Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots

Curated on Posted on by Stefaan Verhulst

Book description: “Robots are poised to transform today’s society as completely as the Internet did twenty years ago. Pulitzer prize-winning New York Times science writer John Markoff argues that we must decide to design ourselves into our future, or risk being excluded from it altogether.

In the past decade, Google introduced us to driverless cars; Apple debuted Siri, a personal assistant that we keep in our pockets; and an Internet of Things connected the smaller tasks of everyday life to the farthest reaches of the Web. Robots have become an integral part of society on the battlefield and the road; in business, education, and health care. Cheap sensors and powerful computers will ensure that in the coming years, these robots will act on their own. This new era offers the promise of immensely powerful machines, but it also reframes a question first raised more than half a century ago, when the intelligent machine was born. Will we control these systems, or will they control us?

In Machines of Loving Grace, John Markoff offers a sweeping history of the complicated and evolving relationship between humans and computers. In recent years, the pace of technological change has accelerated dramatically, posing an ethical quandary. If humans delegate decisions to machines, who will be responsible for the consequences? As Markoff chronicles the history of automation, from the birth of the artificial intelligence and intelligence augmentation communities in the 1950s and 1960s, to the modern-day brain trusts at Google and Apple in Silicon Valley, and on to the expanding robotics economy around Boston, he traces the different ways developers have addressed this fundamental problem and urges them to carefully consider the consequences of their work. We are on the brink of the next stage of the computer revolution, Markoff argues, and robots will profoundly transform modern life. Yet it remains for us to determine whether this new world will be a utopia. Moreover, it is now incumbent upon the designers of these robots to draw a bright line between what is human and what is machine.

After nearly forty years covering the tech industry, Markoff offers an unmatched perspective on the most drastic technology-driven societal shifts since the introduction of the Internet. Machines of Loving Grace draws on an extensive array of research and interviews to present an eye-opening history of one of the most pressing questions of our time, and urges us to remember that we still have the opportunity to design ourselves into the future—before it’s too late….(More)”

2015 Hype Cycle for Emerging Technologies

Curated on Posted on by Stefaan Verhulst

Gartner: “The journey to digital business continues as the key theme of Gartner, Inc.’s “Hype Cycle for Emerging Technologies, 2015.” New to the Hype Cycle this year is the emergence of technologies that support what Gartner defines as digital humanism — the notion that people are the central focus in the manifestation ofdigital businesses and digital workplaces.

The Hype Cycle for Emerging Technologies report is the longest-running annual Hype Cycle, providing a cross-industry perspective on the technologies and trends that business strategists, chief innovation officers, R&D leaders, entrepreneurs, global market developers and emerging-technology teams should consider in developing emerging-technology portfolios.

“The Hype Cycle for Emerging Technologies is the broadest aggregate Gartner Hype Cycle, featuring technologies that are the focus of attention because of particularly high levels of interest, and those that Gartner believes have the potential for significant impact,” said Betsy Burton, vice president and distinguished analyst at Gartner. “This year, we encourage CIOs and other IT leaders to dedicate time and energy focused on innovation, rather than just incremental business advancement, while also gaining inspiration by scanning beyond the bounds of their industry.”

Major changes in the 2015 Hype Cycle for Emerging Technologies (see Figure 1) include the placement ofautonomous vehicles, which have shifted from pre-peak to peak of the Hype Cycle. While autonomous vehicles are still embryonic, this movement still represents a significant advancement, with all major automotive companies putting autonomous vehicles on their near-term roadmaps. Similarly, the growing momentum (from post-trigger to pre-peak) in connected-home solutions has introduced entirely new solutions and platforms enabled by new technology providers and existing manufacturers.

Figure 1. Hype Cycle for Emerging Technologies, 2015

Source: Gartner (August 2015)

“As enterprises continue the journey to becoming digital businesses, identifying and employing the right technologies at the right time will be critical,” said Ms. Burton. “As we have set out on the Gartner roadmap to digital business, there are six progressive business era models that enterprises can identify with today and to which they can aspire in the future….(More)”

Index: Crime and Criminal Justice Data

Curated on Posted on by Ryan Sibley

The Living Library Index – inspired by the Harper’s Index – provides important statistics and highlights global trends in governance innovation. This installment focuses on crime and criminal justice data and was originally published in 2015.

This index provides information about the type of crime and criminal justice data collected, shared and used in the United States. Because it is well known that data related to the criminal justice system is often times unreliable, or just plain missing, this index also highlights some of the issues that stand in the way of accessing useful and in-demand statistics.

Data Collections: National Crime Statistics

  • Number of incident-based crime datasets created by the Federal Bureau of Investigation (FBI): 2
    • Number of U.S. Statistical Agencies: 13
    • How many of those are focused on criminal justice: 1, the Bureau of Justice Statistics (BJS)
    • Number of data collections focused on criminal justice the BJS produces: 61
    • Number of federal-level APIs available for crime or criminal justice data: 1, the National Crime Victimization Survey (NCVS).
    • Frequency of the NCVS: annually
  • Number of Statistical Analysis Centers (SACs), organizations that are essentially clearinghouses for crime and criminal justice data for each state, the District of Columbia, Puerto Rico and the Northern Mariana Islands: 53

Open data, data use and the impact of those efforts

  • Number of datasets that are returned when “criminal justice” is searched for on Data.gov: 417, including federal-, state- and city-level datasets
  • Number of datasets that are returned when “crime” is searched for on Data.gov: 281
  • The percentage that public complaints dropped after officers started wearing body cameras, according to a study done in Rialto, Calif.: 88
  • The percentage that reported incidents of officer use of force fell after officers started wearing body cameras, according to a study done in Rialto, Calif.: 5
  • The percent that crime decreased during an experiment in predictive policing in Shreveport, LA: 35  
  • Number of crime data sets made available by the Seattle Police Department – generally seen as a leader in police data innovation – on the Seattle.gov website: 4
    • Major crime stats by category in aggregate
    • Crime trend reports
    • Precinct data by beat
    • State sex offender database
  • Number of datasets mapped by the Seattle Police Department: 2:
      • 911 incidents
    • Police reports
  • Number of states where risk assessment tools must be used in pretrial proceedings to help determine whether an offender is released from jail before a trial: at least 11.

Police Data

    • Number of federally mandated databases that collect information about officer use of force or officer involved shootings, nationwide: 0
    • The year a crime bill was passed that called for data on excessive force to be collected for research and statistical purposes, but has never been funded: 1994
    • Number of police departments that committed to being a part of the White House’s Police Data Initiative: 21
    • Percentage of police departments surveyed in 2013 by the Office of Community Oriented Policing within the Department of Justice that are not using body cameras, therefore not collecting body camera data: 75

The criminal justice system

  • Parts of the criminal justice system where data about an individual can be created or collected: at least 6
    • Entry into the system (arrest)
    • Prosecution and pretrial
    • Sentencing
    • Corrections
    • Probation/parole
    • Recidivism

Sources

  • Crime Mapper. Philadelphia Police Department. Accessed August 24, 2014.

Review Federal Agencies on Yelp…and Maybe Get a Response

Curated on Posted on by Stefaan Verhulst

Yelp Official Blog: “We are excited to announce that Yelp has concluded an agreement with the federal government that will allow federal agencies and offices to claim their Yelp pages, read and respond to reviews, and incorporate that feedback into service improvements.

We encourage Yelpers to review any of the thousands of agency field offices, TSA checkpoints, national parks, Social Security Administration offices, landmarks and other places already listed on Yelp if you have good or bad feedback to share about your experiences. Not only is it helpful to others who are looking for information on these services, but you can actually make an impact by sharing your feedback directly with the source.

It’s clear Washington is eager to engage with people directly through social media. Earlier this year a group of 46 lawmakers called for the creation of a “Yelp for Government” in order to boost transparency and accountability, and Representative Ron Kind reiterated this call in a letter to the General Services Administration (GSA). Luckily for them, there’s no need to create a new platform now that government agencies can engage directly on Yelp.

As this agreement is fully implemented in the weeks and months ahead, we’re excited to help the federal government more directly interact with and respond to the needs of citizens and to further empower the millions of Americans who use Yelp every day.

In addition to working with the federal government, last week we announced our our partnership with ProPublica to incorporate health care statistics and consumer opinion survey data onto the Yelp business pages of more than 25,000 medical treatment facilities. We’ve also partnered with local governments in expanding the LIVES open data standard to show restaurant health scores on Yelp….(More)”

Open Data: A 21st Century Asset for Small and Medium Sized Enterprises

Curated on Posted on by Stefaan Verhulst

“The economic and social potential of open data is widely acknowledged. In particular, the business opportunities have received much attention. But for all the excitement, we still know very little about how and under what conditions open data really works.

To broaden our understanding of the use and impact of open data, the GovLab has a variety of initiatives and studies underway. Today, we share publicly our findings on how Small and Medium Sized Enterprises (SMEs) are leveraging open data for a variety of purposes. Our paper “Open Data: A 21st Century Asset for Small and Medium Sized Enterprises” seeks to build a portrait of the lifecycle of open data—how it is collected, stored and used. It outlines some of the most important parameters of an open data business model for SMEs….

The paper analyzes ten aspects of open data and establishes ten principles for its effective use by SMEs. Taken together, these offer a roadmap for any SME considering greater use or adoption of open data in its business.

Among the key findings included in the paper:

  • SMEs, which often lack access to data or sophisticated analytical tools to process large datasets, are likely to be one of the chief beneficiaries of open data.
  • Government data is the main category of open data being used by SMEs. A number of SMEs are also using open scientific and shared corporate data.
  • Open data is used primarily to serve the Business-to-Business (B2B) markets, followed by the Business-to-Consumer (B2C) markets. A number of the companies studied serve two or three market segments simultaneously.
  • Open data is usually a free resource, but SMEs are monetizing their open-data-driven services to build viable businesses. The most common revenue models include subscription-based services, advertising, fees for products and services, freemium models, licensing fees, lead generation and philanthropic grants.
  • The most significant challenges SMEs face in using open data include those concerning data quality and consistency, insufficient financial and human resources, and issues surrounding privacy.

This is just a sampling of findings and observations. The paper includes a number of additional observations concerning business and revenue models, product development, customer acquisition, and other subjects of relevance to any company considering an open data strategy.”

5 Tips for Designing a Data for Good Initiative

Curated on Posted on by Stefaan Verhulst

Mitul Desai at Mastercard Center for Inclusive Growth: “The transformative impact of data on development projects, captured in the hashtag #DATARevolution, offers the social and private sectors alike a rallying point to enlist data in the service of high-impact development initiatives.

To help organizations design initiatives that are authentic to their identity and capabilities, we’re sharing what’s necessary to navigate the deeply interconnected organizational, technical and ethical aspects of creating a Data for Good initiative.

1) Define the need

At the center of a Data for Good initiative are the individual beneficiaries you are seeking to serve. This is foundation on which the “Good” of Data for Good rests.

Understanding the data and expertise needed to better serve such individuals will bring into focus the areas where your organization can contribute and the partners you might engage. As we’ve covered in past posts, collaboration between agents who bring different layers of expertise to Data for Good projects is a powerful formula for change….

2) Understand what data can make a difference

Think about what kind of data can tell a story that’s relevant to your mission. Claudia Perlich of Dstillery says: “The question is first and foremost, what decision do I have to make and which data can tell me something about that decision.” This great introduction to what different kinds of data are relevant in different settings can give you concrete examples.

3) Get the right tools for the job

By one estimate, some 90% of business-relevant data are unstructured or semi-structured (think texts, tweets, images, audio) as opposed to structured data like numbers that easily fit into the lines of a spreadsheet. Perlich notes that while it’s more challenging to mine this unstructured data, they can yield especially powerful insights with the right tools—which thankfully aren’t that hard to identify…..

4) Build a case that moves your organization

“While our programs are designed to serve organizations no matter what their capacity, we do find that an organization’s clarity around mission and commitment to using data to drive decision-making are two factors that can make or break a project,” says Jake Porway, founder and executive director of DataKind, a New York-based data science nonprofit that helps organizations develop Data for Good initiatives…..

5) Make technology serve people-centric ethics

The two most critical ethical factors to consider are informed consent and privacy—both require engaging the community you wish to serve as individual actors….

“Employ data-privacy walls, mask the data from the point of collection and encrypt the data you store. Ensure that appropriate technical and organizational safeguards are in place to verify that the data can’t be used to identify individuals or target demographics in a way that could harm them,” recommends Quid’s Pedraza. To understand the technology of data encryption and masking, check out this post. (More)”

The 5Ps of the Crowd Economy

Curated on Posted on by Stefaan Verhulst

Crowdsourcing week: “As a first step towards a transition to a crowd – focussed organization, it helps to understand what makes up the crowd economy.

1. The people. The crowd economy is empowering, inclusive, disruptive and human centric.

Human-centric values need to be embedded in applications geared towards the crowd economy where the community is the starting point. The crowd economy or collective action is not about mob behavior but very targeted cooperative solutions that help communities better their lives. People-powered platforms are forging these interconnections between users that are breaking down the barriers between creators, producers and end users. By empowering people, organizations are finding new, previously unimagined pathways and solutions to complex problems.

2. The purpose. The crowd economy creates meaningful experiences and shared value.

The crowd economy embodies a culture of shared value creation and social responsibility that distinguishes itself from the traditional one-dimensional thinking and practices of the old economy. People driven initiatives often embody a larger mission to create solutions that work for, and, with all stakeholders. There is more than one channel of communication and the notion that everyone can further his or her purpose is life changing.

3. The platform. Crowds need a medium to interact and produce results.

This pillar of the crowd economy has manifested in the form of technology, connectivity and mobile networks. Soon the Internet of Things will contribute to this medium, amplifying human interactions with powerful data. Platforms like Airbnb and Uber have become synonymous with peer marketplaces and have led to new business paradigms taking shape.

4. The participation. Co-creation and participation are emphasized in the crowd economy and communities take an active stake in crafting positive futures.

The power of participation to accelerate innovation is best seen through crowdfunding, that has enabled early ideas get a jumpstart. Crowd verdict is critical to validate business plans and ideas and working with them only bring financial support but also value product input and iteration.

5. The productivity. Crowd economy fosters faster, cheaper, better and resource efficient processes.

Digital crowd applications for civic activities, disaster relief and humanitarian work are creating widespread impact. Helping and participation comes naturally to us and the networked web has fitted this mindset with wings. …(More)”

The Last Mile: Creating Social and Economic Value from Behavioral Insights

Curated on Posted on by Stefaan Verhulst

New book by Dilip Soman: “Most organizations spend much of their effort on the start of the value creation process: namely, creating a strategy, developing new products or services, and analyzing the market. They pay a lot less attention to the end: the crucial “last mile” where consumers come to their website, store, or sales representatives and make a choice.

In The Last Mile, Dilip Soman shows how to use insights from behavioral science in order to close that gap. Beginning with an introduction to the last mile problem and the concept of choice architecture, the book takes a deep dive into the psychology of choice, money, and time. It explains how to construct behavioral experiments and understand the data on preferences that they provide. Finally, it provides a range of practical tools with which to overcome common last mile difficulties.

The Last Mile helps lay readers not only to understand behavioral science, but to apply its lessons to their own organizations’ last mile problems, whether they work in business, government, or the nonprofit sector. Appealing to anyone who was fascinated by Dan Ariely’s Predictably Irrational, Richard Thaler and Cass Sunstein’s Nudge, or Daniel Kahneman’s Thinking, Fast and Slow but was not sure how those insights could be practically used, The Last Mile is full of solid, practical advice on how to put the lessons of behavioral science to work….(More)”

Making data open for everyone

Curated on Posted on by Stefaan Verhulst

Kathryn L.S. Pettit and Jonathan Schwabis at UrbanWire: “Over the past few years, there have been some exciting developments in open source tools and programming languages, business intelligence tools, big data, open data, and data visualization. These trends, and others, are changing the way we interact with and consume information and data. And that change is driving more organizations and governments to consider better ways to provide their data to more people.

The World Bank, for example, has a concerted effort underway to open its data in better and more visual ways. Google’s Public Data Explorer brings together large datasets from around the world into a single interface. For-profit providers like OpenGov and Socrata are helping local, state, and federal governments open their data (both internally and externally) in newer platforms.

We are firm believers in open data. (There are, of course, limitations to open data because of privacy or security, but that’s a discussion for another time). But open data is not simply about putting more data on the Internet. It’s not just only about posting files and telling people where to find them. To allow and encourage more people to use and interact with data, that data needs to be useful and readable not only by researchers, but also by the dad in northern Virginia or the student in rural Indiana who wants to know more about their public libraries.

Open data should be easy to access, analyze, and visualize

Many are working hard to provide more data in better ways, but we have a long way to go. Take, for example, the Congressional Budget Office (full disclosure, one of us used to work at CBO). Twice a year, CBO releases its Budget and Economic Outlook, which provides the 10-year budget projections for the federal government. Say you want to analyze 10-year budget projections for the Pell Grant program. You’d need to select “Get Data” and click on “Baseline Projections for Education” and then choose “Pell Grant Programs.” This brings you to a PDF report, where you can copy the data table you’re looking for into a format you can actually use (say, Excel). You would need to repeat the exercise to find projections for the 21 other programs for which the CBO provides data.

In another case, the Bureau of Labor Statistics has tried to provide users with query tools that avoid the use of PDFs, but still require extra steps to process. You can get the unemployment rate data through their Java Applet (which doesn’t work on all browsers, by the way), select the various series you want, and click “Get Data.” On the subsequent screen, you are given some basic formatting options, but the default display shows all of your data series as separate Excel files. You can then copy and paste or download each one and then piece them together.

Taking a step closer to the ideal of open data, the Institute of Museum and Library Services (IMLS)followed President Obama’s May 2013 executive order to make their data open in a machine-readable format. That’s great, but it only goes so far. The IMLS platform, for example, allows you to explore information about your own public library. But the data are labeled with variable names such as BRANLIB and BKMOB that are not intuitive or clear. Users then have to find the data dictionary to understand what data fields mean, how they’re defined, and how to use them.

These efforts to provide more data represent real progress, but often fail to be useful to the average person. They move from publishing data that are not readable (buried in PDFs or systems that allow the user to see only one record at a time) to data that are machine-readable (libraries of raw data files or APIs, from which data can be extracted using computer code). We now need to move from a world in which data are simply machine-readable to one in which data are human-readable….(More)”

Open data can unravel the complex dealings of multinationals

Curated on Posted on by Stefaan Verhulst

 in The Guardian: “…Just like we have complementary currencies to address shortcomings in national monetary systems, we now need to encourage an alternative accounting sector to address shortcomings in global accounting systems.

So what might this look like? We already are seeing the genesis of this in the corporate open data sector. OpenCorporates in London has been a pioneer in this field, creating a global unique identifier system to make it easier to map corporations. Groups like OpenOil in Berlin are now using the OpenCorporates classification system to map companies like BP. Under the tagline “Imagine an open oil industry”, they have also begun mapping ground-level contract and concession data, and are currently building tools to allow the public to model the economics of particular mines and oil fields. This could prove useful in situations where doubt is cast on the value of particular assets controlled by public companies in politically fragile states.

 OpenOil’s objective is not just corporate transparency. Merely disclosing information does not advance understanding. OpenOil’s real objective is to make reputable sources of information on oil companies usable to the general public. In the case of BP, company data is already deposited in repositories like Companies House, but in unusable, jumbled and jargon-filled pdf formats. OpenOil seeks to take such transparency, and turn it into meaningful transparency.

According to OpenOil’s Anton Rühling, a variety of parties have started to use their information. “During the recent conflicts in Yemen we had a sudden spike in downloads of our Yemeni oil contract information. We traced this to UAE, where a lot of financial lawyers and investors are based. They were clearly wanting to see how the contracts could be affected.” Their BP map even raised interest from senior BP officials. “We were contacted by finance executives who were eager to discuss the results.”

Open mapping

Another pillar of the alternative accounting sector that is emerging are supply chain mapping systems. The supply chain largely remains a mystery. In standard corporate accounts suppliers appear as mere expenses. No information is given about where the suppliers are based and what their standards are. In the absence of corporate management volunteering that information, Sourcemap has created an open platform for people to create supply chain maps themselves. Progressively-minded companies – such as Fairphone – have now begun to volunteer supply chain information on the platform.

One industry forum that is actively pondering alternative accounting is ICAEW’s AuditFutures programme. They recently teamed up with the Royal College of Art’s service design programme to build design thinking into accounting practice. AuditFuture’s Martin Martinoff wants accountants’ to perceive themselves as being creative innovators for the public interest. “Imagine getting 10,000 auditors online together to develop an open crowdsourced audit platform.”…(More)