When Luis von Ahn was 12, he dreamed of becoming a “gazillionaire” by building a chain of free gyms where the kinetic energy people expended on exercise equipment would be captured and sold to power companies.
“I thought this was a genius idea. We’re going to have a set of free gyms, where we don’t have to charge people because as they are exercising they are generating value for us. And because the gyms are free, we are going to take over the whole world of gyms,” von Ahn, an associate professor in Carnegie Mellon University’s computer science department, recounted at the recent MIT Platform Strategy Summit.
As he later discovered, not only was his big idea unoriginal — many people had entertained the same notion — there remain two big reasons it doesn’t work.
“The first is that people are just not very good at generating power, so you can’t make much money off it,” he said. “But second, and most importantly, gyms make their money from people who pay and don’t go.”
A native of Guatemala, von Ahn, 35, is famous for being one of the pioneers of crowdsourcing or, to use his term: human computation. He defines human computation as a system “that combines humans and computers to solve large-scale problems that neither can solve alone.” As a graduate student at Carnegie Mellon he worked on CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart). The security tool, in wide use today on the Web, does double duty as a crowdsourcing tool, using our typed-in transcriptions to turn images of hard-to-read text in old books and magazines into an accurate digital record.
For this work and other projects, von Ahn has become a millionaire, if not the gazillionaire of his pubescent dreams. He was awarded a $500,000 MacArthur Fellowship “genius” award in 2006. Three years later he sold his company, reCAPTCHA, to Google reportedly for more than $25 million.
Von Ahn currently commands the spotlight as co-founder and CEO of Duolingo, a learning/translation/crowdsourcing platform that combines the lofty aim of teaching people a foreign language for free via an interactive app — with crowdsourced labor. As learners acquire language skills, they are asked to translate portions of foreign news articles into English as a way to test their skills; Duolingo then sells these translations to the likes of CNN and Buzzfeed. The site has more than 100 million users, von Ahn said.
“More people are learning language on Duolingo in the United States than in the whole U.S. School system,” he said, a fact that would probably not surprise what’s left of the foreign language school teachers in the nation’s public schools.
Indeed, according to von Ahn, of the 1.2 billion people in the world trying to learn a foreign language (his figure), most are trying to learn a language — English — as a means of getting better work, but can’t afford to pay for classes.
“This is the irony. Most people that are trying to learn a language are doing so to get out of poverty, but it seems you need $1000 to get out of poverty,” he said.
Duolingo aims to level the playing field, von Ahn said, and is part of a larger goal to make education more widely available, regardless of one’s ability to pay.
How to make something like this pay is something he’s been thinking about since he was 12. “The question was, ‘How do we apply the idea of the gym to language learning?'” he said. And the answer is to get users to give you something of value in return for learning. The platform matches up what users are learning to the material CNN and other clients want translated.
Game theory and A/B testing
Three years in, the platform keeps growing and keeps adding languages (e.g. Irish; the number of people learning it on Duolingo now exceeds native speakers, von Ahn said). Schools are starting to adopt Duolingo. Like other platform companies, the company does not rely on traditional marketing to promote itself but has gone to great lengths to figure out how to hook people and keep them coming back.
Language learning is divided into separate skills — the ability to talk about food or animals; the ability to do plurals — and then game theory is applied to encourage people to keep acquiring skills. Every skill level has a “strength bar,” a sophisticated mechanism that goes up as language proficiency increases and decreases when mistakes are made or the student slacks off, disappearing altogether if one ignores ones lessons for too long.
The company has used a lot of mechanisms to lure back Duolingo dropouts, von Ahn said. But the one that has worked the best is sending an image of Duo, the company mascot, crying — crowd tested, of course. “We A/B tested how many tears and how large the puddles of tears should be,” von Ahn said.
Crowdsourcing language acquisition
To figure out how to build a system for learning language, von Ahn and his co-founder read a lot of books (including French for Dummies) on how best to teach a language, but realized the field is rife with conflicting theories. Rather than settle on one method, von Ahn said he and his co-founder “took what we could” from a variety of approaches. As the user community grew, they tested empirically what worked and what didn’t, using A/B testing to improve the heuristics – for example, when is the optimal time to teach plurals.
Whether this back-to-the-future apprentice model has staying power remains to be seen. In the meantime, it is using its current crowd of language learners to not only sell translations but also to perfect itself.
“DuoLingo keeps getting better and better over time, as we are experimenting,” von Ahn said.
Let me know what you think of this post — email me or find me on Twitter @ltucci
Ralph Loura, CIO of the enterprise group at Hewlett-Packard, participated on a panel at the recent MIT Sloan CIO Symposium where he served up plenty of food for thought for IT leaders. Here are four choice Loura-isms on IT leadership.
Post-implementation reviews. “If you’re not doing a post-implementation review and you’re not tracking value, then you’re not doing IT for a business, you’re doing IT for a hobby. It’s as simple as that,” he said.
The rule of seven “dippings.” This one comes from an old Loura mentor. When it comes to complicated concepts or big changes, “it takes seven ‘dippings’ or exposures to that thing before you can begin to internalize it,” Loura said. He didn’t go through all seven “dips,” but a few went something like basic comprehension, understanding how this thing connects to other things, working through the emotional change that comes with thing. So, when IT leaders are trying to drive a different conversation or implement a change that doesn’t seem to be catching on, “it may appear to be a failure at first, but it may be we haven’t gotten to dipping number seven yet,” Loura said.
IT leadership: Embrace what your users are doing, and they’ll show you where IT is falling down. “None of our users, hopefully, show up to work thinking, ‘How can I pull one over on IT today?’ They show up thinking, ‘How can I sell more, hire better, run a more efficient supply chain?’ and they’re just doing it sometimes in spite of you,” Loura said. “So if you pay attention to what they’re doing, they’ll often show you the gaps in what you’re doing.”
3D transformation. Loura is the former CIO at Clorox, where the language of the brand was, we disinfect in you, on you and around you. “‘In you,’ was Britta water filtration and that sort of thing,” he said. So Loura decided to co-opt the language, and apply it to IT. Here’s how he broke it down for his department:
- In you: IT itself needed a different capability set, a different exposure, a different way to approach the business.
- On you: The interface to the business had to change to be more collaborative — in the way they worked and created value together.
- Around you: The ecosystem of vendors had to change, which included technology, in some cases, platforms, and the partners used to deliver it.
“If you only change one of those three dimensions, you’re not getting it done,” he said.
Platforms aren’t just for the software industry anymore.
Companies across industries as varied as farming, food and lighting — businesses based on a traditional product services model — are finding that they must shift to a platform business model to deliver outcomes to these customers, as well as to stay competitive in their fields. And competitive advantage, in turn, requires investment in more agile technology that is able to support the demands of these digital platforms, said Paul Daugherty, CTO of Accenture, at last week’s MIT Platform Strategy Summit in Cambridge, Mass.
“Companies are dealing with big technology estates that they operate — legacy technology — and they know that they need to reinvest in those technologies to create new experiences for their customers,” he said.
Daugherty added that while many of these companies have a good grasp on the need for these reinvestments, there aren’t enough of them that are “reinventing.”
As an example of reinvention, he pointed to how John Deere, the agricultural manufacturing company, started conceiving of the tractor as a platform.
“If you think about the platform as a product, the business starts looking challenging; you have low-cost competitors coming in from all sorts of different places, different countries. You have lots of competitive threats to the business,” he said.
But once John Deere started considering the tractor as a platform — and started embedding it with sensors from which the company gathered valuable meteorological, soil quality and growing information — the company was able to sell a new “product” altogether, which is increased productivity for farmers.
“That’s a more differentiated way to go to market than just selling a great tractor,” Daugherty said.
Another example of a company reinventing its business model is Home Depot, whose business of selling a wide array of low-cost goods, based on a cost-effective supply chain, is now being threatened by Amazon and many others.
While Home Depot has already invested in a mobile app, Daugherty said that the company is also looking at other ways it can build up its platform. One route is through unique, connected experiences for customers via Wink, the company’s connected home system.
Home Depot is developing Wink into an ecosystem by working with its suppliers to make sure that every home product it sells to customers are standardized and compatible with the platform.
Last month, Apple chief exec Tim Cook gave an impassioned speech chiding tech companies such as Facebook and Google about their data collection and monetization practices and how they’re stepping on consumers’ “fundamental right to privacy.”
For a recent Searchlight article on the topic, I talked with three privacy experts to get their take on whether other digital companies — and their customers — are starting to care more about consumer privacy now that a tech bigwig like Apple is speaking out. The consensus: Apple is among a (loud) minority, and there is a lack of incentives for companies and consumers alike to value data privacy and security.
One common thread is the apathy most consumers have about data collection, particularly when the fine print is hard to decipher and they’re getting free and personalized services out of it. While a recent survey by the University of Pennsylvania’s Annenberg School for Communication found that more Americans are certainly becoming conflicted about this trade-off, 451 Research analyst Garrett Bekker believes consumers’ overall attitude toward data privacy and security has not really shifted yet.
One big reason, he said, is the lack of companies’ transparency on how they collect and use data, but another is “how much personal information people are willing to divulge unsolicited.” Bekker was talking about the personal information people share on social media, especially Facebook and LinkedIn, something that puts them at risk: Hackers can mine and use the information as part of targeted social engineering attacks.
For instance, if a hacker wanted to target a specific company, he could easily look for the company’s employees on those social platforms and gather as much personal information as he can, then use that data to create customized emails that sound as if they’re coming from someone who knows the employees — what’s known as spear phishing. (And many of these attacks are successful: An estimated 91% of hacking attacks start with phishing or spear-phishing emails, according to Wired.)
There’s more to the security angle of the consumer privacy issue, as fellow 451 Research analyst Adrian Sanabria brought up. Despite the frequency with which breaches expose precious sensitive data, including consumer data, these days a breach can — paradoxically — actually help many a company and its reputation, he said.
“If [their PR departments] handle it really well and they look really sorry, there’s this whole concept that after a company is breached, you actually feel more comfortable doing business with that company and using their product — because now everything’s out in the open, and you know that they have to take security seriously,” he wrote in an email.
Companies that haven’t yet been breached or encountered a major security issue, on the other hand, haven’t had the chance to publicize that they’ve been hit, been able to handle the screwup, and now take security seriously, said Sanabria.
“Everyone is an unknown until they’ve had this issue,” he added.
In part one of this blog post, Gartner analyst and mobile expert Ken Dulaney discussed why the label Generation Mobile is unnecessary and whether he believes U.S. mobile workers indeed feel guilty for mixing work and personal activities. Read part two to get his opinion on wearables in the workplace and whether the emergence of Gen M calls for new mobility-focused policies.
One of the major findings from a study conducted by mobile security provider MobileIron, which surveyed 3,500 full- and part-time professionals across six countries (including the U.S.), is that there is a new sub-demographic of mobile workers the company is calling Generation Mobile (Gen M) — a group that’s increasingly reliant on mobile for both work and play, and made up of men ages 18 to 24 and parents of children ages 18 and under.
Another interesting finding the report highlighted: A good chunk of Gen M (42%) plan to or already own a wearable device such as an Apple Watch; furthermore, 95% of that group plan to use wearables for work tasks, which include taking phone calls (58%), reading and writing emails (56% and 45%, respectively), and getting alerts such as meeting reminders (44%).
Dulaney thinks that wearables, like mobile devices, have the potential to further expand mobile workers’ connectedness. However, for wearables to gain traction in the workplace, wearable device manufacturers must overcome the current inconvenience of these devices needing to be tethered to smartphones so they can function independently through communications networks.
“Once we see medical [wearable] devices that communicate directly with medical services, we will see results,” he wrote in an email.
The MobileIron study also found that the rise of the Gen M demographic, many of whom reported feeling guilty when doing personal activities during work hours and vice versa, requires companies to create new policies that support Gen M’s new work style “without guilt and with high standards of quality and fairness.”
The study offered the following principles on which to base Gen M-catered policies:
- Accept shifting working styles and understand employees’ actions in detail
- Establish clear goals with employees
- Set top-down boundaries (e.g., CEO should set an example by not sending work emails at 2 a.m.)
- Offer reimbursement stipends for personal mobile technology
- Secure data selectively
While he didn’t exactly disagree with these policies (in part one, he urged companies to embrace BYOA to promote employee satisfaction and innovation), Dulaney warned about the legal problems that could arise from offering stipends for personal devices (although he granted reimbursing for phone services and plans is OK).
“If the phone is owned partially by the employer and the employee gets in trouble on the weekend using that phone, then it’s the employer who gets sued,” he said. He compared the situation to companies paying employees for mileage traveled, but not for the vehicles themselves.
Perhaps more than how seemingly clueless they are toward politics and economics, Millennials are often characterized by how much they live on their smartphones. What’s more, a growing number of Millennials and the general population are increasingly mixing work and play on smartphones and other mobile devices — at a rate that’s, arguably, enough to warrant shining the spotlight on them as a new, emerging demographic, called Generation Mobile, or Generation M.
MobileIron, a mobile device management provider, surveyed 3,400 full- and part-time professionals in six countries, including the U.S., who use a mobile device for work, and discovered that the group it calls Generation M is best represented by men ages 18 to 34 and people with children ages 18 and under in their households. The study found that this demographic is more reliant on mobile technology in general to mix their work and personal activities: For example, 60% of Gen M check or send personal emails at least once a day during work hours, and 51% check or send work emails at least once a day during personal hours.
The study further found that 42% of Gen M plan to either own or buy a wearable device such as the Apple Watch, and the overwhelming majority of that group (95%) plan to use it for work as well as personal tasks.
Why is it so important to home in on Gen M’s mobile habits, and more particularly their attitude toward wearables? Because, said Bob Tinker, MobileIron’s CEO, the new devices “will increase our connectedness and, possibly, our guilt about mixing our work and personal lives.” The MobileIron survey found that 58% of Gen M workers suffer from “mobile guilt” when receiving personal messages during work hours (compared with 46% of non-Gen M workers); moreover, 61% of Gen M workers feel guilty when receiving work communication during personal hours (compared with 47% of non-Gen M workers).
But one mobile expert, Ken Dulaney, begs to differ — first on whether the label Generation M itself is necessary.
Dulaney, an analyst at Gartner, said it’s hard to argue the obvious – Millennials are already a mobile generation. “Sure, they are mobile. … Many of them were given phones at age 7 or so,” he wrote in an email. But, he added, this group also has varying tastes when it comes to art, fashion, music, movies and more — just like any generation before the Millennials. “Aligning them with one aspect of culture doesn’t mean that much to me,” he said. “You could just as easily brand them the ‘Old Navy generation.'”
Second, Dulaney said it’s hardly surprising that a large proportion of Gen M uses their devices for work. “We bring who we are to work,” he said. What is noteworthy about consumerization in the enterprise, he added, is how unprepared the IT department was and how “it took them a number of years” to accommodate both enterprise and consumer needs. “Hopefully, future changes won’t be so cathartic,” he said.
How about the guilt MobileIron measured among mobile workers?
Not a thing, at least not in the U.S., according to Dulaney.
“Maybe it’s a European thing, but I don’t see many guilty employees, and use of personal technology does nothing but increase,” he said.
Instead, he said that what enterprises should focus on is how to embrace the bring your own apps phenomenon so that employees remain satisfied and motivated.
Check out part two of this blog post to get Dulaney’s take on wearables in the workplace.
CIOs are, by now, familiar with the phrase “fail fast.” It’s the idea that experimentation and getting new products to market quickly can expose flaws and weaknesses (and sometimes all around duds) without all the heavy lifting — and heavy investing. Rather than having to anticipate and fix every possible flaw –a potentially costly process — you let the customer of the product or service tell you what’s wrong.
While failing fast sounds great in theory, how can CIOs build an IT culture that celebrates experimentation when they’re often tasked with figuring out how to spend less and be more efficient with what they have? Is it even worth it? So I’ve been asking experts like Mary “Missy” Cummings, director at the Humans and Autonomy Lab at Duke University, to provide examples of how experimentation works for them and what they get out of it.
Cummings, who was one of the Navy’s first female fighter pilots, is a researcher and scientist by training, and so the test-and-learn cycle is practically second nature for her. Still, as someone well versed in experimental testing, the results (and the lessons learned based on those results) sometimes surprise even her: expert assumptions are often proved wrong. I spoke with here at the recent MIT Sloan CIO Symposium. Here’s what she told me about the value of experimentation.
Mary “Missy” Cummings: There was a case once where we had single operator control of multiple air and ground unmanned vehicles [also known as drones]. We were watching [the operators] interact with the system and we thought it was a high workload study because we were giving people more and more tasks to do. But it turns out that people are far more capable than we gave them credit for in terms of being able to handle high workloads.
At the same time, we were testing low workloads. We thought that if we slowed things down, people would take a break and they would slow their pace of activity. What we found was that, because of this inherent need for brain stimulation, the lower workload ended up driving people to frenetic activity, and they had substantially worse performance. These were a younger generation of people. They felt they had to get in there and do more work and, thus, caused a lot more problems in the system.
These kinds of results are really important for people to realize that humans have an incredible predictability in unpredictability. It’s important to get that testing in early so that you understand what issues you’re going run up against with your new technology.
Is Christine Hung, the head of data science and engineering at The New York Times Co., stealing a page from the telecommunications playbook? At the recent CDO Summit in New York City, Hung explained how she’s trying to predict subscriber churn by building predictive models.
Hung, who joined The Times in 2013 after a four-year stint as the global analytics manager of iTunes retail at Apple Inc., is analyzing data The Times has collected, such as a reader’s web browsing history or mobile application usage. “We build a model to predict who is going to cancel their subscription,” she said during a panel discussion.
It’s an example of a predictive analytics application that yields concrete business results. Like any media company, The Times has two revenue streams: advertisements and subscriptions. “If you think about the subscription business,” Hung said, “it’s very hard for us to acquire new customers.” So why not invest more time and energy in keeping the subscribers The Times already has?
The analytics experiment is helping The Times uncover key insights. Hung discovered that readers of general news are much more likely to churn than those who use The Times more extensively. “If you go deeper into the content — if you read a lot of op-eds, if you read a lot of style or travel — you’re more likely to be retained,” Hung said.
That is the kind of insight that helps create more nuanced strategy: Rather than focus on why subscribers leave, The Times can work on how to push general news readers deeper into the product “so that they can really see our value,” Hung said.
At MIT Sloan CIO Symposium, cybersecurity experts painted a grim picture of the state of cybersecurity today. As positive as the speed of technology change is for the next Ubers and Netflixes of the world, cybercriminals are moving even faster to use advanced technology for their own nefarious purposes.
Changes must be made, even in organizations that think they’ve got everything covered from a security perspective, the experts said. I detailed their advice on how to start making those changes in my Searchlight column, “MIT CIO Symposium: Outdated security assumptions put companies at risk.”
“It’s gonna get much much worse before it gets better … now with virtual currency coming online, Bitcoin and so forth, and kidnappings right now are happening virtually,” said George Wrenn, chief security officer (CSO) and vice president of security for Schneider Electric.
Roland Cloutier, CSO and VP of security at ADP, agreed that the attack surface is only going to get bigger, but he believes the benefits of technology will outweigh the threats posed by cyber criminals.
He said the spotlight needs to be on funding startup development and advancing technologies. “Are there enough technologists? … How do we enable that type of compute that will do wonderful things?” he said, urging the audience to start thinking about the possibilities in quantum computing, AI and integrated defense architectures.
“Technology is going to solve so many problems that this will be a drop from the bucket,” he added.
Shuman Ghosmajumder, head of product management at security startup Shape Security, was the out-and-out optimist of the group, pointing out that history suggests that we are up to the threat.
“It’s going to get better. You look at 20 years ago, and all societies were pretty concerned that the world was going to end by the year 2000,” he said. “I think we are going to see these types of moral shifts and innovations that hopefully will make a big dent in the problem.”
Also from MIT Sloan CIO Symposium: See the roadblocks enterprise CIOs have to prepare for as they gear up to adopt IoT.
Chief data officers, a relatively recent breed of executives, are often associated with highly regulated and data-heavy industries like insurance, government, health care and financial services. But chief data officers are beginning to make a play outside of those industries as well, most recently in media.
This week, Time Inc. announced its appointment of J.T. Kostman as its first-ever chief data officer (CDO). And last week, TechTarget, SearchCIO.com’s parent company, introduced Charles Alvarez as its first CDO. Neither have served in a CDO position before (although Kostman did serve as the chief data scientist at Keurig), but both have an extensive history with data, analytics and their supporting systems.
Alvarez’s experience comes from the financial services sector, where he’s worked for the likes of Credit Suisse, Bear Stearns and JP Morgan. SearchCIO had a chance to catch up with Alvarez to discuss his new role and why the complexity of IT systems is casting a shadow on the integrity of corporate data. This conversation was edited for brevity.
Why does a media company need a CDO?
Charles Alvarez: We’re an information company first and foremost. If I’m going to go out and sell to vendors, to purchasers and to people who buy technology or to people who may use this information to manage a hedge fund, for example, I have fundamental principles that I have to keep on top of: I have to be able to maintain the reputation of my firm, which rests on the quality of its data.
And I’ve got to be able to grow and increase sales where I can. I’ve got to be dynamic and agile so I generate new products and generate new services. And I won’t be able to do that if I’m not capable of understanding the information that I have or managing the information that I have.
Alvarez: As it exists, from a legacy standpoint, for 99.99% of the world today, the data has lived in the technology organization. The technologists have to care about it because it’s inside their apps and their databases. If they screw it up, there’s going to be consequences. So from the standpoint of a historical view, it has been managed by IT and it lives in their database.
But what if I’m reengineering how marketing ops manages surveys? [Marketing ops] wants to create a vocabulary for its teams. Now when I want to create a new survey, I don’t have to start from scratch. I don’t have to wonder if this matches the question I asked two years ago because history is important to me, and I can say I have historical sequencing and semantic integrity with time and it’s valid. That’s data in the large.
Data in the small, the stuff that lives in programs, is the stuff IT is responsible for. Data in the large, you have to be concerned about the integrity of the data, you have to be concerned about the processes that create that data.
Why is a ‘data in the small’ perspective too limiting for organizations today?
Alvarez: IT is responsible for the quality of data under its purview. So IT has to know that the business reports this particular item of data as x.y.whatever. But the IT function is not forward-looking, and that function doesn’t understand business semantics. If you stick a number in the database and the top of that numbers says P&L, if you’re in IT, you say, that’s a valid number. To me, as a data person, I’d ask the question is that net, is that gross, are there sales credits, is it compounded, is it a cash number, what currency is it? Now all of a sudden you have a semantic component. Semantics are now important. In the past they weren’t important because we didn’t maintain large time series of data.
That’s the fundamental change that happens.