Entrepreneurial Administration

Curated on Posted on by Stefaan Verhulst

Research Paper by Phil Weiser: “A core failing of today’s administrative state and modern administrative law scholarship is the lack of imagination as to how agencies should operate. On the conventional telling, public agencies follow specific grants of regulatory authority, use the traditional tools of notice-and-comment rulemaking and adjudication, and are checked by judicial review. In reality, however, effective administration depends on entrepreneurial leadership that spearheads policy experimentation and trial-and-error problem-solving, including the development of regulatory programs that use non-traditional tools.

Entrepreneurial administration takes place both at public agencies and private entities, each of which can address regulatory challenges and earn regulatory authority as a result. Consider, for example, that Energy Star, a successful program that has encouraged the manufacture and sale of energy efficient appliances, is developed and overseen by the Environmental Protection Agency (EPA). After the EPA established the program, Congress later codified it and, eventually, other countries followed suit. By contrast, the successful and complementary program encouraging the construction of energy efficient buildings, the well-respected LEED standard, is developed and overseen by a private organization. After it was developed, a number of governmental authorities endorsed it and have encouraged LEED-certified construction projects with both carrots and sticks. Significantly, while neither the Energy Star nor the LEED program were originally anticipated by any regulatory statute, both have had a tremendous impact.

The Energy Star and LEED case studies exemplify the sort of innovative regulatory strategies that are taking root in the modern administrative state. Despite the importance of entrepreneurial administration in practice, scholars have failed to examine the role of entrepreneurial leadership in spurring policy innovation and earning regulatory authority for an agency (or private entity). In short, administrative law needs a richer and more textured account of agency action, why entrepreneurial leadership matters in government, and how agencies should operate.

This Article explains that the conventional view of agency behavior — either following the specific direction of Congress or the President to use notice-and-comment rulemaking or adjudication processes — does not adequately portray how public agencies and private entities develop innovative regulatory strategies and earn regulatory authority as a result. In particular, this Article explains how governmental agencies like the EPA or private entities like the Green Building Council (which oversees the LEED standard) depend on entrepreneurial leadership to develop experimental regulatory strategies. It also explains how, in the wake of such experiments, legislative bodies have the opportunity to evaluate regulatory innovations in practice before deciding whether to embrace, revise, reject, or merely tolerate them.

This Article highlights the importance of entrepreneurial leadership in government, providing a number of examples of emerging regulatory experiments and suggesting how Congress should evaluate such experiments. This discussion explains how entrepreneurial leadership and a culture of experimentation and trial-and-error learning is necessary to develop innovative strategies and overcome the pressure to manage the status quo. In so doing, the Article underscores how policy entrepreneurship is integral to agency effectiveness, an important corrective to public choice theory, and a missing piece of modern administrative law scholarship….(More)”.

Can social media, loud and inclusive, fix world politics

Curated on Posted on by Stefaan Verhulst

 at the Conversation: “Privacy is no longer a social norm, said Facebook founder Mark Zuckerberg in 2010, as social media took a leap to bring more private information into the public domain.

But what does it mean for governments, citizens and the exercise of democracy? Donald Trump is clearly not the first leader to use his Twitter account as a way to both proclaim his policies and influence the political climate. Social media presents novel challenges to strategic policy, and has become a managerial issues for many governments.

But it also offers a free platform for public participation in government affairs. Many argue that the rise of social media technologies can give citizens and observers a better opportunity to identify pitfalls of government and their politics.

As government embrace the role of social media and the influence of negative or positive feedback on the success of their project, they are also using this tool to their advantages by spreading fabricated news.

This much freedom of expression and opinion can be a double-edged sword.

A tool that triggers change

On the positive side, social media include social networking applications such as Facebook and Google+, microblogging services such as Twitter, blogs, video blogs (vlogs), wikis, and media-sharing sites such as YouTube and Flickr, among others.

Social media as a collaborative and participatory tool, connects users with each other and help shaping various communities. Playing a key role in delivering public service value to citizens it also helps people to engage in politics and policy-making, making processes easier to understand, through information and communication technologies (ICTs).

Today four out of five countries in the world have social media features on their national portals to promote interactive networking and communication with the citizen. Although we don’t have any information about the effectiveness of such tools or whether they are used to their full potential, 20% of these countries shows that they have “resulted in new policy decisions, regulation or service”.

Social media can be an effective tool to trigger changes in government policies and services if well used. It can be used to prevent corruption, as it is direct method of reaching citizens. In developing countries, corruption is often linked to governmental services that lack automated processes or transparency in payments.

The UK is taking the lead on this issue. Its anti-corruption innovation hub aims to connect several stakeholders – including civil society, law enforcement and technologies experts – to engage their efforts toward a more transparent society.

With social media, governments can improve and change the way they communicate with their citizens – and even question government projects and policies. In Kazakhstan, for example, a migration-related legislative amendment entered into force early January 2017 and compelled property owners to register people residing in their homes immediately or else face a penalty charge starting in February 2017.

Citizens were unprepared for this requirement, and many responded with indignation on social media. At first the government ignored this reaction. However, as the growing anger soared via social media, the government took action and introduced a new service to facilitate the registration of temporary citizens….

But the campaigns that result do not always evolve into positive change.

Egypt and Libya are still facing several major crises over the last years, along with political instability and domestic terrorism. The social media influence that triggered the Arab Spring did not permit these political systems to turn from autocracy to democracy.

Brazil exemplifies a government’s failure to react properly to a massive social media outburst. In June 2013 people took to the streets to protest the rising fares of public transportation. Citizens channelled their anger and outrage through social media to mobilise networks and generate support.

The Brazilian government didn’t understand that “the message is the people”. Though the riots some called the “Tropical Spring” disappeared rather abruptly in the months to come, they had major and devastating impact on Brazil’s political power, culminating in the impeachment of President Rousseff in late 2016 and the worst recession in Brazil’s history.

As in the Arab Spring countries, the use of social media in Brazil did not result in economic improvement. The country has tumbled down into depression, and unemployment has risen to 12.6%…..

Government typically asks “how can we adapt social media to the way in which we do e-services, and then try to shape their policies accordingly. They would be wiser to ask, “how can social media enable us to do things differently in a way they’ve never been done before?” – that is, policy-making in collaboration with people….(More)”.

The Conversation

Regulating by Robot: Administrative Decision Making in the Machine-Learning Era

Curated on Posted on by Stefaan Verhulst

Paper by Cary Coglianese and David Lehr: “Machine-learning algorithms are transforming large segments of the economy, underlying everything from product marketing by online retailers to personalized search engines, and from advanced medical imaging to the software in self-driving cars. As machine learning’s use has expanded across all facets of society, anxiety has emerged about the intrusion of algorithmic machines into facets of life previously dependent on human judgment. Alarm bells sounding over the diffusion of artificial intelligence throughout the private sector only portend greater anxiety about digital robots replacing humans in the governmental sphere.

A few administrative agencies have already begun to adopt this technology, while others have the clear potential in the near-term to use algorithms to shape official decisions over both rulemaking and adjudication. It is no longer fanciful to envision a future in which government agencies could effectively make law by robot, a prospect that understandably conjures up dystopian images of individuals surrendering their liberty to the control of computerized overlords. Should society be alarmed by governmental use of machine learning applications?

We examine this question by considering whether the use of robotic decision tools by government agencies can pass muster under core, time-honored doctrines of administrative and constitutional law. At first glance, the idea of algorithmic regulation might appear to offend one or more traditional doctrines, such as the nondelegation doctrine, procedural due process, equal protection, or principles of reason-giving and transparency.

We conclude, however, that when machine-learning technology is properly understood, its use by government agencies can comfortably fit within these conventional legal parameters. We recognize, of course, that the legality of regulation by robot is only one criterion by which its use should be assessed. Obviously, agencies should not apply algorithms cavalierly, even if doing so might not run afoul of the law, and in some cases, safeguards may be needed for machine learning to satisfy broader, good-governance aspirations. Yet in contrast with the emerging alarmism, we resist any categorical dismissal of a future administrative state in which key decisions are guided by, and even at times made by, algorithmic automation. Instead, we urge that governmental reliance on machine learning should be approached with measured optimism over the potential benefits such technology can offer society by making government smarter and its decisions more efficient and just….(More)”

Forecasting Freedom of Information – Why it faces problems—and how experts say they could be solved,

Curated on Posted on by Stefaan Verhulst

Report by David Cuillier: “People must have access to reliable public information to make informed decisions and hold their elected officials accountable. Without transparent government at all levels—local, state and federal—representative democracy is threatened. For a generation, presidents of both parties have in different ways tightened controls on government information. “The natural progress of things,” Thomas Jefferson once wrote, “is for liberty to yield, and government to gain ground.”

The John S. and James L. Knight Foundation commissioned this study to better understand the landscape involving public access to government records by gathering information and insights from 336 freedom of information experts—journalists, advocates, record custodians, technology companies, scholars and others. In all, from December 2016 through January 2017, 108 experts were interviewed and 228 surveyed online. The study is not representative of journalists or society as a whole, but rather a cross section of those who deal with public record laws routinely. They are the active members, and in some cases the leaders, of America’s freedom of information community. Freedom of information is not decided only in Washington, D.C. All levels of government are involved, bringing into view a diversity of government officials. Our objective was to canvass experts to identify barriers to information access and possible solutions, looking broadly at the law, public education, networking and new technology. We found dissatisfaction, uncertainty and worry.

Key points:

1. MANY EXPERTS SAY ACCESS IS WORSE TODAY COMPARED WITH FOUR YEARS AGO: About half of the 228 experts surveyed online reported that access to state and local records has gotten worse during the past four years (41 percent said it stayed the same, and 13 percent said it has gotten better2 ), and 41 percent said access to federal records has worsened. “What I hear from reporters in Washington and my students is that exemptions are being used in way too many cases and delays are still very long,” said Leonard Downie, former Washington Post executive editor and current Weil Family Professor of Journalism at Arizona State University’s Walter Cronkite School of Journalism and Mass Communication. “I hope the door doesn’t get shut tighter.”

2. NEARLY 4 IN 10 SEE A RISE IN DENIALS: Though most respondents (57 percent) said denials have stayed the same during the past four years, 38 percent said they have been denied records at any level of government more frequently, and only 6 percent said denials have decreased. …

3. OVERWHELMINGLY, EXPERTS PREDICTED THAT ACCESS WILL GET WORSE: Nearly 9 out of 10 predicted that access to government will worsen because of the new presidential administration. “I think it’s going to be a backyard brawl,” said Ted Bridis, investigations editor for The Associated Press in Washington, D.C. Over the past several months, nonprofit organizations scrambled to save data purged from federal websites and listed the many restrictions placed on communications with the public.

This report lays out problems with freedom of information and synthesizes solutions aimed at making freedom of information laws work as their creators intended—as an open, honest way for the public to know what its government is doing….(More)”

Did artificial intelligence deny you credit?

Curated on Posted on by Stefaan Verhulst

 in The Conversation: “People who apply for a loan from a bank or credit card company, and are turned down, are owed an explanation of why that happened. It’s a good idea – because it can help teach people how to repair their damaged credit – and it’s a federal law, the Equal Credit Opportunity Act. Getting an answer wasn’t much of a problem in years past, when humans made those decisions. But today, as artificial intelligence systems increasingly assist or replace people making credit decisions, getting those explanations has become much more difficult.

Traditionally, a loan officer who rejected an application could tell a would-be borrower there was a problem with their income level, or employment history, or whatever the issue was. But computerized systems that use complex machine learning models are difficult to explain, even for experts.

Consumer credit decisions are just one way this problem arises. Similar concerns exist in health care, online marketing and even criminal justice. My own interest in this area began when a research group I was part of discovered gender bias in how online ads were targeted, but could not explain why it happened.

All those industries, and many others, who use machine learning to analyze processes and make decisions have a little over a year to get a lot better at explaining how their systems work. In May 2018, the new European Union General Data Protection Regulation takes effect, including a section giving people a right to get an explanation for automated decisions that affect their lives. What shape should these explanations take, and can we actually provide them?

Identifying key reasons

One way to describe why an automated decision came out the way it did is to identify the factors that were most influential in the decision. How much of a credit denial decision was because the applicant didn’t make enough money, or because he had failed to repay loans in the past?

My research group at Carnegie Mellon University, including PhD student Shayak Sen and then-postdoc Yair Zick created a way to measure the relative influence of each factor. We call it the Quantitative Input Influence.

In addition to giving better understanding of an individual decision, the measurement can also shed light on a group of decisions: Did an algorithm deny credit primarily because of financial concerns, such as how much an applicant already owes on other debts? Or was the applicant’s ZIP code more important – suggesting more basic demographics such as race might have come into play?…(More)”

Dark Web

Curated on Posted on by Stefaan Verhulst

Kristin Finklea for the Congressional Research Service: “The layers of the Internet go far beyond the surface content that many can easily access in their daily searches. The other content is that of the Deep Web, content that has not been indexed by traditional search engines such as Google. The furthest corners of the Deep Web, segments known as the Dark Web, contain content that has been intentionally concealed. The Dark Web may be used for legitimate purposes as well as to conceal criminal or otherwise malicious activities. It is the exploitation of the Dark Web for illegal practices that has garnered the interest of officials and policymakers.

Individuals can access the Dark Web by using special software such as Tor (short for The Onion Router). Tor relies upon a network of volunteer computers to route users’ web traffic through a series of other users’ computers such that the traffic cannot be traced to the original user. Some developers have created tools—such as Tor2web—that may allow individuals access to Torhosted content without downloading and installing the Tor software, though accessing the Dark Web through these means does not anonymize activity. Once on the Dark Web, users often navigate it through directories such as the “Hidden Wiki,” which organizes sites by category, similar to Wikipedia. Individuals can also search the Dark Web with search engines, which may be broad, searching across the Deep Web, or more specific, searching for contraband like illicit drugs, guns, or counterfeit money.

While on the Dark Web, individuals may communicate through means such as secure email, web chats, or personal messaging hosted on Tor. Though tools such as Tor aim to anonymize content and activity, researchers and security experts are constantly developing means by which certain hidden services or individuals could be identified or “deanonymized.” Anonymizing services such as Tor have been used for legal and illegal activities ranging from maintaining privacy to selling illegal goods—mainly purchased with Bitcoin or other digital currencies. They may be used to circumvent censorship, access blocked content, or maintain the privacy of sensitive communications or business plans. However, a range of malicious actors, from criminals to terrorists to state-sponsored spies, can also leverage cyberspace and the Dark Web can serve as a forum for conversation, coordination, and action. It is unclear how much of the Dark Web is dedicated to serving a particular illicit market at any one time, and, because of the anonymity of services such as Tor, it is even further unclear how much traffic is actually flowing to any given site.

Just as criminals can rely upon the anonymity of the Dark Web, so too can the law enforcement, military, and intelligence communities. They may, for example, use it to conduct online surveillance and sting operations and to maintain anonymous tip lines. Anonymity in the Dark Web can be used to shield officials from identification and hacking by adversaries. It can also be used to conduct a clandestine or covert computer network operation such as taking down a website or a denial of service attack, or to intercept communications. Reportedly, officials are continuously working on expanding techniques to deanonymize activity on the Dark Web and identify malicious actors online….(More)”

Watchdog to launch inquiry into misuse of data in politics

Curated on Posted on by Stefaan Verhulst

, and Alice Gibbs in The Guardian: “The UK’s privacy watchdog is launching an inquiry into how voters’ personal data is being captured and exploited in political campaigns, cited as a key factor in both the Brexit and Trump victories last year.

The intervention by the Information Commissioner’s Office (ICO) follows revelations in last week’s Observer that a technology company part-owned by a US billionaire played a key role in the campaign to persuade Britons to vote to leave the European Union.

It comes as privacy campaigners, lawyers, politicians and technology experts express fears that electoral laws are not keeping up with the pace of technological change.

“We are conducting a wide assessment of the data-protection risks arising from the use of data analytics, including for political purposes, and will be contacting a range of organisations,” an ICO spokeswoman confirmed. “We intend to publicise our findings later this year.”

The ICO spokeswoman confirmed that it had approached Cambridge Analytica over its apparent use of data following the story in the Observer. “We have concerns about Cambridge Analytica’s reported use of personal data and we are in contact with the organisation,” she said….

In the US, companies are free to use third-party data without seeking consent. But Gavin Millar QC, of Matrix Chambers, said this was not the case in Europe. “The position in law is exactly the same as when people would go canvassing from door to door,” Millar said. “They have to say who they are, and if you don’t want to talk to them you can shut the door in their face.That’s the same principle behind the data protection act. It’s why if telephone canvassers ring you, they have to say that whole long speech. You have to identify yourself explicitly.”…

Dr Simon Moores, visiting lecturer in the applied sciences and computing department at Canterbury Christ Church University and a technology ambassador under the Blair government, said the ICO’s decision to shine a light on the use of big data in politics was timely.

“A rapid convergence in the data mining, algorithmic and granular analytics capabilities of companies like Cambridge Analytica and Facebook is creating powerful, unregulated and opaque ‘intelligence platforms’. In turn, these can have enormous influence to affect what we learn, how we feel, and how we vote. The algorithms they may produce are frequently hidden from scrutiny and we see only the results of any insights they might choose to publish.” …(More)”

Americans have lost faith in institutions. That’s not because of Trump or ‘fake news.’

Curated on Posted on by Stefaan Verhulst

Bill Bishop in the Washington Post: “…Trust in American institutions, however, has been in decline for some time. Trump is merely feeding on that sentiment.

The leaders of once-powerful institutions are desperate to resurrect the faith of the people they serve. They act like they have misplaced a credit card and must find the number so that a replacement can be ordered and then FedEx-ed, if possible overnight.

But that delivery truck is never coming. The decline in trust isn’t because of what the press (or politicians or scientists) did or didn’t do. Americans didn’t lose their trust because of some particular event or scandal. And trust can’t be regained with a new app or even an outbreak of competence. To believe so is to misunderstand what was lost.

In 1964, 3 out of 4 Americans trusted their government to do the right thing most of the time. By 1976, that number had dropped to 33 percent. It was a decline that political scientist Walter Dean Burnham described as “among the largest ever recorded in opinion surveys.”…

Everything about modern life works against community and trust. Globalization and urbanization put people in touch with the different and the novel. Our economy rewards initiative over conformity, so that the weight of convention and tradition doesn’t squelch the latest gizmo from coming to the attention of the next Bill Gates. Whereas parents in the 1920s said it was most important for their children to be obedient, that quality has declined in importance, replaced by a desire for independence and autonomy. Widespread education gives people the tools to make up their own minds. And technology offers everyone the chance to be one’s own reporter, broadcaster and commentator.

We have become, in Polish sociologist Zygmunt Bauman’s description, “artists of our own lives,” ignoring authorities and booting traditions while turning power over to the self. The shift in outlook has been all-encompassing. It has changed the purpose of marriage (once a practical arrangement, now a means of personal fulfillment). It has altered the relationship between citizens and the state (an all-volunteer fighting force replacing the military draft). It has transformed the understanding of art (craftsmanship and assessment are out; free-range creativity and self-promotion are in). It has even inverted the orders of humanity and divinity (instead of obeying a god, now we choose one).

People enjoy their freedoms. There’s no clamoring for a return to gray flannel suits and deferential housewives. Constant social retooling and choice come with costs, however. Without the authority and guidance of institutions to help order their lives, many people feel overwhelmed and adrift. “Depression is truly our modern illness,” writes French sociologist Alain Ehrenberg, with rates 20 to 30 times what they were just two generations ago.

Sustained collective action has also become more difficult. Institutions are turning to behavioral “nudges,” hoping to move an increasingly suspicious public to do what once could be accomplished by command or law. As groups based on tradition and consistent association dwindle, they are being replaced by “event communities,” temporary gatherings that come and go without long-term commitment (think Burning Man). The protests spawned by Trump’s election are more about passion than organization and focus. Today’s demonstrations are sometimes compared to civil-rights-era marches, but they have more in common with L.A.’s Sunset Strip riots of 1966, when more than 1,000 young people gathered to object to a 10 p.m. curfew. “There’s something happening here,” goes the Buffalo Springfield song “For What It’s Worth,” commemorating the riots. “What it is ain’t exactly clear.” In our new politics, expression is a purpose itself….(More)”.

Fighting Illegal Fishing With Big Data

Curated on Posted on by Stefaan Verhulst

Emily Matchar in Smithsonian: “In many ways, the ocean is the Wild West. The distances are vast, the law enforcement agents few and far between, and the legal jurisdiction often unclear. In this environment, illegal activity flourishes. Illegal fishing is so common that experts estimate as much as a third of fish sold in the U.S. was fished illegally. This illegal fishing decimates the ocean’s already dwindling fish populations and gives rise to modern slavery, where fishermen are tricked onto vessels and forced to work, sometimes for years.

A new use of data technology aims to help curb these abuses by shining a light on the high seas. The technology uses ships’ satellite signals to detect instances of transshipment, when two vessels meet at sea to exchange cargo. As transshipment is a major way illegally caught fish makes it into the legal supply chain, tracking it could potentially help stop the practice.

“[Transshipment] really allows people to do something out of sight,” says David Kroodsma, the research program director at Global Fishing Watch, an online data platform launched by Google in partnership with the nonprofits Oceana and SkyTruth. “It’s something that obscures supply chains. It’s basically being able to do things without any oversight. And that’s a problem when you’re using a shared resource like the oceans.”

Global Fishing Watch analyzed some 21 billion satellite signals broadcast by ships, which are required to carry transceivers for collision avoidance, from between 2012 and 2016. It then used an artificial intelligence system it created to identify which ships were refrigerated cargo vessels (known in the industry as “reefers”). They then verified this information with fishery registries and other sources, eventually identifying 794 reefers—90 percent of the world’s total number of such vessels. They tracked instances where a reefer and a fishing vessel were moving at similar speeds in close proximity, labeling these instances as “likely transshipments,” and also traced instances where reefers were traveling in a way that indicated a rendezvous with a fishing vessel, even if no fishing vessel was present—fishing vessels often turn off their satellite systems when they don’t want to be seen. All in all there were more than 90,000 likely or potential transshipments recorded.

Even if these encounters were in fact transshipments, they would not all have been for nefarious purposes. They may have taken place to refuel or load up on supplies. But looking at the patterns of where the potential transshipments happen is revealing. Very few are seen close to the coasts of the U.S., Canada and much of Europe, all places with tight fishery regulations. There are hotspots off the coast of Peru and Argentina, all over Africa, and off the coast of Russia. Some 40 percent of encounters happen in international waters, far enough off the coast that no country has jurisdiction.

The tracked reefers were flying flags from some 40 different countries. But that doesn’t necessarily tell us much about where they really come from. Nearly half of the reefers tracked were flying “flags of convenience,” meaning they’re registered in countries other than where the ship’s owners are from to take advantage of those countries’ lax regulations….(More)”

Read more: http://www.smithsonianmag.com/innovation/fighting-illegal-fishing-big-data-180962321/#7eCwGrGS5v5gWjFz.99
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Human Decisions and Machine Predictions

Curated on Posted on by Stefaan Verhulst

NBER Working Paper by Jon Kleinberg, Himabindu Lakkaraju, Jure Leskovec, Jens Ludwig, and Sendhil Mullainatha: “We examine how machine learning can be used to improve and understand human decision-making. In particular, we focus on a decision that has important policy consequences. Millions of times each year, judges must decide where defendants will await trial—at home or in jail. By law, this decision hinges on the judge’s prediction of what the defendant would do if released. This is a promising machine learning application because it is a concrete prediction task for which there is a large volume of data available. Yet comparing the algorithm to the judge proves complicated. First, the data are themselves generated by prior judge decisions. We only observe crime outcomes for released defendants, not for those judges detained. This makes it hard to evaluate counterfactual decision rules based on algorithmic predictions. Second, judges may have a broader set of preferences than the single variable that the algorithm focuses on; for instance, judges may care about racial inequities or about specific crimes (such as violent crimes) rather than just overall crime risk. We deal with these problems using different econometric strategies, such as quasi-random assignment of cases to judges. Even accounting for these concerns, our results suggest potentially large welfare gains: a policy simulation shows crime can be reduced by up to 24.8% with no change in jailing rates, or jail populations can be reduced by 42.0% with no increase in crime rates. Moreover, we see reductions in all categories of crime, including violent ones. Importantly, such gains can be had while also significantly reducing the percentage of African-Americans and Hispanics in jail. We find similar results in a national dataset as well. In addition, by focusing the algorithm on predicting judges’ decisions, rather than defendant behavior, we gain some insight into decision-making: a key problem appears to be that judges to respond to ‘noise’ as if it were signal. These results suggest that while machine learning can be valuable, realizing this value requires integrating these tools into an economic framework: being clear about the link between predictions and decisions; specifying the scope of payoff functions; and constructing unbiased decision counterfactuals….(More)”