social media

Soon Your City Will Know Everything About You

Curated on June 7, 2016May 29, 2019 by Stefaan Verhulst

Philip N. Howard at Yahoo Tech: “They call it “the Internet of Things” — the rapidly growing network of everyday objects equipped with sensors, tiny power supplies, and internet addresses. Within a few years, we will be immersed in a world of these connected devices. The best estimatessuggest that there will be about 60 billion of them by the year 2020. We’ve already seen internet-accessible sensors implanted in dolls, cars, and cows.

Currently, the biggest users of these sensor arrays are in cities, where city governments use them to collect large amounts of policy-relevant data. In Los Angeles, the crowdsourced traffic and navigation app Waze collects data that helps residents navigate the city’s choked highway networks. In Chicago, an ambitious program makes public data available to startups eager to build apps for residents. The city’s 49th ward has been experimenting with participatory budgeting and online votingto take the pulse of the community on policy issues. Chicago has also been developing the “Array of Things,” a network of sensors that track, among other things, the urban conditions that affect bronchitis.

Edmonton uses the cloud to track the condition of playground equipment. And a growing number of countries have purpose-built smart cities, like South Korea’s high tech utopia city of Songdo, where pervasive sensor networks and ubiquitous computing generate immense amounts of civic data for public services.

The drive for smart cities isn’t restricted to the developed world. Rio de Janeiro coordinates the information flows of 30 different city agencies. In Beijing and Da Nang (Vietnam), mobile phone data is actively tracked in the name of real-time traffic management. Urban sensor networks, in other words, are also developing in countries with few legal protections governing the usage of data.

These services are promising and useful. But you don’t have to look far to see why the Internet of Things has serious privacy implications. Public data is used for “predictive policing” in at least 75 cities across the U.S., including New York City, where critics maintain that using social media or traffic data to help officers evaluate probable cause is a form of digital stop-and-frisk. In Los Angeles, the security firm Palantir scoops up publicly generated data on car movements, merges it with license plate information collected by the city’s traffic cameras, and sells analytics back to the city so that police officers can decide whether or not to search a car. In Chicago, concern is growing about discriminatory profiling because so much information is collected and managed by the police department — an agency with a poor reputation for handling data in consistent and sensitive ways. In 2015, video surveillance of the police shooting Laquan McDonald outside a Burger King was erased by a police employee who ironically did not know his activities were being digitally recorded by cameras inside the restaurant.

Since most national governments have bungled privacy policy, cities — which have a reputation for being better with administrative innovations — will need to fill this gap. A few countries, such as Canada and the U.K., have independent “privacy commissioners” who are responsible for advocating for the public when bureaucracies must decide how to use or give out data. It is pretty clear that cities need such advocates too.

What would Urban Privacy Commissioners do? They would teach the public — and other government staff — about how policy algorithms work. They would evaluate the political context in which city agencies make big data investments. They would help a city negotiate contracts that protect residents’ privacy while providing effective analysis to policy makers and ensuring that open data is consistently serving the public good….(more)”.

Private Data and the Public Good

Curated on June 3, 2016August 3, 2018 by Stefaan Verhulst

Gideon Mann‘s remarks on the occasion of the Robert Khan distinguished lecture at The City College of New York on 5/22/16: and opportunities about a specific aspect of this relationship, the broader need for computer science to engage with the real world. Right now, a key aspect of this relationship is being built around the risks and opportunities of the emerging role of data.

Ultimately, I believe that these relationships, between computer science andthe real world, between data science and real problems, hold the promise tovastly increase our public welfare. And today, we, the people in this room,have a unique opportunity to debate and define a more moral dataeconomy….

The hybrid research model proposes something different. The hybrid research model, embeds, as it were, researchers as practitioners.The thought was always that you would be going about your regular run of business,would face a need to innovate to solve a crucial problem, and would do something novel. At that point, you might choose to work some extra time and publish a paper explaining your innovation. In practice, this model rarely works as expected. Tight deadlines mean the innovation that people do in their normal progress of business is incremental..

This model separated research from scientific publication, and shortens thetime-window of research, to what can be realized in a few year time zone.For me, this always felt like a tremendous loss, with respect to the older so-called “ivory tower” research model. It didn’t seem at all clear how this kindof model would produce the sea change of thought engendered byShannon’s work, nor did it seem that Claude Shannon would ever want towork there. This kind of environment would never support the freestanding wonder, like the robot mouse that Shannon worked on. Moreover, I always believed that crucial to research is publication and participation in the scientific community. Without this engagement, it feels like something different — innovation perhaps.

It is clear that the monopolistic environment that enabled AT&T to support this ivory tower research doesn’t exist anymore. .

Now, the hybrid research model was one model of research at Google, butthere is another model as well, the moonshot model as exemplified byGoogle X. Google X brought together focused research teams to driveresearch and development around a particular project — Google Glass and the Self-driving car being two notable examples. Here the focus isn’t research, but building a new product, with research as potentially a crucial blocking issue. Since the goal of Google X is directly to develop a new product, by definition they don’t publish papers along the way, but they’re not as tied to short-term deliverables as the rest of Google is. However, they are again decidedly un-Bell-Labs like — a secretive, tightly focused, non-publishing group. DeepMind is a similarly constituted initiative — working, for example, on a best-in-the-world Go playing algorithm, with publications happening sparingly.

Unfortunately, both of these approaches, the hybrid research model and the moonshot model stack the deck towards a particular kind of research — research that leads to relatively short term products that generate corporate revenue. While this kind of research is good for society, it isn’t the only kind of research that we need. We urgently need research that is longterm, and that is undergone even without a clear financial local impact. Insome sense this is a “tragedy of the commons”, where a shared public good (the commons) is not supported because everyone can benefit from itwithout giving back. Academic research is thus a non-rival, non-excludible good, and thus reasonably will be underfunded. In certain cases, this takes on an ethical dimension — particularly in health care, where the choice ofwhat diseases to study and address has a tremendous potential to affect human life. Should we research heart disease or malaria? This decisionmakes a huge impact on global human health, but is vastly informed by the potential profit from each of these various medicines….

Private Data means research is out of reach

The larger point that I want to make, is that in the absence of places where long-term research can be done in industry, academia has a tremendous potential opportunity. Unfortunately, it is actually quite difficult to do the work that needs to be done in academia, since many of the resources needed to push the state of the art are only found in industry: in particular data.

Of course, academia also lacks machine resources, but this is a simpler problem to fix — it’s a matter of money, resources form the government could go to enabling research groups building their own data centers or acquiring the computational resources from the market, e.g. Amazon. This is aided by the compute philanthropy that Google and Microsoft practice that grant compute cycles to academic organizations.

But the data problem is much harder to address. The data being collected and generated at private companies could enable amazing discoveries and research, but is impossible for academics to access. The lack of access to private data from companies actually is much more significant effects than inhibiting research. In particular, the consumer level data, collected by social networks and internet companies could do much more than ad targeting.

Just for public health — suicide prevention, addiction counseling, mental health monitoring — there is enormous potential in the use of our online behavior to aid the most needy, and academia and non-profits are set-up to enable this work, while companies are not.

To give a one examples, anorexia and eating disorders are vicious killers. 20 million women and 10 million men suffer from a clinically significant eating disorder at some time in their life, and sufferers of eating disorders have the highest mortality rate of any other mental health disorder — with a jaw-dropping estimated mortality rate of 10%, both directly from injuries sustained by the disorder and by suicide resulting from the disorder.

Eating disorders are particular in that sufferers often seek out confirmatory information, blogs, images and pictures that glorify and validate what sufferers see as “lifestyle” choices. Browsing behavior that seeks out images and guidance on how to starve yourself is a key indicator that someone is suffering. Tumblr, pinterest, instagram are places that people host and seek out this information. Tumblr has tried to help address this severe mental health issue by banning blogs that advocate for self-harm and by adding PSA announcements to query term searches for queries for or related to anorexia. But clearly — this is not the be all and end all of work that could be done to detect and assist people at risk of dying from eating disorders. Moreover, this data could also help understand the nature of those disorders themselves…..

There is probably a role for a data ombudsman within private organizations — someone to protect the interests of the public’s data inside of an organization. Like a ‘public editor’ in a newspaper according to how you’ve set it up. There to protect and articulate the interests of the public, which means probably both sides — making sure a company’s data is used for public good where appropriate, and making sure the ‘right’ to privacy of the public is appropriately safeguarded (and probably making sure the public is informed when their data is compromised).

Next, we need a platform to make collaboration around social good between companies and between companies and academics. This platform would enable trusted users to have access to a wide variety of data, and speed process of research.

Finally, I wonder if there is a way that government could support research sabbaticals inside of companies. Clearly, the opportunities for this research far outstrip what is currently being done…(more)”

How Open Data Is Creating New Opportunities in the Public Sector

Curated on June 2, 2016August 3, 2018 by Stefaan Verhulst

Martin Yan at GovTech: Increased availability of open data in turn increases the ease with which citizens and their governments can collaborate, as well as equipping citizens to be active in identifying and addressing issues themselves. Technology developers are able to explore innovative uses of open data in combination with digital tools, new apps or other products that can tackle recognized inefficiencies. Currently, both the public and private sectors are teeming with such apps and projects….

Open data has proven to be a catalyst for the creation of new tools across industries and public-sector uses. Examples of a few successful projects include:

Citymapper — The popular real-time public transport app uses open data from Apple, Google, Cyclestreets, OpenStreetMaps and more sources to help citizens navigate cities. Features include A-to-B trip planning with ETA, real-time departures, bike routing, transit maps, public transport line status, real-time disruption alerts and integration with Uber.
Dataverse Project — This project from Harvard’s Institute for Quantitative Social Science makes it easy to share, explore and analyze research data. By simplifying access to this data, the project allows researchers to replicate others’ work to the benefit of all.
Liveplasma — An interactive search engine, Liveplasma lets users listen to music and view a web-like visualization of similar songs and artists, seeing how they are related and enabling discovery. Content from YouTube is streamed into the data visualizations.
Provenance — The England-based online platform lets users trace the origin and history of a product, also providing its manufacturing information. The mission is to encourage transparency in the practices of the corporations that produce the products we all use.

These examples demonstrate open data’s reach, value and impact well beyond the public sector. As open data continues to be put to wider use, the results will not be limited to increased efficiency and reduced wasteful spending in government, but will also create economic growth and jobs due to the products and services using the information as a foundation.

However, in the end, it won’t be the data alone that solves issues. Rather, it will be dependent on individual citizens, developers and organizations to see the possibilities, take up the call to arms and use this available data to introduce changes that make our world better….(More)”

Is civic technology the killer app for democracy?

Curated on June 2, 2016August 15, 2018 by Stefaan Verhulst

Lorelei Kelly at TechCrunch: “Smartphone apps have improved convenience for public transportation in many urban centers. In Washington, DC, riders can download apps to help them figure out where to go, when to show up and how long to wait for a bus or train. However, the problem with public transport in DC is not the lack of modern, helpful and timely information. The problem is that the Metro subway system is onfire.

Critical infrastructure refers to the vital systems that connect us. Like the water catastrophe in Flint, Michigan and our crumbling roads, bridges and airports, the Metro system in DC is experiencing a systems failure. The Metro’s problems arise from typical public challenges like poor management and deferred maintenance.

Upgrades of physical infrastructure are not easy and nimble like a software patch or an agile design process. They are slow, expensive and subject to deliberation and scrutiny. In other words, they are the fundamental substance of democratic decision-making: big decisions with long-term implications that require thoughtful strategy, significant investment, political leadership and public buy-in.

A killer app is an application you love so much you buy into a whole new way of doing things. Email and social media are good examples of killer apps. The killer app for Metro would have to get political leaders to look beyond their narrow, short-term interests and be willing to invest in modern public transportation for our national capital region.

The same is true for fixing our critical infrastructure throughout the nation. The killer apps for the systems on which we rely daily won’t be technical, they will be human. It will be Americans working together to a build a technology-enabled resilient democracy —one that is inclusive, responsive and successful in the Information Age.

In 2007, the I-35 bridge in Minneapolis collapsed into the Mississippi river. During his presidential bid, Senator John McCain used this event as an example of the failure of our leaders to make trade-offs for common national purpose. Case in point, an extravagantly expensive congressionally funded Alaskan “bridge to nowhere” that served just a handful of people on an island. But how many apps to nowhere are we building?.

In DC, commuters who can afford alternatives will leave Metro. They’ll walk, drive, ordera car service or locate a bikeshare. The people who suffer from the public service risk and imbalance of the current Metro system are those who have no choice.

So here’s the challenge: Modern technology needs to create an inclusive society. Our current technical approach too often means that we’re prioritizing progress or profit for the few over the many. This pattern defeats the purpose of both the technology revolution and American democracy. Government and infrastructure are supposed to serve everyone, but technology thus far has made it so that public failures affect some Americans more than others. …

For democracy to succeed in the Information Age, we’ll need some new rules of engagement with technology. The White House recently released its third report on data and its implications for society. The 2016 report pays special attention to the ethics of machine automation and algorithms. The authors stress the importance of ethical analytics and propose the principle of “equal opportunity by design.” It’s an excellent point of departure as we recalibrate old systems and build new bridges to a more resilient, inclusive and prosperous nation….(more)”

Twiplomacy Study 2016

Curated on June 1, 2016August 3, 2018 by Stefaan Verhulst

Executive Summary: “Social media has become diplomacy’s significant other. It has gone from being an afterthought to being the very first thought of world leaders and governments across the globe, as audiences flock to their newsfeeds for the latest news. This recent worldwide embrace of online channels has brought with it a wave of openness and transparency that has never been experienced before. Social media provides a platform for unconditional communication, and has become a communicator’s most powerful tool. Twitter in particular, has even become a diplomatic ‘barometer, a tool used to analyze and forecast international relations.

There is a vast array of social networks for government communicators to choose from. While some governments and foreign ministries still ponder the pros and cons of any social media engagement, others have gone beyond Twitter, Facebook and Instagram to reach their target audiences, even embracing emerging platforms such as Snapchat, WhatsApp and Telegram where communications are under the radar and almost impossible to track.

Burson-Marsteller’s 2016 Twiplomacy study has been expanded to include other social media platforms such as Facebook, Instagram and YouTube, as well as more niche digital diplomacy platforms such as Snapchat, LinkedIn, Google+,Periscope and Vine.

There is a growing digital divide between governments that are active on social media with dedicated teams and those that see digital engagement as an afterthought and so devote few resources to it. There is still a small number of government leaders who refuse to embrace the new digital world and, for these few, their community managers struggle to bring their organizations into the digital century.

Over the past year, the most popular world leaders on social media have continued to increase their audiences, while new leaders have emerged in the Twittersphere. Argentina’s Mauricio Macri, Canada’s Justin Trudeau and U.S. President Barack Obama have all made a significant impact on Twitter and Facebook over the past year.

Obama’s social media communication has become even more personal through his @POTUS Twitter account and Facebook page, and the first “president of the social media age” will leave the White House in January 2017 with an incredible 137 million fans, followers and subscribers. Beyond merely Twitter and Facebook, world leaders such as the Argentinian President have also become active on new channels like Snapchat to reach a younger audience and potential future voters. Similarly, a number of governments, mainly in Latin America, have started to use Periscope, a cost-effective medium to live-stream their press conferences.

We have witnessed occasional public interactions between leaders, namely the friendly fighting talk between the Obamas, the Queen of England and Canada’s Justin Trudeau. Foreign ministries continue to expand their diplomatic and digital networks by following each other and creating coalitions on specific topics, in particular the fight against ISIS….

A number of world leaders, including the President of Colombia and Australia’s Julie Bishop, also use emojis to brighten up their tweets, creating what can be described as a new diplomatic sign language. The Foreign Ministry in Finland has even produced its own set of 49 emoticons depicting summer and winter in the Nordic country.

We asked a number of digital leaders of some of the best connected foreign ministries and governments to share their thoughts on their preferred social media channel and examples of their best campaigns on our blog. You will learn:

How social media has become the main driving force for change in diplomatic communication for the European Union External Action Service
How Digital Diplomacy is a team tester across the Spanish diplomatic network
How Social media has transformed how the Foreign Ministry of Iceland operates in times of crisis
How digital diplomacy can influence public opinion in the case of the Brazilian Foreign Ministry
How the Foreign Ministry of Ukraine is active on eleven social media channels
How @Canada paints a country portrait one tweet at a time
How Quality trumps Quantity in Finland’s country branding communication
How comments and feedback are key measures of success for the Foreign Ministry of Peru
How the government of Montenegro uses Twitter to reach out to a local and international audience

Here is our list of the #Twiplomacy Top Twenty Twitterati in 2016….(More)”

Smart crowds in smart cities: real life, city scale deployments of a smartphone based participatory crowd management platform

Curated on May 25, 2016August 3, 2018 by Stefaan Verhulst

Tobias Franke, Paul Lukowicz and Ulf Blanke at the Journal of Internet Services and Applications: “Pedestrian crowds are an integral part of cities. Planning for crowds, monitoring crowds and managing crowds, are fundamental tasks in city management. As a consequence, crowd management is a sprawling R&D area (see related work) that includes theoretical models, simulation tools, as well as various support systems. There has also been significant interest in using computer vision techniques to monitor crowds. However, overall, the topic of crowd management has been given only little attention within the smart city domain. In this paper we report on a platform for smart, city-wide crowd management based on a participatory mobile phone sensing platform. Originally, the apps based on this platform have been conceived as a technology validation tool for crowd based sensing within a basic research project. However, the initial deployments at the Notte Bianca Festival¹ in Malta and at the Lord Mayor’s Show in London² generated so much interest within the civil protection community that it has gradually evolved into a full-blown participatory crowd management system and is now in the process of being commercialized through a startup company. Until today it has been deployed at 14 events in three European countries (UK, Netherlands, Switzerland) and used by well over 100,000 people….

Obtaining knowledge about the current size and density of a crowd is one of the central aspects of crowd monitoring . For the last decades, automatic crowd monitoring in urban areas has mainly been performed by means of image processing . One use case for such video-based applications can be found in, where a CCTV camera-based system is presented that automatically alerts the staff of subway stations when the waiting platform is congested. However, one of the downsides of video-based crowd monitoring is the fact that video cameras tend to be considered as privacy invading. Therefore, presents a privacy preserving approach to video-based crowd monitoring where crowd sizes are estimated without people models or object tracking.

With respect to the mitigation of catastrophes induced by panicking crowds (e.g. during an evacuation), city planners and architects increasingly rely on tools simulating crowd behaviors in order to optimize infrastructures. Murakami et al. presents an agent based simulation for evacuation scenarios. Shendarkar et al. presents a work that is also based on BSI (believe, desire, intent) agents – those agents however are trained in a virtual reality environment thereby giving greater flexibility to the modeling. Kluepfel et al. on the other hand uses a cellular automaton model for the simulation of crowd movement and egress behavior.

With smartphones becoming everyday items, the concept of crowd sourcing information from users of mobile application has significantly gained traction. Roitman et al. presents a smart city system where the crowd can send eye witness reports thereby creating deeper insights for city officials. Szabo et al. takes this approach one step further and employs the sensors built into smartphones for gathering data for city services such as live transit information. Ghose et al. utilizes the same principle for gathering information on road conditions. Pan et al. uses a combination of crowd sourcing and social media analysis for identifying traffic anomalies….(More)”.

Reining in the Big Promise of Big Data: Transparency, Inequality, and New Regulatory Frontiers

Curated on May 23, 2016August 3, 2018 by Stefaan Verhulst

Paper by Philipp Hacker and Bilyana Petkova: “The growing differentiation of services based on Big Data harbors the potential for both greater societal inequality and for greater equality. Anti-discrimination law and transparency alone, however, cannot do the job of curbing Big Data’s negative externalities while fostering its positive effects.

To rein in Big Data’s potential, we adapt regulatory strategies from behavioral economics, contracts and criminal law theory. Four instruments stand out: First, active choice may be mandated between data collecting services (paid by data) and data free services (paid by money). Our suggestion provides concrete estimates for the price range of a data free option, sheds new light on the monetization of data collecting services, and proposes an “inverse predatory pricing” instrument to limit excessive pricing of the data free option. Second, we propose using the doctrine of unconscionability to prevent contracts that unreasonably favor data collecting companies. Third, we suggest democratizing data collection by regular user surveys and data compliance officers partially elected by users. Finally, we trace back new Big Data personalization techniques to the old Hartian precept of treating like cases alike and different cases – differently. If it is true that a speeding ticket over $50 is less of a disutility for a millionaire than for a welfare recipient, the income and wealth-responsive fines powered by Big Data that we suggest offer a glimpse into the future of the mitigation of economic and legal inequality by personalized law. Throughout these different strategies, we show how salience of data collection can be coupled with attempts to prevent discrimination against and exploitation of users. Finally, we discuss all four proposals in the context of different test cases: social media, student education software and credit and cell phone markets.

Many more examples could and should be discussed. In the face of increasing unease about the asymmetry of power between Big Data collectors and dispersed users, about differential legal treatment, and about the unprecedented dimensions of economic inequality, this paper proposes a new regulatory framework and research agenda to put the powerful engine of Big Data to the benefit of both the individual and societies adhering to basic notions of equality and non-discrimination….(More)”

Scientists Are Just as Confused About the Ethics of Big-Data Research as You

Curated on May 21, 2016August 3, 2018 by Stefaan Verhulst

Sarah Zhang at Wired: “When a rogue researcher last week released 70,000 OkCupid profiles, complete with usernames and sexual preferences, people were pissed. When Facebook researchers manipulated stories appearing in Newsfeeds for a mood contagion study in 2014, people were really pissed. OkCupid filed a copyright claim to take down the dataset; the journal that published Facebook’s study issued an “expression of concern.” Outrage has a way of shaping ethical boundaries. We learn from mistakes.

Shockingly, though, the researchers behind both of those big data blowups never anticipated public outrage. (The OkCupid research does not seem to have gone through any kind of ethical review process, and a Cornell ethics review board approved the Facebook experiment.) And that shows just how untested the ethics of this new field of research is. Unlike medical research, which has been shaped by decades of clinical trials, the risks—and rewards—of analyzing big, semi-public databases are just beginning to become clear.

And the patchwork of review boards responsible for overseeing those risks are only slowly inching into the 21st century. Under the Common Rule in the US, federally funded research has to go through ethical review. Rather than one unified system though, every single university has its own institutional review board, or IRB. Most IRB members are researchers at the university, most often in the biomedical sciences. Few are professional ethicists.

Even fewer have computer science or security expertise, which may be necessary to protect participants in this new kind of research. “The IRB may make very different decisions based on who is on the board, what university it is, and what they’re feeling that day,” says Kelsey Finch, policy counsel at the Future of Privacy Forum. There are hundreds of these IRBs in the US—and they’re grappling with research ethics in the digital age largely on their own….

Or maybe other institutions, like the open science repositories asking researchers to share data, should be picking up the slack on ethical issues. “Someone needs to provide oversight, but the optimal body is unlikely to be an IRB, which usually lacks subject matter expertise in de-identification and re-identification techniques,” Michelle Meyer, a bioethicist at Mount Sinai, writes in an email.

Even among Internet researchers familiar with the power of big data, attitudes vary. When Katie Shilton, an information technology research at the University of Maryland, interviewed 20 online data researchers, she found “significant disagreement” over issues like the ethics of ignoring Terms of Service and obtaining informed consent. Surprisingly, the researchers also said that ethical review boards had never challenged the ethics of their work—but peer reviewers and colleagues had. Various groups like theAssociation of Internet Researchers and the Center for Applied Internet Data Analysis have issued guidelines, but the people who actually have power—those on institutional review boards–are only just catching up.

Outside of academia, companies like Microsoft have started to institute their own ethical review processes. In December, Finch at the Future of Privacy Forum organized a workshop called Beyond IRBs to consider processes for ethical review outside of federally funded research. After all, modern tech companies like Facebook, OkCupid, Snapchat, Netflix sit atop a trove of data 20th century social scientists could have only dreamed up.

Of course, companies experiment on us all the time, whether it’s websites A/B testing headlines or grocery stores changing the configuration of their checkout line. But as these companies hire more data scientists out of PhD programs, academics are seeing an opportunity to bridge the divide and use that data to contribute to public knowledge. Maybe updated ethical guidelines can be forged out of those collaborations. Or it just might be a mess for a while….(More)”