Collection

The Entrepreneurial Impact of Open Data

Curated on February 8, 2018October 9, 2018 by Stefaan Verhulst

Sheena Iyengar and Patrick Bergemann at Opening Governance Research Network: “…To understand how open data is being used to spur innovation and create value, the Governance Lab (GovLab) at NYU Tandon School of Engineering conducted the first ever census of companies that use open data. Using outreach campaigns, expert advice and other sources, they created a database of more than 500 companies founded in the United States called the Open Data 500 (OD500). Among the small and medium enterprises identified that use government data, the most common industries they found are data and technology, followed by finance and investment, business and legal services, and healthcare.

In the context of our collaboration with the GovLab-chaired MacArthur Foundation Research Network on Opening Governance, we sought to dig deeper into the broader impact of open data on entrepreneurship. To do so we combined the OD500 with databases on startup activity from Crunchbase and AngelList. This allowed us to look at the trajectories of open data companies from their founding to the present day. In particular, we compared companies that use open data to similar companies with the same founding year, location and industry to see how well open data companies fare at securing funding along with other indicators of success.

We first looked at the extent to which open data companies have access to investor capital, wondering if open data companies have difficulty gaining funding because their use of public data may be perceived as insufficiently innovative or proprietary. If this is the case, the economic impact of open data may be limited. Instead, we found that open data companies obtain more investors than similar companies that do not use open data. Open data companies have, on average, 1.74 more investors than similar companies founded at the same time. Interestingly, investors in open data companies are not a specific group who specialize in open data startups. Instead, a wide variety of investors put money into these companies. Of the investors who funded open data companies, 59 percent had only invested in one open data company, while 81 percent had invested in one or two. Open data companies appear to be appealing to a wide range of investors….(More)”.

Is full transparency good for democracy?

Curated on February 8, 2018August 3, 2018 by Stefaan Verhulst

Austin Sarat at The Conversation: “Public knowledge about what government officials do is essential in a representative democracy. Without such knowledge, citizens cannot make informed choices about who they want to represent them or hold public officials accountable.

Political theorists have traced arguments about publicity and democracy back to ancient Greece and Rome. Those arguments subsequently flowered in the middle of the 19th century.

For example, writing about British parliamentary democracy, the famous philosopher Jeremy Bentham urged that legislative deliberation be carried out in public. Public deliberation, in his view, would be an important factor in “constraining the members of the assembly to perform their duty” and in securing “the confidence of the people.”

Moreover, Bentham noted that “suspicion always attaches to mystery.”

Even so, Bentham did not think the public had an unqualified “right to know.” As he put it, “It is not proper to make the law of publicity absolute.” Bentham acknowledged that publicity “ought to be suspended” when informing the public would “favor the projects of an enemy.”

Well into the 20th century, the U.S. and other democracies existed with far less public transparency than Bentham advocated.

Push for transparency

The authors of a 2016 U.S. Congressional report on access to government information observed that, “Throughout the first 150 years of the federal government, access to government information does not appear to have been a major issue for the federal branches or the public.” In short, the public generally did not demand more information than the government provided….

For at least the last 50 years, American legal and political institutions have tried to find a balance between publicity and secrecy. The courts have identified limits to claims of executive privilege like those made by President Nixon during Watergate. Watergate also led Congress in 1978 to pass the Foreign Intelligence Surveillance Act, or FISA. That act created a special court, whose procedures were highlighted in the Nunes memo. The FISA court authorizes collection of intelligence information between foreign powers and “agents of foreign powers.”

Finding the proper balance between making information public in order to foster accountability and the government’s concern for national security is not easy. Just look to the heated debates that accompanied passage of the Patriot Act and what WikiLeaks did in 2010 when it published more than 300,000 classified U.S. Army field reports.

Americans can make little progress in resolving such debates until they can get beyond the cynical, partisan use of slogans like “the public’s right to know” and “full transparency” by President Trump’s loyalists. Now more than ever, Americans must understand how and when transparency contributes to the strength and vitality of our democratic institutions and how and when the invocation of the public’s right to know is being used to erode them….(More)”.

Big Data, Thick Mediation, and Representational Opacity

Curated on February 8, 2018October 9, 2018 by Stefaan Verhulst

Rafael Alvarado and Paul Humphreys in the New Literary History: “In 2008, the phrase “big data” shifted in meaning. It turned from referring to a problem and an opportunity for organizations with very large data sets to being the talisman for an emerging economic and cultural order that is both celebrated and feared for its deep and pervasive effects on the human condition. Economically, the phrase now denotes a data-mediated form of commerce exemplified by Google. Culturally, the phrase stands for a new form of knowledge and knowledge production. In this essay, we explore the connection between these two implicit meanings, considered as dimensions of a real social and scientific transformation with observable properties. We develop three central concepts: the datasphere, thick mediation, and representational opacity. These concepts provide a theoretical framework for making sense of how the economic and cultural dimensions interact to produce a set of effects, problems, and opportunities, not all of which have been addressed by big data’s critics and advocates….(More)”.

Is your software racist?

Curated on February 8, 2018August 3, 2018 by Stefaan Verhulst

Li Zhou at Politico: “Late last year, a St. Louis tech executive named Emre Şarbak noticed something strange about Google Translate. He was translating phrases from Turkish — a language that uses a single gender-neutral pronoun “o” instead of “he” or “she.” But when he asked Google’s tool to turn the sentences into English, they seemed to read like a children’s book out of the 1950’s. The ungendered Turkish sentence “o is a nurse” would become “she is a nurse,” while “o is a doctor” would become “he is a doctor.”

The website Quartz went on to compose a sort-of poem highlighting some of these phrases; Google’s translation program decided that soldiers, doctors and entrepreneurs were men, while teachers and nurses were women. Overwhelmingly, the professions were male. Finnish and Chinese translations had similar problems of their own, Quartz noted.

What was going on? Google’s Translate tool “learns” language from an existing corpus of writing, and the writing often includes cultural patterns regarding how men and women are described. Because the model is trained on data that already has biases of its own, the results that it spits out serve only to further replicate and even amplify them.

It might seem strange that a seemingly objective piece of software would yield gender-biased results, but the problem is an increasing concern in the technology world. The term is “algorithmic bias” — the idea that artificially intelligent software, the stuff we count on to do everything from power our Netflix recommendations to determine our qualifications for a loan, often turns out to perpetuate social bias.

Voice-based assistants, like Amazon’s Alexa, have struggled to recognize different accents. A Microsoft chatbot on Twitter started spewing racist posts after learning from other users on the platform. In a particularly embarrassing example in 2015, a black computer programmer found that Google’s photo-recognition tool labeled him and a friend as “gorillas.”

Sometimes the results of hidden computer bias are insulting, other times merely annoying. And sometimes the effects are potentially life-changing….(More)”.

Our Hackable Political Future

Curated on February 7, 2018August 3, 2018 by Stefaan Verhulst

Henry J. Farrell and Rick Perlstein at the New York Times: “….A program called Face2Face, developed at Stanford, films one person speaking, then manipulates that person’s image to resemble someone else’s. Throw in voice manipulation technology, and you can literally make anyone say anything — or at least seem to….

Another harrowing potential is the ability to trick the algorithms behind self-driving cars to not recognize traffic signs. Computer scientists have shown that nearly invisible changes to a stop sign can fool algorithms into thinking it says yield instead. Imagine if one of these cars contained a dissident challenging a dictator.

In 2007, Barack Obama’s political opponents insisted that footage existed of Michelle Obama ranting against “whitey.” In the future, they may not have to worry about whether it actually existed. If someone called their bluff, they may simply be able to invent it, using data from stock photos and pre-existing footage.

The next step would be one we are already familiar with: the exploitation of the algorithms used by social media sites like Twitter and Facebook to spread stories virally to those most inclined to show interest in them, even if those stories are fake.

It might be impossible to stop the advance of this kind of technology. But the relevant algorithms here aren’t only the ones that run on computer hardware. They are also the ones that undergird our too easily hacked media system, where garbage acquires the perfumed scent of legitimacy with all too much ease. Editors, journalists and news producers can play a role here — for good or for bad.

Outlets like Fox News spread stories about the murder of Democratic staff members and F.B.I. conspiracies to frame the president. Traditional news organizations, fearing that they might be left behind in the new attention economy, struggle to maximize “engagement with content.”

This gives them a built-in incentive to spread informational viruses that enfeeble the very democratic institutions that allow a free media to thrive. Cable news shows consider it their professional duty to provide “balance” by giving partisan talking heads free rein to spout nonsense — or amplify the nonsense of our current president.

It already feels as though we are living in an alternative science-fiction universe where no one agrees on what it true. Just think how much worse it will be when fake news becomes fake video. Democracy assumes that its citizens share the same reality. We’re about to find out whether democracy can be preserved when this assumption no longer holds….(More)”.

Should We Treat Data as Labor? Moving Beyond ‘Free’

Curated on February 7, 2018August 3, 2018 by Stefaan Verhulst

Paper by Imanol Arrieta Ibarra, Leonard Goff, Diego Jiménez Hernández and Jaron Lanier: “In the digital economy, user data is typically treated as capital created by corporations observing willing individuals. This neglects users’ role in creating data, reducing incentives for users, distributing the gains from the data economy unequally and stoking fears of automation. Instead treating data (at least partially) as labor could help resolve these issues and restore a functioning market for user contributions, but may run against the near-term interests of dominant data monopsonists who have benefited from data being treated as ‘free’. Countervailing power, in the form of competition, a data labor movement and/or thoughtful regulation could help restore balance….(More)”.

Behavioral Analysis of International Law: On Lawmaking and Nudging

Curated on February 6, 2018August 3, 2018 by Stefaan Verhulst

Article by Doron Teichman and Eyal Zamir: “… examines the application of insights from behavioral economics to the area of international law. It reviews the unique challenges facing such application and demonstrates the contribution of behavioral findings to the understanding of lawmaking, the use of nudges, and states’ practices in the international arena.

In the sphere of lawmaking, the article first highlights the contribution of experimental game theory to understanding international customary law. It then analyzes the psychological mechanisms underpinning the advancement of treaty law through the use of deadlines, grandfather provisions, deferred implementation, and temporary arrangements. More generally, it provides insight into the processes through which international soft law evolves into hard law.

The article then argues that in the absence of a central legislative body or strong enforcement mechanisms, nudges (that is, low-cost, choice-preserving, behaviorally informed regulatory tools) can play a particularly important role in influencing the behavior of states and other entities. The article describes the current use of nudges, such as opt-in and opt-out arrangements in multilateral treaties, goal settings, and international rankings—and calls for further employment of such means.

Finally, the article suggests that the extent to which states comply with international norms may be explained by phenomena such as loss aversion and the identifiability effect; and that further insight into states’ (non)compliance may be gained from the emerging research in behavioral ethics…(More)”

And Yet They Thrive!—Regaining the Relevance of a Transparency System

Curated on February 6, 2018August 3, 2018 by Stefaan Verhulst

Paper by Pontus Hedlin in Development Policy Review: “Over the past decade, a host of donor organizations implemented transparency systems to make international development aid more transparent to the public. These initiatives have met with little public interest, but their proliferation and development show no sign of diminishing. This article shows how internal importance to the political system, fueled by formal rankings and the exhibition of transparency systems as a flagship initiative, can replace relevance to the public as a driving force for sustainable development. The article concludes by discussing the possibility of a future development where transparency systems finally do connect with user groups, such as citizens of both donor and recipient countries, and gain a relevance even beyond original intentions….(More)”.