blog post

The global race is on to build ‘City Brains’

Curated on December 16, 2018July 19, 2019 by Stefaan Verhulst

Prediction by Geoff Mulgan, Eva Grobbink and Vincent Straub: “The USSR’s launch of the Sputnik 1 satellite in 1958 was a major psychological blow to the United States. The US had believed it was technologically far ahead of its rival, but was confronted with proof that the USSR was pulling ahead in some fields. After a bout of soul-searching the country responded with extraordinary vigour, massively increasing investment in space technologies and promising to put a man on the Moon by the end of the 1960s.

In 2019, China’s success in smart cities could prompt a similar “Sputnik Moment” for the rest of the world. It may not be as dramatic as that of 1958. But unlike beeping satellites and Moon landings, it could be coming to a town near you….

The concept of a “smart city” has been around for several decades, often associated with hype, grandiose failures, and an overemphasis on hardware rather than people (Nesta has previously written on how we can rethink smart cities and ensure digital innovation realises the potential of technology and people). But various technologies are now coming of age which bring the vision of a smart city closer to fruition. China is in the forefront, investing heavily in sensors and infrastructures, and its ET City Brain project shows just how far the country’s thinking has progressed.

First launched in September 2016, ET City Brain is a collaboration between Chinese technology giant Alibaba and several cities. It was first trialled in Hangzhou, the hometown of Alibaba’s executive chairman, Jack Ma, but has since expanded to other Chinese cities. Earlier this year, Kuala Lumpurbecame the first city outside of China to import the ET City Brain model.

The ET City Brain system gathers large amounts of data (including logs, videos, and data stream) from sensors. These are then processed by algorithms in supercomputers and fed back into control centres around the city for administrators to act on—in some cases, automation means the system works without any human intervention at all.

So far, the project has been used to monitor congestion in Hangzhou, improve the response of emergency services in Guangzhou, and detect traffic accidents in Suzhou. In Hangzhou, Alibaba was given control of 104 traffic light junctions in the city’s Xiaoshan district and tasked with managing traffic flows. By combining mass video surveillance with live data from public transportation systems, ET City Brain was able to autonomously change traffic lights so that emergency vehicles could travel to accident scenes without interruption. As a result, arrival times for ambulances improved by 49 percent….(More)”.

Innovations In The Fight Against Corruption In Latin America

Curated on December 13, 2018May 29, 2019 by Stefaan Verhulst

Blog Post by Beth Noveck: “…The Inter-American Development Bank (IADB) has published an important, practical and prescriptive report with recommendations for every sector of society from government to individuals on innovative and effective approaches to combatting corruption. While focused on Latin America, the report’s proposals, especially those on the application of new technology in the fight against corruption, are relevant around the world….

The recommendations about the use of new technologies, including big data, blockchain and collective intelligence, are drawn from an effort undertaken last year by the Governance Lab at New York University’s Tandon School of Engineering to crowdsource such solutions and advice on how to implement them from a hundred global experts. (See the Smarter Crowdsourcing against Corruption report here.)…

Big data, when published as open data, namely in a form that can be re-used without legal or technical restriction and in a machine-readable format that computers can analyze, is another tool in the fight against corruption. With machine readable, big and open data, those outside of government can pinpoint and measure irregularities in government contracting, as Instituto Observ is doing in Brazil.

Opening up judicial data, such as information about case processing times, judges’ and prosecutors’ salaries, information about selection processes, such as CV’s, professional and academic backgrounds, and written and oral exam scores provides activists and reformers with the tools to fight judicial corruption. The Civil Association for Equality and Justice (ACIJ) (a non-profit advocacy group) in Argentina uses such open justice data in its Concursos Transparentes (Transparent Contests) to fight judicial corruption. Jusbrasil is a private open justice company also using open data to reform the courts in Brazil….(More)”

Long Live the Human Network Effect

Curated on December 13, 2018 by Stefaan Verhulst

Julia Hobsbawm at Strategy + Business: “Picture the scene. The eyes of the world are on the Tham Luang cave system in Thailand, near the border with Myanmar. Trapped on a rock ledge deep inside is the Wild Boars soccer team of 12 boys and their coach, who had ventured into the caves about two weeks earlier. It is monsoon season. Water is rising and oxygen levels are falling. Not all of the boys can even swim. Time is running out.

Elon Musk proposes building a “kid-sized submarine” to assist the rescue effort. Musk’s solution is politely declined by Thai authorities as “not practical.” In fact, by the time Musk’s sub arrives, most of the boys are already out, alive. One of the most audacious, moving, complex, and successful rescue operations in history relied not on a single technology or hero but on the collaboration of many people, working together in a spontaneous network.

This web of connections came together organically and quickly, unassisted by algorithms, in a unique collaboration led by humans. It was a stunning example of what physicist Albert-László Barabási calls “scale-free networks”: networks that reproduce exponentially by their very nature. The exact same network effects that can be lethal in spreading a virus can be productive — beautiful, even — in creating a web of diverse human skills quickly. Networks, as Barabási puts it, “are everywhere. You just have to look for them.”…

Networks that come together like this and use technology, community, and communications in a timely manner are an example of what the U.N. calls its “leave no one behind” strategy for achieving sustainable development goals. I consider it an example of social health in action: They are the kinds of collaborations that help us live full and productive lives. And in business, there is an exciting opportunity to harness social health and the power of networks to help solve problems.

This kind of social health network, perhaps unsurprisingly, is very visible in innovations in the healthcare sector. A digital health community called The Mighty, for example, is a forum to find information about rare illnesses and connect people facing similar challenges, so that they might learn from the experiences of others. It now has 90 million engagements on its website per month and a new member joins every 20 seconds….(More)”.

We Need an FDA For Algorithms

Curated on December 12, 2018 by Stefaan Verhulst

Interview with Hannah Fry on the promise and danger of an AI world by Michael Segal:”…Why do we need an FDA for algorithms?

It used to be the case that you could just put any old colored liquid in a glass bottle and sell it as medicine and make an absolute fortune. And then not worry about whether or not it’s poisonous. We stopped that from happening because, well, for starters it’s kind of morally repugnant. But also, it harms people. We’re in that position right now with data and algorithms. You can harvest any data that you want, on anybody. You can infer any data that you like, and you can use it to manipulate them in any way that you choose. And you can roll out an algorithm that genuinely makes massive differences to people’s lives, both good and bad, without any checks and balances. To me that seems completely bonkers. So I think we need something like the FDA for algorithms. A regulatory body that can protect the intellectual property of algorithms, but at the same time ensure that the benefits to society outweigh the harms.

Why is the regulation of medicine an appropriate comparison?

If you swallow a bottle of colored liquid and then you keel over the next day, then you know for sure it was poisonous. But there are much more subtle things in pharmaceuticals that require expert analysis to be able to weigh up the benefits and the harms. To study the chemical profile of these drugs that are being sold and make sure that they actually are doing what they say they’re doing. With algorithms it’s the same thing. You can’t expect the average person in the street to study Bayesian inference or be totally well read in random forests, and have the kind of computing prowess to look up a code and analyze whether it’s doing something fairly. That’s not realistic. Simultaneously, you can’t have some code of conduct that every data science person signs up to, and agrees that they won’t tread over some lines. It has to be a government, really, that does this. It has to be government that analyzes this stuff on our behalf and makes sure that it is doing what it says it does, and in a way that doesn’t end up harming people.

How did you come to write a book about algorithms?

Back in 2011 in London, we had these really bad riots in London. I’d been working on a project with the Metropolitan Police, trying mathematically to look at how these riots had spread and to use algorithms to ask how could the police have done better. I went to go and give a talk in Berlin about this paper we’d published about our work, and they completely tore me apart. They were asking questions like, “Hang on a second, you’re creating this algorithm that has the potential to be used to suppress peaceful demonstrations in the future. How can you morally justify the work that you’re doing?” I’m kind of ashamed to say that it just hadn’t occurred to me at that point in time. Ever since, I have really thought a lot about the point that they made. And started to notice around me that other researchers in the area weren’t necessarily treating the data that they were working with, and the algorithms that they were creating, with the ethical concern they really warranted. We have this imbalance where the people who are making algorithms aren’t talking to the people who are using them. And the people who are using them aren’t talking to the people who are having decisions made about their lives by them. I wanted to write something that united those three groups….(More)”.

The Seductive Diversion of ‘Solving’ Bias in Artificial Intelligence

Curated on December 10, 2018May 29, 2019 by Stefaan Verhulst

Blog by Julia Powles and Helen Nissenbaum: “Serious thinkers in academia and business have swarmed to the A.I. bias problem, eager to tweak and improve the data and algorithms that drive artificial intelligence. They’ve latched onto fairness as the objective, obsessing over competing constructs of the term that can be rendered in measurable, mathematical form. If the hunt for a science of computational fairness was restricted to engineers, it would be one thing. But given our contemporary exaltation and deference to technologists, it has limited the entire imagination of ethics, law, and the media as well.

There are three problems with this focus on A.I. bias. The first is that addressing bias as a computational problem obscures its root causes. Bias is a social problem, and seeking to solve it within the logic of automation is always going to be inadequate.

Second, even apparent success in tackling bias can have perverse consequences. Take the example of a facial recognition system that works poorly on women of color because of the group’s underrepresentation both in the training data and among system designers. Alleviating this problem by seeking to “equalize” representation merely co-opts designers in perfecting vast instruments of surveillance and classification.

When underlying systemic issues remain fundamentally untouched, the bias fighters simply render humans more machine readable, exposing minorities in particular to additional harms.

Third — and most dangerous and urgent of all — is the way in which the seductive controversy of A.I. bias, and the false allure of “solving” it, detracts from bigger, more pressing questions. Bias is real, but it’s also a captivating diversion.

What has been remarkably underappreciated is the key interdependence of the twin stories of A.I. inevitability and A.I. bias. Against the corporate projection of an otherwise sunny horizon of unstoppable A.I. integration, recognizing and acknowledging bias can be seen as a strategic concession — one that subdues the scale of the challenge. Bias, like job losses and safety hazards, becomes part of the grand bargain of innovation.

The reality that bias is primarily a social problem and cannot be fully solved technically becomes a strength, rather than a weakness, for the inevitability narrative. It flips the script. It absorbs and regularizes the classification practices and underlying systems of inequality perpetuated by automation, allowing relative increases in “fairness” to be claimed as victories — even if all that is being done is to slice, dice, and redistribute the makeup of those negatively affected by actuarial decision-making.

In short, the preoccupation with narrow computational puzzles distracts us from the far more important issue of the colossal asymmetry between societal cost and private gain in the rollout of automated systems. It also denies us the possibility of asking: Should we be building these systems at all?…(More)”.

Prototyping for policy

Curated on December 5, 2018December 5, 2018 by Stefaan Verhulst

Camilla Buchanan at Policy Lab Blog: “…Prototyping is common in the product and industrial design process – it has also extended to less tangible design sub-specialisms like service design. Prototypes are low fidelity mockups of an imagined idea or solution and they allow for testing before implementation. A product can be tested in cardboard form, a website can be tested through a hand drawn wireframe, a service interaction can be tested with roleplay….

Policy is a more hazy concept, it implies a message or statement of intent which sets a direction of work. Before a policy statement is made there will be some form of strategic conversation. In governments this usually takes place at the political level amongst ministers or within political parties and there is little scope for outsiders to enter these spaces. Policies set by elected officials tend to be high-level statements – as short as a line or two in a manifesto – expressed through speeches or other policy documents like White Papers.

A policy statement therefore expresses a goal and it sets in motion realisations of that goal through laws, programmes or other activities. A short policy statement can determine major programmes of government work for many years. Policy programmes have their own problem spaces to define and there is much to do in order to translate a policy goal into practical activities. Whether consciously or not, policy programmes touch the lives of millions of people and the unintended consequences or conflicting results from the enactment of poor policies can be extremely harmful. The potential benefits of testing policy goals before they are put in place are therefore huge.

The idea of design interacting directly with policy making has been explored in the last five or so years, and the first book on this subject was published in 2014. In government terms this work is very new and there is relatively little precision in current explanations. Prototyping for Policy made space to explore this better….

It is still early days for articulating exactly how and why the “physical making” aspect of design is so important in government contexts but almost all designers working in this way will emphasis it. An obvious benefit to building something real is that operational errors become more evident. And because prototypes make ideas manifest, they can help to build consensus or reveal where it is absent. They are also a way of asking questions and the presence of a prototype often prompts discussion of broader issues.

As an example, the picture below shows staff from the Service Design team at the consultancy OpenRoad in Vancouver considering advanced prototypes of changes to transit fare policy for the city for their client TransLink….(More).

Prototypes of changes to transit fares by OpenRoad

New possibilities for cutting corruption in the public sector

Curated on December 5, 2018December 6, 2018 by Stefaan Verhulst

Rema Hanna and Vestal McIntyre at VoxDev: “In their day-to-day dealings with the government, citizens of developing countries frequently encounter absenteeism, demands for bribes, and other forms of low-level corruption. When researchers used unannounced visits to gauge public-sector attendance across six countries, they found that 19% of teachers and 35% of health workers were absent during work hours (Chaudhury et al. 2006). A recent survey found that nearly 70% of Indians reported paying a bribe to access public services.

Corruption can set into motion vicious cycles: the government is impoverished of resources to provide services, and citizens are deprived of the things they need. For the poor, this might mean that they live without quality education, electricity, healthcare, and so forth. In contrast, the rich can simply pay the bribe or obtain the service privately, furthering inequality.

Much of the discourse around corruption focuses on punishing corrupt offenders. But punitive measures can only go so far, especially when corruption is seen as the ‘norm’ and is thus ingrained in institutions.

What if we could find ways of identifying the ‘goodies’ – those who enter the public sector out of a sense of civic responsibility, and serve honestly – and weeding out the ‘baddies’ before they are hired? New research shows this may be possible....

You can test personality

For decades, questionnaires have dissected personality into the ‘Big Five’ traits of openness, conscientiousness, extraversion, agreeableness, and neuroticism. These traits have been shown to be predictors of behaviour and outcomes in the workplace (Heckman 2011). As a result, private sector employers often use them in recruiting. Nobel laureate James Heckman and colleagues found that standardized adolescent measures of locus control and self-esteem (components of neuroticism) predict adult earnings to a similar degree as intelligence (Kautz et al. 2014).

Personality tests have also been put to use for the good of the poor: our colleague at Harvard’s Evidence for Policy Design (EPoD), Asim Ijaz Khwaja and collaborators have tested, and then subsequently expanded, personality tests as a basis for identifying reliable borrowers. This way, lenders can offer products to poor entrepreneurs who lack traditional credit histories, but who are nonetheless creditworthy. (See the Entrepreneurial Finance Lab’s website.)

You can test for civic-mindedness and honesty

Out of the personality-test literature grew the Perry Public Sector Motivation questionnaire (Perry 1996), which comprises a series of statements that respondents can state their level of agreement or disagreement with measures of civic-mindedness. The questionnaire has six modules, including “Attraction to Policy Making”, “Commitment to Public Interest”, “Social Justice”, “Civic Duty”, “Compassion”, and “Self-Sacrifice.” Studies have found that scores on the instrument correlate positively with job performance, ethical behaviour, participation in civic organisations, and a host of other good outcomes (for a review, see Perry and Hondeghem 2008).

You can also measure honesty in different ways. For example, Fischbacher and Föllmi-Heusi (2013) formulated a game in which subjectsroll a die and write down the number that they get, receiving higher cash rewards for larger reported numbers. While this does not reveal with certainty if any one subject lied since no one else sees the die, it does reveal how far their reported numbers were from the uniform distribution. Those with high dice high points have a higher probability of having cheated. Implementing this, the authors found that “about 20% of inexperienced subjects lie to the fullest extent possible while 39% of subjects are fully honest.”

These and a range of other tools for psychological profiling have opened up new possibilities for improving governance. Here are a few lessons this new literature has yielded….(More)”.

Artificial Intelligence: Public-Private Partnerships join forces to boost AI progress in Europe

Curated on December 4, 2018December 6, 2018 by Stefaan Verhulst

European Commission Press Release: “…the Big Data Value Association and euRobotics agreed to cooperate more in order to boost the advancement of artificial intelligence’s (AI) in Europe. Both associations want to strengthen their collaboration on AI in the future. Specifically by:

Working together to boost European AI, building on existing industrial and research communities and on results of the Big Data Value PPP and SPARC PPP. This to contribute to the European Commission’s ambitious approach to AI, backed up with a drastic increase investment, reaching €20 billion total public and private funding in Europe until 2020.
Enabling joint-pilots, for example, to accelerate the use and integration of big data, robotics and AI technologies in different sectors and society as a whole
Exchanging best practices and approaches from existing and future projects of the Big Data PPP and the SPARC PPP
Contributing to the European Digital Single Market, developing strategic roadmaps and position papers

This Memorandum of Understanding between the PPPs follows the European Commission’s approach to AI presented in April 2018 and the Declaration of Cooperation on Artificial Intelligence signed by all 28 Member States and Norway. This Friday 7 December the Commission will present its EU coordinated plan….(More)”.

Using Mobile Network Data for Development: How it works

Curated on December 3, 2018December 5, 2018 by Stefaan Verhulst

Blog by Derval Usher and Darren Hanniffy: “…We aim to equip decision makers with data tools so that they have access to the analysis on the fly. But to help this scale we need progress in three areas:

1. The framework to support Shared Value partnerships.

2. Shared understanding of The Proposition and the benefits for all parties.

3. Access to finance and a funding strategy, designing-in innovation.

1. Any Public-Private Partnership should be aligned to achieve impact centered on the SDGs through a Shared Value / Inclusive Business approach. Mobile network operators are consumed with the challenge of maintaining or upgrading their infrastructure, driving device sales and sustaining their agent networks to reach the last mile. Measuring impact against the SDGs has not been a priority. Mobile network operators tend not to seek out partnerships with traditional development donors or development implementers. But there is a growing realisation of the potential and the need to partner. It’s important to move from a service level transactional relationship to a strategic partnership approach.

Private sector partners have been fundamental to the success of UN Global Pulse as these companies are often the custodians of the big data sets from which we develop valuable development and humanitarian insights. Although in previous years our private sector partners were framed primarily as data philanthropists, we are beginning to see a shift in the relationship to one of shared value. Our work generates public value and also insights that can enhance business operations. This shared value model is attracting more private enterprises to engage and to explore their own data, and more broadly to investigate the value of their networks and data as part of the data innovation ecosystem, which the Global Pulse lab network will build on as we move forward.

2. Partners need to be more propositional and less charitable. They need to recognise the fact that earning profit may help ensure the sustainability of digital platforms and services that offer developmental impact. Through partnership we can attract innovative finance, deliver mobile for development programmes, measure impact and create affordable commercial solutions to development challenges that become sustainable by design. Pulse Lab Jakarta and Digicel have been flexible with one another which is important as this partnership has not always been a priority for either side all the time. But we believe in unlocking the power of mobile data for development and therefore continue to make progress.

3. Development and commercial strategies should be more aligned to create an enabling environment. Currently they are not. Private sector needs to become a strategic partner to development where multi-annual development funds align with commercial strategy. Mobile network operators continue to invest in their network particularly in developing countries and the digital platform is coming into being in the markets where Digicel operates. But the platform is new and experience is limited within governments, the development community and indeed even within mobile network operators.

We need to see donors actively engage during the development of multi-annual funding facilities….(More)”.

Reimagining Public-Private Partnerships: Four Shifts and Innovations in Sharing and Leveraging Private Assets and Expertise for the Public Good

Curated on November 29, 2018November 29, 2018 by Stefaan Verhulst

Blog by Stefaan G. Verhulst and Andrew J. Zahuranec: “For years, public-private partnerships (PPPs) have promised to help governments do more for less. Yet, the discussion and experimentation surrounding PPPs often focus on outdated models and narratives, and the field of experimentation has not fully embraced the opportunities provided by an increasingly networked and data-rich private sector.

Private-sector actors (including businesses and NGOs) have expertise and assets that, if brought to bear in collaboration with the public sector, could spur progress in addressing public problems or providing public services. Challenges to date have largely involved the identification of effective and legitimate means for unlocking the public value of private-sector expertise and assets. Those interested in creating public value through PPPs are faced with a number of questions, including:

How do we broaden and deepen our understanding of PPPs in the 21st Century?
How can we innovate and improve the ways that PPPs tap into private-sector assets and expertise for the public good?
How do we connect actors in the PPP space with open governance developments and practices, especially given that PPPs have not played a major role in the governance innovation space to date?

The PPP Knowledge Lab defines a PPP as a “long-term contract between a private party and a government entity, for providing a public asset or service, in which the private party bears significant risk and management responsibility and remuneration is linked to performance.”…

To maximize the value of PPPs, we don’t just need new tools or experiments but new models for using assets and expertise in different sectors. We need to bring that capacity to public problems.

At the latest convening of the MacArthur Foundation Research Network on Opening Governance, Network members and experts from across the field tried to chart this new course by exploring questions about the future of PPPs.

The group explored the new research and thinking that enables many new types of collaboration beyond the typical “contract” based approaches. Through their discussions, Network members identified four shifts representing ways that cross-sector collaboration could evolve in the future: