Sector: future of work

The Responsive City: Engaging Communities Through Data-Smart Governance

Curated on Posted on by Stefaan Verhulst

New book by Stephen Goldsmith, and Susan P. Crawford: “The Responsive City: Engaging Communities Through Data-Smart Governance. The Responsive City is a guide to civic engagement and governance in the digital age that will help leaders link important breakthroughs in about technology and big data analytics with age-old lessons of small-group community input to create more agile, competitive, and economically resilient cities. Featuring vivid case-studies highlighting the work of individuals in New York, Boston, Rio de Janeiro, Stockholm, Indiana, and Chicago, the book provides a compelling model for the future of cities and states. The authors demonstrate how digital innovations will drive a virtuous cycle of responsiveness centered on “empowerment” : 1) empowering public employees with tools to both power their performance and to help them connect more personally to those they service, 2) empowering constituents to see and understand problems and opportunities faced by cities so that they can better engage in the life of their communities, and 3) empowering leaders to drive towards their missions and address the grand challenges confronting cities by harnessing the predictive power of cross-government Big Data, the book will help mayors, chief technology officers, city administrators, agency directors, civic groups and nonprofit leaders break out of current paradigms in order to collectively address civic problems. Co-authored by Stephen Goldsmith, former Mayor of Indianapolis, and current Director of the Innovations in Government Program at the Harvard Kennedy School and Susan Crawford, co-director of Harvard’s Berkman Center for Internet and Society.

The Responsive City highlights the ways in which leadership, empowered government employees, thoughtful citizens, and 21st century technology can combine to improve government operations and strengthen civic trust. It provides actionable advice while exploring topics like:

  • Visualizing service delivery and predicting improvement
  • Making the work of government employees more meaningful
  • Amplification and coordination of focused citizen engagement
  • Big Data in big cities – stories of surprising successes and enormous potential”

 

Policy bubbles: What factors drive their birth, maturity and death?

Curated on Posted on by Stefaan Verhulst

Moshe Maor at LSE Blog: “A policy bubble is a real or perceived policy overreaction that is reinforced by positive feedback over a relatively long period of time. This type of policy imposes objective and/or perceived social costs without producing offsetting objective and/or perceived benefits over a considerable length of time. A case in point is when government spending over a policy problem increases due to public demand for more policy while the severity of the problem decreases over an extended period of time. Another case is when governments raise ‘green’ or other standards due to public demand while the severity of the problem does not justify this move…
Drawing on insights from a variety of fields – including behavioural economics, psychology, sociology, political science and public policy – three phases of the life-cycle of a policy bubble may be identified: birth, maturity and death. A policy bubble may emerge when certain individuals perceive opportunities to gain from public policy or to exploit it by rallying support for the policy, promoting word-of-mouth enthusiasm and widespread endorsement of the policy, heightening expectations for further policy, and increasing demand for this policy….
How can one identify a policy bubble? A policy bubble may be identified by measuring parliamentary concerns, media concerns, public opinion regarding the policy at hand, and the extent of a policy problem, against the budget allocation to said policy over the same period, preferably over 50 years or more. Measuring the operation of different transmission mechanisms in emotional contagion and human herding, particularly the spread of social influence and feeling, can also work to identify a policy bubble.
Here, computer-aided content analysis of verbal and non-verbal communication in social networks, especially instant messaging, may capture emotional and social contagion. A further way to identify a policy bubble revolves around studying bubble expectations and individuals’ confidence over time by distributing a questionnaire to a random sample of the population, experts in the relevant policy sub-field, as well as decision makers, and comparing the results across time and nations.
To sum up, my interpretation of the process that leads to the emergence of policy bubbles allows for the possibility that different modes of policy overreaction lead to different types of human herding, thereby resulting in different types of policy bubbles. This interpretation has the added benefit of contributing to the explanation of economic, financial, technological and social bubbles as well”

The Myth of Everybody

Curated on Posted on by Stefaan Verhulst

Laurenellen McCann at Medium: “What is the difference between “with” and “for”? “With” implies togetherness, a network: a larger group, possibly, a messier group, but a group (meaning 2 people+) nonetheless. Acting “with” others implies certain degrees of collaboration, collective action, coordination, and even unity. You run a three-legged race with your partner (or you’re going to fall). When you use the word “with” it means that, however many people are involved, whatever their individual roles, they’re acting as one — or at least, towards a shared goal.

By contrast, when we use the word “for” we center on the experience of individuals in a relationship, with one unit acting on behalf of or doing something to another. (“For another.”) In the “for” universe, there’s usually a receiver and a giver. There can be many people involved or few, but there are almost always actors and those acted upon. In a democracy like ours, where we have government of, by, and for the people, we understand that when we vote for an elected representative, they are then empowered to speak and act for us. To govern for us….but with our consent.

Representative democracy in action.

At least, that’s the way it’s described in textbooks. In reality, however, governance is awash with intermediaries: companies, contractors, public/private partnerships, lobbyists, NGOs, think tanks — organizations of people, formal and informal, that support, distribute, and sometimes do the work of our government for our government and for us. This (very simplified overview of our) system of proxies isn’t necessarily good or bad; it’s just the way we’ve structured things to work in the US.

Why? Well, because we govern in a “for” system. Because there are so many of us and our lives are interconnected. Because we balance majority rule with minority rights. Because of all the reasons you learned in social studies class (if you went to a US public high school) and because this is the way most of us believes society has to work.

But there are other ways.

— Take your hand off the “COMMUNIST” alarm. I’m talking about the “civic” revolution.

In the last 6 or so years, as the buzz around “Gov2.0” waned, obsession with “civic”-ness waxed. What “civic” means exactly, well, we’re all still figuring that out. Sure, there are official definitions that relate “civic” to all things local…and overlapping understandings of “civics” that lend the air of government involvement…but with increasing interest from folks in the tech and innovation sectors (and funders), the word has taken on new shape. Today, “civic” is the center of a Venn Diagram encircling notions commonly associated with “society,” “community,” “governance,” and public commons (or goods). The sheen of social impact, social responsibility, and “community-ness” — that’s what terms of art like “civic innovation,” “civic engagement,” “civic decisions,” “civic participation”, and “civic tech” are all trying to describe.

To be clear, it’s not that this intersection of societal something hasn’t been outlined before: language like “social” (see “social innovation”) and civil (see “civil society”) has been used to describe similar concepts for decades. “Civic” is just the newest coat of paint, its popularity driven in part by interest from NGOs, start-ups, digital strategists, and governing bodies attempting to bring new flavor and energy to long-standing questions, like

How can we make democracy work? What can we do to make the systems in place work better? And what do we need to change to make systems work better for everybody?…”

Powerful new patent service shows every US invention, and a new view of R&D relationships

Curated on Posted on by Stefaan Verhulst
at GigaOm: “The website for the U.S. Patent Office website is famously clunky: searching and sorting patents can feel like playing an old Atari game, rather than watching innovation at work. But now a young inventor has come along with a tool to build a better patent office.
The service is called Trea, and was launched by Max Yuan, an engineer who received a patent of his own for a bike motor in 2007. After writing a tool to download patents related to his own invention, he expanded the process to slurp every patent and image in the USPTO database, and compile the information in a user-friendly interface.
Trea has been in beta for a while, but will formally launch on Wednesday. The tool not only provides an easy way to see what inventions a company or inventor is patenting, but also shows the fields in which they are most active. Here is a screenshot from Trea that shows what Apple has been up to in the last 12 months:
Trea screenshot of Apple inventions
Such information could be valuable to investors or to companies that want to use the filings as a way to track what might be in their competitors’ product pipelines. The Trea database also probes the USPTO for new filings, and can send alerts to subscribers. Yuan has also created a Twitter account just for new Apple filings.
Trea also draws on the patent database to display what Yuan calls a “unified knowledge graph” of relationships between inventors. Pictures, like the one below for IBM, show clusters of inventors and, at a broader level, the viral transmission of human ideas within a company:
Trea IBM screenshot
 
This type of information, gleaned from patent filings, could be valuable to corporate strategists, or to journalists, scholars or business historians. And making government websites more user-friendly, as Rankandfiled.com is attempting to do with Securities and Exchange Commission filings, can certainly help people understand what their regulators are doing….”

How to harness the wisdom of crowds to improve public service delivery and policymaking

Curated on Posted on by Stefaan Verhulst

Eddie Copeland in PolicyBytes: “…In summary, government has used technology to streamline transactions and better understand the public’s opinions. Yet it has failed to use it to radically change the way it works. Have public services been reinvented? Is government smaller and leaner? Have citizens, businesses and civic groups been offered the chance to take part in the work of government and improve their own communities? On all counts the answer is unequivocally, no. What is needed, therefore, is a means to enable citizens to provide data to government to inform policymaking and to improve – or even help deliver – public services. What is needed is a Government Data Marketplace.

Government Data Marketplace

A Government Data Marketplace (GDM) would be a website that brought together public sector bodies that needed data, with individuals, businesses and other organisations that could provide it. Imagine an open data portal in reverse: instead of government publishing its own datasets to be used by citizens and businesses, it would instead publish its data needs and invite citizens, businesses or community groups to provide that data (for free or in return for payment). Just as open data portals aim to provide datasets in standard, machine-readable formats, GDM would operate according to strict open standards, and provide a consistent and automated way to deliver data to government through APIs.
How would it work? Imagine a local council that wished to know where instances of graffiti occurred within its borough. The council would create an account on GDM and publish a new request, outlining the data it required (not dissimilar to someone posting a job on a site like Freelancer). Citizens, businesses and other organisations would be able to view that request on GDM and bid to offer the service. For example, an app-development company could offer to build an app that would enable citizens to photograph and locate instances of graffiti in the borough. The app would be able to upload the data to GDM. The council could connect its own IT system to GDM to pass the data to their own database.
Importantly, the app-development company would specify via GDM how much it would charge to provide the data. Other companies and organisations could offer competing bids for delivering the same – or an even better service – at different prices. Supportive local civic hacker groups could even offer to provide the data for free. Either way, the council would get the data it needed without having to collect it for itself, whilst also ensuring it paid the best price from a number of competing providers.
Since GDM would be a public marketplace, other local authorities would be able to see that a particular company had designed a graffiti-reporting solution for one council, and could ask for the same data to be collected in their own boroughs. This would be quick and easy for the developer, as instead of having to create a bespoke solution to work with each council’s IT system, they could connect to all of them using one common interface via GDM. That would good for the company, as they could sell to a much larger market (the same solution would work for one council or all), and good for the councils, as they would benefit from cheaper prices generated from economies of scale. And since GDM would use open standards, if a council was unhappy with the data provided by one supplier, it could simply look to another company to provide the same information.
What would be the advantages of such a system? Firstly, innovation. GDM would free government from having to worry about what software it needed, and instead allow it to focus on the data it required to provide a service. To be clear: councils themselves do not need a graffiti app – they need data on where graffiti is. By focusing attention on its data needs, the public sector could let the market innovate to find the best solutions for providing it. That might be via an app, perhaps via a website, social media, or Internet of Things sensors, or maybe even using a completely new service that collected information in a radically different way. It will not matter – the right information would be provided in a common format via GDM.
Secondly, the potential cost savings of this approach would be many and considerable. At the very least, by creating a marketplace, the public sector would be able to source data at a competitive price. If several public sector bodies needed the same service via GDM, companies providing that data would be able to offer much cheaper prices for all, as instead of having to deal with hundreds of different organisations (and different interfaces) they could create one solution that worked for all of them. As prices became cheaper for standard solutions, this would in turn encourage more public sector bodies to converge on common ways of working, driving down costs still further. Yet these savings would be dwarfed by those possible if GDM could be used to source data that public sectors bodies currently have to manually collect themselves. Imagine if instead of having teams of inspectors to locate instances X, Y or Z, it could instead source the same data from citizens via GDM?
There would no limit to the potential applications to which GDM could be put by central and local government and other public sector bodies: for graffiti, traffic levels, environmental issues, education or welfare. It could be used to crowdsource facts, figures, images, map coordinates, text – anything that can be collected as data. Government could request information on areas on which it previously had none, helping them to assign their finite resources and money in a much more targeted way. New York City’s Mayor’s Office of Data Analytics has demonstrated that up to 500% increases in the efficiency of providing some public services can be achieved, if only the right data is available.
For the private sector, GDM would stimulate the growth of innovative new companies offering community data, and make it easier for them to sell data solutions across the whole of the public sector. They could pioneer in new data methods, and potentially even take over the provision of entire services which the public sector currently has to provide itself. For citizens, it would offer a means to genuinely get involved in solving issues that matter to their local communities, either by using apps made by businesses, or working to provide the data themselves.
And what about the benefits for policymaking? It is important to acknowledge that the idea of harnessing the wisdom of crowds for policymaking is currently experimental. In the case of Policy Futures Markets, some applications have also been considered to be highly controversial. So which methods would be most effective? What would they look like? In what policy domains would they provide most value? The simple fact is that we do not know. What is certain, however, is that innovation in open policymaking and crowdsourcing ideas will never be achieved until a platform is available that allows such ideas to be tried and tested. GDM could be that platform.
Public sector bodies could experiment with asking citizens for information or answers to particular, fact-based questions, or even for predictions on future outcomes, to help inform their policymaking activities. The market could then innovate to develop solutions to source that data from citizens, using the many different models for harnessing the wisdom of crowds. The effectiveness of those initiatives could then be judged, and the techniques honed. In the worst case scenario that it did not work, money would not have been wasted on building the wrong platform – GDM would continue to have value in providing data for public service needs as described above….”

OkCupid reveals it’s been lying to some of its users. Just to see what’ll happen.

Curated on Posted on by Stefaan Verhulst

Brian Fung in the Washington Post: “It turns out that OkCupid has been performing some of the same psychological experiments on its users that landed Facebook in hot water recently.
In a lengthy blog post, OkCupid cofounder Christian Rudder explains that OkCupid has on occasion played around with removing text from people’s profiles, removing photos, and even telling some users they were an excellent match when in fact they were only a 30 percent match according to the company’s systems. Just to see what would happen.
OkCupid defends this behavior as something that any self-respecting Web site would do.
“OkCupid doesn’t really know what it’s doing. Neither does any other Web site,” Rudder wrote. “But guess what, everybody: if you use the Internet, you’re the subject of hundreds of experiments at any given time, on every site. That’s how websites work.”…
we have a bigger problem on our hands: A problem about how to reconcile the sometimes valuable lessons of data science with the creep factor — particularly when you aren’t notified about being studied. But as I’ve written before, these kinds of studies happen all the time; it’s just rare that the public is presented with the results.
Short of banning the practice altogether, which seems totally unrealistic, corporate data science seems like an opportunity on a number of levels, particularly if it’s disclosed to the public. First, it helps us understand how human beings tend to behave at Internet scale. Second, it tells us more about how Internet companies work. And third, it helps consumers make better decisions about which services they’re comfortable using.
I suspect that what bothers us most of all is not that the research took place, but that we’re slowly coming to grips with how easily we ceded control over our own information — and how the machines that collect all this data may all know more about us than we do ourselves. We had no idea we were even in a rabbit hole, and now we’ve discovered we’re 10 feet deep. As many as 62.5 percent of Facebook users don’t know the news feed is generated by a company algorithm, according to a recent study conducted by Christian Sandvig, an associate professor at the University of Michigan, and Karrie Karahalios, an associate professor at the University of Illinois.
OkCupid’s blog post is distinct in several ways from Facebook’s psychological experiment. OkCupid didn’t try to publish its findings in a scientific journal. It isn’t even claiming that what it did was science. Moreover, OkCupid’s research is legitimately useful to users of the service — in ways that Facebook’s research is arguably not….
But in any case, there’s no such motivating factor when it comes to Facebook. Unless you’re a page administrator or news organization, understanding how the newsfeed works doesn’t really help the average user in the way that understanding how OkCupid works does. That’s because people use Facebook for all kinds of reasons that have nothing to do with Facebook’s commercial motives. But people would stop using OkCupid if they discovered it didn’t “work.”
If you’re lying to your users in an attempt to improve your service, what’s the line between A/B testing and fraud?”

UK: Open standards for sharing and viewing government documents announced

Curated on Posted on by Stefaan Verhulst

Digital by Default news: “The open standards selected for sharing and viewing government documents have been announced by the Minister for the Cabinet Office, Francis Maude.
The standards set out the document file formats that are expected to be used across all government bodies. Government will begin using open formats that will ensure that citizens and people working in government can use the applications that best meet their needs when they are viewing or working on documents together.
When departments have adopted these open standards:

  • citizens, businesses and voluntary organisations will no longer need specialist software to open or work with government documents
  • people working in government will be able to share and work with documents in the same format, reducing problems when they move between formats
  • government organisations will be able to choose the most suitable and cost effective applications, knowing their documents will work for people inside and outside of government

The selected standards, which are compatible with commonly used document applications, are:

  • PDF/A or HTML for viewing government documents
  • Open Document Format (ODF) for sharing or collaborating on government documents

The move supports the government’s policy to create a level playing field for suppliers of all sizes, with its digital by default agenda on track to make cumulative savings of £1.2 billion in this Parliament for citizens, businesses and taxpayers….”

Sharing Data Is a Form of Corporate Philanthropy

Curated on Posted on by Stefaan Verhulst

Matt Stempeck in HBR Blog:  “Ever since the International Charter on Space and Major Disasters was signed in 1999, satellite companies like DMC International Imaging have had a clear protocol with which to provide valuable imagery to public actors in times of crisis. In a single week this February, DMCii tasked its fleet of satellites on flooding in the United Kingdom, fires in India, floods in Zimbabwe, and snow in South Korea. Official crisis response departments and relevant UN departments can request on-demand access to the visuals captured by these “eyes in the sky” to better assess damage and coordinate relief efforts.

DMCii is a private company, yet it provides enormous value to the public and social sectors simply by periodically sharing its data.
Back on Earth, companies create, collect, and mine data in their day-to-day business. This data has quickly emerged as one of this century’s most vital assets. Public sector and social good organizations may not have access to the same amount, quality, or frequency of data. This imbalance has inspired a new category of corporate giving foreshadowed by the 1999 Space Charter: data philanthropy.
The satellite imagery example is an area of obvious societal value, but data philanthropy holds even stronger potential closer to home, where a wide range of private companies could give back in meaningful ways by contributing data to public actors. Consider two promising contexts for data philanthropy: responsive cities and academic research.
The centralized institutions of the 20th century allowed for the most sophisticated economic and urban planning to date. But in recent decades, the information revolution has helped the private sector speed ahead in data aggregation, analysis, and applications. It’s well known that there’s enormous value in real-time usage of data in the private sector, but there are similarly huge gains to be won in the application of real-time data to mitigate common challenges.
What if sharing economy companies shared their real-time housing, transit, and economic data with city governments or public interest groups? For example, Uber maintains a “God’s Eye view” of every driver on the road in a city:
stempeck2
Imagine combining this single data feed with an entire portfolio of real-time information. An early leader in this space is the City of Chicago’s urban data dashboard, WindyGrid. The dashboard aggregates an ever-growing variety of public datasets to allow for more intelligent urban management.
stempeck3
Over time, we could design responsive cities that react to this data. A responsive city is one where services, infrastructure, and even policies can flexibly respond to the rhythms of its denizens in real-time. Private sector data contributions could greatly accelerate these nascent efforts.
Data philanthropy could similarly benefit academia. Access to data remains an unfortunate barrier to entry for many researchers. The result is that only researchers with access to certain data, such as full-volume social media streams, can analyze and produce knowledge from this compelling information. Twitter, for example, sells access to a range of real-time APIs to marketing platforms, but the price point often exceeds researchers’ budgets. To accelerate the pursuit of knowledge, Twitter has piloted a program called Data Grants offering access to segments of their real-time global trove to select groups of researchers. With this program, academics and other researchers can apply to receive access to relevant bulk data downloads, such as an period of time before and after an election, or a certain geographic area.
Humanitarian response, urban planning, and academia are just three sectors within which private data can be donated to improve the public condition. There are many more possible applications possible, but few examples to date. For companies looking to expand their corporate social responsibility initiatives, sharing data should be part of the conversation…
Companies considering data philanthropy can take the following steps:

  • Inventory the information your company produces, collects, and analyzes. Consider which data would be easy to share and which data will require long-term effort.
  • Think who could benefit from this information. Who in your community doesn’t have access to this information?
  • Who could be harmed by the release of this data? If the datasets are about people, have they consented to its release? (i.e. don’t pull a Facebook emotional manipulation experiment).
  • Begin conversations with relevant public agencies and nonprofit partners to get a sense of the sort of information they might find valuable and their capacity to work with the formats you might eventually make available.
  • If you expect an onslaught of interest, an application process can help qualify partnership opportunities to maximize positive impact relative to time invested in the program.
  • Consider how you’ll handle distribution of the data to partners. Even if you don’t have the resources to set up an API, regular releases of bulk data could still provide enormous value to organizations used to relying on less-frequently updated government indices.
  • Consider your needs regarding privacy and anonymization. Strip the data of anything remotely resembling personally identifiable information (here are some guidelines).
  • If you’re making data available to researchers, plan to allow researchers to publish their results without obstruction. You might also require them to share the findings with the world under Open Access terms….”

How Three Startups Are Using Data to Renew Public Trust In Government

Curated on Posted on by Stefaan Verhulst

Mark Hall: “Chances are that when you think about the word government, it is with a negative connotation.Your less-than-stellar opinion of government may be caused by everything from Washington’s dirty politics to the long lines at your local DMV.Regardless of the reason, local, state and national politics have frequently garnered a bad reputation. People feel like governments aren’t working for them.We have limited information, visibility and insight into what’s going on and why. Yes, the data is public information but it’s difficult to access and sift through.
Good news. Things are changing fast.
Innovative startups are emerging and they are changing the way we access government information at all levels.
Here are three tech startups that are taking a unique approach to opening up government data:
1. OpenGov is a Mountain View-based software company that enables government officials and local residents to easily parse through the city’s financial data.
Founded by a team with extensive technology and finance experience, this startup has already racked up some of the largest cities to join the movement, including the City of Los Angeles.OpenGov’s approach pairs data with good design in a manner that makes it easy to use.Historically, information like expenditures of public funds existed in a silo within the mayor’s office or city manager, diminishing  the accountability of public employees.Imagine you are a citizen who is interested in seeing how much your city spent on a particular matter?
Now you can find out within just a few clicks.
This data is always of great importance but could also become increasingly critical during events like local elections.This level of openness and accessibility to data will be game-changing.
2. FiscalNote is a one-year old startup that uses analytical signals and intelligent government data to map legislation and predict an outcome.
Headquartered in Washington D.C., the company has developed a search layer and unique algorithm that makes tracking legislative data extremely easy. If you are an organization that has vested interests in specific legislative bills, tools by FiscalNote can give you insights into its progress and likelihood of being passed or held up. Want to know if your local representative favors a bill that could hurt your industry? Find out early and take the steps necessary to minimize the impact. Large corporations and special interest groups have traditionally held lobbying power with elected officials. This technology is important because small businesses, nonprofits and organizations now have an additional tool to see a changing legislative landscape in ways that were previously unimaginable.
3. Civic Industries is a San Francisco startup that allows citizens and local government officials to easily access data that previously required you to drive down to city hall. Building permits, code enforcements, upcoming government projects and construction data is now openly available within a few clicks.
Civic Insight maps various projects in your community and enables you to see all the projects with the corresponding start and completion dates, along with department contacts.
Accountability of public planning is no longer concealed to the city workers in the back-office. Responsibility is made clear. The startup also pushes underutilized city resources like empty storefronts and abandoned buildings to the forefront in an effort to drive action, either by residents or government officials.
So What’s Next?
While these three startups using data to push government transparency in the right direction, more work is needed…”

'Big Data' Will Change How You Play, See the Doctor, Even Eat

Curated on Posted on by Stefaan Verhulst

We’re entering an age of personal big data, and its impact on our lives will surpass that of the Internet. Data will answer questions we could never before answer with certainty—everyday questions like whether that dress actually makes you look fat, or profound questions about precisely how long you will live.

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Every 20 years or so, a powerful technology moves from the realm of backroom expertise and into the hands of the masses. In the late-1970s, computing made that transition—from mainframes in glass-enclosed rooms to personal computers on desks. In the late 1990s, the first web browsers made networks, which had been for science labs and the military, accessible to any of us, giving birth to the modern Internet.

Each transition touched off an explosion of innovation and reshaped work and leisure. In 1975, 50,000 PCs were in use worldwide. Twenty years later: 225 million. The number of Internet users in 1995 hit 16 million. Today it’s more than 3 billion. In much of the world, it’s hard to imagine life without constant access to both computing and networks.

The 2010s will be the coming-out party for data. Gathering, accessing and gleaning insights from vast and deep data has been a capability locked inside enterprises long enough. Cloud computing and mobile devices now make it possible to stand in a bathroom line at a baseball game while tapping into massive computing power and databases. On the other end, connected devices such as the Nest thermostat or Fitbit health monitor and apps on smartphones increasingly collect new kinds of information about everyday personal actions and habits, turning it into data about ourselves.

More than 80 percent of data today is unstructured: tangles of YouTube videos, news stories, academic papers, social network comments. Unstructured data has been almost impossible to search for, analyze and mix with other data. A new generation of computers—cognitive computing systems that learn from data—will read tweets or e-books or watch video, and comprehend its content. Somewhat like brains, these systems can link diverse bits of data to come up with real answers, not just search results.

Such systems can work in natural language. The progenitor is the IBM Watson computer that won on Jeopardy in 2011. Next-generation Watsons will work like a super-powered Google. (Google today is a data-searching wimp compared with what’s coming.)

Sports offers a glimpse into the data age. Last season the NBA installed in every arena technology that can “watch” a game and record, in 48 minutes of action, more than 4 million data points about every movement and shot. That alone could yield new insights for NBA coaches, such as which group of five players most efficiently passes the ball around….

Think again about life before personal computing and the Internet. Even if someone told you that you’d eventually carry a computer in your pocket that was always connected to global networks, you would’ve had a hard time imagining what that meant—imagining WhatsApp, Siri, Pandora, Uber, Evernote, Tinder.

As data about everything becomes ubiquitous and democratized, layered on top of computing and networks, it will touch off the most spectacular technology explosion yet. We can see the early stages now. “Big data” doesn’t even begin to describe the enormity of what’s coming next.”

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