AI software created for drones monitors wild animals and poachers


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?


 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


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


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)”.

Could Big Data Help End Hunger in Africa?


Lenny Ruvaga at VOA News: “Computer algorithms power much of modern life from our Facebook feeds to international stock exchanges. Could they help end malnutrition and hunger in Africa? The International Center for Tropical Agriculture thinks so.

The International Center for Tropical Agriculture has spent the past four years developing the Nutrition Early Warning System, or NEWS.

The goal is to catch the subtle signs of a hunger crisis brewing in Africa as much as a year in advance.

CIAT says the system uses machine learning. As more information is fed into the system, the algorithms will get better at identifying patterns and trends. The system will get smarter.

Information Technology expert Andy Jarvis leads the project.

“The cutting edge side of this is really about bringing in streams of information from multiple sources and making sense of it. … But it is a huge volume of information and what it does, the novelty then, is making sense of that using things like artificial intelligence, machine learning, and condensing it into simple messages,” he said.

Other nutrition surveillance systems exist, like FEWSnet, the Famine Early Warning System Network which was created in the mid-1980s.

But CIAT says NEWS will be able to draw insights from a massive amount of diverse data enabling it to identify hunger risks faster than traditional methods.

“What is different about NEWS is that it pays attention to malnutrition, not just drought or famine, but the nutrition outcome that really matters, malnutrition especially in women and children. For the first time, we are saying these are the options way ahead of time. That gives policy makers an opportunity to really do what they intend to do which is make the lives of women and children better in Africa,” said Dr. Mercy Lung’aho, a CIAT nutrition expert.

While food emergencies like famine and drought grab headlines, the International Center for Tropical Agriculture says chronic malnutrition affects one in four people in Africa, taking a serious toll on economic growth and leaving them especially vulnerable in times of crisis….(More)”.

Information for the People: Tunisia Embraces Open Government, 2011–2016


Case study by Tristan Dreisback at Innovations for Successful Societies: “In January 2011, mass demonstrations in Tunisia ousted a regime that had tolerated little popular participation, opening the door to a new era of transparency. The protesters demanded an end to the secrecy that had protected elite privilege. Five months later, the president issued a decree that increased citizen access to government data and formed a steering committee to guide changes in information practices, building on small projects already in development. Advocates in the legislature and the public service joined with civil society leaders to support a strong access-to-information policy, to change the culture of public administration, and to secure the necessary financial and technical resources to publish large quantities of data online in user-friendly formats. Several government agencies launched their own open-data websites. External pressure, coupled with growing interest from civil society and legislators, helped keep transparency reforms on the cabinet office agenda despite frequent changes in top leadership. In 2016, Tunisia adopted one of the world’s strongest laws regarding access to information. Although members of the public did not put all of the resources to use immediately, the country moved much closer to having the data needed to improve access to services, enhance government performance, and support the evidence-based deliberation on which a healthy democracy depended…(More)”

A Framework for Assessing Technology Hubs in Africa


Paper by Jeremy de BeerPaula MillarJacquelen MwangiVictor 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)”

Tech Companies Should Speak Up for Refugees, Not Only High-Skilled Immigrants


Mark Latonero at Harvard Business Review: “The Trump administration’s latest travel ban is back in U.S. federal court. The Fourth Circuit, based in Virginia, and Ninth Circuit, based in San Francisco, are hearing cases challenging the latest executive order banning immigrants and refugees from six Muslim majority countries from entering the United States. Joining the fray are 162 technology companies, whose lawyers collectively filed an amicus brief to both courts. Amazon, eBay, Google, Facebook, Netflix, and Uber are among the companies urging federal judges to rule against the executive order, detailing why it is unjust and how it would hurt their businesses.

While the 40-page brief is filled with arguments in support of immigration, it hardly speaks about refugees, except to note that those seeking protection should be welcomed. Any multinational company with a diverse workforce would be concerned about limits to international hiring and employee travel. But tech companies should also be concerned about the refugee populations that depend on their digital services for safety and survival.

In researching migration and the refugee crisis in Europe, my team and I interviewed over 140 refugees from Syria, and I’ve learned that technology has been crucial to those fleeing war and violence across the Middle East and North Africa. Services like Google Maps, Facebook, WhatsApp, Skype, and Western Union have helped refugees find missing loved ones or locate safe places to sleep. Mobile phones have been essential — refugees have even used them on sinking boats to call rescue officials patrolling the Mediterranean.

Refugees’ reliance on these platforms demonstrates what tech companies often profess: that innovation can empower people to improve their lives and society. Tech companies did not intend for their tools to facilitate one of the largest mass movements of refugees in history, but they have a responsibility to look out for the safety and security of the vulnerable consumers using their products.

Some tech companies have intervened directly in the refugee crisis. Google has created apps to help refugees in Greece find medical facilities and other services; Facebook promised to provide free Wi-Fi in U.N. refugee camps. A day after President Trump issued the first travel ban, which initially suspended the U.S. Refugee Admissions Program, Airbnb announced it would provide free housing to refugees left stranded….

The sector should extend these efforts by making sure its technologies aren’t used to target broad groups of people based on nationality or religion. Already the U.S. Customs and Border Protection (CPB) is asking for the social media accounts — even passwords — of visitors from other counties. The Council on American-Islamic Relations has filed complaints against the CPB, stating that Muslim American citizens have been subjected to enhanced screening that includes scrutiny of their social media accounts and cell phones.

Trump has talked about creating a database to identify and register Muslims in America, including refugees. A number of companies, including IBM, Microsoft, and Salesforce, have stated they will not help build a Muslim registry if asked by the government. In addition, a group of nearly 3,000 American tech employees signed an online pledge promising they would not develop data processing systems to help the U.S. government target individuals based on race, religion, or national origin….(More)”.

Why big-data analysis of police activity is inherently biased


 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


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)”