the answers and, at age 43, he refers to them endearingly as “the kids.” His office gives the impression of a high-tech start-up — but without the cool furniture. Nick O’Brien, 30 and the team’s chief of staff, works standing at a lectern. Ben Dean, the 24-year-old chief analyst, sits on an ergonomic rubber ball.

One drawer in the filing cabinet is filled with spare neckties. These are to spruce team members up for meetings with “That Guy,” as Mr. Flowers likes to call his boss, Mayor Michael R. Bloomberg, invariably chucking a thumb in the direction of City Hall.

Two weeks ago, with Mr. O’Brien in Texas for the South-by-Southwest conference, the rest of the team was working on a project to make the city’s response to natural disasters like Hurricane Sandy more robust. Catherine Kwan, 24, was doing some “MacGyver stuff,” as Mr. Flowers called it, correlating city information with data from utilities, like Con Edison, to put in place a system that would eventually detect, in real time, when a building’s heat or lights were out.

“So what’s the current ratio of Con Ed customer accounts per residential unit?” Mr. Flowers asked. (Ms. Kwan’s answer: 0.88.) And the ratio of people per unit was “2.6,” she said.

One of the benefits that come from working with the informational atoms of the city is an almost molecular understanding of New York itself. The youthful quants were surprised to learn, for instance, that it was mathematically possible to create safer streets by encouraging local businesses to keep their doors open later after dark. They also had not known that a significant percentage of 311 complaints derived from certain neighborhoods in Lower Manhattan — an area they now refer to jokingly as “whine country.”

“What’s impressed me most about this job,” Mr. Flowers said, “is learning how insanely complicated this city is.” He mentioned, in particular, the 900,000 buildings the city oversees and the 12,000 tons of trash it picks up daily.

“That activity is reflected in the data and on an amazingly detailed level. What we’re really running here is an office of New Yorkology,” he said.

WHAT THE CITY KNOWS about its 8 million residents is staggering. Contained in public archives is information about their boilers and their sprinkler systems, the state of their local taxes, the number of heart attacks and fires that occur inside their buildings and whether they have ever logged complaints about roaches or construction noise. Additional data is gathered about their businesses, their commuting habits and their children’s test scores.

If a parking meter sits outside their apartment, the city knows how many cars have parked there on any given day, the number and dollar amount of tickets handed out and, of course, the identities of those who have received them.

“There’s a deep, deep relationship between New Yorkers and their government,” Mr. Flowers said, “and that relationship is captured in the data.”

In all, a terabyte of raw information — enough to fill nearly 143 million printed pages — passes daily through Mr. Flowers’s office, and his team’s first job, he said, was to get that information into a comprehensible form: to, in effect, create a lingua franca for the bureaucracy’s Tower of Babel. As Mr. Feinblatt put it, “The data will tell you a story, but only if you do certain things that encourages it to speak.”

Among the first things the city did was to establish in 1989 the Commission on Public Information and Communication, or Copic, which under the aegis of the Public Advocate’s office was charged with helping New Yorkers get better access to municipal information.

While “good-government” advocates like Noel Hidalgo, executive director of the Open New York Forum, which advocates for the use of technology in city management, have questioned the effectiveness of Copic, they have also said its existence laid the groundwork for the passage last year of Local Law 11, one of the country’s most progressive open-data laws.

“Copic was Version 1.0 for greater transparency in public information,” Mr. Hidalgo said, “but it needed updating for the 21st century. Now, with Law 11, there is the potential to radically change how government services are used by citizens. It opens the door to a unique partnership between the city and its residents so that people can come up with innovative ways of using information.”

The law’s chief provision created a clearinghouse called the Open Data Portal, which offers to the public hundreds of sets of city data, including the location of Wi-Fi hot spots, the results of restaurant inspections, yearly power use by ZIP code and maps of public parks.

Mr. Flowers is responsible for managing the portal — which just this month placed online all city data now available — but the information on the site has been employed by a wide variety of people. Two weeks ago, the Office of Financial Empowerment, a city agency that helps low-income residents, held a “hackathon” at which tech geeks using information from the portal built an internal scheduling system for the agency’s counselors.

The portal has also served as a primary source for hackers in the city’s Big Apps competition, which annually awards cash prizes to developers who have created applications like ones helping cyclists avoid city streets where accidents often occur and providing the locations of public restrooms.

With each passing week, it seems another hackathon — think hacking marathon, usually to a beneficial purpose — is mounted in New York. There was Foursquare’s effort in January that resulted in the Nasdrunk app (it matched the closing value of the Nasdaq with smartphone check-ins at various city bars), and then there was Decoded Fashion, which took place during Fashion Week and was billed by its sponsor, Condé Nast, as the world’s first fashion industry hackathon.

Though many of these events used proprietary data — Occupy Wall Street held a hackathon this month crunching numbers from its Hurricane Sandy relief effort — their diversity and frequency have created a kind of hothouse atmosphere, a local data frenzy in which private efforts at analysis have spurred city government on to do the same.

“I think New York is the natural place for Big Data,” Mr. Flowers said. “We have the right culture. We have a mayor who understands that management is measurement. And, of course, we’re big enough so that it makes sense analyzing the data that we have.

“All the pieces, all the structures, are in place,” he said. “In New York, it’s kind of like the triumph of the nerds.”

ONE DAY THIS MONTH, Mr. Flowers, in a military swag vest from Iraq, was in his office kicking around ideas for future projects. Unlike the ascendant nerds he mentioned, he tends to speak in a soldier’s clipped language: “Mission critical” or “Actionable outcomes.”

This, indeed, was a “spitballing” session, and the plans being tossed around revealed where he would like to go next with his team. One idea was to analyze, and hopefully reduce, the time it takes for the city to issue permits to new small businesses. Another was to create a public version of the Web site Walkscore.com, on which ordinary people rate the walkability of their cities.

His most ambitious plan was a proposal to move beyond public information into the deeper and possibly more profitable mine of social-media data. Every day, he said, there are 250,000 New York-centric posts on Twitter alone — some concerning trash complaints, others unsanitary restaurant conditions. “If Young & Rubicam can use tweets to sell you stuff,” he hypothetically asked, “why can’t the city use them to make you less sick?”

This makes civil libertarians uncomfortable, particularly at a time when the Police Department’s chief Big Data project — its use of the Compstat system to guide stop-and-frisk — is being questioned by the courts. Mr. Flowers insists that he has put in place safeguards, like keystroke logs on his employees’ computers, to ensure that information is not abused. Still, groups like the New York Civil Liberties Union say that they are watching public data mining with a guarded, if optimistic, eye.

“I think that the Bloomberg administration’s attention to data has enormous potential for good,” Donna Lieberman, the executive director of the union, said. “Obviously, it means that the city can make and tweak policies based on reality. But the potential for the selective use and release of data is one aspect that raises concern.”

Another, at least for Mr. Flowers, is whether his geek squad will survive the end of Mr. Bloomberg’s tech-friendly tenure. For now, he said, he is proceeding under the assumption that it will, adding that the best way to ensure its viability is to create an appetite among city agencies for the analytical work his group produces.

“We know that there will always be a Fire Department, a Finance Department, a Department of Buildings,” Mr. Flowers said. “So hopefully by building a common data infrastructure that shares information in real time, it won’t matter who sits in City Hall.”

Working in his favor is the firm belief among information activists that Big Data’s moment, especially in the management of cities, has powerfully and irreversibly arrived. This is a conviction based on certain technological advancements and a discernible shift in how the younger generation sees its relationship to government.

What used to be about passively receiving services and dictates is now about participation, said Jennifer Pahlka, the executive director of Code for America, a volunteer group of techies that helps city governments, including New York City’s, write code for public projects.

“Young people, because of social media, have always felt they’ve had a voice,” Ms. Pahlka said. “They’re coming from the assumption that government is a hackable system — an operating system that can be optimized. It’s in their DNA, and they just go and do it.”

 

Saturday, March 23, 2013

Big Data Is Opening Doors, but Maybe Too Many

March 23, 2013

Big Data Is Opening Doors, but Maybe Too Many

By STEVE LOHR
http://www.nytimes.com/2013/03/24/technology/big-data-and-a-renewed-debate-over-privacy.html?pagewanted=all&_r=0&pagewanted=print
 

IN the 1960s, mainframe computers posed a significant technological challenge to common notions of privacy. That’s when the federal government started putting tax returns into those giant machines, and consumer credit bureaus began building databases containing the personal financial information of millions of Americans. Many people feared that the new computerized databanks would be put in the service of an intrusive corporate or government Big Brother.

“It really freaked people out,” says Daniel J. Weitzner, a former senior Internet policy official in the Obama administration. “The people who cared about privacy were every bit as worried as we are now.”

Along with fueling privacy concerns, of course, the mainframes helped prompt the growth and innovation that we have come to associate with the computer age. Today, many experts predict that the next wave will be driven by technologies that fly under the banner of Big Data — data including Web pages, browsing habits, sensor signals, smartphone location trails and genomic information, combined with clever software to make sense of it all.

Proponents of this new technology say it is allowing us to see and measure things as never before — much as the microscope allowed scientists to examine the mysteries of life at the cellular level. Big Data, they say, will open the door to making smarter decisions in every field from business and biology to public health and energy conservation.

“This data is a new asset,” says Alex Pentland, a computational social scientist and director of the Human Dynamics Lab at the M.I.T. “You want it to be liquid and to be used.”

But the latest leaps in data collection are raising new concern about infringements on privacy — an issue so crucial that it could trump all others and upset the Big Data bandwagon. Dr. Pentland is a champion of the Big Data vision and believes the future will be a data-driven society. Yet the surveillance possibilities of the technology, he acknowledges, could leave George Orwell in the dust.

The World Economic Forum published a report late last month that offered one path — one that leans heavily on technology to protect privacy. The report grew out of a series of workshops on privacy held over the last year, sponsored by the forum and attended by government officials and privacy advocates, as well as business executives. The corporate members, more than others, shaped the final document.

The report, “Unlocking the Value of Personal Data: From Collection to Usage,” recommends a major shift in the focus of regulation toward restricting the use of data. Curbs on the use of personal data, combined with new technological options, can give individuals control of their own information, according to the report, while permitting important data assets to flow relatively freely.

“There’s no bad data, only bad uses of data,” says Craig Mundie, a senior adviser at Microsoft, who worked on the position paper.

The report contains echoes of earlier times. The Fair Credit Reporting Act, passed in 1970, was the main response to the mainframe privacy challenge. The law permitted the collection of personal financial information by the credit bureaus, but restricted its use mainly to three areas: credit, insurance and employment.

The forum report suggests a future in which all collected data would be tagged with software code that included an individual’s preferences for how his or her data is used. All uses of data would have to be registered, and there would be penalties for violators. For example, one violation might be a smartphone application that stored more data than is necessary for a registered service like a smartphone game or a restaurant finder.

The corporate members of the forum say they recognize the need to address privacy concerns if useful data is going to keep flowing. George C. Halvorson, chief executive of Kaiser Permanente, the large health care provider, extols the benefits of its growing database on nine million patients, tracking treatments and outcomes to improve care, especially in managing costly chronic and debilitating conditions like heart disease, diabetes and depression. New smartphone applications, he says, promise further gains — for example, a person with a history of depression whose movement patterns slowed sharply would get a check-in call.

“We’re on the cusp of a golden age of medical science and care delivery,” Mr. Halvorson says. “But a privacy backlash could cripple progress.”

Corporate executives and privacy experts agree that the best way forward combines new rules and technology tools. But some privacy professionals say the approach in the recent forum report puts way too much faith in the tools and too little emphasis on strong rules, particularly in moving away from curbs on data collection.

“We do need use restrictions, but there is a real problem with getting rid of data collection restrictions,” says David C. Vladeck, a professor of law at Georgetown University. “And that’s where they are headed.”

“I don’t buy the argument that all data is innocuous until it’s used improperly,” adds Mr. Vladeck, former director of the Bureau of Consumer Protection at the Federal Trade Commission.

HE offers this example: Imagine spending a few hours looking online for information on deep fat fryers. You could be looking for a gift for a friend or researching a report for cooking school. But to a data miner, tracking your click stream, this hunt could be read as a telltale signal of an unhealthy habit — a data-based prediction that could make its way to a health insurer or potential employer.

Dr. Pentland, an academic adviser to the World Economic Forum’s initiatives on Big Data and personal data, agrees that limitations on data collection still make sense, as long as they are flexible and not a “sledgehammer that risks damaging the public good.”

He is leading a group at the M.I.T. Media Lab that is at the forefront of a number of personal data and privacy programs and real-world experiments. He espouses what he calls “a new deal on data” with three basic tenets: you have the right to possess your data, to control how it is used, and to destroy or distribute it as you see fit.

Personal data, Dr. Pentland says, is like modern money — digital packets that move around the planet, traveling rapidly but needing to be controlled. “You give it to a bank, but there’s only so many things the bank can do with it,” he says.

His M.I.T. group is developing tools for controlling, storing and auditing flows of personal data. Its data store is an open-source version, called openPDS. In theory, this kind of technology would undermine the role of data brokers and, perhaps, mitigate privacy risks. In the search for a deep fat fryer, for example, an audit trail should detect unauthorized use.

Dr. Pentland’s group is also collaborating with law experts, like Scott L. David of the University of Washington, to develop innovative contract rules for handling and exchanging data that insures privacy and security and minimizes risk.

The M.I.T. team is also working on living lab projects. One that began recently is in the region around Trento, Italy, in cooperation with Telecom Italia and Telefónica, the Spanish mobile carrier. About 100 young families with young children are participating. The goal is to study how much and what kind of information they share on smartphones with one another, and with social and medical services — and their privacy concerns.

“Like anything new,” Dr. Pentland says, “people make up just-so stories about Big Data, privacy and data sharing,” often based on their existing beliefs and personal bias. “We’re trying to test and learn,” he says.

 

Connections Science and Reinventing Society in the Wake of Big Data

  • March 22, 2013, 1:52 PM ET

Reinventing Society in the Wake of Big Data

  •  

Irving Wladawsky-Berger

Guest Contributor

http://blogs.wsj.com/cio/2013/03/22/reinventing-society-in-the-wake-of-big-data/

For several years now, Big Data has been one of the hottest topics in the IT industry. But what do we mean by Big Data? What are people really excited about? Is it real, hype, or something in between?

A number of recent articles have been sounding the alarm that Big Data may be at the peak of inflated expectations in Gartner’s hype cycle. Gartner’s Research director Svetlana Sicular recently observed that Big Data has already reached the peak of the hype cycle, and is now falling into the trough of disillusionment, a necessary step before (hopefully) moving on to the slope of enlightenment. She writes that a number of her most advanced Big Data clients are starting to get disillusioned:

***

“These organizations have fascinating ideas, but they are disappointed with the difficulty of figuring out reliable solutions. . . framing a right question to express a game-changing idea is extremely challenging: first, selecting a question from multiple candidates; second, breaking it down to many sub-questions; and, third, answering even one of them reliably… Formulating a right question is always hard, but with big data, it is an order of magnitude harder, because you are blazing the trail (not grazing on the green field).”

***

As is typically the case with major disruptive technologies, many people are waking up to the fact that realizing the value from Big Data and becoming a data-driven institution is a lot harder and will take longer than they originally anticipated.  But, is it worth it? What is this data-driven world all about?

MIT Media Lab Professor Alex “Sandy” Pentland talks about the promise of becoming a data-driven society in a very interesting online conversation, Reinventing Society in the Wake of Big Data. Pentland is a Big Data pioneer, whom O’Reilly Media founder Tim O’Reilly named one of The World’s 7 Most Powerful Data Scientists in Forbes.

“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,” says Mr. Pentland. “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.”

In the video and accompanying transcript, he explains the power of Big Data.

***

“I believe that the power of Big Data is that it’s information about people’s behavior – it’s about customers, employees, and prospects for your new business… This Big Data comes from location data from your cell phone and transaction data about the things you buy with your credit card. It’s the little data breadcrumbs that you leave behind you as you move around in the world.

“What those breadcrumbs tell is the story of your life. It tells what you’ve chosen to do. . . . Who you actually are is determined by where you spend time, and which things you buy. Big Data is increasingly about real behavior, and by analyzing this sort of data, scientists can tell an enormous amount about you. They can tell whether you are the sort of person who will pay back loans. They can tell you if you’re likely to get diabetes.”

***

Wikipedia defines Big Data as “a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications.” Gartner developed a 3V framework that looks at Big Data as “high volume, high velocity, and/or high variety information assets that require new forms of processing to enable enhanced decision making, insight discovery and process optimization.”

These are both good, succinct descriptions from the point of view of the technologies used to store, manage, access and analyze the data. But Mr. Pentland tells us that the real value of Big Data is what it enables us to learn about people–not as undifferentiated members of a group, but as unique individuals. And because our behavior is so determined by our social context, that is, our connections with the all the people around us, as well as our connections with the various communities and organizations we are a part of, Big Data is particularly valuable in helping to sort out our social fabric.

To help better understand the connected world we are enmeshed in, Mr. Pentland and Asu Ozdaglar recently created the MIT Center for Connections Science and Engineering. Connections Science is an example of the new data science disciplines being enabled by the advent of Big Data.

We have generally been studying complex systems in terms of averages, probability distributions and expected values. This has worked well for complex physical and engineered systems, where in general, similar components exhibit similar properties and behaviors – e.g, electrons, water molecules, car tires, airplane wings. But, it does not work so well for complex sociotechnical systems – e.g., cities, health systems, financial markets, companies, governments – where the key components are people.

We share behaviors and beliefs with other members of the groups we are part of.  These groups can be based on our personal attributes – e.g., gender, age, ethnicity, religion, sexual preference; our home and family status; our educational history; our work and career; our income and assets; our entertainment and sports preferences; and so on. Big Data can help infer our key traits based on the traits we share with each of these groups.

But unlike physical and engineered objects, each person is unique. What makes us unique is that each of us has many dimensions. Our traits are a composite of the traits of many different groups. Many different kinds of data sources are thus required to make accurate predictions about our behaviors and beliefs. That’s why it’s so unfair when people are profiled as financial or security risks based on only a few of their attributes, when a more extensive knowledge of who they are might lead to very different decisions.

“Social phenomena are really made up of millions of small transactions between individuals,” says Mr. Pentland. “You need to get down into these new patterns, these micro-patterns, because they don’t just average out to the classical way of understanding society. We’re entering a new era of social physics, where it’s the details of all the particles – the you and me – that actually determine the outcome.”

For Big Data to realize its potential requires access to vast amounts of personal information, which leads to very serious issues about privacy, data ownership and data control. Mr. Pentland strongly 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. He has been working closely with the World Economic Forum (WEF) to help develop the proper guidelines for the collection and use of personal data in collaboration with private companies, government representatives, end user privacy and rights groups, academics and others.

In 2011 Mr. Pentland 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.

“The fact that we can now begin to actually look at the dynamics of social interactions and how they play out, and are not just limited to reasoning about averages like market indices is for me simply astonishing,” said Mr. Pentland. “To be able to see the details of variations in the market and the beginnings of political revolutions, to predict them, and even control them, is definitely a case of Promethean fire. . . We’re going to reinvent what it means to have a human society.”

 

Big Data: The Key to Economic Development?

Quote: Over the last few decades, companies have increasingly looked to do business across borders, helping to drive economic growth around the world (see Japan, South Korea, Taiwan, Mainland China, India). Companies doing business across borders have largely done so without the benefit of data, because our data-providing institutions have been focused on the domestic market. This has meant higher risk, but typically the rewards of expanding into big new markets or finding massive cost savings through low wage labor have more than compensated the risk-takers.

Now, economic development in these emerging markets is leading to an increase in data, as increasingly sophisticated governments work to make more data available in order to further grease the wheels of commerce. This seems to suggest that economic development comes first, then data, then more economic development.

But what if data could come first? What if we could see more data coming out of emerging markets even before governments have the capacity to collect, and make available, large amounts of data? Might the transparency provided by data give more companies the confidence they need to do business in these markets – and in fact jump-start the process of economic development?

 

Big Data: The Key to Economic Development?

  • By Josh Green, Panjiva
  • 03.22.13

http://www.wired.com/insights/2013/03/big-data-the-key-to-economic-development/

Is Big Data as an engine of economic development destined to not live up to its potential, a la Siri? Image: Sean MacEntee/Flickr

In recent years, we’ve seen an explosion in the amount of data generated by humanity. This data explosion is the direct consequence of significant advances in technology. Interestingly, the “Big Data” work currently being done has the potential to invert the classic relationship between data and technological advancement. If the Big Data boosters are to be believed, the recent explosion of data will in fact drive significant advances in technology.

According to this line of thinking, we can apply new approaches to old problems, approaches that are only possible now that data is so abundant. An oft-cited example is speech recognition. With so many people talking to Siri, Apple engineers have the raw material they need to finally deliver speech recognition technology that actually, um, recognizes speech. As with many claims about the wonders of technology, the promise of Big Data will likely take longer to realize than many of us would like. (If you’ve used Siri recently, I’m sure you’ll agree.)

But today I’d like to make a different claim, a claim that some might consider more outrageous than the claim that Siri will one day work. My claim is this: Big Data has the potential to accelerate economic development in parts of the world where development has been most elusive.

If you look at the rise of America’s industrial economy over the last few hundred years, it’s clear that economic development has been accompanied by – and aided by – the rise of institutions that provide data. Take, for example, credit agencies, which – love ‘em or hate ‘em – pioneered the collection of information on people and companies around the United States. These agencies, by giving companies a clear sense of who could be trusted with credit and who could not, gave companies the confidence they needed to do business with people and companies they’d never met. Without question, these data providers facilitated economic growth.

Over the last few decades, companies have increasingly looked to do business across borders, helping to drive economic growth around the world (see Japan, South Korea, Taiwan, Mainland China, India). Companies doing business across borders have largely done so without the benefit of data, because our data-providing institutions have been focused on the domestic market. This has meant higher risk, but typically the rewards of expanding into big new markets or finding massive cost savings through low wage labor have more than compensated the risk-takers.

Now, economic development in these emerging markets is leading to an increase in data, as increasingly sophisticated governments work to make more data available in order to further grease the wheels of commerce. This seems to suggest that economic development comes first, then data, then more economic development.

But what if data could come first? What if we could see more data coming out of emerging markets even before governments have the capacity to collect, and make available, large amounts of data? Might the transparency provided by data give more companies the confidence they need to do business in these markets – and in fact jump-start the process of economic development?

This brings us back to Big Data. Humanity is producing so much data these days not because we’ve all decided to make the production of data our top priority, or because the government has dramatically ramped up the amount of data it’s collecting and making available. Rather, technology has created a world where people are generating massive amounts of data simply by living their lives, and companies are generating massive amounts of data simply by going about their business. Clearly, this is already the case in advanced economies. As the costs of key technologies continue to plummet, this will increasingly be the case in emerging economies as well. And, when that happens, we’ll see more companies digging into the data and emerging with the confidence to seize new opportunities in these markets. The result? Economic development in places where you’d least expect it.

(In some sense, I’m describing a leap-frogging phenomenon, in which emerging markets skip over the long and painful process of institution building and go directly to generating large amounts of data. It’s interesting to note that this leap-frogging phenomenon will be enabled by another leap-frogging phenomenon, as emerging markets skip over older communications technologies and go directly to wireless networks and smart devices.)

Now, I’m sensitive to the fact that technology is not a cure-all for the world’s problems; after all, Big Data is not going to provide the food, medicine, and shelter that are desperately needed in so many places. And, as with Siri, the reality of Big Data as an engine of economic development may fall short of the promise, for quite some time.

But, sooner or later, Big Data will come to – and from – emerging markets, and, when it does, the world will never be the same.

Josh Green is co-founder and CEO of Panjiva, a B2B platform that leverages Big Data to connect global buyers and suppliers.

 

Friday, March 22, 2013

FT on Smartwear

. http://www.ft.com/cms/s/0/cf0ff634-79cf-11e2-9015-00144feabdc0.html#ixzz2OHbuUleP

Innovation: Smartwear

A wave of wearable computers has the potential to be more intrusive than previous technology

 

On a brisk evening at an avant-garde art gallery in downtown San Francisco, the crowd looked as hip and healthy as you would expect at a show dedicated to the convergence of fashion, industrial design and technology. But this group of technorati had not come to admire exhibits hanging on the gallery walls. Instead, the discussion was about what was hanging from many of their own wrists.

Among them were entrepreneurs catering to the Bay Area’s many health and fitness fanatics, who were packed in for a debate on new wearable tech trends.

“Does anyone here know what a GSR – a galvanic skin response – is?” asks Adam Gazzaley, director of the Neuroscience Imaging Center at the University of California, San Francisco. “Wow, that’s a lot of people,” he says, surveying a sea of upraised arms adorned with health bands and smart watches.

Dr Gazzaley was not there chiefly to explain health vitals – GSR is a helpful measure for assessing physical activity – to devotees of Quantified Self, a movement promoting self-tracking of health statistics.

Instead, he warned of the wave of data soon to be unleashed by wearable computers – the wristbands, watches, glasses and other smart devices being dreamt up just a few miles away. Among the dangers are ever more distracted brains and technology companies with ever more personal information about users.

But Dr Gazzaley’s concerns are likely to be lost in the wave of hype about wearable computing projects by Google, Apple and other tech companies that could define the next generation of computing.

Google has developed glasses that incorporate a computer screen and camera, enabling users to call up information with voice commands and capture their surroundings. Apple’s watch is expected to link up with an iPhone to alert you to incoming calls, as well as tell you how many steps you have walked today.

And there are many other smartwatches, pendants, clip-ons, bracelets and patches embedded with sensors being developed by start-ups.

Taken together, these moves represent the logical next step in the evolution of computing. The large, complex and expensive mainframes of the 1950s and 1960s gave way to the personal computer in the 1980s. This century has seen the rise of smartphones and tablets, driven by ever smaller and cheaper components. Wearable computers represent a new era of the ultimate personal technology: gadgets attached to, and in some cases interacting with, the body itself.

. . .

It has taken 50 years for wearable computing to be ready for the mass market. The first wearable computer was used in a Las Vegas casino in 1961 by Claude Shannon and Ed Thorp, mathematicians and gamblers from MIT. They hid a primitive computer in their shoes that could predict where a ball would land on a roulette wheel. Operating it with their big toes, it would send musical tones as signals to a concealed earpiece but the wire connecting shoe and ear would often break.

The signals being sent out by today’s wearable gadgets will offer far wider insights, says Sarah Rotman Epps, analyst with Forrester Research. “They unlock a domain of data that was previously inaccessible: data about the body. And that has unlimited potential,” she says.

“If you think about other domains and what we’ve been able to do – such as shopping or maps data – once something is mapped, you can create products and services around it, and so we’re only just scratching the surface with body-generated data that’s captured by these wearable devices.”

Imagine your smartphone knows through your wearable device that you had a poor night’s sleep. It can show you an offer from a local coffee bar for a pick-me-up. Or it knows you are a compulsive shopper: it can flash a warning on your credit card balance as you consider another purchase.

This has the potential to be more intrusive than any previous technology, triggering privacy concerns that researchers are already addressing.

“As we sense in real time more and more about the individual, such as moods and behaviour, we need to provide near absolute guarantees that the information will not be subject to theft or attack, down to the silicon melting and still not giving up its data,” says Justin Rattner, chief technology officer at Intel, the world’s biggest chipmaker.

If this is not done, the potential for a backlash from users is very high, he says. This kind of personal information cannot suffer the security breaches we see with credit card information today.

Focus shifts from talking shoes to your wrist

At the South by Southwest Interactive festival, the annual geek gathering in Austin, Texas, the new Google gadget was the talk of the town – literally. Google’s “talking shoes” crammed a tiny computer, sensors, speakers and a Bluetooth wireless controller into a pair of Adidas that shout at their wearer when they aren’t moving around enough.

Google’s latest venture into wearable technology was more an attention-seeking gimmick than a serious new venture. But with the search giant ploughing significant resources into Google Glass , which embeds a screen, camera, microphone and other sensors into a pair of futuristic spectacles, it’s another indication that Google is serious about moving from the digital to the physical.

Continue reading

Apart from providing more jobs for security experts, wearable computing could create new industries and hybrid professions: data scientists who understand physiology and ethnography, for example.

To begin with, though, the industry needs to get past first base by proving there is a market for such devices. It also needs to solve problems of manufacturing computers that don’t just sit on a desk but can stand up to being worn all day, every day.

Jawbone, best known for its wireless Bluetooth headsets, brought out its UP health band in 2011, a fashion­able bracelet that monitors sleep and daytime activity, with its data uploadable to a smartphone app. But it had to halt production within weeks after users complained the bands were losing their charge.

The flexible, rubberised band was meant to be showerproof but Jawbone discovered it was being overflexed by users, causing cracks in the circuit boards and allowing water to enter.

It had passed industry standard tests but the company found it had needed its own more rigorous testing as it explored the unknown territory of wearables. “The newness of this entire category meant consumers didn’t understand it and even us, as the industry leaders, we realised that we didn’t understand it yet,” says Travis Bogard, head of product management. Jawbone took almost a year perfecting a stronger band before launching it at a price 30 per cent higher than the original.

Most of the current wearable devices confine themselves to health and fitness uses and contain basic technology, such as a motion-sensing pedometer that may offer less than precise readings.

“We had been facing six new competitors and two or three dropped out because their product wasn’t credible in terms of their sensors. People caught on to that pretty quickly,” says Christine Robins, chief executive of Bodymedia, whose armband sensors measure sweat, skin temperature, heat dissipation and motion.

“It’s taking some time but the uptick will come when the data are factually right, and the analytics and algorithms turn that data into something meaningful. Nobody wants 5,000 data points back but if you can start to turn it into insights that can effect behavioural change, that’s the next phase.”

While much of the analysis can take place in the cloud data centres of the internet, the smartphone is the intermediary that is making the new wearable movement possible, as the devices connect to apps over Bluetooth wireless technology or other tethering methods.

Smartphone adoption has reached critical mass: 41 per cent of US mobile phone users had one at the end of 2012, says Forrester Research. “[Wearable tech companies] can piggyback off a display, the processor, the radio, the developer community – there’s this whole infrastructure that’s in place,” says Ms Rotman Epps.

The key to mass consumer acceptance is to add social and “gamification” elements, according to Dave Wang, chief executive of Striiv. His company’s clip-on device relays steps taken or climbed to a smartphone app that rewards the user for completing challenges with points. They can then be exchanged for virtual goods in a game within the app, while friends’ progress can also be tracked.

Just as photos on camera phones needed Instagram’s filters for their distribution to grow, and GPS chips went from preventing you from getting lost to Foursquare’s social check-ins, so the physiological signals that are currently generating charts, graphs and analysis will eventually be moulded into more social experiences, he argues. He also sees more aggregation and “mash-ups” of data in the near future. A lack of developed and open standards is an inhibitor to progress but companies such as Striiv, Bodymedia, and the Runkeeper and MyFitnessPal apps are agreeing to share data to allow users a more complete picture of their health and fitness.

Adoption of the devices should also increase as costs of the hardware falls. “We do see hardware becoming rapidly commoditised,” says Mr Wang. “It’s going to get to a price point where you can start slipping multiple sensors into your shoes, into your pants or into clothing that makes this literally wearable. When it gets to under $10 to make these, they are just going to be everywhere.”

Facebook appears well placed as a future aggregator of data from wearables. “It’s folded in location and photos to its service. Your physical activity is another signal it could pull in,” says Mr Wang.

Apple’s entry with a smart watch could also jump-start the market, although Sonny Vu, chief executive of Misfit Wearables, says positioning a device on a wrist could be too restrictive for many people.

Buyers of Misfit’s Shine wearable activity monitor, which borrows Apple’s minimalist approach to design, have wanted to put this small disc, the size of a quarter, on their wrist, on a chain, around their ankles or even use it as a hairpin.

“As we looked at the wearable space we thought it was a misnomer because the devices were not that wearable. They kind of stuck out,” he says. “We made some bold design decisions: there’s no buttons, no wires, no docking stations, no charging and no display other than some lights that show your progress.”

Devices as non-intrusive and intimate as Shine show how machines are learning how to work with us in the age of wearables, rather than the other way round, says Olof Schybergson, chief executive of Fjord, a design consultancy. He says the look of the products will be crucial to their successful adoption. “Tablets and smartphones say something about you but not nearly as much in terms of style and fashion as something that you wear as part of your outfit.”

But wearables are superficial by nature and cannot provide the level of in-depth data of embedded sensors being developed for the body.

Silicon Valley’s Proteus Digital Health has won regulatory approval for ingestible sensors – pills with chips inside that communicate with a smartphone app as they pass through the body.

Internalising sensors may be the inevitable next step after wearables. But to a public that has yet to embrace health bracelets, this may ultimately prove too hard to swallow.

 

Thursday, March 21, 2013

CIA Chief Tech Officer: Big Data Is The Future And We Own It

Quotes:

"You're already a walking sensor platform," Hunt said, referring to all of the information captured by smartphones. "You are aware of the fact that somebody can know where you are at all times because you carry a mobile device, even if that mobile device is turned off. You know this, I hope? Yes? Well, you should."

In fact Hunt noted that based on the sensors in a smartphone, someone can be identified (with 100 percent accuracy) by the way they walk — implying that someone could be identified even when carrying someone else's phone.

The challenge for the CIA is to find the relevance is the ocean of information when something happens. The first step is for "data scientists" to save and analyze all digital breadcrumbs — even the ones people don't know they are creating (i.e. "More is always better").

"Since you can't connect dots you don't have, it drives us into a mode of, we fundamentally try to collect everything and hang on to it forever," Hunt said. "It is really very nearly within our grasp to be able to compute on all human generated information." 

 

 

CIA Chief Tech Officer: Big Data Is The Future And We Own It

Michael Kelley | Mar. 21, 2013, 1:50 PM | 20,710 | 12

http://www.businessinsider.com/cia-presentation-on-big-data-2013-3#

 

On Wednesday, the CIA's chief technology officer detailed the Agency's vision for collecting and analyzing all of the information people put on the Internet.

The wide-ranging presentation at GigaOM's Structure:Data conference in New York City came two days after it was reported the spy agency is on the verge of signing a cloud computing contract with Amazon — worth up to $600 million over 10 years — that involves Amazon Web Services helping the CIA build a "private cloud" filled with technologies like big data.

After laying out what the CIA does — i.e. collect intelligence, conduct analysis, perform covert action — CIA CTO Ira "Gus" Hunt detailed just how the agency plans to acquire, store, and analyze digital data on a massive scale.

"You're already a walking sensor platform," Hunt said, referring to all of the information captured by smartphones. "You are aware of the fact that somebody can know where you are at all times because you carry a mobile device, even if that mobile device is turned off. You know this, I hope? Yes? Well, you should."

In fact Hunt noted that based on the sensors in a smartphone, someone can be identified (with 100 percent accuracy) by the way they walk — implying that someone could be identified even when carrying someone else's phone.

The challenge for the CIA is to find the relevance is the ocean of information when something happens. The first step is for "data scientists" to save and analyze all digital breadcrumbs — even the ones people don't know they are creating (i.e. "More is always better").

"Since you can't connect dots you don't have, it drives us into a mode of, we fundamentally try to collect everything and hang on to it forever," Hunt said. "It is really very nearly within our grasp to be able to compute on all human generated information." 

He ends with comments about how the "inanimate is becoming sentient," how cognitive machines (e.g. Watson) are going to "explode upon us," and how technology is moving faster than governments, legal systems, and even individuals can keep up.

Check out the key slides from the presentation >


Read more: http://www.businessinsider.com/cia-presentation-on-big-data-2013-3?op=1#ixzz2OEJfJ93Y