Lessons from Airbnb and Uber to Open Government as a Platform

Curated on Posted on by Stefaan Verhulst

Interview by Marquis Cabrera with Sangeet Paul Choudary: “…Platform companies have a very strong core built around data, machine learning, and a central infrastructure. But they rapidly innovate around it to try and test new things in the market and that helps them open themselves for further innovation in the ecosystem. Governments can learn to become more modular and more agile, the way platform companies are. Modularity in architecture is a very fundamental part of being a platform company; both in terms of your organizational architecture, as well as your business model architecture.

The second thing that governments can learn from a platform company is that successful platform companies are created with intent. They are not created by just opening out what you have available. If you look at the current approach of applying platform thinking in government, a common approach is just to take data and open it out to the world. However, successful platform companies first create a shaping strategy to shape-out and craft a direction of vision for the ecosystem in terms of what they can achieve by being on the platform. They then provision the right tools and services that serve the vision to enable success for the ecosystem[1] . And only then do they open up their infrastructure. It’s really important that you craft the right shaping strategy and use that to define the rights tools and services before you start pursuing a platform implementation.

In my work with governments, I regularly find myself stressing the importance of thinking as a market maker rather than as a service provider. Governments have always been market makers but when it comes to technology, they often take the service provider approach.

In your book, you used San Francisco City Government and Data.gov as examples of infusing platform thinking in government. But what are some global examples of governments, countries infusing platform thinking around the world?

One of the best examples is from my home country Singapore, which has been at the forefront of converting the nation into a platform. It has now been pursuing platform strategy both overall as a nation by building a smart nation platform, and also within verticals. If you look particularly at mobility and transportation, it has worked to create a central core platform and then build greater autonomy around how mobility and transportation works in the country. Other good examples of governments applying this are Dubai, South Korea, Barcelona; they are all countries and cities that have applied the concept of platforms very well to create a smart nation platform. India is another example that is applying platform thinking with the creation of the India stack, though the implementation could benefit from better platform governance structures and a more open regulation around participation….(More)”.

Volunteers teach AI to spot slavery sites from satellite images

Curated on Posted on by Stefaan Verhulst

Matt Reynolds at New Scientist: “Online volunteers are helping to track slavery from space. A new crowdsourcing project aims to identify brick-making kilns in South Asia – frequently the site of forced labour – in satellite images.

This data will then be used to train machine learning algorithms to automatically recognise brick kilns in satellite imagery. If computers can pinpoint the location of such possible slavery sites, then the coordinates could be passed to local charities to investigate, says Kevin Bales, the project leader, at the University of Nottingham, UK.

South Asian brick kilns are notorious as modern-day slavery sites. There are an estimated 5 million people working in brick kilns in South Asia, and of those nearly 70 per cent are thought to be working there under duress – often to pay off financial debts.

 However, no one is quite sure how many of these kilns there are in the so-called “Brick Belt”, a region that stretches across parts of Pakistan, India and Nepal. Some estimates put the figure at 20,000, but it may be as high as 50,000.

Bales is hoping that his machine learning approach will produce a more accurate figure and help organisations on the ground know where to direct their anti-slavery efforts.

It’s great to have a tool for identifying possible forced labour sites, says Sasha Jesperson at St Mary’s University in London. But it is just a start – to really find out how many people are being enslaved in the brick kiln industry, investigators still need to visit every site and work out exactly what’s going on there, she says….

So far, volunteers have identified over 4000 potential slavery sites across 400 satellite images taken via Google Earth. Once these have been checked several times by volunteers, Bales plans to use these images to teach the machine learning algorithm what kilns look like, so that it can learn to recognise them in images automatically….(More)”.

AI software created for drones monitors wild animals and poachers

Curated on Posted on by Stefaan Verhulst

Springwise: “Artificial intelligence software installed into drones is to be used by US tech company Neurala to help protect endangered species from poachers. Working with the region’s Lingbergh Foundation, Neurala is currently helping operations in South Africa, Malawi and Zimbabwe and have had requests from Botswana, Mozambique and Zambia for assistance with combatting poaching.

The software is designed to monitor video as it is streamed back to researchers from unmanned drones that can fly for up to five hours, identifying animals, vehicles and poachers in real time without any human input. It can then alert rangers via the mobile command center if anything out of the ordinary is detected. The software can analyze regular or infrared footage, and therefore works with video taken day or night.

The Lindbergh Foundation will be deploying the technology as part of operation Air Shepherd, which is aimed at protecting elephants and rhinos in Southern Africa from poachers. According to the Foundation, elephants and rhinos are at risk of being extinct in just 10 years if current poaching rates continue, and has logged 5,000 hours of drone flight time over the course of 4,000 missions to date.

The use of drones within business models is proving popular, with recent innovations including a drone painting systemthat created crowdfunded murals and two Swiss hospitals that used a drone to deliver lab samples between them….(More)”.

Can we predict political uprisings?

Curated on Posted on by Stefaan Verhulst

 at The Conversation: “Forecasting political unrest is a challenging task, especially in this era of post-truth and opinion polls.

Several studies by economists such as Paul Collier and Anke Hoeffler in 1998 and 2002 describe how economic indicators, such as slow income growth and natural resource dependence, can explain political upheaval. More specifically, low per capita income has been a significant trigger of civil unrest.

Economists James Fearon and David Laitin have also followed this hypothesis, showing how specific factors played an important role in Chad, Sudan and Somalia in outbreaks of political violence.

According to the International Country Risk Guide index, the internal political stability of Sudan fell by 15% in 2014, compared to the previous year. This decrease was after a reduction of its per capita income growth rate from 12% in 2012 to 2% in 2013.

By contrast, when the income per capita growth increased in 1997 compared to 1996, the score for political stability in Sudan increased by more than 100% in 1998. Political stability across any given year seems to be a function of income growth in the previous one.

When economics lie

But as the World Bank admitted, “economic indicators failed to predict Arab Spring”.

Usual economic performance indicators, such as gross domestic product, trade, foreign direct investment, showed higher economic development and globalisation of the Arab Spring countries over a decade. Yet, in 2010, the region witnessed unprecedented uprisings that caused the collapse of regimes such as those in Tunisia, Egypt and Libya.

In our 2016 study we used data for more than 100 countries for the 1984–2012 period. We wanted to look at criteria other than economics to better understand the rise of political upheavals.

We found out and quantified how corruption is a destabilising factor when youth (15-24 years old) exceeds 20% of adult population.

Let’s examine the two main components of the study: demographics and corruption….

We are 90% confident that a youth bulge beyond 20% of adult population, on average, combined with high levels of corruption can significantly destabilise political systems within specific countries when other factors described above also taken into account. We are 99% confident about a youth bulge beyond 30% levels.

Our results can help explain the risk of internal conflict and the possible time window for it happening. They could guide policy makers and international organisations in allocating their anti-corruption budget better, taking into account the demographic structure of societies and the risk of political instability….(More).

Technology is making the world more unequal. Only technology can fix this

Curated on Posted on by Stefaan Verhulst
Cory Doctorow at The Guardian: “Here’s the bad news: technology – specifically, surveillance technology – makes it easier to police disaffected populations, and that gives badly run, corrupt states enough stability to get themselves into real trouble.

Here’s the good news: technology – specifically, networked technology – makes it easier for opposition movements to form and mobilise, even under conditions of surveillance, and to topple badly run, corrupt states.

Inequality creates instability, and not just because of the resentments the increasingly poor majority harbours against the increasingly rich minority. Everyone has a mix of good ideas and terrible ones, but for most of us, the harm from our terrible ideas is capped by our lack of political power and the checks that others – including the state – impose on us.

As rich people get richer, however, their wealth translates into political influence, and their ideas – especially their terrible ideas – take on outsized importance….

After all, there comes a point when the bill for guarding your wealth exceeds the cost of redistributing some of it, so you won’t need so many guards.

But that’s where technology comes in: surveillance technology makes guarding the elites much cheaper than it’s ever been. GCHQ and the NSA have managed to put the entire planet under continuous surveillance. Less technologically advanced countries can play along: Ethiopia was one of the world’s first “turnkey surveillance states”, a country with a manifestly terrible, looting elite class that has kept guillotines and firing squads at bay through buying in sophisticated spying technology from European suppliers, and using this to figure out which dissidents, opposition politicians and journalists represent a threat, so it can subject them to arbitrary detention, torture and, in some cases, execution….

That’s the bad news.

Now the good news: technology makes forming groups cheaper and easier than it’s ever been. Forming and coordinating groups is the hard problem of the human condition; the reason we have religions and corporations and criminal undergrounds and political parties. Doing work together means doing more than one person could do on their own, but it also means compromising, subjecting yourself to policies or orders from above. It’s costly and difficult, and the less money and time you have, the harder it is to form a group and mobilise it.

This is where networks shine. Modern insurgent groups substitute software for hierarchy, networks for bosses. They are able to come together without agreeing to a crisp agenda that you have to submit to in order to be part of the movement. When it costs less to form a group, it doesn’t matter so much that you aren’t all there for the same reason, and thus are doomed to fall apart. Even a small amount of work done together amounts to more than the tiny cost of admission…

The future is never so normal as we think it will be. The only sure thing about self-driving cars, for instance, is that whether or not they deliver fortunes to oligarchic transport barons, that’s not where it will end. Changing the way we travel has implications for mobility (both literal and social), the environment, surveillance, protest, sabotage, terrorism, parenting …

Long before the internet radically transformed the way we organise ourselves, theorists were predicting we’d use computers to achieve ambitious goals without traditional hierarchies – but it was a rare pundit who predicted that the first really successful example of this would be an operating system (GNU/Linux), and then an encyclopedia (Wikipedia).

The future will see a monotonic increase in the ambitions that loose-knit groups can achieve. My new novel, Walkaway, tries to signpost a territory in our future in which the catastrophes of the super-rich are transformed into something like triumphs by bohemian, anti-authoritarian “walkaways” who build housing and space programmes the way we make encyclopedias today: substituting (sometimes acrimonious) discussion and (sometimes vulnerable) networks for submission to the authority of the ruling elites….(More).

South Sudan: Satellite Images Used to Track Food Insecurity

Curated on Posted on by Stefaan Verhulst

Salem Solomon at VOA news: “The world is watching closely as food shortages grip parts of Africa and the Middle East. As humanitarian groups respond to the crisis, they have to solve a major problem: how to track food security in areas that are simply too remote or too dangerous to access.

The Famine Early Warning Systems Network (FEWSNET) has come up with an innovative answer. The U.S.-funded organization is working with DigitalGlobe, a Colorado satellite company, to crowdsource analysis of satellite imagery of South Sudan.

The effort will rely on thousands of volunteers — normal people with no subject matter expertise — to scour satellite images looking for things like livestock herds, temporary dwellings and permanent dwellings. The group has selected an area of 18,000 square kilometers across five counties in South Sudan to analyze.

“The crowd can identify settlement imagery, they can identify roads, hospitals, airplanes, you name it. It allows us to tap into this network of folks around the world, not necessarily in country, but they are folks who are interested and compelled by whatever the campaign is,” said Rhiannan Price, senior manager of the Seeing a Better World Program at DigitalGlobe….(More)”.

A Framework for Assessing Technology Hubs in Africa

Curated on Posted on by Stefaan Verhulst

Paper by Jeremy de Beer, Paula Millar, Jacquelen Mwangi, Victor B. Nzomo, and Isaac Rutenberg: “This article explains the importance of technology hubs as drivers of innovation, social change, and economic opportunity within and beyond the African continent. The article is the first to thoroughly review and synthesize findings from multi-disciplinary literature, and integrate insights from qualitative data gathered via interviews and fieldwork. It identifies three archetypes of hubs — clusters, companies, and countries — and discusses examples of each archetype using Kenya as a case study. The article discusses potential collaboration, conflicts, and competition among these archetypes of hubs, and concludes with recommendations for future researchers….(More)”

Why big-data analysis of police activity is inherently biased

Curated on Posted on by Stefaan Verhulst

 and  in The Conversation: “In early 2017, Chicago Mayor Rahm Emanuel announced a new initiative in the city’s ongoing battle with violent crime. The most common solutions to this sort of problem involve hiring more police officers or working more closely with community members. But Emanuel declared that the Chicago Police Department would expand its use of software, enabling what is called “predictive policing,” particularly in neighborhoods on the city’s south side.

The Chicago police will use data and computer analysis to identify neighborhoods that are more likely to experience violent crime, assigning additional police patrols in those areas. In addition, the software will identify individual people who are expected to become – but have yet to be – victims or perpetrators of violent crimes. Officers may even be assigned to visit those people to warn them against committing a violent crime.

Any attempt to curb the alarming rate of homicides in Chicago is laudable. But the city’s new effort seems to ignore evidence, including recent research from members of our policing study team at the Human Rights Data Analysis Group, that predictive policing tools reinforce, rather than reimagine, existing police practices. Their expanded use could lead to further targeting of communities or people of color.

Working with available data

At its core, any predictive model or algorithm is a combination of data and a statistical process that seeks to identify patterns in the numbers. This can include looking at police data in hopes of learning about crime trends or recidivism. But a useful outcome depends not only on good mathematical analysis: It also needs good data. That’s where predictive policing often falls short.

Machine-learning algorithms learn to make predictions by analyzing patterns in an initial training data set and then look for similar patterns in new data as they come in. If they learn the wrong signals from the data, the subsequent analysis will be lacking.

This happened with a Google initiative called “Flu Trends,” which was launched in 2008 in hopes of using information about people’s online searches to spot disease outbreaks. Google’s systems would monitor users’ searches and identify locations where many people were researching various flu symptoms. In those places, the program would alert public health authorities that more people were about to come down with the flu.

But the project failed to account for the potential for periodic changes in Google’s own search algorithm. In an early 2012 update, Google modified its search tool to suggest a diagnosis when users searched for terms like “cough” or “fever.” On its own, this change increased the number of searches for flu-related terms. But Google Flu Trends interpreted the data as predicting a flu outbreak twice as big as federal public health officials expected and far larger than what actually happened.

Criminal justice data are biased

The failure of the Google Flu Trends system was a result of one kind of flawed data – information biased by factors other than what was being measured. It’s much harder to identify bias in criminal justice prediction models. In part, this is because police data aren’t collected uniformly, and in part it’s because what data police track reflect longstanding institutional biases along income, race and gender lines….(More)”.

What data do we want? Understanding demands for open data among civil society organisations in South Africa

Curated on Posted on by Stefaan Verhulst

Report by Kaliati, Andrew; Kachieng’a, Paskaliah and de Lanerolle, Indra: “Many governments, international agencies and civil society organisations (CSOs) support and promote open data. Most open government data initiatives have focused on supply – creating portals and publishing information. But much less attention has been given to demand – understanding data needs and nurturing engagement. This research examines the demand for open data in South Africa, and asks under what conditions meeting this demand might influence accountability. Recognising that not all open data projects are developed for accountability reasons, it also examines barriers to using government data for accountability processes. The research team identified and tested ‘use stories’ and ‘use cases’. How did a range of civil society groups with an established interest in holding local government accountable use – or feel that they could use – data in their work? The report identifies and highlights ten broad types of open data use, which they divided into two streams: ‘strategy and planning’ – in which CSOs used government data internally to guide their own actions; and ‘monitoring, mobilising and advocacy’ – in which CSOs undertake outward-facing activities….(More)”

Solving a Global Digital Identity Crisis

Curated on Posted on by Stefaan Verhulst

Seth Berkley at MIT Technology Review:” In developing countries, one in three children under age five has no record of their existence. Technology can help….Digital identities have become an integral part of modern life, but things like e-passports, digital health records, or Apple Pay really only provide faster, easier, or sometimes smarter ways of accessing services that are already available.

In developing countries it’s a different story. There, digital ID technology can have a profound impact on people’s lives by enabling them to access vital and often life-saving services for the very first time….The challenge is that in poor countries, an increasing number of people live under the radar, invisible to the often archaic, paper-based methods used to certify births, deaths, and marriages. One in three children under age five does not officially exist because their birth wasn’t registered. Even when it is, many don’t have proof in the form of birth certificates. This can have a lasting impact on children’s lives, leaving them vulnerable to neglect and abuse.

In light of this, it is difficult to see how we will meet the SDG16 deadline without a radical solution. What we need are new and affordable digital ID technologies capable of working in poorly resourced settings—for example, where there is no reliable electricity—and yet able to leapfrog current approaches to reach everyone, whether they’re living in remote villages or urban slums.

Such technologies are already emerging as part of efforts to increase global childhood vaccination coverage, with small-scale trials across Africa and Asia. With 86 percent of infants now having access to routine immunization—where they receive all three doses of a diphtheria-pertussis-tetanus vaccine—there are obvious advantages of building on an existing system with such a broad reach.

These systems were designed to help the World Health Organization, UNICEF, and my organization, Gavi, the Vaccine Alliance, close the gap on the one in seven infants still missing out. But they can also be used to help us achieve SDG16.

One, called MyChild, helps countries transition from paper to digital. At first glance it looks like a typical paper booklet on which workers can record health-record details about the child, such as vaccinations, deworming, or nutritional supplements. But each booklet contains a unique identification number and tear-out slips that are collected and scanned later. This means that even if a child’s birth hasn’t been registered, a unique digital record will follow them through childhood. Developed by Swedish startup Shifo, this system has been used to register more than 95,000 infants in Uganda, Afghanistan, and the Gambia, enabling health workers to follow up either in person or using text reminders to parents.

Another system, called Khushi Baby, is entirely paperless and involves giving each child a digital necklace that contains a unique ID number on a near-field communication chip. This can be scanned by community health workers using a cell phone, enabling them to update a child’s digital health records even in remote areas with no cell coverage. Trials in the Indian state of Rajasthan have been carried out across 100 villages to track more than 15,000 vaccination events. An organization called ID2020 is exploring the use of blockchain technology to create access to a unique identity for those who currently lack one….(More)”