The silence of Apple, Google, Facebook, and Amazon with respect to blockchain is conspicuous.
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Uber CEO Travis Kalanick Is Taking a Leave of Absence
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Why WannaCry Signals a Coming Escalation of Cyber Attacks
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Empowering Digital Societies – SPONSOR CONTENT FROM MICROSOFT
Hit fast-forward in your mind. Imagine a world where data about traffic, public transportation, and pedestrian patterns is continuously analyzed to provide the smoothest possible commute for the largest number of people. Centralized, one-click tax preparation and payment. A single, voice-activated digital assistant ready to answer any civic question.
How far ahead do you think you’d have to jump to make these things happen? Five years? Ten years? Neither. In fact, each of these innovations is already up and running somewhere in the world today, with more happening every day. They are signs of profound change.
Digital transformation—or the way of thinking about this change—refers to the use of technology to improve the reach and performances of enterprises. It’s not limited to private enterprise. When applied to the social fabric, digital transformation points to a reimagining of the way governments interact with their people, cities serve their inhabitants, and public agencies address the needs of their communities.
As diverse forces such as social media, climate change, urban migration, and sprawl continue to upend the status quo, employing every tool and service available to help societies respond to disruption is critical. Today, new devices coupled with artificial intelligence using vast amounts of data from millions of sensors are helping us tackle key social concerns.
Read more from Microsoft:
Building more efficient, secure, and resilient governments
Turn to Estonia for an example of a digital transformation of the social infrastructure. Estonia has only 1.3 million citizens but is larger in landmass than Switzerland; as a result, many towns do not have a nearby government office. Every citizen carries a digital ID card that allows him or her to vote remotely, pay taxes with a few clicks, manage health care, and much more. These days, the country has opened its digital service to everyone in the world via e-Residency. But because of this digital dependence, the government needed to ensure its resilience in the event of a natural disaster, cyberattack, or other disruption. How? As part of a joint research project with Microsoft, Estonia moved the official digital record of land ownership to the cloud. Since then, they have clarified public cloud usage guidelines to allow most data to be stored in a public cloud located within the EU, and they are building up data embassies to keep critical e-government databases and systems abroad backed up in the cloud.
Globally, these types of changes will be most effective when they’re supported by a legal and policy framework that reinforces the technology, particularly for issues of security, privacy, and resilience. A collaborative research project has launched in New Zealand to explore some of these larger questions of how governments can harness digital technologies to develop smarter, more inclusive societies.
“Essentially, we are interested in better understanding what it takes for New Zealand to become a digital society, what opportunities and challenges it presents, and what role digital government plays in getting there,” says Graeme Osborne, the general manager for system transformation at the New Zealand Government Chief Information Office (GCIO). The results of the project—a collaboration between the GCIO, Microsoft Digital, and the Fletcher School at Tufts University—will be published in a future white paper that will provide insights and ideas not only for New Zealand but also for countries around the world.
Urban digital nervous system
“Digital transformation is helping people and organizations reimagine work and personal life. It’s empowering cities and countries to realize digital dreams that create better education, and safer, healthier and more sustainable living. The opportunity for our digital societies to drive social and economic progress is unprecedented,” according to Anand Eswaran, Corporate Vice President, Worldwide Services and Microsoft Digital.
The technology is sophisticated enough now that the possibilities seem almost limitless. Thanks to advances in artificial intelligence and data analytics, technology is now able to anticipate human intentions, becoming increasingly responsive to the needs of the people it’s designed to serve. Underpinning this work at Microsoft is a belief in inclusive design, which holds that technology should be empathetic; habitable environments should be not only aesthetically pleasing but also usable by everyone, regardless of ability, age, or life status.
Inclusive design helps inform the concept of the urban digital nervous system (UDNS), which is a metaphor (first used by Bill Gates in 1999) for the systems that regulate a city’s operations and automate its core functions. Thanks to advances in artificial intelligence and data analytics, it’s a metaphor with strong connections to the real thing. As it matures, the UDNS will start to anticipate human intentions, becoming increasingly responsive to the needs of the people it’s designed to serve. One such project is under way in Auckland.
With 1.4 million residents, Auckland is New Zealand’s largest city, and it’s growing fast; its population is expected to double by 2040. With growth comes traffic, and already Auckland’s existing transportation infrastructure is struggling to cope. Auckland Transport, the agency responsible for helping people move around the city safely and efficiently, worked with Microsoft Digital to better understand how to plan for population growth. The project used Internet of Things data from public transport nodes, traffic lights, and intersections to shorten travel time, ease congestion, and make the streets safer for pedestrians. Eventually, a social listening tool and a mobile app for parking will help Auckland Transport become even more responsive.
Digital transformation is a central element in what is increasingly being referred to as the fourth industrial revolution, signaled by our burgeoning understanding of how to embed technologies in the physical and biological spheres. The pace of this change is historically unprecedented and disrupting nearly every industry in every country. Societies too must adapt, not only to protect their members’ livelihoods, lifestyles, and longevity but also to offer their communities the services they need and to provide a framework for future growth. As that happens, governments will become more customer-focused—and will contribute to a better quality of life for everyone.
For more information visit www.microsoft.com/digitaldifference.
Uber Board Embraces All Recommendations to Improve Corporate Culture
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Transforming Today’s Bad Jobs into Tomorrow’s Good Jobs

All eyes are on the future of work and the impact that automation and machine learning will have on U.S. jobs. The blizzard of conferences, initiatives, articles, and reports on how to prepare for the changes technology will bring to our economy is important. But so is today — and it feels to us like the futurists are leaving behind what’s happening now.
Work currently does not work for millions of Americans. Nearly 11.5 million people who work as retail salespeople and cashiers and in food prep and service — the three largest occupations in the United States — earn poverty-level wages and have unpredictable schedules, few opportunities for success and growth, and little meaning and dignity in their jobs. These workers have bad jobs, and they need and deserve good jobs now, regardless of who’s going to be doing what in the future.
But in fact, transforming these bad jobs into good jobs is a good way to prepare for that future. Keep in mind that many retail and restaurant jobs require nonroutine manual labor, physical dexterity, and social interaction, which, according to MIT researchers Daron Acemoglu and David Autor, are less amenable to automation. But let’s say that automation really does reduce retail and restaurant employment. Good jobs stores and restaurants will do better in leveraging that automation — as well as better serving their customers, employees, and investors today. Here’s why.
Developing Skills that Will Matter in the Future
Thought leaders and futurists name complex problem solving, critical thinking, and creativity as the most important future job skills. But at good jobs companies, these very skills are already demanded, developed, and put to use.
Companies that offer good jobs today — with decent wages, predictable schedules, and opportunities for success and growth — do so by combining investment in people with operational choices that increase their employees’ productivity and contributions. We call this approach the Good Jobs Strategy. One of the key choices they make is empowering employees to make decisions to benefit their customers and involving employees in improvement.
For example, Mercadona, a good jobs retailer that’s Spain’s largest supermarket chain, uses its employees’ creative and problem-solving skills to suggest product, packaging, and transportation improvements that have already saved the company millions of euros. Mercadona’s store employees are empowered to order products and present them in a way that satisfies their customers and improves company performance.
At Costco, another good jobs retailer, store managers are empowered to display merchandise and provide input into the merchandising system. A merchandising algorithm does provide insight into what should be stocked, but the store managers are on the floor every day, putting their own and their employees’ problem solving, critical thinking, and creativity — the skills of the future — to work today. When that future comes, who will have the competitive advantage?
Seeing Automation as a Complement to People
The Good Jobs Strategy enables companies to make the most of their employees’ full potential. So good jobs companies are less likely to focus on machines replacing workers and more likely to focus on machines as a valuable complement to their valuable people. When one of us visited Mercadona’s fully automated distribution center, the director said, “Its construction was based on one premise: Don’t make a person do what a machine can do. The only effort we want from our employees is for them to give us their skills and their knowledge.”
When asked about automation in retail, a good jobs company CEO who recently visited our class at MIT said he saw automation as a force multiplier. Right now, his employees do many tasks (such as mopping floors and counting change) that don’t directly add to the customer experience. If robots can perform these functions in the future, his employees can focus that much more on providing even better customer experience. “Anyone’s employees can mop a floor,” he said, “but not every company trains and supports their staff to provide excellent customer service.” He knows his company already has a competitive advantage — its frontline workers — and that automation will only increase their value.
Indeed, as our colleagues Erik Brynjolfsson and Andrew McAfee argue in their book The Second Machine Age, humans working hand in hand with machines do better work than either does by itself. Chess-playing computers can now beat even grandmasters like Garry Kasparov, but in so-called “freestyle chess,” human-computer teams beat computers. So if Amazon’s new cashier-free test store succeeds and eliminates the need for people to count change, good jobs companies — including their frontline workers — will probably be delighted!
Ability to Implement New Technologies
A company that engages its workforce now will not only provide good jobs and good customer experience today but also will be best prepared for whatever the robotics revolution brings. It’s easy to forget that technology rollouts require an engaged frontline. Even in the future, robots won’t just walk in the door, wave to the old employees on the way out, and get to work. Customers will need to be educated and supported along the way to greater efficiencies. Systems that work in labs and boardrooms will have hiccups in stores that require troubleshooting. Collaborative, productive, empowered employees will be best equipped to help companies roll out new innovations. They will gain new skills in the process, a win for everyone.
In fact, rollouts have sometimes gone badly — not yielding the expected benefits on very large investments — partly because the frontlines were not involved in the process. For example, when Bob Nardelli became the CEO of Home Depot, he started investing heavily in systems and technologies. In 2005 alone, Home Depot spent $1 billion on automating merchandising and store processes. But these changes, sensible in themselves, were accompanied by reduced investment in associates and were largely forced on the associates and store managers. Many of the systems either failed or fell short of their promised impact due to mismanaged rollouts, lack of user training, or because of lack of fit to in-store needs — in part because store associates were not involved.
Mercadona, on the other hand, spent €600 million between 2005 and 2008 to install the most up-to-date logistics and in-store retail technologies, and the rollout went smoothly because their workers were engaged in the process. Nobody was laid off — so the workers didn’t see the new technology as the enemy. They were well trained in the new technology and had the time — as well as the autonomy — to help customers get used to it. It helped that as part of its Good Jobs Strategy, Mercadona has a laser focus on the customer and the new in-store technologies were developed not just to increase efficiencies but also to make the customer experience better.
So despite a large expense and no downsizing, Mercadona’s productivity went up. Sales per employee went from 1979,142 euros in 2005 to 232,260 euros in 2008. That is what the Good Jobs Strategy is all about — now and in the future.
How AI Is Streamlining Marketing and Sales

In 1950, Alan Turing, already famous for helping to crack the German Enigma code during World War II, devised the Turing test to define intelligence in machines. Could a computer, Turing asked, fool a human into thinking he was interacting with another person, or imitate human responses so well that it would be impossible for a person to tell the difference? If the machine could, Turing proposed, it could be considered intelligent. Turing’s thought experiment spawned scores of science-fiction tales, such as the 2015 hit movie Ex Machina. Now, artificial intelligence (AI) and autonomous algorithms are not only passing the Turing test every day but, more importantly, are making and saving money for the businesses that deploy them.
CenturyLink is one of the largest telecommunications providers in the United States, serving both small and large businesses nationwide. The collects thousands of sales leads from the businesses it serves, and it wishes to interact with them in the intimate, personal manner consumers have come to expect. Pursuing those leads more effectively would accelerate the company’s growth, and converting and upselling a larger percentage of hot leads (people who have expressed interest in the company’s services by filling out a form, clicking on an ad, or emailing the company) would boost the company’s bottom line.
Insight Center
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Putting Data to Work
Sponsored by Accenture
Analytics are critical to companies’ performance.
Accordingly, in the latter half of 2016, CenturyLink made a small investment in an AI-powered sales assistant made by Conversica to see if it could help the company identify hot leads without hiring an expensive army of sales reps to comb through the leads. The Conversica AI, a virtual assistant named Angie, sends about 30,000 emails a month and interprets the responses to determine who is a hot lead. She sets the appointment for the appropriate salesperson and seamlessly hands off the conversation to the human.
The potential customer gets a prompt and helpful outreach from Angie, and the reps — who may each have 300 accounts — save time because Angie vets the inquiries to identify the ones with the most potential. The reps also become more efficient because Angie routes the right leads to the right reps. In the small pilot CenturyLink ran, Angie could understand 99% of the emails she received; the 1% that she couldn’t understand were sent to her manager.
According to Scott Berns, CenturyLink’s Director of Marketing Operations, the company has approximately 1,600 sales people, and the Angie pilot started with four of them. That number soon rose to 20, and continues to grow today. Initially, Angie was identifying about 25 hot leads per week. That has now increased to 40, and the results have certainly validated the company’s investment. It has earned $20 in new contracts for every dollar it spent on the system.
Tom Wentworth, Chief Marketing Officer at RapidMiner, a company that provides an analytical tool for data scientists, had a problem that was similar to CenturyLink’s. Like many software companies, RapidMiner offers free trials, and Wentworth was struggling to serve the approximately 60,000 users who come to the company’s site each month for the free trial. Many of the visitors using RapidMiner’s software, and needing help, are not paying anything for the service. So, how could Wentworth help them in a cost-effective way?
The company had a popular chat feature on its site, but its salesforce was overwhelmed — and spending a great deal of time — sorting through the chat sessions to find potential customers. It was like looking for the proverbial needle in a haystack.
Wentworth approached a friend who suggested he try a chat tool called Drift, which would ask a visitor initiating a chat, “What brought you to RapidMiner today?” The visitor would respond, and the Drift bot would provide one of seven potential follow-up answers. For example, a visitor might say, “I need help,” and Drift would send him or her to the support section of the website.
Drift was relatively easy to set up. Wentworth, like CenturyLink, started small, running the tool on a few of RapidMiner’s smaller web pages to test how helpful it was.
In less than two weeks, he had deployed it on every page.
The Drift bot now conducts about a thousand chats per month. It resolves about two-thirds of customer inquiries; those that it cannot, it routes to humans. In addition to Wentworth, who is monitoring the tool’s interactions, two co-op college students support the inquiries part-time. Wentworth told me that Drift is generating qualified leads for the sales team by making customers. “It’s the most productive thing I’m doing in marketing,” he said.
Every day, Wentworth reviews conversations people have had with Drift. “I’ve learned things about my visitors that no other analytics system would show,” said Wentworth. “We’ve learned about new use cases, and we’ve learned about product problems.”
This is the strength of an AI agent that can elicit information like a person, rather than an analytics tool that simply finds patterns in the data it collects, like a machine.
In 2016, Epson America, the printer and imaging giant, piloted the same Conversica AI assistant as CenturyLink. Chris Nickel, Epson’s senior manager of commercial marketing, was drowning in all the leads he was getting for the company’s diverse line of products: big printers, projectors, scanners, point of sale solutions, and industrial robots. Epson America was getting 40,000 to 60,000 leads per year from trade shows, direct mail, email marketing, social media, print and online advertising, and a successful brand awareness campaign. The leads would pour in, and whether they were good, bad, qualified or not, they would all be turned over to salespeople whose availability to follow up was inconsistent.
After implementing the AI assistant, Epson’s leads are now followed up promptly and persistently until their AI assistant gets a response. “Because the outreach to leads takes 6-8 times, Conversica is a true force multiplier for our sales team,” say Nickel. After a lead is passed to one of Epson’s partners, the AI assistant follows up to make sure the customer was satisfied. Sometimes, the response to that follow-up identifies a new sales opportunity, such as “everything went great, and actually we are looking to buy another 60 projectors,” giving Epson the opportunity to quickly capitalize on a new sales opportunity before the competition. Or it can uncover an unresolved customer support issue, such as “I’m having a problem with my projector.”
As Nickel told me, “Before, if we gave 100 leads to the reps, we might get a couple of responses from customers. Now, if we give 100 leads to the AI assistant, we get 50 responses.” Epson reports that the official response rate with the AI assistant is 51%, representing a 240% increase from the baseline established at the beginning of the pilot, and a 75% increase in qualified leads. According to Nickel, that has produced $2 million in incremental revenue in just 90 days.
Because the AI tools that Epson America, RapidMiner, and CenturyLink deployed are offered as-a-service, it was easy for these companies to conduct pilots, and then scale up. Clearly, it’s worthwhile for companies to test AI-powered chat or email tools to see if they can convert more leads, and improve their understanding of what customers want and need.
When it comes to AI in business, a machine doesn’t have to fool people; it doesn’t have to pass the Turing test; it just needs to help them and thereby help the businesses that deploy them. And that test has already been passed. As one CMO told me, “AI tools are the only way I can scale ‘helpfulness’ to a global community of 200,000-plus users with a team of two.”