How to be a public entrepreneur

Curated on Posted on by Stefaan Verhulst

Rowan Conway at the RSA: “Political theorist Elinor Ostrom was the first to coin the phrase “public entrepreneur” in her 1965 UCLA PhD thesis where she proposed that government actors should be the makers of purpose-driven businesses. She later went on to surprise the world of economics by winning a Nobel prize.

To the economic establishment Ostrom was a social scientist and her theories of common goods and public purpose enterprise ran counter to the economic orthodoxy. 44 years later, at the same time that she was taking the stage as the first (and only) woman to win a Nobel prize for economics, another California-based thinker was positing his own vision for entrepreneurship… “Move fast and break things” was famously Mark Zuckerberg’s credo for Silicon Valley entrepreneurs. “Unless you are breaking stuff,” he said in 2009, “you are not moving fast enough.” This phrase came to epitomise the “fail fast” start-up culture that has seeped into our consciousness and redefined modern life in the last decade.

Public vs Private entrepreneurs

So which of these two types of entrepreneurship should prevail? I’d say that they’re not playing on the same field and barely even playing the same game. While the Silicon Valley model glorifies the frat boys who dreamt up tech start-ups in their dorm rooms and took the “self-made” financial gains when big tech took off, public entrepreneurs are not cast from this mold. They are the government actors taking on the system to solve social and environmental problems and the idea of “breaking things” won’t appeal to them. “Moving fast”, however, speaks to their ambitions for an agile government that wants to make change in a digital world.

Public entrepreneurs are socially minded — but they differ from social entrepreneurs in that they carry out a public or state role. In a Centre for Public Impact briefing paper entitled “Enter the Public Entrepreneur” the difference is clear:

“While “social entrepreneurs” are people outside government, public entrepreneurs act within government and, at their heart, are a blend of two different roles: that of a public servant, and that of an entrepreneur. The underlying premise is that these roles are usually distinct but the skill sets they require need not be. Indeed, the future public servant will increasingly need to think and act like an entrepreneur — building new relationships, leveraging resources, working across sector lines and acting, and sometimes failing, fast.”

Today we publish a RSA Lab report entitled “Move Fast and Fix Things” in partnership with Innovate UK. The report examines the role of Public Entrepreneurs who want to find ways to move fast without leaving a trail of destruction. It builds on the literature that makes the case for public missionsand entrepreneurship in government and acts as a kind of “how to guide” for those in the public sector who want to think and act like entrepreneurs, but sometimes feel like they are pushing up against an immovable bureaucratic system.

Acting entrepreneurially with procurement

A useful distinction of types of government innovation by the European Commission describes “innovation in government” as transforming public administration, such as the shift to digital service provision and “innovation through government” as initiatives that “foster innovation elsewhere in society, such as the public procurement of innovation”. Our report looks at public procurement — specifically the Small Business Research Initiative (SBRI) — as a route for innovation through government.

Governments have catalytic spending power. The UK public sector alone spends over £251.5 billion annually procuring goods and services which accounts for 33% of public sector spend and 13.7% of GDP. A profound shift in practice is required if government is to proactively use this power to stimulate innovation in the way that Mariana Mazzucato, author of The Entrepreneurial State calls for. As Director of the UCL Institute for Innovation and Public Purpose she advocates for “mission-oriented innovation” which can enable speed as it has “not only a rate, but also a direction” — purposefully using government’s purchasing power to stimulate innovation for good.

But getting procurement professionals to understand how to be entrepreneurial with public funds is no mean feat….(More)”.

Collective Awareness

Curated on Posted on by Stefaan Verhulst

A Conversation with J. Doyne Farmer at the Edge: “Economic failures cause us serious problems. We need to build simulations of the economy at a much more fine-grained level that take advantage of all the data that computer technologies and the Internet provide us with. We need new technologies of economic prediction that take advantage of the tools we have in the 21st century.

Places like the US Federal Reserve Bank make predictions using a system that has been developed over the last eighty years or so. This line of effort goes back to the middle of the 20th century, when people realized that we needed to keep track of the economy. They began to gather data and set up a procedure for having firms fill out surveys, for having the census take data, for collecting a lot of data on economic activity and processing that data. This system is called “national accounting,” and it produces numbers like GDP, unemployment, and so on. The numbers arrive at a very slow timescale. Some of the numbers come out once a quarter, some of the numbers come out once a year. The numbers are typically lagged because it takes a lot of time to process the data, and the numbers are often revised as much as a year or two later. That system has been built to work in tandem with the models that have been built, which also process very aggregated, high-level summaries of what the economy is doing. The data is old fashioned and the models are old fashioned.

It’s a 20th-century technology that’s been refined in the 21st century. It’s very useful, and it represents a high level of achievement, but it is now outdated. The Internet and computers have changed things. With the Internet, we can gather rich, detailed data about what the economy is doing at the level of individuals. We don’t have to rely on surveys; we can just grab the data. Furthermore, with modern computer technology we could simulate what 300 million agents are doing, simulate the economy at the level of the individuals. We can simulate what every company is doing and what every bank is doing in the United States. The model we could build could be much, much better than what we have now. This is an achievable goal.

But we’re not doing that, nothing close to that. We could achieve what I just said with a technological system that’s simpler than Google search. But we’re not doing that. We need to do it. We need to start creating a new technology for economic prediction that runs side-by-side with the old one, that makes its predictions in a very different way. This could give us a lot more guidance about where we’re going and help keep the economic shit from hitting the fan as often as it does….(More)”.

America’s Problem Isn’t Too Little Democracy. It’s Too Much.

Curated on Posted on by Stefaan Verhulst

Joshua A. Geltzer at PoliticoMagazine: “Democracy’s lamentations sometimes seem deafening these days. “Democracy is dying,” proclaimed a recent article in Foreign Policy—and another in the Guardian, and yet another in Quartz. We’ve reached “the end of democracy,” avows a new book—as well as an op-ed in the Washington Post.

But what if these perspectives have it all backwards? What if our problem isn’t too little democracy, but too much?

There’s no doubt that democracy in the United States appears on shaky ground. That’s not because 2016 marked the first time in American history that the presidency was captured by a candidate with no political or military experience. It’s not even because Donald Trump did so despite losing the popular vote by almost 3 million ballots, with his adversary garnering the most votes ever cast for a losing presidential candidate.

It’s because the 2016 election revealed new vulnerabilities in our democracy, generated by social media’s explosion and utilized by Russia and Russian-linked actors—possibly including Trump’s team itself. And it’s also because the aftermath of that election has laid bare a Congress so polarized, gridlocked and downright incapacitated that it has proved unable even to keep our government from shutting down and has consistently failed to fulfill its responsibility to exercise meaningful oversight of the executive branch.

What ails us? The current vogue is to place the blame on the inadequacies of our incarnation of democracy. The brilliant Yascha Mounk, for example, argues that the American people may think they’re living in a democracy, but—unbeknownst to them—it’s really all a charade. On Mounk’s account, Americans speak at town halls, organize on behalf of candidates and cast ballots; but, because the game’s been rigged by the powerful, all of that activity doesn’t really matter compared to the influence of the well-placed and well-heeled. In the words of two political scientists quoted favorably by Mounk, what we think of as democracy in action really amounts to “a minuscule, near-zero, statistically non-significant impact upon public policy.”

Some suggest that democracy’s insufficiencies are global, and the defining problem of our times. In his magisterial account of democracy’s fading allure in Hungary and Poland, Roger Cohen echoes earlier scholars in seeing democracy now eclipsed by “competitive authoritarianism, a form of European single-party rule that retains a veneer of democracy while skewing the contest sufficiently to ensure it is likely to yield only one result.”

But while these commentators are right that the cracks are there, the cause is the very opposite of what they claim, at least when it comes to America. The problem isn’t that democracy is in short supply in the United States. It’s that technology has helped to unleash hyper-democratization—a shift away from the mediated, checked republic that America’s founders carefully crafted toward an impulsive, unleashed direct democracy that’s indulging the worst impulses of our most extreme elements.

To put it bluntly, we’re increasingly ruled by an online mob. And it’s a mob getting besieged with misinformation…(More)”.

Hope for Democracy: 30 years of Participatory Budgeting Worldwide

Curated on Posted on by Stefaan Verhulst

Book edited by Nelson Dias: “Hope for Democracy” is not only the title of this book, but also the translation of a state of mind infected by innovation and transformative action of many people who in different parts of the world, are engaged in the construction of more lasting and intense ways of living democracy.

The articles found within this publication are “scales” of a fascinating journey through the paths of participatory democracy, from North America to Asia, Oceania to Europe, and Latin America to Africa.

With no single directions, it is up to the readers to choose the route they want to travel, being however invited to reinforce this “democratizing wave”, encouraging the emergence of new and renewed spaces of participation in the territories where they live and work….(More)

What if people were paid for their data?

Curated on Posted on by Stefaan Verhulst

The Economist: “Data Slavery” Jennifer Lyn Morone, an American artist, thinks this is the state in which most people now live. To get free online services, she laments, they hand over intimate information to technology firms. “Personal data are much more valuable than you think,” she says. To highlight this sorry state of affairs, Ms Morone has resorted to what she calls “extreme capitalism”: she registered herself as a company in Delaware in an effort to exploit her personal data for financial gain. She created dossiers containing different subsets of data, which she displayed in a London gallery in 2016 and offered for sale, starting at £100 ($135). The entire collection, including her health data and social-security number, can be had for £7,000.

Only a few buyers have taken her up on this offer and she finds “the whole thing really absurd”. ..Given the current state of digital affairs, in which the collection and exploitation of personal data is dominated by big tech firms, Ms Morone’s approach, in which individuals offer their data for sale, seems unlikely to catch on. But what if people really controlled their data—and the tech giants were required to pay for access? What would such a data economy look like?…

Labour, like data, is a resource that is hard to pin down. Workers were not properly compensated for labour for most of human history. Even once people were free to sell their labour, it took decades for wages to reach liveable levels on average. History won’t repeat itself, but chances are that it will rhyme, Mr Weyl predicts in “Radical Markets”, a provocative new book he has co-written with Eric Posner of the University of Chicago. He argues that in the age of artificial intelligence, it makes sense to treat data as a form of labour.

To understand why, it helps to keep in mind that “artificial intelligence” is something of a misnomer. Messrs Weyl and Posner call it “collective intelligence”: most AI algorithms need to be trained using reams of human-generated examples, in a process called machine learning. Unless they know what the right answers (provided by humans) are meant to be, algorithms cannot translate languages, understand speech or recognise objects in images. Data provided by humans can thus be seen as a form of labour which powers AI. As the data economy grows up, such data work will take many forms. Much of it will be passive, as people engage in all kinds of activities—liking social-media posts, listening to music, recommending restaurants—that generate the data needed to power new services. But some people’s data work will be more active, as they make decisions (such as labelling images or steering a car through a busy city) that can be used as the basis for training AI systems….

But much still needs to happen for personal data to be widely considered as labour, and paid for as such. For one thing, the right legal framework will be needed to encourage the emergence of a new data economy. The European Union’s new General Data Protection Regulation, which came into effect in May, already gives people extensive rights to check, download and even delete personal data held by companies. Second, the technology to keep track of data flows needs to become much more capable. Research to calculate the value of particular data to an AI service is in its infancy.

Third, and most important, people will have to develop a “class consciousness” as data workers. Most people say they want their personal information to be protected, but then trade it away for nearly nothing, something known as the “privacy paradox”. Yet things may be changing: more than 90% of Americans think being in control of who can get data on them is important, according to the Pew Research Centre, a think-tank….(More)”.

Tribal World: Group Identity Is All

Curated on Posted on by Stefaan Verhulst

Amy Chua in Foreign Affairs: “Humans, like other primates, are tribal animals. We need to belong to groups, which is why we love clubs and teams. Once people connect with a group, their identities can become powerfully bound to it. They will seek to benefit members of their group even when they gain nothing personally. They will penalize outsiders, seemingly gratuitously. They will sacrifice, and even kill and die, for their group.

This may seem like common sense. And yet the power of tribalism rarely factors into high-level discussions of politics and international affairs, especially in the United States. In seeking to explain global politics, U.S. analysts and policymakers usually focus on the role of ideology and economics and tend to see nation-states as the most important units of organization. In doing so, they underestimate the role that group identification plays in shaping human behavior. They also overlook the fact that, in many places, the identities that matter most—the ones people will lay down their lives for—are not national but ethnic, regional, religious, sectarian, or clan-based. A recurring failure to grasp this truth has contributed to some of the worst debacles of U.S. foreign policy in the past 50 years: most obviously in Afghanistan and Iraq, but also in Vietnam.

This blindness to the power of tribalism affects not only how Americans see the rest of the world but also how they understand their own society….(More)”.

Can Smart Cities Be Equitable?

Curated on Posted on by Stefaan Verhulst

Homi Kharas and Jaana Remes at Project Syndicate: “Around the world, governments are making cities “smarter” by using data and digital technology to build more efficient and livable urban environments. This makes sense: with urban populations growing and infrastructure under strain, smart cities will be better positioned to manage rapid change.

But as digital systems become more pervasive, there is a danger that inequality will deepen unless local governments recognize that tech-driven solutions are as important to the poor as they are to the affluent.

While offline populations can benefit from applications running in the background of daily life – such as intelligent signals that help with traffic flows – they will not have access to the full range of smart-city programs. With smartphones serving as the primary interface in the modern city, closing the digital divide, and extending access to networks and devices, is a critical first step.

City planners can also deploy technology in ways that make cities more inclusive for the poor, the disabled, the elderly, and other vulnerable people. Examples are already abundant.

In New York City, the Mayor’s Public Engagement Unit uses interagency data platforms to coordinate door-to-door outreachto residents in need of assistance. In California’s Santa Clara County, predictive analytics help prioritize shelter space for the homeless. On the London Underground, an app called Wayfindr uses Bluetooth to help visually impaired travelers navigate the Tube’s twisting pathways and escalators.

And in Kolkata, India, a Dublin-based startup called Addressing the Unaddressedhas used GPS to provide postal addresses for more than 120,000 slum dwellers in 14 informal communities. The goal is to give residents a legal means of obtaining biometric identification cards, essential documentation needed to access government services and register to vote.

But while these innovations are certainly significant, they are only a fraction of what is possible.

Public health is one area where small investments in technology can bring big benefits to marginalized groups. In the developing world, preventable illnesses comprise a disproportionate share of the disease burden. When data are used to identify demographic groups with elevated risk profiles, low-cost mobile-messaging campaigns can transmit vital prevention information. So-called “m-health” interventions on issues like vaccinations, safe sex, and pre- and post-natal care have been shown to improve health outcomes and lower health-care costs.

Another area ripe for innovation is the development of technologies that directly aid the elderly….(More)”.

When Technology Gets Ahead of Society

Curated on Posted on by Stefaan Verhulst

Tarun Khanna at Harvard Business Review: “Drones, originally developed for military purposes, weren’t approved for commercial use in the United States until 2013. When that happened, it was immediately clear that they could be hugely useful to a whole host of industries—and almost as quickly, it became clear that regulation would be a problem. The new technology raised multiple safety and security issues, there was no consensus on who should write rules to mitigate those concerns, and the knowledge needed to develop the rules didn’t yet exist in many cases. In addition, the little flying robots made a lot of people nervous.

Such regulatory, logistical, and social barriers to adopting novel products and services are very common. In fact, technology routinely outstrips society’s ability to deal with it. That’s partly because tech entrepreneurs are often insouciant about the legal and social issues their innovations birth. Although electric cars are subsidized by the federal government, Tesla has run afoul of state and local regulations because it bypasses conventional dealers to sell directly to consumers. Facebook is only now facing up to major regulatory concerns about its use of data, despite being massively successful with users and advertisers.

It’s clear that even as innovations bring unprecedented comfort and convenience, they also threaten old ways of regulating industries, running a business, and making a living. This has always been true. Thus early cars weren’t allowed to go faster than horses, and some 19th-century textile workers used sledgehammers to attack the industrial machinery they feared would displace them. New technology can even upend social norms: Consider how dating apps have transformed the way people meet.

Entrepreneurs, of course, don’t really care that the problems they’re running into are part of a historical pattern. They want to know how they can manage—and shorten—the period between the advent of a technology and the emergence of the rules and new behaviors that allow society to embrace its possibilities.

Interestingly, the same institutional murkiness that pervades nascent industries such as drones and driverless cars is something I’ve also seen in developing countries. And strange though this may sound, I believe that tech entrepreneurs can learn a lot from businesspeople who have succeeded in the world’s emerging markets.

Entrepreneurs in Brazil or Nigeria know that it’s pointless to wait for the government to provide the institutional and market infrastructure their businesses need, because that will simply take too long. They themselves must build support structures to compensate for what Krishna Palepu and I have referred to in earlier writings as “institutional voids.” They must create the conditions that will allow them to create successful products or services.

Tech-forward entrepreneurs in developed economies may want to believe that it’s not their job to guide policy makers and the public—but the truth is that nobody else can play that role. They may favor hardball tactics, getting ahead by evading rules, co-opting regulators, or threatening to move overseas. But in the long term, they’d be wiser to use soft power, working with a range of partners to co-create the social and institutional fabric that will support their growth—as entrepreneurs in emerging markets have done.…(More)”.

Wikipedia vandalism could thwart hoax-busting on Google, YouTube and Facebook

Curated on Posted on by Stefaan Verhulst

Daniel Funke at Poynter: “For a brief moment, the California Republican Party supported Nazism. At least, that’s what Google said.

That’s because someone vandalized the Wikipedia page for the party on May 31 to list “Nazism” alongside ideologies like “Conservatism,” “Market liberalism” and “Fiscal conservatism.” The mistake was removed from search results, with Google clarifying to Vice News that the search engine had failed to catch the vandalism in the Wikipedia entry….

Google has long drawn upon the online encyclopedia for appending basic information to search results. According to the edit log for the California GOP page, someone added “Nazism” to the party’s ideology section around 7:40 UTC on May 31. The edit was removed within a minute, but it appears Google’s algorithm scraped the page just in time for the fake.

“Sometimes people vandalize public information sources, like Wikipedia, which can impact the information that appears in search,” a Google spokesperson told Poynter in an email. “We have systems in place that catch vandalism before it impacts search results, but occasionally errors get through, and that’s what happened here.”…

According to Google, more than 99.9 percent of Wikipedia edits that show up in Knowledge Panels, which display basic information about searchable keywords at the top of results, aren’t vandalism. The user who authored the original edit to the California GOP’s page did not use a user profile, making them hard to track down.

That’s a common tactic among people who vandalize Wikipedia pages, a practice the nonprofit has documented extensively. But given the volume of edits that are made on Wikipedia — about 10 per second, with 600 new pages per day — and the fact that Facebook and YouTube are now pulling from them to provide more context to posts, the potential for and effect of abuse is high….(More)”.

Ontario is trying a wild experiment: Opening access to its residents’ health data

Curated on Posted on by Stefaan Verhulst

Dave Gershorn at Quartz: “The world’s most powerful technology companies have a vision for the future of healthcare. You’ll still go to your doctor’s office, sit in a waiting room, and explain your problem to someone in a white coat. But instead of relying solely on their own experience and knowledge, your doctor will consult an algorithm that’s been trained on the symptoms, diagnoses, and outcomes of millions of other patients. Instead of a radiologist reading your x-ray, a computer will be able to detect minute differences and instantly identify a tumor or lesion. Or at least that’s the goal.

AI systems like these, currently under development by companies including Google and IBM, can’t read textbooks and journals, attend lectures, and do rounds—they need millions of real life examples to understand all the different variations between one patient and another. In general, AI is only as good as the data it’s trained on, but medical data is exceedingly private—most developed countries have strict health data protection laws, such as HIPAA in the United States….

These approaches, which favor companies with considerable resources, are pretty much the only way to get large troves of health data in the US because the American health system is so disparate. Healthcare providers keep personal files on each of their patients, and can only transmit them to other accredited healthcare workers at the patient’s request. There’s no single place where all health data exists. It’s more secure, but less efficient for analysis and research.

Ontario, Canada, might have a solution, thanks to its single-payer healthcare system. All of Ontario’s health data exists in a few enormous caches under government control. (After all, the government needs to keep track of all the bills its paying.) Similar structures exist elsewhere in Canada, such as Quebec, but Toronto, which has become a major hub for AI research, wants to lead the charge in providing this data to businesses.

Until now, the only people allowed to study this data were government organizations or researchers who partnered with the government to study disease. But Ontario has now entrusted the MaRS Discovery District—a cross between a tech incubator and WeWork—to build a platform for approved companies and researchers to access this data, dubbed Project Spark. The project, initiated by MaRS and Canada’s University Health Network, began exploring how to share this data after both organizations expressed interest to the government about giving broader health data access to researchers and companies looking to build healthcare-related tools.

Project Spark’s goal is to create an API, or a way for developers to request information from the government’s data cache. This could be used to create an app for doctors to access the full medical history of a new patient. Ontarians could access their health records at any time through similar software, and catalog health issues as they occur. Or researchers, like the ones trying to build AI to assist doctors, could request a different level of access that provides anonymized data on Ontarians who meet certain criteria. If you wanted to study every Ontarian who had Alzheimer’s disease over the last 40 years, that data would only be authorization and a few lines of code away.

There are currently 100 companies lined up to get access to data, comprised of health records from Ontario’s 14 million residents. (MaRS won’t say who the companies are). …(More)”