Motivating Bureaucrats through Social Recognition


Evidence from Simultaneous Field Experiments by Varun Gauri,Julian C. Jamison, Nina Mazar, Owen Ozier, Shomikho Raha and Karima Saleh: “Bureaucratic performance is a crucial determinant of economic growth. Little is known about how to improve it in resource-constrained settings.

This study describes a field trial of a social recognition intervention to improve record keeping in clinics in two Nigerian states, replicating the intervention—implemented by a single organization—on bureaucrats performing identical tasks in both states.

Social recognition improved performance in one state but had no effect in the other, highlighting both the potential and the limitations of behavioral interventions. Differences in observables did not explain cross-state differences in impacts, however, illustrating the limitations of observable-based approaches to external validity….(More)”.

Think Strategically About Prize Hosting


Charlie Brown & Robert Q. Benedict at Stanford Social Innovation Review: ” For many in the social sector, hosting a prize has become practically compulsory. But prizes have also proved divisive, sparking debates about their intended use, the value they provide, and the costs they incur. With so many conflicting perspectives, are there any guidelines to help decide whether a prize is worth pursuing?

We have spent more than a decade working with foundations, corporations, government agencies, and NGOs to design and host prizes; we’ve also observed dozens more competitions hosted by others and made our fair share of missteps along the way. The motivations behind prizes vary but generally cluster into one of two groups: awareness, an aim to raise the profile of an organization or issue area to generate momentum; and disruption, which incentivizes innovation, surfaces new solutions, or fundamentally changes an entrenched system.

Some organizations already have a solution in mind and use a prize to find the best partners for implementing it—more like an open request for proposals (open RFP) than an innovation search. We would categorize this sort of effort under the awareness rubric. Another large share of prizes, also overtly about awareness, are essentially marketing efforts, and lay the groundwork for future brand positioning and programmatic grants and activities. By contrast, disruption prizes seek the attention of highly focused experts to address a long-standing, difficult problem by drawing innovative solutions from the fringes of the field.

These motivations are legitimate and meaningful. But nearly all prizes use the language of innovation and disruption in their communications, to spark excitement and lend weight to the challenge being posed. This tendency can create potential problems by treating disparate goals—awareness versus disruption or even innovation—as equivalent and can lead organizations to use a counterproductive strategy for their needs. An awareness campaign that is marketed as an innovation prize, for example, risks alienating participants, who often invest enormous effort with the expectation of seeing their ideas, or those of a worthy competitor, implemented in a significant way.

Matching a host’s goal with the right kind of prize strategy is perhaps the most important, most ignored task that prize hosts face. A mismatch of intention and strategy can result in not only lackluster results but, more important, damaged trust with entrants and weakened credibility for the host….(More)”.

The Monarchy of Fear: A Philosopher Looks at Our Political Crisis


Book by Martha C. Nussbaum: “…In The Monarchy of Fear she turns her attention to the current political crisis that has polarized American since the 2016 election.

Although today’s atmosphere is marked by partisanship, divisive rhetoric, and the inability of two halves of the country to communicate with one another, Nussbaum focuses on what so many pollsters and pundits have overlooked. She sees a simple truth at the heart of the problem: the political is always emotional. Globalization has produced feelings of powerlessness in millions of people in the West. That sense of powerlessness bubbles into resentment and blame. Blame of immigrants. Blame of Muslims. Blame of other races. Blame of cultural elites. While this politics of blame is exemplified by the election of Donald Trump and the vote for Brexit, Nussbaum argues it can be found on all sides of the political spectrum, left or right.

Drawing on a mix of historical and contemporary examples, from classical Athens to the musical HamiltonThe Monarchy of Fearuntangles this web of feelings and provides a roadmap of where to go next….(More)”.

Google.gov


Adam J. White at New Atlantis: “Google exists to answer our small questions. But how will we answer larger questions about Google itself? Is it a monopoly? Does it exert too much power over our lives? Should the government regulate it as a public utility — or even break it up?

In recent months, public concerns about Google have become more pronounced. This February, the New York Times Magazine published “The Case Against Google,” a blistering account of how “the search giant is squelching competition before it begins.” The Wall Street Journal published a similar article in January on the “antitrust case” against Google, along with Facebook and Amazon, whose market shares it compared to Standard Oil and AT&T at their peaks. Here and elsewhere, a wide array of reporters and commentators have reflected on Google’s immense power — not only over its competitors, but over each of us and the information we access — and suggested that the traditional antitrust remedies of regulation or breakup may be necessary to rein Google in.

Dreams of war between Google and government, however, obscure a much different relationship that may emerge between them — particularly between Google and progressive government. For eight years, Google and the Obama administration forged a uniquely close relationship. Their special bond is best ascribed not to the revolving door, although hundreds of meetings were held between the two; nor to crony capitalism, although hundreds of people have switched jobs from Google to the Obama administration or vice versa; nor to lobbying prowess, although Google is one of the top corporate lobbyists.

Rather, the ultimate source of the special bond between Google and the Obama White House — and modern progressive government more broadly — has been their common ethos. Both view society’s challenges today as social-engineering problems, whose resolutions depend mainly on facts and objective reasoning. Both view information as being at once ruthlessly value-free and yet, when properly grasped, a powerful force for ideological and social reform. And so both aspire to reshape Americans’ informational context, ensuring that we make choices based only upon what they consider the right kinds of facts — while denying that there would be any values or politics embedded in the effort.

Addressing an M.I.T. sports-analytics conference in February, former President Obama said that Google, Facebook, and prominent Internet services are “not just an invisible platform, but they are shaping our culture in powerful ways.” Focusing specifically on recent outcries over “fake news,” he warned that if Google and other platforms enable every American to personalize his or her own news sources, it is “very difficult to figure out how democracy works over the long term.” But instead of treating these tech companies as public threats to be regulated or broken up, Obama offered a much more conciliatory resolution, calling for them to be treated as public goods:

I do think that the large platforms — Google and Facebook being the most obvious, but Twitter and others as well that are part of that ecosystem — have to have a conversation about their business model that recognizes they are a public good as well as a commercial enterprise.

This approach, if Google were to accept it, could be immensely consequential….(More)”.

On the Rise of FinTechs – Credit Scoring using Digital Footprints


NBER Working Paper by Tobias Berg, Valentin Burg, Ana Gombović and Manju Puri: “We analyze the information content of the digital footprint – information that people leave online simply by accessing or registering on a website – for predicting consumer default. Using more than 250,000 observations, we show that even simple, easily accessible variables from the digital footprint equal or exceed the information content of credit bureau (FICO) scores. Furthermore, the discriminatory power for unscorable customers is very similar to that of scorable customers. Our results have potentially wide implications for financial intermediaries’ business models, for access to credit for the unbanked, and for the behavior of consumers, firms, and regulators in the digital sphere….(More)”.

Ways to think about machine learning


Benedict Evans: “We’re now four or five years into the current explosion of machine learning, and pretty much everyone has heard of it. It’s not just that startups are forming every day or that the big tech platform companies are rebuilding themselves around it – everyone outside tech has read the Economist or BusinessWeek cover story, and many big companies have some projects underway. We know this is a Next Big Thing.

Going a step further, we mostly understand what neural networks might be, in theory, and we get that this might be about patterns and data. Machine learning lets us find patterns or structures in data that are implicit and probabilistic (hence ‘inferred’) rather than explicit, that previously only people and not computers could find. They address a class of questions that were previously ‘hard for computers and easy for people’, or, perhaps more usefully, ‘hard for people to describe to computers’. And we’ve seen some cool (or worrying, depending on your perspective) speech and vision demos.

I don’t think, though, that we yet have a settled sense of quite what machine learning means – what it will mean for tech companies or for companies in the broader economy, how to think structurally about what new things it could enable, or what machine learning means for all the rest of us, and what important problems it might actually be able to solve.

This isn’t helped by the term ‘artificial intelligence’, which tends to end any conversation as soon as it’s begun. As soon as we say ‘AI’, it’s as though the black monolith from the beginning of 2001 has appeared, and we all become apes screaming at it and shaking our fists. You can’t analyze ‘AI’.

Indeed, I think one could propose a whole list of unhelpful ways of talking about current developments in machine learning. For example:

  • Data is the new oil
  • Google and China (or Facebook, or Amazon, or BAT) have all the data
  • AI will take all the jobs
  • And, of course, saying AI itself.

More useful things to talk about, perhaps, might be:

  • Automation
  • Enabling technology layers
  • Relational databases. …(More).

Blockchain’s governance paradox


Izabella Kaminska at the Financial Times: “Distributed ledger technologies “are starting to look an awful lot like some of the more conventional technical solutions that we have,” says Prof. Vili Lehdonvirta, an associate professor and senior research fellow at the Oxford Internet Institute, at a recent talk he gave at the Alan Turing Institute.

At the heart of the issue (as always) is who dictates and enforces the rules of the system if and when things go wrong, according to Lehdonvirta. He echoes a point we’ve long made, namely, that what really matters in these systems is how they deal with exceptions rather than norms.

The industry’s continuous shifting of nomenclature hints at the inherent challenges and revisionism at hand. As blockchains become DLTs, shared databases and permissioned consensus networks, what the techies working on these systems fail to publicly highlight is that much of the time, “advance” means returning to tried and tested paradigms, or reintroducing trusted or governance-focused nodes.

Albeit, the “back to square one” solution isn’t unique to blockchain. We see the same pattern playing out across the network/platform industry. For example, Airbnb was built on the notion that peers could organise accommodation for each other bilaterally without any dependence on a centralised manager. As time went on, however, trust issues across the platform — everything from fraud, misrepresentation, bad consumer experience, abuse, vandalism or damage — forced the once proudly employee-light company to load up on staff who could troubleshoot many of these problems. In so doing, Airbnb — much like Ebay before it — transformed itself from a tech company into an adjudicator, value custodian and rules-and-standards authority.

And by and large, that’s not been an unwelcome transformation, from the consumer’s perspective. Indeed, what libertarian tech anarchists often fail to understand is that the public is not opposed to the idea of putting their trust in institutions, especially when they’re operated by real people who can be held accountable for things going wrong.

What they seemingly understand and technologists don’t is this: Trusting other parties to protect, enforce and adjudicate the rules of operation enhances division of labour and thus efficiency. I no longer have to waste hours of time trying to figure out if the counterparty I’ve dealt with on Ebay is trustworthy or not. Ebay governs the platform in such a way that I can be confident failed trades will always be compensated, and that Ebay’s own judgement about compensation entitlement will always be fair. After all, its continuing reputation as an efficient exchange platform depends on it.

But back to blockchian.

As Lehdonvirta observes, the vision of blockchain is of a system which can enforce contracts, prevent double spending, and cap the money supply pool without ceding power to anyone:

No rent-seeking, no abuses of power, no politics — blockchain technologies can be used to create “math-based money” and “unstoppable” contracts that are enforced with the impartiality of a machine instead of the imperfect and capricious human bureaucracy of a state or a bank. This is why so many people are so excited about blockchain: its supposed ability change economic organization in a way that transforms dominant relationships of power.

The problem which blockchain claims to have solved, in other words, is a rule-enforcement one, not a technological one….(More)”.

A platform that puts political lobbying back into the hands of everyday people


Michael Krumholtz at StartUpBeat: “Amit Thakkar saw first hand how messy and inefficient politics can be from the inside. While working as a political consultant for a decade, Thakkar said he became frustrated with seeing the same old players decide policy with almost no influence from actual constituents or voters.

That’s a large part of why he decided to create LawMaker.io, which bills itself as a revolutionary platform that gives those in the U.S. the chance to create propositions for new laws through crowdsourcing. That allows for support to build for popular ideas that are eventually handed over to legislators to propose them as real laws. Touting itself as a “free lobby for the lobbyless,” Thakkar said its a platform that could very much change the face of U.S. democracy.

“It didn’t make sense to me that such a small group of wealthy and well-connected people had such an outsized influence on the laws that are written and the way our government works,” he told Techli. “I knew there needed to be a free way that all Americans could propose common-sense ideas for laws and influence elected officials in a way that benefitted all Americans instead of just a powerful few.”

Lawmaker.io works by finding ideas at the ground level that can shape politics and then making sure it gets a wider audience after a user proposes a policy idea. It’s then shared widely by the user and suggestions are made for possible amendments to the initial proposal. Support is then gathered until the idea has at least 100 registered supporters and it is eventually sent off to the appropriate legislators.

LawMaker.io recently held its 2nd Lawmaker Challenge to offer up a winning policy proposal to legislators. As the Supreme Court’s Citizen United has become so influential in allowing big money to essentially buy politics, the winning proposal looked to reverse the impacts of the decision and shift back influence to voters over the power of wealthy interests….(More)”.

Microsoft Research Open Data


Microsoft Research Open Data: “… is a data repository that makes available datasets that researchers at Microsoft have created and published in conjunction with their research. You can browse available datasets and either download them or directly copy them to an Azure-based Virtual Machine or Data Science Virtual Machine. To the extent possible, we follow FAIR (findable, accessible, interoperable and reusable) data principles and will continue to push towards the highest standards for data sharing. We recognize that there are dozens of data repositories already in use by researchers and expect that the capabilities of this repository will augment existing efforts. Datasets are categorized by their primary research area. You can find links to research projects or publications with the dataset.

What is our goal?

Our goal is to provide a simple platform to Microsoft’s researchers and collaborators to share datasets and related research technologies and tools. The site has been designed to simplify access to these data sets, facilitate collaboration between researchers using cloud-based resources, and enable the reproducibility of research. We will continue to evolve and grow this repository and add features to it based on feedback from the community.

How did this project come to be?

Over the past few years, our team, based at Microsoft Research, has worked extensively with the research community to create cloud-based research infrastructure. We started this project as a prototype about a year ago and are excited to finally share it with the research community to support data-intensive research in the cloud. Because almost all research projects have a data component, there is real need for curated and meaningful datasets in the research community, not only in computer science but in interdisciplinary and domain sciences. We have now made several such datasets available for download or use directly on cloud infrastructure….(More)”.

The Value of Government Risk Taking


Video by While many in the private sector consider themselves “wealth creators,” governments have come to believe that their economic role is more passive. But this is short-sighted; when mission-driven public-sector actors collaborate to tackle problems, they co-create new markets that affect both the rate of growth and its direction….(More)”.