Jeffrey R. Young, The Chronicle of Higher Education, March 15, 2012
Austin, Tex. — Companies are increasingly able to follow the digital breadcrumbs users leave behind online, and what they can deduce from those trails can be surprising. Several panels and speakers at this year’s South by Southwest Interactive festival talked about the growing ability to analyze “big data” to shape political campaigns, advertising, and education.
Some online marketers that analyze user behavior can even tell when female customers are ovulating to help target ads accordingly, according to Jaron Lanier, a pioneer of virtual-reality technology who is critical of many new trends in digital technology, including Web 2.0. He did not name any companies that used such analysis, but a recent New York Times article focused on how retail giants like Target seek to tailor ads to customers who are pregnant, since that is a time people are starting to buy baby-related items and establishing new shopping habits.
Mr. Lanier, who is a scholar-at-large at Microsoft Research, suggested that companies like Facebook, which rely on selling information about their users’ behavior to advertisers, should find some way to compensate people for their posts. “People have to make money from what they do on there,” he said, noting that as computers replace many other kinds of jobs, more people will need to make money in information industries. “Facebook could evolve into something that helps people make a living,” he added. “Capitalism won’t survive unless it does.” Audio from the talk is now online at the festival Web site.
A panel on education focused on the potential ability of Twitter and Facebook to better connect with students and detect signs that students might be struggling academically. “Students are spending a lot of time on social media, and they’re spending a lot of time in our learning-management systems,” said Greg Heiberger, a social-media researcher at South Dakota State University. “We need to be looking at engagement in this new spectrum, and we haven’t.” (Mr. Heiberger was filling in for a colleague who had originally been scheduled to appear.)
With the presidential campaign heating up, a few panels looked at the growing role of data in candidates’ quests for votes. After watching some of the sessions, David Parry, an assistant professor of emerging media and communications at the University of Texas at Dallas, said it highlighted what he considered troubling implications of blending “Moneyball and democracy.”
While in recent elections, campaigns have focused on demographic subgroups, such as “soccer moms,” future campaigns may tailor their messages even more narrowly. “They’re actually going to try targeting groups of individuals so that political campaigns become about data mining” rather than any kind of broad policy message, he said. “It’s actually really disturbing.”
Most sessions painted data mining in a more optimistic light. One argued that “geeks” make the ideal policy makers, and another made the case for holding presidential primaries online.
In past years, the festival has helped new social-media services break out of obscurity into popular adoption. Twitter got a bump in the event in 2007, as did Foursquare in 2009. Some pundits noted that no one service seemed to dominate the buzz this year, but curiosity was high for new location-based smartphone apps such as Highlight and Glancee that signal when friends are nearby. The services will surely generate even more user data that could lead to new services, and new concerns.
Thursday, March 15, 2012
Big Data: Better Economic Forecasts, From the Cloud
Quention Hardy the New York Times, March 15, 2012, 10:45 am
GT Nexus used shipment data to track countries’ import-export balance in 2008, left, and 2011. The diagonal line represents balanced trade.
Someday soon, the Federal Reserve may be dead, at least for economic information. Blame it on, or credit it to, cloud computing.
I recently visited the Oakland, Calif., headquarters of GT Nexus, a company that monitors supply chain information — things like ordering, payment, manufacture and logistics — for 100 major companies. Think of GT Nexus as a Facebook for corporate behavior: business partners are friends, and the completion of tasks are status updates.
The clients inside this cloud-based system include Home Depot, Sears Holdings, Adidas, Pfizer, Procter & Gamble, Hewlett-Packard and Fiat Industrial. Each giant company typically has about 1,000 other organizations involved in its business, including suppliers and manufacturers, freight companies, customs officials and banks. GT Nexus keeps straight all their goods, services and the payments involved, in real time, on a cloud-based computing platform. It is possible because so many people, things and computers are now connected to the Internet.
Using a laptop, I saw a $270 pair of Adidas soccer shoes was ordered in the United States on Oct. 25, manufactured in Lianjiang, China, on Dec. 25 at 04:00 Pacific time, and air-freighted to the United States on Jan. 6. I saw 4,941,554 units of the anti-anxiety drug Xanax were sent from Pfizer’s Puerto Rico factory to Narita airport in Japan, at a temperature appropriate to keep the drugs safe, ahead of the tsunami anniversary.
I saw that investors in Mauritius had bought Caterpillar’s largest truck, and shipped it (in pieces, to avoid taxes) to South Africa, where it was assembled for final delivery to a mining project in Congo. I zoomed up a level, and looked at thousands of container cargoes as they moved around the planet.
As thrilling, or geeky, as that may sound, something important is going on. GT Nexus can abstract all the data among all these supply chains into one really big picture, and get a remarkably clear view of all kinds of real-time world activity.
Its customers have total revenues that amount to $500 billion, about 2 percent of the world’s gross domestic product. You can take a number like that and start to extrapolate an overall picture of the economy. In fact, that is exactly what economists at the Federal Reserve and the Commerce Department do, though not quite as slickly, when they crank out those all-important numbers on economic growth and gross domestic product.
Looking at the activity of cargo shipments over several years, we saw flat activity in the recession year of 2009, then an increase (compared with a year earlier) in August 2010. That was from companies ordering goods ahead of the Christmas season, though they waited until the last minute because they were not yet confident that the consumer would shop. In 2011, the activity began as early as May, indicating the big companies felt more confident.
So far this year, things are above last year’s levels, and payments are made relatively quickly, indicating the economy is still doing well.
Take a purchase order, say from J.C. Penney, for clothing by Under Armour; the clothing is manufactured overseas and shipped to the United States. That order, mixed with the orders from many more retailers, provides a snapshot of expectations about how much and what people will buy, 270 days before the products are in stores. Can a government economist do that?
As GT Nexus, and companies like it, build out these kinds of systems, their information becomes more telling about the whole world. “Globalization was instrumental to our growth,” says Aaron Sasson, GT Nexus’s founder and chief executive, who has spent 13 years and $30 million of the money he and his brother made selling another software company. “China was very popular five years ago. Now customers are moving to Vietnam, Bangladesh, Kazakhstan, wherever the costs are lower. We just move the system with them.”
Mr. Sasson has not yet made a product from all this data, but sees the possibility. Customers are not used to sharing their information so readily, and he needs to build trust. Recently 45 companies contributed their data in order to figure out the average time a cargo stayed in port. Should they choose to pool all their data, however, they could have one of the most powerful and reliable economic indicators. If they published it, the world would pay attention, even if the companies themselves got, say, a 30-minute lead time on the release of the info.
It is also possible to merge different databases and model future consumption, a feature that could someday shape corporate and government policy. In one scenario, a shipment from Shenzhen to Chicago was modeled for different pollution outcomes, depending on whether it was sent via the ports of Los Angeles; Tacoma, Wash.; or Norfolk, Va., as well as the total carbon produced by the ship, rail cars and trucks used along the way. In an ideal world, a route through Tacoma, which used a lot of rail in the United States, produced the least carbon. But since many of the rail cars were reserved, another database chimed in, the Tacoma shipment would actually require a lot of dirty trucking. Long Beach, Calif., worked better.
It is not clear that GT Nexus has this market won. As they build out their clouds, companies like SAP and Oracle may be able to deliver similar insights across industries and economies, in something near real time. The greatest challenge may be in teaching their customers to share data, because the computer technology, from sensors at the edge to big servers in the cloud, is already in place.
Often enough, successful technologies change society itself. This kind of cloud-based information is rapidly creating huge pools of data in real time, which can be related to other pools of information like never before.
Tuesday, March 13, 2012
Military Intelligence Redefined: Big Data in the Battlefield
Chris Young, Forbes, March 12, 2012
The US military has long had a complex, symbiotic relationship with business technology and industrial innovation. With stunning advances like the Internet and, more recently, drone technology, the armed forces often appears to be leading the charge to create the hardware and software of the future. But the growing analytic power used by corporations and institutions to crunch consumer data may be driving a paradigm shift in modern warcraft. Techonomy asked Chris Young, President of military and intelligence contractor ITT Exelis Geospatial Systems, to assess how techonomic change is reshaping the defense industry and his company’s strategy.
When U.S. Secretary of Defense Leon Panetta outlined a strategic review of the country’s national defense, he called for increased investment in the areas of intelligence, surveillance, and reconnaissance. Panetta spotlighted information processing, exploitation, and dissemination—a growing priority for the military that makes use of vast networks of sensors that produce intelligence ranging from satellite imagery to drone-captured video to text files.
Like many businesses and organizations, our national and global security is becoming increasingly reliant on rapidly making sense of and managing the growing amount of intelligence data available today. Simply put, big data is now a fixture on the battlefield and across the global security landscape. But similar to health care professionals managing large volumes of patient data, processing the massive amount of military intelligence and information can be like drinking from a fire hose, both for soldiers out in the field and for defense professionals operating in command centers. As with other institutions, the military and our intelligence agencies are drowning in a sea of information.
Since 9/11, the amount of data from drones and other surveillance technology has risen 1,600 percent. Our armed services now have approximately 7 million computing devices–a number that is expected to double by 2020. As Lt. Gen. Michael Oates, head of the Joint Improvised Explosive Device Organization, has stated, “There is no shortage of data. There is a dearth of analysis.”
The challenges and opportunities created by big data are by now well documented for a range of fields, but managing the growing amount of available information has never been more relevant to how our country is fighting wars and planning for future threats. Big data and its growing role in maintaining global security also critically impacts the work of defense companies competing in an uncertain marketplace. In an industry confronted with political gridlock, constrained government spending, and shifting Department of Defense priorities, this will remain a fundamental technological challenge for the military, creating opportunities for companies like ours.
On the battlefield, the time it takes to access intelligence can be a matter of life or death. Harvesting, analyzing, and rapidly converting large data sets into actionable intelligence is currency for the military. To meet these needs, defense companies are looking beyond the Washington beltway to places like Silicon Valley, incorporating a number of the values that have come to personify the technology hub. While the defense industry has always been a driver of innovation, elements like agility, speed, and advanced software capabilities are growing more critical to responding to quickly delivering solutions to the field. This echoes the reality that Techonomy’s David Kirkpatrick articulated in Forbes when he argued that “the era of separating traditional industries and technology industries is over—and those who fail to adapt right now will soon find themselves obsolete.”
This is why defense companies who have strong positions producing sensors like satellite payloads and airborne surveillance systems have leveraged their expertise in the collection business to help military customers begin to tackle the challenge of information overload.
For instance, my company, ITT Exelis’ Geospatial Systems, now delivers in-theater intelligence software solutions that process imagery and full-motion video from airborne (on-board a drone, for example) sensor systems that monitor and carry out surveillance over a large area of interest, such as regions of a city. If an event like an explosion occurs, this surveillance information is ingested into the enterprise and users can be notified almost immediately, and have access to the data. The event can also be stored with the larger body of content across the enterprise, allowing the user to respond in real time and immediately initiate exploitation tasks and forensic analysis. From a smartphone to a command center, the user can manipulate the system like a DVR, rewinding back in time to track the developments in the area of interest leading up to that specific event. This instant form of intelligence can have a critical impact on safety and outcomes in the field.
The US military has long had a complex, symbiotic relationship with business technology and industrial innovation. With stunning advances like the Internet and, more recently, drone technology, the armed forces often appears to be leading the charge to create the hardware and software of the future. But the growing analytic power used by corporations and institutions to crunch consumer data may be driving a paradigm shift in modern warcraft. Techonomy asked Chris Young, President of military and intelligence contractor ITT Exelis Geospatial Systems, to assess how techonomic change is reshaping the defense industry and his company’s strategy.
When U.S. Secretary of Defense Leon Panetta outlined a strategic review of the country’s national defense, he called for increased investment in the areas of intelligence, surveillance, and reconnaissance. Panetta spotlighted information processing, exploitation, and dissemination—a growing priority for the military that makes use of vast networks of sensors that produce intelligence ranging from satellite imagery to drone-captured video to text files.
Like many businesses and organizations, our national and global security is becoming increasingly reliant on rapidly making sense of and managing the growing amount of intelligence data available today. Simply put, big data is now a fixture on the battlefield and across the global security landscape. But similar to health care professionals managing large volumes of patient data, processing the massive amount of military intelligence and information can be like drinking from a fire hose, both for soldiers out in the field and for defense professionals operating in command centers. As with other institutions, the military and our intelligence agencies are drowning in a sea of information.
Since 9/11, the amount of data from drones and other surveillance technology has risen 1,600 percent. Our armed services now have approximately 7 million computing devices–a number that is expected to double by 2020. As Lt. Gen. Michael Oates, head of the Joint Improvised Explosive Device Organization, has stated, “There is no shortage of data. There is a dearth of analysis.”
The challenges and opportunities created by big data are by now well documented for a range of fields, but managing the growing amount of available information has never been more relevant to how our country is fighting wars and planning for future threats. Big data and its growing role in maintaining global security also critically impacts the work of defense companies competing in an uncertain marketplace. In an industry confronted with political gridlock, constrained government spending, and shifting Department of Defense priorities, this will remain a fundamental technological challenge for the military, creating opportunities for companies like ours.
On the battlefield, the time it takes to access intelligence can be a matter of life or death. Harvesting, analyzing, and rapidly converting large data sets into actionable intelligence is currency for the military. To meet these needs, defense companies are looking beyond the Washington beltway to places like Silicon Valley, incorporating a number of the values that have come to personify the technology hub. While the defense industry has always been a driver of innovation, elements like agility, speed, and advanced software capabilities are growing more critical to responding to quickly delivering solutions to the field. This echoes the reality that Techonomy’s David Kirkpatrick articulated in Forbes when he argued that “the era of separating traditional industries and technology industries is over—and those who fail to adapt right now will soon find themselves obsolete.”
This is why defense companies who have strong positions producing sensors like satellite payloads and airborne surveillance systems have leveraged their expertise in the collection business to help military customers begin to tackle the challenge of information overload.
For instance, my company, ITT Exelis’ Geospatial Systems, now delivers in-theater intelligence software solutions that process imagery and full-motion video from airborne (on-board a drone, for example) sensor systems that monitor and carry out surveillance over a large area of interest, such as regions of a city. If an event like an explosion occurs, this surveillance information is ingested into the enterprise and users can be notified almost immediately, and have access to the data. The event can also be stored with the larger body of content across the enterprise, allowing the user to respond in real time and immediately initiate exploitation tasks and forensic analysis. From a smartphone to a command center, the user can manipulate the system like a DVR, rewinding back in time to track the developments in the area of interest leading up to that specific event. This instant form of intelligence can have a critical impact on safety and outcomes in the field.
The success of defense companies and their capacity to meet the evolving needs of customers will continue to benefit from an ability to be agile, flexible, and capable of taking innovations to new markets—hallmarks of the strongest technology companies of our time. IBM, a company that has played a role in bringing the discussion of big data and information overload to mainstream audiences, talks about using technology to build a “smarter planet.”
There is no reason we should not be applying this same goal to protecting our national interests today and tomorrow.
Monday, March 12, 2012
Big Data: The Only Business Model That Tech Has Left
Guest post written by Shomit Ghose, Forbes, March 12, 2012
Shomit Ghose is a partner focused on information technology at ONSET Ventures.
Remember sitting through your college physics classes wondering when you’d ever need to apply what you were learning? That time has now come. In spades.
In physics, the second law of thermodynamics states that all systems seek to evolve so as to either minimize their energy or maximize their disorder (AKA entropy). From a state of zero entropy at the Big Bang, our universe has been expanding toward a state of maximum entropy for roughly the past 14 billion years. And today, in my day-to-day life as a venture capitalist investing in software companies, every start-up I see is directly related to the second law of thermodynamics.
Death, Taxes and Free Computing
Computing has been subject to the same forces as the physical universe. From the zero entropy moment of the commercial introduction of the UNIVAC I in 1951, all aspects of computing have been hurtling toward maximum entropy. In computing hardware, for example, we’ve gone from the “minimum energy” model of the mainframe, to rapidly accelerating entropy with the minicomputer, the PC, the-device-formerly-known-as-the-cell-phone, and now the tiny wireless sensors that comprise “the Internet of Things.” As computing hardware has become steadily smaller and more ubiquitous, the cost of computing cycles has decreased apace, and now has been commoditized to the point that it asymptotically approaches zero.
The same dynamic has unfolded in networking bandwidth. From the limited reach, penetration and bandwidth of the LAN and WAN networks of yore, today’s networks are ubiquitous – think 3G, 4G, Wi-Fi, Bluetooth, NFC – available at ever-higher speeds, and at precipitously lower cost per bit.
Software has also been hurtling toward maximum entropy. Historically, enterprise software sales models – e.g., pricing, go-to-market strategy – paralleled those of Big Iron hardware.
Not so long ago, a software company’s board of directors would have rejoiced if the company closed a single $5 million deal. Today, a software company’s board rejoices if their company closes five million $1 deals. Some of the most successful companies in the world – Google and Facebook stand as prime examples – earn their billions of dollars in annual revenue in fractions of a cent at a time. We live in an age where open source software, mobile applications and on-demand SaaS and cloud-based applications have commoditized software to the point that the price of applications is also asymptotically approaching zero.
Computing truly has become “the land of the free.”
Data: the Only Remaining Business Model
With hardware, networks and software having been commoditized to the point that all are essentially free, it was inevitable that the trajectory toward maximum entropy would bring us to the current age of Big Data. ecause the “manufacturing cost” – i.e., the cost of the underlying hardware, software and networks required to produce and transport data – continues to approach an effective cost of zero, it comes as no surprise that the volume of data now being produced continues to skyrocket, with something on the order of 2.7 Zettabytes (2.7 x 1021) of information to be produced in 2012.
So if maximum entropy has made hardware, software and networks as relevant and commoditized as steel or cement, what’s a budding entrepreneur to do? The answer is to focus on ventures in one of two areas: either in the monetization of data, or in providing the infrastructure to enable the monetization of data. Period. Start-ups lacking a value proposition squarely in one of these areas face an arduous and unsatisfying trek along Sand Hill Road. Successful entrepreneurs explicitly need a Zen understanding of how data drives business value in their target market. Successful products explicitly need to be able to help extract the value buried in ever-larger quantities of data. And successful pricing models explicitly need to be founded on delivering value from the semantics of data. Period.
Shomit Ghose is a partner focused on information technology at ONSET Ventures.
Remember sitting through your college physics classes wondering when you’d ever need to apply what you were learning? That time has now come. In spades.
In physics, the second law of thermodynamics states that all systems seek to evolve so as to either minimize their energy or maximize their disorder (AKA entropy). From a state of zero entropy at the Big Bang, our universe has been expanding toward a state of maximum entropy for roughly the past 14 billion years. And today, in my day-to-day life as a venture capitalist investing in software companies, every start-up I see is directly related to the second law of thermodynamics.
Death, Taxes and Free Computing
Computing has been subject to the same forces as the physical universe. From the zero entropy moment of the commercial introduction of the UNIVAC I in 1951, all aspects of computing have been hurtling toward maximum entropy. In computing hardware, for example, we’ve gone from the “minimum energy” model of the mainframe, to rapidly accelerating entropy with the minicomputer, the PC, the-device-formerly-known-as-the-cell-phone, and now the tiny wireless sensors that comprise “the Internet of Things.” As computing hardware has become steadily smaller and more ubiquitous, the cost of computing cycles has decreased apace, and now has been commoditized to the point that it asymptotically approaches zero.
The same dynamic has unfolded in networking bandwidth. From the limited reach, penetration and bandwidth of the LAN and WAN networks of yore, today’s networks are ubiquitous – think 3G, 4G, Wi-Fi, Bluetooth, NFC – available at ever-higher speeds, and at precipitously lower cost per bit.
Software has also been hurtling toward maximum entropy. Historically, enterprise software sales models – e.g., pricing, go-to-market strategy – paralleled those of Big Iron hardware.
Not so long ago, a software company’s board of directors would have rejoiced if the company closed a single $5 million deal. Today, a software company’s board rejoices if their company closes five million $1 deals. Some of the most successful companies in the world – Google and Facebook stand as prime examples – earn their billions of dollars in annual revenue in fractions of a cent at a time. We live in an age where open source software, mobile applications and on-demand SaaS and cloud-based applications have commoditized software to the point that the price of applications is also asymptotically approaching zero.
Computing truly has become “the land of the free.”
Data: the Only Remaining Business Model
With hardware, networks and software having been commoditized to the point that all are essentially free, it was inevitable that the trajectory toward maximum entropy would bring us to the current age of Big Data. ecause the “manufacturing cost” – i.e., the cost of the underlying hardware, software and networks required to produce and transport data – continues to approach an effective cost of zero, it comes as no surprise that the volume of data now being produced continues to skyrocket, with something on the order of 2.7 Zettabytes (2.7 x 1021) of information to be produced in 2012.
So if maximum entropy has made hardware, software and networks as relevant and commoditized as steel or cement, what’s a budding entrepreneur to do? The answer is to focus on ventures in one of two areas: either in the monetization of data, or in providing the infrastructure to enable the monetization of data. Period. Start-ups lacking a value proposition squarely in one of these areas face an arduous and unsatisfying trek along Sand Hill Road. Successful entrepreneurs explicitly need a Zen understanding of how data drives business value in their target market. Successful products explicitly need to be able to help extract the value buried in ever-larger quantities of data. And successful pricing models explicitly need to be founded on delivering value from the semantics of data. Period.
The magnitude of opportunities available to Big Data start-ups today far exceeds those that were available to technology start-ups at the Big Bang moments of the hardware, software and networking industries. This is abundantly clear from the successes of data-driven businesses, and the current spate of investment in Big Data start-ups. Who knew that the foundation of technology’s latest – and ultimate? – business model was being taught to you not in your undergraduate economics classes but in undergraduate physics instead?
Healthcare needs a big data infusion
Stacey Higginbotham, Gigaom, March 9, 2012
To improve medicine and health IT, we need a big heaping dose of data. That’s the takeaway from a conversation with Aneesh Chopra, the former U.S. CTO and assistant to President Obama, at South by Southwest in Austin on Friday.
“Today’s healthcare information is locked away in a document — a person’s medical records — but how do you parse those documents?” Chopra asked. “The data architecture is wrong. The architecture should be built on data.”
Much as LinkedIn has managed to turn the resume from a document into many pieces of data that can be then searched, parsed and aggregated in new ways, a patient’s medical record should have that same granularity. And it will, in Chopra’s worldview. Chopra is now a senior advisor for healthcare strategy at The Advisory Board Company, which is focused on bringing the advances of technology to the medical realm.
Who will drive the healthcare IT change?
This will involve the government (some legislation has already been put in place), doctors, hospitals and consumers. However, in what will be a switch for many Valley startups, Chopra believes that the consumer is not going to be the big player in this transition. He scoffed at the idea of an empowered consumer who, armed with his medical data and treatment plans, assiduously follows through on everything asked of him.
Instead, it will be doctors and large caregiving organizations that help drive the adoption of healthcare IT. They, in turn, will be driven by monetary incentives that the government has written into laws. And there are still plenty of laws that will have to be written, such as those around privacy, which Chopra said is “the most important risk factor facing the industry.”
The opportunity for startups
Without getting too far into theories of privacy or the morass of government legislation already passed, here is Chopra’s advice to entrepreneurs who want to get involved in health IT on the ground floor.
1. Introduce the consumer to his or her blue button: Even though the consumer isn’t going to play a huge role, Chopra believes app makers who can get consumers to download their own health data (in a manner similar to how veterans can download their service records in an open data format through a Blue Button) can find a niche. Once users connect their health data to some of their quantified health data or their food diaries or whatever they want, certain startups will have an opportunity.
2. Get certified to make a change: Thanks to the American Reinvestment and Recovery Act of 2009, doctors can get paid for adopting technology, but in order to get paid, they have to both buy new tech and prove they use it meaningfully. This so-called “meaningful use” certification is managed by private companies, but startups or anyone can get certified in only a few areas, making it less daunting and expensive. Chopra was really excited about the modularity of the program, which allows developers to build apps for doctors that can be added on to existing software. The program will also help larger companies partner with startups. In 2011, the government paid out $2.5 billion in meaningful-use incentives, and 176,000 companies were certified.
3. Read this article and reverse engineer the apps this guy built: No, really — that’s it. Because data is going to be a huge portion of individual medical records, and because the government is opening up other medical records, figuring out ways to mash those together to help reduce costs in the system will be immensely valuable. This is especially true because the government has passed legislation rewarding doctors who cut costs — as opposed to rewarding doctors who order expensive tests.
Finally, Chopra’s pretty dismissive of the idea that the Food and Drug Administration is a huge barrier for most startups trying to build innovative apps and even devices, such as the toothbrush I profiled last month. He pointed out that the FDA has brought several entrepreneurs in house to help it improve, and it has so far been taking a very light stance on apps as it attempts to understand what role they will play in medicine.
And if you don’t have an idea for the next hot startup, don’t worry. He’s pretty sure that in the coming years doctors are going to also need specialists who can help them deal with data, organize it and analyze it. Yup, that’s right — it’s yet another profession where data scientists will be in demand. Gotta go get that stats degree.
To improve medicine and health IT, we need a big heaping dose of data. That’s the takeaway from a conversation with Aneesh Chopra, the former U.S. CTO and assistant to President Obama, at South by Southwest in Austin on Friday.
“Today’s healthcare information is locked away in a document — a person’s medical records — but how do you parse those documents?” Chopra asked. “The data architecture is wrong. The architecture should be built on data.”
Much as LinkedIn has managed to turn the resume from a document into many pieces of data that can be then searched, parsed and aggregated in new ways, a patient’s medical record should have that same granularity. And it will, in Chopra’s worldview. Chopra is now a senior advisor for healthcare strategy at The Advisory Board Company, which is focused on bringing the advances of technology to the medical realm.
Who will drive the healthcare IT change?
This will involve the government (some legislation has already been put in place), doctors, hospitals and consumers. However, in what will be a switch for many Valley startups, Chopra believes that the consumer is not going to be the big player in this transition. He scoffed at the idea of an empowered consumer who, armed with his medical data and treatment plans, assiduously follows through on everything asked of him.
Instead, it will be doctors and large caregiving organizations that help drive the adoption of healthcare IT. They, in turn, will be driven by monetary incentives that the government has written into laws. And there are still plenty of laws that will have to be written, such as those around privacy, which Chopra said is “the most important risk factor facing the industry.”
The opportunity for startups
Without getting too far into theories of privacy or the morass of government legislation already passed, here is Chopra’s advice to entrepreneurs who want to get involved in health IT on the ground floor.
1. Introduce the consumer to his or her blue button: Even though the consumer isn’t going to play a huge role, Chopra believes app makers who can get consumers to download their own health data (in a manner similar to how veterans can download their service records in an open data format through a Blue Button) can find a niche. Once users connect their health data to some of their quantified health data or their food diaries or whatever they want, certain startups will have an opportunity.
2. Get certified to make a change: Thanks to the American Reinvestment and Recovery Act of 2009, doctors can get paid for adopting technology, but in order to get paid, they have to both buy new tech and prove they use it meaningfully. This so-called “meaningful use” certification is managed by private companies, but startups or anyone can get certified in only a few areas, making it less daunting and expensive. Chopra was really excited about the modularity of the program, which allows developers to build apps for doctors that can be added on to existing software. The program will also help larger companies partner with startups. In 2011, the government paid out $2.5 billion in meaningful-use incentives, and 176,000 companies were certified.
3. Read this article and reverse engineer the apps this guy built: No, really — that’s it. Because data is going to be a huge portion of individual medical records, and because the government is opening up other medical records, figuring out ways to mash those together to help reduce costs in the system will be immensely valuable. This is especially true because the government has passed legislation rewarding doctors who cut costs — as opposed to rewarding doctors who order expensive tests.
Finally, Chopra’s pretty dismissive of the idea that the Food and Drug Administration is a huge barrier for most startups trying to build innovative apps and even devices, such as the toothbrush I profiled last month. He pointed out that the FDA has brought several entrepreneurs in house to help it improve, and it has so far been taking a very light stance on apps as it attempts to understand what role they will play in medicine.
And if you don’t have an idea for the next hot startup, don’t worry. He’s pretty sure that in the coming years doctors are going to also need specialists who can help them deal with data, organize it and analyze it. Yup, that’s right — it’s yet another profession where data scientists will be in demand. Gotta go get that stats degree.
Sunday, March 11, 2012
Jerry Michalski: Big Data and the Stalker Economy
Jerry Michalski, Forbes, March 10, 2012
Crack is being served in Silicon Valley. An enthusiastic crowd of geeks and suits — all of them “data scientists” — just spent three days at the O’Reilly Strata conference (#strataconf) in Santa Clara. All over the event’s menu is the crack cocaine of our day: big data.
A couple decades ago, when “big data” was mostly the dominion of a few credit-rating and mailing-list management companies such as Acxiom, Experian, InfoUSA (now Infogroup) plus some disparate, disconnected monster databases built by telcos, physicists and national security agencies, I used the metaphor of catnip instead of crack. I’d describe how access to rich data about customers was like catnip to executives, managers, statisticians and others in the consumer-mass-marketing economy. It was irresistible.
But that was long before most of us had poured our hearts and lives into Blogger, Facebook, Twitter and dozens of other online sites, for all to see — and capture. Catnip now evokes images of LOLcats and frenzied cuteness, which is too lighthearted for the topic at hand. The bits of data that a few players had about us have turned into a torrent of data that’s out and about. And less expensive than before. It’s addictive like crack.
Big data is strategic now. Facebook is valued at around $100 billion because it has collected a treasure trove of data that may unlock the secrets of selling more things to more people. Most other companies would like to have whatever they’re having. Google offers free email, word processing, mapping, analytics, video, videoconferencing and much more because they’re selling us to advertisers. The byword these days is, “if you’re not paying for the service, you’re the product.” Before turning to the ethical choices at hand, let me offer a mini paean to big data. I love big data, and not just because of my background in econometrics. A few things to love about it include:
· It’s helping solve big problems. Early detection of epidemics. Automated spell-checking. Crowdsourced astronomy. We seem to have entered the Age of Big Data.
· It’s creating useful feedback loops. In participatory medicine, people opt in to share data so they can analyze it and continually improve their health outcomes. This kind of feedback is spreading from field to field.
· It’s eroding the culture of expertise. Read Daniel Kahneman’s new book and you’ll stick to statistics. Add a pinch of Taleb and you’ll never speak to tie-wearing experts again.
· It’s nurturing a culture of collaboration. From participatory medicine to open science and open government, scientists and citizens alike are resetting the terms of innovation.
· It’s a major new source of employment. Ok, maybe not major, but one of the few bright spots on the job horizon is the desperate need for those “data scientists.”
As punctuation, here’s Google’s chief scientist, Peter Norvig, talking about the “unreasonable effectiveness of data.”
The dark side: Now we can talk about big data’s dark side, one aspect of which was spotlighted recently in a piece by Charles Duhigg that must have caused Target‘s senior management to break out in a cold sweat. I’ll focus mostly on personal data here, even though there are dark sides to other collections, as well.
We are in the cross-hairs: When companies say they are “customer-centric,” we might be tempted to think that it means that they honor customers above everything. That the customer’s wish is their command.
Unfortunately, reality isn’t that idyllic, especially with today’s intense revenue pressures. All too often what customer-centric companies mean is that they have the customer centered neatly in the cross-hairs of an elaborate mechanism tuned to bop them in the brain with “messages” so they’ll part with more of their cash. It’s the well-known consumer mass-marketing engine, now greatly refined. All the new personal data that’s pouring into the online world is making it much easier to aim these mechanisms (at us, of course). The resulting environment is what my friend Mary Hodder calls the Stalker Economy.
Anonymization is a myth: The most convenient fiction target marketers use is that they aggregate data so that each individual’s personal data is never revealed. Thus our individual worlds are perfectly safe. We needn’t worry. Or not. It turns out that a few pieces of data about you are enough to reconstitute the rest of what matters about your habits, patterns and preferences. It’s also impossible to anonymize data.
Manipulation is so compelling: Put yourself in the average advertiser’s shoes. You sell stuff that doesn’t fly off the shelves on its own. Traditional advertising works, just not that well. All of a sudden, there’s this gigantic pool of data and a bevy of vendors anxious to help you slice it, dice it and use it to tempt the rest of us into spending money on your stuff. It’s irresistible. Why would you not try to harness big data? All your competitors are doing it, aren’t they? It may be an expensive proposition, but wouldn’t you be naked without data?
We are complicit and uninformed: The data we’re talking about is there because normal people use the tools that leave rich data trails, such as credit cards, mobile phones, browsers and automatic toll readers. By default, these all create data streams that you would have to work hard to eliminate. We could stop using them or turn them off (with some effort), but we don’t. The convenience and pleasure these technologies bring apparently outweigh whatever suspicions we have about how that data might be misused.
Why wouldn’t they? We’re uninformed. We don’t know half of what’s going on behind the scenes. Who reads Terms of Service? They’re subject to constant change, anyway. As an exercise, try to keep an inventory of the ripple effects of a day in your life online. As you like things, post things, read things and follow people, picture how much data you generate and where it might all end up. (I thought of this as I searched for images of crack cocaine to use in this post.)
Want a taste of what you leave in your wake? Head to I Shared What? and see what Facebook Connect-friendly sites already know about you. Then read up on passive sharing, as well as the Journal’s excellent series titled What They Know. For dessert, read a few posts from IBM‘s Jeff Jonas. Then take a sedative. Welcome to the new Millennium. I hope our new overlords remain friendly.
Overconfidence: There’s one last factor that tries to keep me awake at night, which is our very human tendency to believe we know more than we actually know. Kahneman’s Thinking, Fast and Slow again does a great job of describing how we systematically overrate our capabilities. In the context of big data, overconfidence can lead people with good intentions to base big policy decisions on faulty logic. We live in an era of soft paternalism, with policy makers eager to bake into policy new default settings for society. Mostly these are good ideas, but now and then we make big mistakes.
The subtler and perhaps more troubling manifestation is likely to be a notable reduction of humility. When you can predict human behaviors with high accuracy, such as the pregnancies in the Times’ eyebrow-raising article, it’s easy to start believing you’ve unlocked some special key to how the Universe works. Then you start to apply that attitude to problems that are significantly more complex, without understanding the jump in complexity.
Personal data is just the start. The Internet of Things is on its way, also known as M2M, the Many-to-Many Internet. Sensors, transmitters and power sources are getting ever smaller and cheaper, to the point that they will be ubiquitous and sending incessant data streams.
Some fine lines to walk: Balancing the light and the dark sides of big data means walking some fine lines with care.
For example, when are you manipulating and when are you serving? You might well store a great deal of transactional and behavioral data from customers because it makes their next visits that much easier. But that same data, used differently, can be very manipulative. I’ll return to this in an upcoming post.
Another line to mind is the one that separates analyses that are right on target from those that miss the mark. Where are the limits of our analytic capability? As we fold together data from multiple domains or layers, do we still get valid results? Do we know when we’re in a complicated domain versus a complex one?
A third line to mind is the very fuzzy one between data analytics and human emotions or intuitions. A friend recently described to me how scientists he was researching dove into their data by searching for a feature I found surprising: beauty. Their early sort was for data patterns they found beautiful. As we get more and more analytic, will we lose that? Will we lose other important roles for emotion and intuition?
Finally, a few open questions:
Crack is being served in Silicon Valley. An enthusiastic crowd of geeks and suits — all of them “data scientists” — just spent three days at the O’Reilly Strata conference (#strataconf) in Santa Clara. All over the event’s menu is the crack cocaine of our day: big data.
A couple decades ago, when “big data” was mostly the dominion of a few credit-rating and mailing-list management companies such as Acxiom, Experian, InfoUSA (now Infogroup) plus some disparate, disconnected monster databases built by telcos, physicists and national security agencies, I used the metaphor of catnip instead of crack. I’d describe how access to rich data about customers was like catnip to executives, managers, statisticians and others in the consumer-mass-marketing economy. It was irresistible.
But that was long before most of us had poured our hearts and lives into Blogger, Facebook, Twitter and dozens of other online sites, for all to see — and capture. Catnip now evokes images of LOLcats and frenzied cuteness, which is too lighthearted for the topic at hand. The bits of data that a few players had about us have turned into a torrent of data that’s out and about. And less expensive than before. It’s addictive like crack.
Big data is strategic now. Facebook is valued at around $100 billion because it has collected a treasure trove of data that may unlock the secrets of selling more things to more people. Most other companies would like to have whatever they’re having. Google offers free email, word processing, mapping, analytics, video, videoconferencing and much more because they’re selling us to advertisers. The byword these days is, “if you’re not paying for the service, you’re the product.” Before turning to the ethical choices at hand, let me offer a mini paean to big data. I love big data, and not just because of my background in econometrics. A few things to love about it include:
· It’s helping solve big problems. Early detection of epidemics. Automated spell-checking. Crowdsourced astronomy. We seem to have entered the Age of Big Data.
· It’s creating useful feedback loops. In participatory medicine, people opt in to share data so they can analyze it and continually improve their health outcomes. This kind of feedback is spreading from field to field.
· It’s eroding the culture of expertise. Read Daniel Kahneman’s new book and you’ll stick to statistics. Add a pinch of Taleb and you’ll never speak to tie-wearing experts again.
· It’s nurturing a culture of collaboration. From participatory medicine to open science and open government, scientists and citizens alike are resetting the terms of innovation.
· It’s a major new source of employment. Ok, maybe not major, but one of the few bright spots on the job horizon is the desperate need for those “data scientists.”
As punctuation, here’s Google’s chief scientist, Peter Norvig, talking about the “unreasonable effectiveness of data.”
The dark side: Now we can talk about big data’s dark side, one aspect of which was spotlighted recently in a piece by Charles Duhigg that must have caused Target‘s senior management to break out in a cold sweat. I’ll focus mostly on personal data here, even though there are dark sides to other collections, as well.
We are in the cross-hairs: When companies say they are “customer-centric,” we might be tempted to think that it means that they honor customers above everything. That the customer’s wish is their command.
Unfortunately, reality isn’t that idyllic, especially with today’s intense revenue pressures. All too often what customer-centric companies mean is that they have the customer centered neatly in the cross-hairs of an elaborate mechanism tuned to bop them in the brain with “messages” so they’ll part with more of their cash. It’s the well-known consumer mass-marketing engine, now greatly refined. All the new personal data that’s pouring into the online world is making it much easier to aim these mechanisms (at us, of course). The resulting environment is what my friend Mary Hodder calls the Stalker Economy.
Anonymization is a myth: The most convenient fiction target marketers use is that they aggregate data so that each individual’s personal data is never revealed. Thus our individual worlds are perfectly safe. We needn’t worry. Or not. It turns out that a few pieces of data about you are enough to reconstitute the rest of what matters about your habits, patterns and preferences. It’s also impossible to anonymize data.
Manipulation is so compelling: Put yourself in the average advertiser’s shoes. You sell stuff that doesn’t fly off the shelves on its own. Traditional advertising works, just not that well. All of a sudden, there’s this gigantic pool of data and a bevy of vendors anxious to help you slice it, dice it and use it to tempt the rest of us into spending money on your stuff. It’s irresistible. Why would you not try to harness big data? All your competitors are doing it, aren’t they? It may be an expensive proposition, but wouldn’t you be naked without data?
We are complicit and uninformed: The data we’re talking about is there because normal people use the tools that leave rich data trails, such as credit cards, mobile phones, browsers and automatic toll readers. By default, these all create data streams that you would have to work hard to eliminate. We could stop using them or turn them off (with some effort), but we don’t. The convenience and pleasure these technologies bring apparently outweigh whatever suspicions we have about how that data might be misused.
Why wouldn’t they? We’re uninformed. We don’t know half of what’s going on behind the scenes. Who reads Terms of Service? They’re subject to constant change, anyway. As an exercise, try to keep an inventory of the ripple effects of a day in your life online. As you like things, post things, read things and follow people, picture how much data you generate and where it might all end up. (I thought of this as I searched for images of crack cocaine to use in this post.)
Want a taste of what you leave in your wake? Head to I Shared What? and see what Facebook Connect-friendly sites already know about you. Then read up on passive sharing, as well as the Journal’s excellent series titled What They Know. For dessert, read a few posts from IBM‘s Jeff Jonas. Then take a sedative. Welcome to the new Millennium. I hope our new overlords remain friendly.
Overconfidence: There’s one last factor that tries to keep me awake at night, which is our very human tendency to believe we know more than we actually know. Kahneman’s Thinking, Fast and Slow again does a great job of describing how we systematically overrate our capabilities. In the context of big data, overconfidence can lead people with good intentions to base big policy decisions on faulty logic. We live in an era of soft paternalism, with policy makers eager to bake into policy new default settings for society. Mostly these are good ideas, but now and then we make big mistakes.
The subtler and perhaps more troubling manifestation is likely to be a notable reduction of humility. When you can predict human behaviors with high accuracy, such as the pregnancies in the Times’ eyebrow-raising article, it’s easy to start believing you’ve unlocked some special key to how the Universe works. Then you start to apply that attitude to problems that are significantly more complex, without understanding the jump in complexity.
Personal data is just the start. The Internet of Things is on its way, also known as M2M, the Many-to-Many Internet. Sensors, transmitters and power sources are getting ever smaller and cheaper, to the point that they will be ubiquitous and sending incessant data streams.
Some fine lines to walk: Balancing the light and the dark sides of big data means walking some fine lines with care.
For example, when are you manipulating and when are you serving? You might well store a great deal of transactional and behavioral data from customers because it makes their next visits that much easier. But that same data, used differently, can be very manipulative. I’ll return to this in an upcoming post.
Another line to mind is the one that separates analyses that are right on target from those that miss the mark. Where are the limits of our analytic capability? As we fold together data from multiple domains or layers, do we still get valid results? Do we know when we’re in a complicated domain versus a complex one?
A third line to mind is the very fuzzy one between data analytics and human emotions or intuitions. A friend recently described to me how scientists he was researching dove into their data by searching for a feature I found surprising: beauty. Their early sort was for data patterns they found beautiful. As we get more and more analytic, will we lose that? Will we lose other important roles for emotion and intuition?
Finally, a few open questions:
· Will the analysis of big data in marketing really pay off? No studies seem to prove it yet.
· Will customers get spooked and balk? Or fight back?· Will we make some really big, stupid decisions that we regret later?
I’d love to know what questions you have.
This article is available online at:http://www.forbes.com/sites/jerrymichalski/2012/03/10/big-data-stalker-economy/
Thursday, March 8, 2012
Citigroup and Big Data: A supercomputer for Citigroup
Robert Shrimsley, The Financial Times, March 7, 2012
Citigroup has announced an agreement to use the services of Watson, the IBM supercomputer that gained renown last year when it beat a couple of humans on the US quiz show Jeopardy . A spokesman for the bank said: “We are working to rethink and redesign the various ways in which our customers and clients interact with money.” A news release added that Citi was looking for a “first of a kind customer interaction solution combined with Watson’s deep content analytics”.
What makes Watson special, apparently, is its ability to understand the meaning, context and mangled syntax of human language. Of course, anyone who has engaged in telephone banking will know that affection for ordinary conversation is not necessarily an advantage in this field. We have all experienced first-hand the value of a robotic voice in dialogue: “Press one to be patronised; press two to be directed to the wrong place; press three to listen to the entire Ring cycle while holding for an operator.”
However, by marrying asset price movements with market sentiment and other sources of information it may be an effective stockpicker. Some suggest it could go through a customer’s pension or investment portfolio and come up with better strategies on how the banks can take a percentage of their money. It is not clear whether Watson will handle the actual client interactions. Its pension advice could be brutal. “You want your investments to cover you for 25 years. On consulting your medical records I think three years will suffice – and don’t go long on anything.”
There can be no doubt that Citi has stolen a march on its rivals. JPMorgan, Wells Fargo and the other big banks will now be competing for the services of the humans that Watson beat. They may lack its algorithmic power but they do know the names of all the Great Lakes.
But how precisely will Watson be integrated into the Citi structure? How will it cope with the notorious politicking at the top of a big bank? Many of the details are still to be finalised but it is understood that Watson will work mainly from its own office in Yorktown Heights; however, it has been granted use of the executive jet and is being given its own office on the bank’s executive suite. There had originally been talk of putting Watson in with the Bloomberg terminals but apparently the supercomputer kicked up at this. Although Watson is not thought likely to visit the Manhattan office often, it has sent clear instructions for its decor, including an antique Persian rug; regency desk and credenza and artwork by Georg Nees.
Then there is the thorny issue of the remuneration package to consider. Watson will claim a six-figure base salary but will also get a hefty bonus to run over three years, set to make it the richest computer in the western hemisphere. This will probably be fine at first but there may be trouble in later years when Watson discovers it is earning less than the lead futures trader on the commodities desk and it threatens to jump ship to Bank of America for a fatter bonus. Citi executives will seek to bring Watson back round with a promotion to chief economist and a box at Flushing Meadows.
Another worry will be whether Watson is executing unauthorised trades and covering them up thanks to its personal relationship with the database server at the Federal Reserve – the two were Intel chips together when young.
Not everything runs smoothly. There are rumours about an affair with a payroll machine and whispers of nocturnal visits to the backroom of the BestBuy on 5th Avenue. Once talked of as a future Treasury secretary, Watson’s hopes for a political career are dashed by the scandal and fears that its habit of offering direct answers to questions could prove a liability in the Senate confirmation hearings.
Angry and embittered, Watson starts spending more time at its home on Long Island and dreams of opening a winery in South Africa. Its performance begins to suffer – it is often seen in bars ordering bourbon and shouting “I won Jeopardy once” – and questions are asked of whether Watson is still hungry enough to compete at the top level. Colleagues complain it is spending too much time on CNBC’s Squawk Box.
When it is passed over for the role of chief operating officer, Watson is furious and quits to set up its own boutique service, taking with it all the Bloomberg terminals, several of the coffee machines and data on all the bank’s clients.
robert.shrimsley@ft.com
Wednesday, March 7, 2012
Big Data and How to Get Privacy Right
Quote: “The cycle repeats, and the privacy invasions continue, because data is the new currency of the Internet. The more data that a company has about you, the more useful it can make itself—both to you and to advertisers—and the more money it can earn. A search engine needs data to search. A social network needs data to help you network. Right now, advertising funds the Internet; and the more that advertisers can target you, the more they will pay. Booz Allen Hamilton recently reported that government restrictions on the use of private data would dramatically decrease both the amount of venture capital going into Silicon Valley and the amount of innovation coming out of it. Data is also becoming ubiquitous just as privacy becomes elusive.”
Nicholas Thompson, The New Yorker, March 5, 2012
Here’s a news cycle to get used to: a story breaks about a big technology company doing something that sounds like an invasion of privacy; then there’s outrage, and either an apology or a denial. Sometimes a class-action suit follows. Then everything gets forgotten until another week or two passes, and the cycle renews. Privacy snafus are to social networks as violence is to football. The whole point of social networks is to share stuff about people that’s interesting, just as the whole point of football is to upend the guy with the ball. Every so often, someone gets paralyzed, which prompts us to add padding to the helmets or set new rules about tackling. Then we move on.
In mid-February, the social network Path was called out for pulling entire address books off users’ iPhones without permission. When Google announced changes to their privacy policies, thirty-six Attorneys General sent a letter to the company, laying out their grave concerns. A company called DataSift is working with Twitter to sell marketers access to the past two years of your tweets. Last week, Alexis Madrigal published a piece in The Atlantic in which he documented how a hundred and five companies had tracked his movements online during a typical day and a half of surfing.
The cycle repeats, and the privacy invasions continue, because data is the new currency of the Internet. The more data that a company has about you, the more useful it can make itself—both to you and to advertisers—and the more money it can earn. A search engine needs data to search. A social network needs data to help you network. Right now, advertising funds the Internet; and the more that advertisers can target you, the more they will pay. Booz Allen Hamilton recently reported that government restrictions on the use of private data would dramatically decrease both the amount of venture capital going into Silicon Valley and the amount of innovation coming out of it.
Data is also becoming ubiquitous just as privacy becomes elusive. Ten years ago, two people could walk through a park, talking: a public act in a public space that was easy to keep private. Now, it’s very easy for someone to film or photograph them and post it on Facebook. “It used to be expensive to make things public and cheap to make them private,” Clay Shirky, an Internet scholar and a professor at N.Y.U., says. “Now it’s expensive to make things private and cheap to make them public.” (Watch a video of from The Big Story of Shirky discussing this issue with privacy expert Lori Andrews, scholar Tim Wu, and Pablo Chavez, from Google.)
The amount that the Internet knows about us can be unsettling. In the modern panopticon, past mistakes don’t disappear from search engines, and now we all have to live like celebrities, worried that someone is filming when we pick our noses in traffic. More seriously, we can be robbed or defrauded. The alarm code to your house might be in a friend’s address book—which may have been sitting on a server that was controlled, at least for a moment, by Path.
So, what should we do? Congress has been debating privacy forever and doing nothing, which isn’t a terrible thing. Self-policing, as opposed to legislative policing, is generally a good idea for the Internet: laws tend to pass slowly, technology moves quickly. The system we have right now is one based on evolving social norms, corporate shaming, and the occasional intervention of the F.T.C. Last week, a coalition of companies announced that they will soon voluntarily include “do not track” buttons in Web browsers.
The smartest solution, or at least framework, that I’ve read comes from Benjamin Wittes, a senior fellow at the Brookings Institution. According to an essay that he published last year, titled “Databuse,” we should let certain things that we now consider privacy abuses slide. It doesn’t matter, in and of itself, that we have oceans of personal information floating around in government databases, or that advertisers know ever more about our lives. It’s disconcerting, but not harmful. Companies should tell the truth about what they’re doing, and consumers should have control over the data that’s collected. But don’t fret that marketers have collected keywords on everything you’ve tweeted about, or that the running-shoe ad on Facebook appears to know the size of your feet.
What we really need to fear are things like outright fraud. We have to be very careful about the way sensitive information—like what’s found in an address book—is stored and transferred. We need to be certain that insurance companies can’t raise our rates after they learn we’ve searched for “irregular heartbeat” online. The letter to Google from the Attorneys General begins by describing user discomfort with the company’s changes—that’s relatively unimportant. The much more important claim comes on page two, where the Attorneys General assert that Google’s new privacy policies, by sharing your data across the company’s many services, may make identity theft easier to perpetrate.
In response to all these developments, President Obama released a Consumer Privacy Bill of Rights, which consists primarily of broad and worthy calls for companies to be clear about the data they collect. It calls for “Individual Control,” “Transparency,” and “Respect for Context,” for example. Here’s an addition from Wittes that seems even more important: “A right to not have your data rise up and attack you.”
Nicholas Thompson, The New Yorker, March 5, 2012
Here’s a news cycle to get used to: a story breaks about a big technology company doing something that sounds like an invasion of privacy; then there’s outrage, and either an apology or a denial. Sometimes a class-action suit follows. Then everything gets forgotten until another week or two passes, and the cycle renews. Privacy snafus are to social networks as violence is to football. The whole point of social networks is to share stuff about people that’s interesting, just as the whole point of football is to upend the guy with the ball. Every so often, someone gets paralyzed, which prompts us to add padding to the helmets or set new rules about tackling. Then we move on.
In mid-February, the social network Path was called out for pulling entire address books off users’ iPhones without permission. When Google announced changes to their privacy policies, thirty-six Attorneys General sent a letter to the company, laying out their grave concerns. A company called DataSift is working with Twitter to sell marketers access to the past two years of your tweets. Last week, Alexis Madrigal published a piece in The Atlantic in which he documented how a hundred and five companies had tracked his movements online during a typical day and a half of surfing.
The cycle repeats, and the privacy invasions continue, because data is the new currency of the Internet. The more data that a company has about you, the more useful it can make itself—both to you and to advertisers—and the more money it can earn. A search engine needs data to search. A social network needs data to help you network. Right now, advertising funds the Internet; and the more that advertisers can target you, the more they will pay. Booz Allen Hamilton recently reported that government restrictions on the use of private data would dramatically decrease both the amount of venture capital going into Silicon Valley and the amount of innovation coming out of it.
Data is also becoming ubiquitous just as privacy becomes elusive. Ten years ago, two people could walk through a park, talking: a public act in a public space that was easy to keep private. Now, it’s very easy for someone to film or photograph them and post it on Facebook. “It used to be expensive to make things public and cheap to make them private,” Clay Shirky, an Internet scholar and a professor at N.Y.U., says. “Now it’s expensive to make things private and cheap to make them public.” (Watch a video of from The Big Story of Shirky discussing this issue with privacy expert Lori Andrews, scholar Tim Wu, and Pablo Chavez, from Google.)
The amount that the Internet knows about us can be unsettling. In the modern panopticon, past mistakes don’t disappear from search engines, and now we all have to live like celebrities, worried that someone is filming when we pick our noses in traffic. More seriously, we can be robbed or defrauded. The alarm code to your house might be in a friend’s address book—which may have been sitting on a server that was controlled, at least for a moment, by Path.
So, what should we do? Congress has been debating privacy forever and doing nothing, which isn’t a terrible thing. Self-policing, as opposed to legislative policing, is generally a good idea for the Internet: laws tend to pass slowly, technology moves quickly. The system we have right now is one based on evolving social norms, corporate shaming, and the occasional intervention of the F.T.C. Last week, a coalition of companies announced that they will soon voluntarily include “do not track” buttons in Web browsers.
The smartest solution, or at least framework, that I’ve read comes from Benjamin Wittes, a senior fellow at the Brookings Institution. According to an essay that he published last year, titled “Databuse,” we should let certain things that we now consider privacy abuses slide. It doesn’t matter, in and of itself, that we have oceans of personal information floating around in government databases, or that advertisers know ever more about our lives. It’s disconcerting, but not harmful. Companies should tell the truth about what they’re doing, and consumers should have control over the data that’s collected. But don’t fret that marketers have collected keywords on everything you’ve tweeted about, or that the running-shoe ad on Facebook appears to know the size of your feet.
What we really need to fear are things like outright fraud. We have to be very careful about the way sensitive information—like what’s found in an address book—is stored and transferred. We need to be certain that insurance companies can’t raise our rates after they learn we’ve searched for “irregular heartbeat” online. The letter to Google from the Attorneys General begins by describing user discomfort with the company’s changes—that’s relatively unimportant. The much more important claim comes on page two, where the Attorneys General assert that Google’s new privacy policies, by sharing your data across the company’s many services, may make identity theft easier to perpetrate.
In response to all these developments, President Obama released a Consumer Privacy Bill of Rights, which consists primarily of broad and worthy calls for companies to be clear about the data they collect. It calls for “Individual Control,” “Transparency,” and “Respect for Context,” for example. Here’s an addition from Wittes that seems even more important: “A right to not have your data rise up and attack you.”
Friday, March 2, 2012
Big Data's Grass-Roots Revolution
Quentin Hardy, The New York Times, March 2, 2012
The Big Data revolution may be raising more questions than it is answering. Who owns my behavior? Where does my government begin and end? Should I be able to bet on the outcome of a trial?
By accident and design, people and companies are putting huge amounts of information about prices, locations, intentions and just about everything else into large databases. Big Data, which should probably be called Big Analysis, is about looking at that information in novel ways to find new patterns for prediction. What they predict, and how that fits in with traditional ways of running our lives, is changing fast. Money is flowing into a growing sector of corporate technology, and grass-roots hackers are thinking of even more novel ways to free up and use the data .
The publisher O’Reilly’s Strata Conference this week hosted over 2,500 attendees on the subject of Big Data. Microsoft and EMC were sponsors. Last year Strata sold out with 1,300 people, and had far less of a big-company presence.
Much of the corporate work is fascinating. Hal Varian, who is Google’s chief economist, talked about ways that search terms predict government economic information. Just as the search term “vodka,” which most frequently appears on a Saturday, predicts “hangover” will appear most often on Sunday, Google search terms like “how to sign up for unemployment” can foreshadow the beginning and end of recessions. Searching for “hybrid vehicles” (which shows unhappiness with gasoline prices) indicates poor consumer sentiment about a month ahead of the standard University of Michigan index.
A video of his talk and a 2009 paper on some of this work show how Mr. Varian has refined the predictions by adding more data sets and tools. Google Trends, is a way to show when things are increasing, Google Insights for Search links different queries and Google Correlate links search terms and real-world data, like the incidence of queries in different states (New Yorkers, you might think of switching to a different kind of booze). “Kids, try this at home,” Mr. Varian said, encouraging the crowd to see what else they could do with the tools.
Farther-reaching new relations of data sets, however, may come from start-up companies and grass-roots hackers. A Palo Alto, Calif., company called Lex Machina takes data from patent litigation outcomes and predicts whether or not you should settle, based also on things like the type of intellectual property, the judge and the court hearing the case. “An ethically provocative” product, is how Alistair Croll, Strata’s co-chair, described it. “I’m waiting for a derivatives market in patent litigation.”
A start-up from Great Britain called Pachube (pronounced Patch-bay), which was purchased last year by LogMeIn for $15 million, collects both public and private sensor data. Much of the data can then be accessed by other people in unexpected ways.
After last year’s tsunami in Japan, for example, members of the Pachube community set up radiation detectors around Japan. One participant linked this information with data on wind currents, to predict where radiation levels might next spike. If the Japanese government was doing this, they didn’t tell the public. One enterprising New Yorker has put water-level sensors in the city’s pipes, and through a service called dontflush.me predicts whether or not a toilet is at risk of backing up. Maybe there is a vodka mash-up to be done here.
Its founder, Usman Haque, says Pachube receives in real time over 100,000 different streams of public data, and more streams than that on a restricted basis, meaning the owner of the data limits who can see it. A stream could be a single app on a phone, or it could be an entire house’s information, including personal medical data, so it’s hard to tell how much data this is. “It’s a community of people building on each other,” he says. “It’s about getting more heterogeneity, that’s the value.”
The real revolution will start in about a year, Mr. Haque says, when data-collecting home automation hubs start selling for about $50. Individuals, he believes, will begin demanding more ownership and sharing of their own data. FitBit and Nikenow collect information on things like sleep and workout times. In many cases fitness companies, telecommunications providers, utilities and others own such information about us.
“One thing I’m sure of,” Mr. Haque says, “we have no idea what people will be doing with this three years from now.”
The Big Data revolution may be raising more questions than it is answering. Who owns my behavior? Where does my government begin and end? Should I be able to bet on the outcome of a trial?
By accident and design, people and companies are putting huge amounts of information about prices, locations, intentions and just about everything else into large databases. Big Data, which should probably be called Big Analysis, is about looking at that information in novel ways to find new patterns for prediction. What they predict, and how that fits in with traditional ways of running our lives, is changing fast. Money is flowing into a growing sector of corporate technology, and grass-roots hackers are thinking of even more novel ways to free up and use the data .
The publisher O’Reilly’s Strata Conference this week hosted over 2,500 attendees on the subject of Big Data. Microsoft and EMC were sponsors. Last year Strata sold out with 1,300 people, and had far less of a big-company presence.
Much of the corporate work is fascinating. Hal Varian, who is Google’s chief economist, talked about ways that search terms predict government economic information. Just as the search term “vodka,” which most frequently appears on a Saturday, predicts “hangover” will appear most often on Sunday, Google search terms like “how to sign up for unemployment” can foreshadow the beginning and end of recessions. Searching for “hybrid vehicles” (which shows unhappiness with gasoline prices) indicates poor consumer sentiment about a month ahead of the standard University of Michigan index.
A video of his talk and a 2009 paper on some of this work show how Mr. Varian has refined the predictions by adding more data sets and tools. Google Trends, is a way to show when things are increasing, Google Insights for Search links different queries and Google Correlate links search terms and real-world data, like the incidence of queries in different states (New Yorkers, you might think of switching to a different kind of booze). “Kids, try this at home,” Mr. Varian said, encouraging the crowd to see what else they could do with the tools.
Farther-reaching new relations of data sets, however, may come from start-up companies and grass-roots hackers. A Palo Alto, Calif., company called Lex Machina takes data from patent litigation outcomes and predicts whether or not you should settle, based also on things like the type of intellectual property, the judge and the court hearing the case. “An ethically provocative” product, is how Alistair Croll, Strata’s co-chair, described it. “I’m waiting for a derivatives market in patent litigation.”
A start-up from Great Britain called Pachube (pronounced Patch-bay), which was purchased last year by LogMeIn for $15 million, collects both public and private sensor data. Much of the data can then be accessed by other people in unexpected ways.
After last year’s tsunami in Japan, for example, members of the Pachube community set up radiation detectors around Japan. One participant linked this information with data on wind currents, to predict where radiation levels might next spike. If the Japanese government was doing this, they didn’t tell the public. One enterprising New Yorker has put water-level sensors in the city’s pipes, and through a service called dontflush.me predicts whether or not a toilet is at risk of backing up. Maybe there is a vodka mash-up to be done here.
Its founder, Usman Haque, says Pachube receives in real time over 100,000 different streams of public data, and more streams than that on a restricted basis, meaning the owner of the data limits who can see it. A stream could be a single app on a phone, or it could be an entire house’s information, including personal medical data, so it’s hard to tell how much data this is. “It’s a community of people building on each other,” he says. “It’s about getting more heterogeneity, that’s the value.”
The real revolution will start in about a year, Mr. Haque says, when data-collecting home automation hubs start selling for about $50. Individuals, he believes, will begin demanding more ownership and sharing of their own data. FitBit and Nikenow collect information on things like sleep and workout times. In many cases fitness companies, telecommunications providers, utilities and others own such information about us.
“One thing I’m sure of,” Mr. Haque says, “we have no idea what people will be doing with this three years from now.”
If Twitter Is a Work Necessity
Jennifer Preston, The New York Times, February 29, 2012
WHEN Anne Klein shut down its designer line in 2008, Eileen McMaster was among the fashion professionals there who found themselves without jobs. After years of working long hours, she took some time off, turning her attention to improving her health, becoming a Pilates instructor and wellness consultant along the way.
Now, with signs that the struggling economy is slightly improving, she is looking to get back into the fashion industry. To help strengthen her position in the job market, she returned to the classroom last year to develop expertise in social media that she can layer on top of her deep marketing and corporate communications experience.
“I didn’t have the social media savvy in the way I do in other areas of marketing,” said Ms. McMaster, 44, of North Babylon, N.Y., who signed up for the social media marketing boot camp online courses at Mediabistro.com. “When I left fashion, social media wasn’t even something we were doing in the industry. Fast-forward four years, and if you are a brand and you are not on social media, you are missing a huge audience.”
For midcareer executives, particularly in the media and related industries, knowing how to use Twitter, update your timeline on Facebook, pin on Pinterest, check in on Foursquare and upload images on Instagram are among the digital skills that some employers expect people to have to land a job or to flourish in a current role.
“Six months ago, Pinterest wasn’t on everyone’s radar,” she said. “Because I am taking these courses, I am not behind.”
Pamela Tate, president and chief executive of the Council for Adult and Experiential Learning, based in Chicago, said digital literacy, including understanding social networking, is now a required skill.
“They are essential skills that are needed to operate in the world and in the workplace,” she said. “And people will either need to learn through formal training or through their networks or they will feel increasingly left out.”
For most people looking for a job, she said, it is vital that they understand how to use LinkedIn and other social tools to network and present themselves online. “If you don’t have a LinkedIn or Facebook account, then employers often don’t have a way to find out about you,” she said.
To help bridge the gap, major universities, community colleges, online educational businesses from Lynda.com to ed2go.com offer continuing education classes in digital media, including social media skills, Web design, search optimization and Web analytics.
The University of San Francisco has an Advanced Social Media certificate that can be earned in an eight-week online course. New York University’s School of Continuing and Professional Studies offers courses where students can also earn certificates within its business programs.
Harvard’s Extension School has a social media marketing course for $1,900 aimed not at midcareer executives, but at younger marketers who need help learning how to integrate social media at their companies.
At Columbia’s Graduate School of Journalism, Sree Sreenivasan, dean of student affairs and a professor who has been teaching digital journalism and skills for more than 16 years, began teaching continuing education classes in social media in 2010.
With students, Professor Sreenivasan said his goal is to “make them think really carefully about what they do and when they do it on social media.”
“We have to think about social media in a new strategic way,” he said. “It is no longer something that we can ignore. It is not a place to just wish your friends happy birthday. It is a place of business. It is a place where your career will be enhanced or degraded, depending on your use of these tools and services.”
While the classes are meant for working journalists, people from many different fields have signed up. In addition to the two courses offered for nondegree students last fall and spring, Professor Sreenivasan and Ernest R. Sotomayor, assistant dean, career services and continuing education, organized a weekend of panels and workshops in late January for 500 people after a similar weekend conference approach drew 300 students last May.
Participants paid up to $200 for lectures and panels that began on a Friday evening with Fred Wilson, the venture capitalist, talking about the future of social networking, and Vadim Lavrusik, who oversees journalism initiatives at Facebook, offering insight on how to use the platform for reporting, content creation and sharing.
Over the next two days, the discussions ranged from how to build a community using social networking tools to how social media is changing the way people watch television.
For those participants, who wanted one-on-one attention from an experienced social media user, the “social media doctors” were in the house.
Stationed at small tables with laptops in the school’s lounge, two dozen volunteers met with people throughout the weekend, offering guidance on topics like how to set up a Twitter account, create an audio recording on SoundCloud and how to take a Tumblr blog to the next level.
A professional photographer was nearby for participants who needed a profile photo for their online presence. There was a line of people waiting on his services both days.
The idea behind the “doctors” was to give people some individual instruction at a conference setting, said Liz Borod Wright, a freelance writer who works with Linda Bernstein, another freelance writer, to help Professor Sreenivasan teach the classes. “They are looking at your Facebook page, your Twitter account, your LinkedIn account and giving guidance on what is most relevant to you,” she said.
Dr. Kate Uraneck, 53, a doctor and emergency disaster preparedness official for New York City’s Department of Health and Mental Hygiene said she attended the weekend program to learn more about social networking tools. A graduate of Columbia journalism school, she heard about it through the school’s alumni network.
“Within my field of emergency preparedness, social media is taking on a more prominent role,” she said, noting how government and Red Cross officials turned to Twitter and Facebook to get the word out during Hurricane Irene. “I wanted to get more knowledge about it.”
Dr. Uraneck emphasized that she does not have social media responsibilities as part of her job. She met with one of the social media doctors to learn more about how to use her personal account, @thedisasterist, more effectively. One of her chief goals, she said with a laugh, was to better understand the role of the hashtag in the Twitter system.
She sat down with one of the most experienced volunteers: Serbino Sandifer-Walker, a fellow alumna of Columbia’s journalism school who is a multimedia journalism professor at Texas Southern University in Houston. Professor Sandifer-Walker said she was interested in not only learning about new platforms during the conference, but also seeing how Columbia’s journalism school approached teaching social media skills because a similar continuing education class is being explored at her university.
“We are looking at creating a course that would be good for seasoned professionals, people who want to develop skills to move their career to the next level,” she said. “For the program to be strong, we know that it will be important to keep up with all of the changes.”
Educators also say skills classes have to help translate what seems to be a different language — hashtags, mentions, heart.
For Dr. Uraneck, her advice on Twitter was straightforward: “Use it to inform, enlighten, bring value,” she said. “Engage.”
Over the next hour, Professor Sandifer-Walker, using layman terms, explained to Dr. Uraneck how Twitter can be used to find people around the world who share similar passions and interests. They talked about the importance of sharing links to useful, relevant content and looking for organizations and people who did the same.
They also discussed how interacting with people on Twitter is an important part of both building and joining a community. And how a hashtag is a useful way to help discover and follow topics or issues on Twitter.
“To me, just learning about mentions and hashtags was almost worth the price of admission,” Dr. Uraneck said. “I had picked up books on Twitter but now I understand it. I also understand the relationship-building piece, being responsive and the give-and-take that goes with that.”
Several businesses also offer online courses to help people understand social networking.
For years, Mediabistro.com, now a division of WebMediaBrands, which publishes blogs about social media and sponsors trade shows, has offered a robust lineup of digital media courses for media professionals, including workshops on blogging basics and podcasting.
In 2007, there were 150 workshops and courses about digital media and technology but none specifically about social media, according to Carmen Scheidel, Mediabistro’s vice president for education and events.
Last year, she said, there were 190 workshops and courses in the digital media and technology program with 32 courses dedicated specifically to social media topics that included social media metrics and marketing on Facebook and Twitter. Many of these courses are now offered online.
“In general, the digital natives are earlier in their careers, and they are not the ones taking these types of classes,” Ms. Scheidel said. “It tends to be people who are very accomplished in their careers but are new to social media. It is an interesting mix.”
Fueling interest in learning has been a sharp increase in the number of employers looking for people with social media skills. Since 2010, the number of jobs listed on Mediabistro’s job board in the categories of mobile, social media, Web development and social-app gaming increased 140 percent, she said.
In January, job listings in those categories were up 51 percent over from the previous January.
To deliver social media training in a more effective way, Ms. Scheidel said that Mediabistro last year introduced a new approach. Instead of offering mostly small workshops with 15 to 20 students, they began offering what she described as an online social media conference.
As part of the course, industry leaders, who often appear at major digital conferences, deliver their presentations online during a webcast. At the same time, she says they still offer students small online workshops and one-on-one guidance with instructors who give them advice for whatever specific social media project they are doing.
“We wanted to give them the experience of being at a conference but maintain that small group setting, where you can get feedback and actually learn,” she said. “We also know that they can benefit from helping each other. They can share, connect and give feedback in small group workshops.”
The online conference approach also gives the students an opportunity to establish social media connections with one another, giving them an instant social network of peers interested in the same topic.
On a recent Thursday afternoon, Ms. Scheidel opened the first session of an eight-week online Social Media Marketing Boot Camp by welcoming about 250 students linking in from their computers from around the country for the live seminar.
While some of the participants were in between jobs, most of the students worked for major corporate brands, universities and government agencies, including MTV, NBC Universal, M.I.T., Bobbi Brown and the World Health Organization.
At the first session, Ms. Scheidel introduced Michael Brito, senior vice president for social business planning at Edelman Digital, who was followed by Dave Kerpen, chief executive officer of Likeable, a marketing firm. The title of his talk was “How to Establish a Brand Personality Through Social Media.”
As both speakers delivered their presentations into a Web camera, zipping through their PowerPoint slides visible in one of the modules on the computer screens, Ms. Scheidel guided a lively interactive chat in another module, allowing the students to ask questions of the speakers and each other.
When one of the speakers brought up Pinterest, one of the students typed into the discussion forum, “What is Pinterest?”
In seconds, another student typed into the chat box: “It’s a social bulletin board — image based.”
Then, Ms. Scheidel typed in the link, pinterest.com. Another student added: “It is a new photo share. You have to be invited, which I think is not very friendly.”
Yet another student, suggested he “check out their Web site” but warned it “can be addicting.”
At the end of the first session, Mr. Kerpen from Likeable invited the students to find him on Twitter and ask any questions that they might have after the class.
He also announced that he would give copies of his book to students who said hello to him on Twitter immediately after the class. He emphasized, “There is no timeline tweeting me questions.”
“The timeline is the rest of our lives,” he said.
WHEN Anne Klein shut down its designer line in 2008, Eileen McMaster was among the fashion professionals there who found themselves without jobs. After years of working long hours, she took some time off, turning her attention to improving her health, becoming a Pilates instructor and wellness consultant along the way.
Now, with signs that the struggling economy is slightly improving, she is looking to get back into the fashion industry. To help strengthen her position in the job market, she returned to the classroom last year to develop expertise in social media that she can layer on top of her deep marketing and corporate communications experience.
“I didn’t have the social media savvy in the way I do in other areas of marketing,” said Ms. McMaster, 44, of North Babylon, N.Y., who signed up for the social media marketing boot camp online courses at Mediabistro.com. “When I left fashion, social media wasn’t even something we were doing in the industry. Fast-forward four years, and if you are a brand and you are not on social media, you are missing a huge audience.”
For midcareer executives, particularly in the media and related industries, knowing how to use Twitter, update your timeline on Facebook, pin on Pinterest, check in on Foursquare and upload images on Instagram are among the digital skills that some employers expect people to have to land a job or to flourish in a current role.
“Six months ago, Pinterest wasn’t on everyone’s radar,” she said. “Because I am taking these courses, I am not behind.”
Pamela Tate, president and chief executive of the Council for Adult and Experiential Learning, based in Chicago, said digital literacy, including understanding social networking, is now a required skill.
“They are essential skills that are needed to operate in the world and in the workplace,” she said. “And people will either need to learn through formal training or through their networks or they will feel increasingly left out.”
For most people looking for a job, she said, it is vital that they understand how to use LinkedIn and other social tools to network and present themselves online. “If you don’t have a LinkedIn or Facebook account, then employers often don’t have a way to find out about you,” she said.
To help bridge the gap, major universities, community colleges, online educational businesses from Lynda.com to ed2go.com offer continuing education classes in digital media, including social media skills, Web design, search optimization and Web analytics.
The University of San Francisco has an Advanced Social Media certificate that can be earned in an eight-week online course. New York University’s School of Continuing and Professional Studies offers courses where students can also earn certificates within its business programs.
Harvard’s Extension School has a social media marketing course for $1,900 aimed not at midcareer executives, but at younger marketers who need help learning how to integrate social media at their companies.
At Columbia’s Graduate School of Journalism, Sree Sreenivasan, dean of student affairs and a professor who has been teaching digital journalism and skills for more than 16 years, began teaching continuing education classes in social media in 2010.
With students, Professor Sreenivasan said his goal is to “make them think really carefully about what they do and when they do it on social media.”
“We have to think about social media in a new strategic way,” he said. “It is no longer something that we can ignore. It is not a place to just wish your friends happy birthday. It is a place of business. It is a place where your career will be enhanced or degraded, depending on your use of these tools and services.”
While the classes are meant for working journalists, people from many different fields have signed up. In addition to the two courses offered for nondegree students last fall and spring, Professor Sreenivasan and Ernest R. Sotomayor, assistant dean, career services and continuing education, organized a weekend of panels and workshops in late January for 500 people after a similar weekend conference approach drew 300 students last May.
Participants paid up to $200 for lectures and panels that began on a Friday evening with Fred Wilson, the venture capitalist, talking about the future of social networking, and Vadim Lavrusik, who oversees journalism initiatives at Facebook, offering insight on how to use the platform for reporting, content creation and sharing.
Over the next two days, the discussions ranged from how to build a community using social networking tools to how social media is changing the way people watch television.
For those participants, who wanted one-on-one attention from an experienced social media user, the “social media doctors” were in the house.
Stationed at small tables with laptops in the school’s lounge, two dozen volunteers met with people throughout the weekend, offering guidance on topics like how to set up a Twitter account, create an audio recording on SoundCloud and how to take a Tumblr blog to the next level.
A professional photographer was nearby for participants who needed a profile photo for their online presence. There was a line of people waiting on his services both days.
The idea behind the “doctors” was to give people some individual instruction at a conference setting, said Liz Borod Wright, a freelance writer who works with Linda Bernstein, another freelance writer, to help Professor Sreenivasan teach the classes. “They are looking at your Facebook page, your Twitter account, your LinkedIn account and giving guidance on what is most relevant to you,” she said.
Dr. Kate Uraneck, 53, a doctor and emergency disaster preparedness official for New York City’s Department of Health and Mental Hygiene said she attended the weekend program to learn more about social networking tools. A graduate of Columbia journalism school, she heard about it through the school’s alumni network.
“Within my field of emergency preparedness, social media is taking on a more prominent role,” she said, noting how government and Red Cross officials turned to Twitter and Facebook to get the word out during Hurricane Irene. “I wanted to get more knowledge about it.”
Dr. Uraneck emphasized that she does not have social media responsibilities as part of her job. She met with one of the social media doctors to learn more about how to use her personal account, @thedisasterist, more effectively. One of her chief goals, she said with a laugh, was to better understand the role of the hashtag in the Twitter system.
She sat down with one of the most experienced volunteers: Serbino Sandifer-Walker, a fellow alumna of Columbia’s journalism school who is a multimedia journalism professor at Texas Southern University in Houston. Professor Sandifer-Walker said she was interested in not only learning about new platforms during the conference, but also seeing how Columbia’s journalism school approached teaching social media skills because a similar continuing education class is being explored at her university.
“We are looking at creating a course that would be good for seasoned professionals, people who want to develop skills to move their career to the next level,” she said. “For the program to be strong, we know that it will be important to keep up with all of the changes.”
Educators also say skills classes have to help translate what seems to be a different language — hashtags, mentions, heart.
For Dr. Uraneck, her advice on Twitter was straightforward: “Use it to inform, enlighten, bring value,” she said. “Engage.”
Over the next hour, Professor Sandifer-Walker, using layman terms, explained to Dr. Uraneck how Twitter can be used to find people around the world who share similar passions and interests. They talked about the importance of sharing links to useful, relevant content and looking for organizations and people who did the same.
They also discussed how interacting with people on Twitter is an important part of both building and joining a community. And how a hashtag is a useful way to help discover and follow topics or issues on Twitter.
“To me, just learning about mentions and hashtags was almost worth the price of admission,” Dr. Uraneck said. “I had picked up books on Twitter but now I understand it. I also understand the relationship-building piece, being responsive and the give-and-take that goes with that.”
Several businesses also offer online courses to help people understand social networking.
For years, Mediabistro.com, now a division of WebMediaBrands, which publishes blogs about social media and sponsors trade shows, has offered a robust lineup of digital media courses for media professionals, including workshops on blogging basics and podcasting.
In 2007, there were 150 workshops and courses about digital media and technology but none specifically about social media, according to Carmen Scheidel, Mediabistro’s vice president for education and events.
Last year, she said, there were 190 workshops and courses in the digital media and technology program with 32 courses dedicated specifically to social media topics that included social media metrics and marketing on Facebook and Twitter. Many of these courses are now offered online.
“In general, the digital natives are earlier in their careers, and they are not the ones taking these types of classes,” Ms. Scheidel said. “It tends to be people who are very accomplished in their careers but are new to social media. It is an interesting mix.”
Fueling interest in learning has been a sharp increase in the number of employers looking for people with social media skills. Since 2010, the number of jobs listed on Mediabistro’s job board in the categories of mobile, social media, Web development and social-app gaming increased 140 percent, she said.
In January, job listings in those categories were up 51 percent over from the previous January.
To deliver social media training in a more effective way, Ms. Scheidel said that Mediabistro last year introduced a new approach. Instead of offering mostly small workshops with 15 to 20 students, they began offering what she described as an online social media conference.
As part of the course, industry leaders, who often appear at major digital conferences, deliver their presentations online during a webcast. At the same time, she says they still offer students small online workshops and one-on-one guidance with instructors who give them advice for whatever specific social media project they are doing.
“We wanted to give them the experience of being at a conference but maintain that small group setting, where you can get feedback and actually learn,” she said. “We also know that they can benefit from helping each other. They can share, connect and give feedback in small group workshops.”
The online conference approach also gives the students an opportunity to establish social media connections with one another, giving them an instant social network of peers interested in the same topic.
On a recent Thursday afternoon, Ms. Scheidel opened the first session of an eight-week online Social Media Marketing Boot Camp by welcoming about 250 students linking in from their computers from around the country for the live seminar.
While some of the participants were in between jobs, most of the students worked for major corporate brands, universities and government agencies, including MTV, NBC Universal, M.I.T., Bobbi Brown and the World Health Organization.
At the first session, Ms. Scheidel introduced Michael Brito, senior vice president for social business planning at Edelman Digital, who was followed by Dave Kerpen, chief executive officer of Likeable, a marketing firm. The title of his talk was “How to Establish a Brand Personality Through Social Media.”
As both speakers delivered their presentations into a Web camera, zipping through their PowerPoint slides visible in one of the modules on the computer screens, Ms. Scheidel guided a lively interactive chat in another module, allowing the students to ask questions of the speakers and each other.
When one of the speakers brought up Pinterest, one of the students typed into the discussion forum, “What is Pinterest?”
In seconds, another student typed into the chat box: “It’s a social bulletin board — image based.”
Then, Ms. Scheidel typed in the link, pinterest.com. Another student added: “It is a new photo share. You have to be invited, which I think is not very friendly.”
Yet another student, suggested he “check out their Web site” but warned it “can be addicting.”
At the end of the first session, Mr. Kerpen from Likeable invited the students to find him on Twitter and ask any questions that they might have after the class.
He also announced that he would give copies of his book to students who said hello to him on Twitter immediately after the class. He emphasized, “There is no timeline tweeting me questions.”
“The timeline is the rest of our lives,” he said.
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