The Magic of “Multisolving”


Elizabeth Sawin at Stanford Social Innovation Review: “In Japan, manufacturing facilities use “green curtains”—living panels of climbing plants—to clean the air, provide vegetables for company cafeterias, and reduce energy use for cooling. A walk-to-school program in the United Kingdom fights a decline in childhood physical activity while reducing traffic congestion and greenhouse gas emissions from transportation. A food-gleaning program staffed by young volunteers and families facing food insecurity in Spain addresses food waste, hunger, and a desire for sustainability.

Each of these is a real-life example of what I call “multisolving”—where people pool expertise, funding, and political will to solve multiple problems with a single investment of time and money. It’s an approach with great relevance in this era of complex, interlinked, social and environmental challenges. But what’s the best formula for implementing projects that tackle many problems at once?

Climate Interactive, which uses systems analysis to help people address climate change, recently completed a year-long study of multisolving for climate and health. We learned there is no one-size-fits-all recipe, but we did identify three operating principles and three practices that showed up again and again in the projects we studied. What’s more, anyone wanting to access the power of cross-sectoral partnership can adopt them….(More)”.

Introducing CitizENGAGE – How Citizens Get Things Done


Open Gov Partnership: “In a world full of autocracy, bureaucracy, and opacity, it can be easy to feel like you’re fighting an uphill battle against these trends.

Trust in government is at historic lows. Autocratic leaders have taken the reins in countries once thought bastions of democracy. Voter engagement has been declining around the globe for years.

Despite this reality, there is another, powerful truth: citizens are using open government to engage in their communities in innovative, exciting ways, bringing government closer and creating a more inclusive system.

These citizens are everywhere.

In Costa Rica, they are lobbying the government for better and fairer housing for indigenous communities.

In Liberia, they are bringing rights to land back to the communities who are threatened by companies on their traditional lands.

In Madrid, they are using technology to make sure you can participate in government – not just every four years, but every day.

In Mongolia, they are changing the face of education and healthcare services by empowering citizens to share their needs with government.

In Paraguay, hundreds of municipal councils are hearing directly from citizens and using their input to shape how needed public services are delivered.

These powerful examples are the inspiration for the Open Government Partnership’s (OGP) new global campaign to CItizENGAGE.  The campaign will share the stories of citizens engaging in government and changing lives for the better.

CitizENGAGE includes videos, photo essays, and impact stories about citizens changing the way government is involved in their lives. These stories talk about the very real impact open government can have on the lives of everyday citizens, and how it can change things as fundamental as schools, roads, and houses.

We invite you to visit CitizENGAGE and find out more about these reforms, and get inspired. Whether or not your government participates in OGP, you can take the lessons from these powerful stories of transformation and use them to make an impact in your own community….(More)”.

What Democracy Needs Now


The RSA Chief Executive’s Lecture 2018 by Matthew Taylor: “In 1989 with the fall of the Berlin Wall still echoing, Francis Fukuyama prophesied the global triumph of liberal democracy and the end of history. Thirty years on it is not history in jeopardy but liberal democracy itself.

China – the rising global power – is thriving with a system which combines economic freedom with political autocracy. There is the growth of what Yascha Mounk calls illiberal democracies – countries with notionally free elections but without the liberal foundations of accountability, civil liberties and cultural openness. The issue with nations like Russia, Hungary and Turkey, and with those exhibiting a backlash against liberalism like America and Italy, is not just how they operate but the tendency for populism – when given the excuse or opportunity – to drift towards authoritarianism.

While the alternatives to the liberal democratic system grow more confident the citizens living in those systems become more restless. Politicians and political institutions in countries are viewed with dismay and contempt. We don’t like them, we don’t trust them, we don’t think they can solve the problems that most matter to us. The evidence, particularly from the US, is starting to suggest that disillusionment with politics is now becoming indifference towards democracy itself.

Will liberal democracy come back into fashion – is this a cycle or is it a trend? Behind the global patterns each country is different, but think of what is driving anger and disillusionment in our own.

Living standards flat-lining for longer than at any time since the industrial revolution. A decade of austerity leaving our public services threadbare and in a mode of continual crisis management. From social care to gangs, from cybercrime to mental health, how many of us think Government is facing up to the problems let alone developing solutions?

Inequality, having risen precipitously in the 1980s, remains stubbornly high, fuelling anger about elites and making not just the economic divide but all divisions worse.

Social media – where increasingly people get their information and engage in political discourse – has the seemingly in-built tendency to confirm prejudice and polarise opinion.

The great intertwined forces shaping the future – globalisation, unprecedented corporate power, technological change – continue to reinforce a sense in people, places and nations that they have no agency. Yet the hunger to take back control which started as tragedy is rapidly becoming a farce.

If this is the warm climate in which disillusionment has taken root and grown it shows few signs of cooling.

For all its many failings, I have always believed that over the long term liberal democracy would carry on making lives better for most people most of the time. As a progressive my guiding star is what Roberto Unger has called ‘the larger life for all’. But for the first time, I view the future with more fear than hope.

There are those who disparage pessimism. To them the backlash against liberalism, the signs of a declining faith in democracy, are passing responses to failure and misfortune. Populism will give the system the wake-up call it needs. In time a new generation of leaders will renew the system. Populism need neither be extreme nor beget authoritarianism – look at Macron.

This underestimates the dangers that face us. It is too reminiscent of those who believed, until the results came in, that the British people would not take the risk of Brexit or that the Americans would reject the madness of Trump. It underestimates too how the turn against liberal democracy in one country can beget it in another. Paradoxically, today nationalists seem more able to collaborate with each other than countries ostensibly committed to internationalism. Chaos spreads more quickly than order. Global treaties and institutions take years to agree, they can breakdown overnight.

Of course, liberal democracy has failed over and again to live up to its own promise. But the fact that things need to change doesn’t mean they can’t get a whole lot worse.

We are also in danger of underestimating the coherence and confidence of liberalism’s critics. Last month Hungarian Prime Minister Victor Orban made a powerful speech defending his brand of nationalist populism and boasting of his growing alliances across Europe. He appealed to the continent’s centre-right to recognise that it has more in common with conservative nationalism than the EU’s liberal establishment. There are aspects of Orban’s analysis which have an understandable appeal to the mainstream, but remember this is also a man who is unashamedly hostile to Islam, contemptuous of humanitarianism, and who is playing fast and loose with democratic safeguards in his own country.

We may disagree about how malign or dangerous are figures like Orban or Erdogan, or Trump or Salvini, but surely we can agree that those who want to defend the open, pluralistic, inclusive values of liberal democracy must try to make a better case for what we believe?

In part this involves defending the record of liberal societies in improving lives, creating opportunities and keeping the peace, at least between themselves. But it also means facing up to what is going wrong and what must change.

Complex problems are rarely addressed with a single solution. To ever again achieve the remarkable and unprecedented economic and social advances of the three decades after the Second World War, liberal democracy needs profound renewal. But change must start some place. This evening I want to argue that place should be the way we do democracy itself…(More) (Video)”.

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).

My City Forecast: Urban planning communication tool for citizen with national open data


Paper by Y. Hasegawa, Y. Sekimoto, T. Seto, Y. Fukushima et al in Computers, Environment and Urban Systems: “In urban management, the importance of citizen participation is being emphasized more than ever before. This is especially true in countries where depopulation has become a major concern for urban managers and many local authorities are working on revising city master plans, often incorporating the concept of the “compact city.” In Japan, for example, the implementation of compact city plans means that each local government decides on how to designate residential areas and promotes citizens moving to these areas in order to improve budget effectiveness and the vitality of the city. However, implementing a compact city is possible in various ways. Given that there can be some designated withdrawal areas for budget savings, compact city policies can include disadvantages for citizens. At this turning point for urban structures, citizen–government mutual understanding and cooperation is necessary for every step of urban management, including planning.

Concurrently, along with the recent rapid growth of big data utilization and computer technologies, a new conception of cooperation between citizens and government has emerged. With emerging technologies based on civic knowledge, citizens have started to obtain the power to engage directly in urban management by obtaining information, thinking about their city’s problems, and taking action to help shape the future of their city themselves (Knight Foundation, 2013). This development is also supported by the open government data movement, which promotes the availability of government information online (Kingston, Carver, Evans, & Turton, 2000). CityDashboard is one well-known example of real-time visualization and distribution of urban information. CityDashboard, a web tool launched in 2012 by University College London, aggregates spatial data for cities around the UK and displays the data on a dashboard and a map. These new technologies are expected to enable both citizens and government to see their urban situation in an interface presenting an overhead view based on statistical information.

However, usage of statistics and governmental data is as yet limited in the actual process of urban planning…

To help improve this situation and increase citizen participation in urban management, we have developed a web-based urban planning communication tool using open government data for enhanced citizen–government cooperation. The main aim of the present research is to evaluate the effect of our system on users’ awareness of and attitude toward the urban situation. We have designed and developed an urban simulation system, My City Forecast (http://mycityforecast.net,) that enables citizens to understand how their environment and region are likely to change by urban management in the future (up to 2040)….(More)”.

Ghost Cities: Built but Never Inhabited


Civic Data Design Lab at UrbanNext: “Ghost Cities are vacant neighborhoods and sometimes whole cities that were built but were never inhabited. Their existence is a physical manifestation of Chinese overdevelopment in real estate and the dependence on housing as an investment strategy. Little data exists which establishes the location and extent of these Ghost Cities in China. MIT’s Civic Data Design Lab developed a model using data scraped from Chinese social media sites and Baidu (Chinese Google Maps) to create one of the first maps identifying the locations of Chinese Ghost Cities….

Quantifying the extent and location of Ghost Cities is complicated by the fact that the Chinese government keeps a tight hold on data about sales and occupancy of buildings. Even local planners may have a hard time acquiring it. The Civic Data Design Lab developed a model to identify Ghost Cities based on the idea that amenities (grocery stores, hair salons, restaurants, schools, retail, etc.) are the mark of a healthy community and the lack of amenities might indicate locations where no one lives. Given the lack of openly available data in China, data was scraped from Chinese social media and websites, including Dianping (Chinese Yelp), Amap (Chinese Map Quest), Fang (Chinese Zillow), and Baidu (Chinese Google Maps) using openly accessible Application Programming Interfaces(APIs). 

Using data scraped from social media sites in Chengdu and Shenyang, the model was tested using 300 m x 300 m grid cells marking residential locations. Each grid cell was given an amenity accessibility score based on the distance and clustering of amenities nearby. Residential areas that had a cluster of low scores were marked as Ghost Cities. The results were ground-truthed through site visits documenting the location using aerial photography from drones and interviews with local stakeholders.

The model worked well at documenting under-utilized residential locations in these Chinese cities, picking up everything from vacant housing and stalled construction to abandoned older residential locations, creating the first data set that marks risk in the Chinese real estate market. The research shows that data available through social media can help locate and estimate risk in the Chinese real estate market. Perhaps more importantly, however, identifying where these areas are concentrated can help city planners, developers and local citizens make better investment decisions and address the risk created by these under-utilized developments….(More)”.

The promise and peril of military applications of artificial intelligence


Michael C. Horowitz at the Bulletin of the Atomic Scientists: “Artificial intelligence (AI) is having a moment in the national security space. While the public may still equate the notion of artificial intelligence in the military context with the humanoid robots of the Terminatorfranchise, there has been a significant growth in discussions about the national security consequences of artificial intelligence. These discussions span academia, business, and governments, from Oxford philosopher Nick Bostrom’s concern about the existential risk to humanity posed by artificial intelligence to Tesla founder Elon Musk’s concern that artificial intelligence could trigger World War III to Vladimir Putin’s statement that leadership in AI will be essential to global power in the 21st century.

What does this really mean, especially when you move beyond the rhetoric of revolutionary change and think about the real world consequences of potential applications of artificial intelligence to militaries? Artificial intelligence is not a weapon. Instead, artificial intelligence, from a military perspective, is an enabler, much like electricity and the combustion engine. Thus, the effect of artificial intelligence on military power and international conflict will depend on particular applications of AI for militaries and policymakers. What follows are key issues for thinking about the military consequences of artificial intelligence, including principles for evaluating what artificial intelligence “is” and how it compares to technological changes in the past, what militaries might use artificial intelligence for, potential limitations to the use of artificial intelligence, and then the impact of AI military applications for international politics.

The potential promise of AI—including its ability to improve the speed and accuracy of everything from logistics to battlefield planning and to help improve human decision-making—is driving militaries around the world to accelerate their research into and development of AI applications. For the US military, AI offers a new avenue to sustain its military superiority while potentially reducing costs and risk to US soldiers. For others, especially Russia and China, AI offers something potentially even more valuable—the ability to disrupt US military superiority. National competition in AI leadership is as much or more an issue of economic competition and leadership than anything else, but the potential military impact is also clear. There is significant uncertainty about the pace and trajectory of artificial intelligence research, which means it is always possible that the promise of AI will turn into more hype than reality. Moreover, safety and reliability concerns could limit the ways that militaries choose to employ AI…(More)”,

How Do You Control 1.4 Billion People?


Robert Foyle Hunwick at The New Republic: China’s “social credit system”, which becomes mandatory in 2020, aims to funnel all behavior into a credit score….The quoted text is from a 2014 State Council resolution which promises that every involuntary participant will be rated according to their “commercial sincerity,” “social security,” “trust breaking” and “judicial credibility.”

Some residents welcome it. Decades of political upheaval and endemic corruption has bred widespread mistrust; most still rely on close familial networks (guanxi) to get ahead, rather than public institutions. An endemic lack of trust is corroding society; frequent incidents of “bystander effect”—people refusing to help injured strangers for fear of being held responsible—have become a national embarrassment. Even the most enthusiastic middle-class supporters of the ruling Communist Party (CCP) feel perpetually insecure. “Fraud has become ever more common,” Lian Weiliang, vice chairman of the CCP’s National Development and Reform Commission, recently admitted. “Swindlers must pay a price.”

The solution, apparently, lies in a data-driven system that automatically separates the good, the bad, and the ugly…

once compulsory state “social credit” goes national in 2020, these shadowy algorithms will become even more opaque. Social credit will align with Communist Party policy to become another form of law enforcement. Since Beijing relaxed its One Child Policy to cope with an aging population (400 million seniors by 2035), the government has increasingly indulged in a form of nationalist natalism to encourage more two-child families. Will women be penalized for staying single, and rewarded for swapping their careers for childbirth? In April, one of the country’s largest social-media companies banned homosexual content from its Weibo platform in order to “create a bright and harmonious community environment” (the decision was later rescinded in favor of cracking down on all sexual content). Will people once again be forced to hide non-normative sexual orientations in order to maintain their rights? An investigation by the University of Toronto’s Citizen Lab also warns that social credit policies would be used to discourage protest.

State media has defended social credit against Orwellian charges, arguing that China’s maturing economy requires a “well-functioning” apparatus like the U.S.’s FICO credit score system. But, counters Lubman, “the U.S. systems, maintained by three companies, collect only financially related information.” In the UK, citizens are entitled to an Equifax report itemizing their credit status. In China, only the security services have access to an individual’s dang’an, the personal file containing every scrap of information the state keeps on them, from exam results to their religious and political views….(More)”.

China asserts firm grip on research data


ScienceMag: “In a move few scientists anticipated, the Chinese government has decreed that all scientific data generated in China must be submitted to government-sanctioned data centers before appearing in publications. At the same time, the regulations, posted last week, call for open access and data sharing.

The possibly conflicting directives puzzle researchers, who note that the yet-to-be-established data centers will have latitude in interpreting the rules. Scientists in China can still share results with overseas collaborators, says Xie Xuemei, who specializes in innovation economics at Shanghai University. Xie also believes that the new requirements to register data with authorities before submitting papers to journals will not affect most research areas. Gaining approval could mean publishing delays, Xie says, but “it will not have a serious impact on scientific research.”

The new rules, issued by the powerful State Council, apply to all groups and individuals generating research data in China. The creation of a national data center will apparently fall to the science ministry, though other ministries and local governments are expected to create their own centers as well. Exempted from the call for open access and sharing are data involving state and business secrets, national security, “public interest,” and individual privacy… (More)”

The digital economy is disrupting our old models


Diane Coyle at The Financial Times: “One of the many episodes of culture shock I experienced as a British student in the US came when I first visited the university health centre. They gave me my medical notes to take away. Once I was over the surprise, I concluded this was entirely proper. After all, the true data was me, my body. I was reminded of this moment from the early 1980s when reflecting on the debate about Facebook and data, one of the collective conclusions of which seems to be that personal data are personal property so there need to be stronger rights of ownership. If I do not like what Facebook is doing with my data, I should be able to withdraw them. Yet this fix for the problem is not straightforward.

“My” data are inextricably linked with that of other people, who are in my photographs or in my network. Once the patterns and correlations have been extracted from it, withdrawing my underlying data is neither here nor there, for the value lies in the patterns. The social character of information can be seen from the recent example of Strava accidentally publishing maps of secret American military bases because the aggregated route data revealed all the service personnel were running around the edge of their camps. One or two withdrawals of personal data would have made no difference. To put it in economic jargon, we are in the territory of externalities and public goods. Information once shared cannot be unshared.
The digital economy is one of externalities and public goods to a far greater degree than in the past. We have not begun to get to grips with how to analyse it, still less to develop policies for the common good. There are two questions at the heart of the challenge: what norms and laws about property rights over intangibles such as data or ideas or algorithms are going to be needed? And what will the best balance between collective and individual actions be or, to put it another way, between government and market?
Tussles about rights over intangible or intellectual property have been going on for a while: patent trolls on the one hand, open source creators on the other. However, the issue is far from settled. Do we really want to accept, for example, that John Deere, in selling an expensive tractor to a farmer, is only in fact renting it out because it claims property rights over the installed software?

Free digital goods of the open source kind are being cross-subsidised by their creators’ other sources of income. Free digital goods of the social media kind are being funded by various advertising services — and that turns out to be an ugly solution. Yet the network effects are so strong, the benefits they provide so great, that if Facebook and Google were shut down by antitrust action tomorrow, replacement digital groups could well emerge before too long. China seems to be in effect nationalising its big digital platforms but many in the west will find that even less appealing than a private data market. In short, neither “market” nor “state” looks like the right model for ownership and governance in an information economy pervaded by externalities and public goods. Finding alternative models for the creation and sharing of value in the digital world, when these are inherently collective and non-rival activities, is an urgent challenge….(More).