Book edited by Masamichi Sasaki: “… deals with conceptual, theoretical and social interaction analyses, historical data on societies, national surveys or cross-national comparative studies, and methodological issues related to trust. The authors are from a variety of disciplines: psychology, sociology, political science, organizational studies, history, and philosophy, and from Britain, the United States, the Czech Republic, the Netherlands, Australia, Germany, and Japan. They bring their vast knowledge from different historical and cultural backgrounds to illuminate contemporary issues of trust and distrust. The socio-cultural perspective of trust is important and increasingly acknowledged as central to trust research. Accordingly, future directions for comparative trust research are also discussed….(More)”.
This Is Not an Atlas.
Book by kollektiv orangotango: “This Is Not an Atlas gathers more than 40 counter-cartographies from all over the world. This collection shows how maps are created and transformed as a part of political struggle, for critical research or in art and education: from indigenous territories in the Amazon to the anti-eviction movement in San Francisco; from defending commons in Mexico to mapping refugee camps with balloons in Lebanon; from slums in Nairobi to squats in Berlin; from supporting communities in the Philippines to reporting sexual harassment in Cairo. This Is Not an Atlas seeks to inspire, to document the underrepresented, and to be a useful companion when becoming a counter-cartographer yourself….(More)”.
The Psychology of Prediction
Blog post by Morgan Housel: “During the Vietnam War Secretary of Defense Robert McNamara tracked every combat statistic he could, creating a mountain of analytics and predictions to guide the war’s strategy.
Edward Lansdale, head of special operations at the Pentagon, once looked at McNamara’s statistics and told him something was missing.
“What?” McNamara asked.
“The feelings of the Vietnamese people,” Landsdale said.
That’s not the kind of thing a statistician pays attention to. But, boy, did it matter.
I believe in prediction. I think you have to in order to get out of bed in the morning.
But prediction is hard. Either you know that or you’re in denial about it.
A lot of the reason it’s hard is because the visible stuff that happens in the world is a small fraction of the hidden stuff that goes on inside people’s heads. The former is easy to overanalyze; the latter is easy to ignore.
This report describes 12 common flaws, errors, and misadventures that occur in people’s heads when predictions are made….(More)”.
The plan to mine the world’s research papers
Priyanka Pulla in Nature: “Carl Malamud is on a crusade to liberate information locked up behind paywalls — and his campaigns have scored many victories. He has spent decades publishing copyrighted legal documents, from building codes to court records, and then arguing that such texts represent public-domain law that ought to be available to any citizen online. Sometimes, he has won those arguments in court. Now, the 60-year-old American technologist is turning his sights on a new objective: freeing paywalled scientific literature. And he thinks he has a legal way to do it.
Over the past year, Malamud has — without asking publishers — teamed up with Indian researchers to build a gigantic store of text and images extracted from 73 million journal articles dating from 1847 up to the present day. The cache, which is still being created, will be kept on a 576-terabyte storage facility at Jawaharlal Nehru University (JNU) in New Delhi. “This is not every journal article ever written, but it’s a lot,” Malamud says. It’s comparable to the size of the core collection in the Web of Science database, for instance. Malamud and his JNU collaborator, bioinformatician Andrew Lynn, call their facility the JNU data depot.
No one will be allowed to read or download work from the repository, because that would breach publishers’ copyright. Instead, Malamud envisages, researchers could crawl over its text and data with computer software, scanning through the world’s scientific literature to pull out insights without actually reading the text.
The unprecedented project is generating much excitement because it could, for the first time, open up vast swathes of the paywalled literature for easy computerized analysis. Dozens of research groups already mine papers to build databases of genes and chemicals, map associations between proteins and diseases, and generate useful scientific hypotheses. But publishers control — and often limit — the speed and scope of such projects, which typically confine themselves to abstracts, not full text. Researchers in India, the United States and the United Kingdom are already making plans to use the JNU store instead. Malamud and Lynn have held workshops at Indian government laboratories and universities to explain the idea. “We bring in professors and explain what we are doing. They get all excited and they say, ‘Oh gosh, this is wonderful’,” says Malamud.
But the depot’s legal status isn’t yet clear. Malamud, who contacted several intellectual-property (IP) lawyers before starting work on the depot, hopes to avoid a lawsuit. “Our position is that what we are doing is perfectly legal,” he says. For the moment, he is proceeding with caution: the JNU data depot is air-gapped, meaning that no one can access it from the Internet. Users have to physically visit the facility, and only researchers who want to mine for non-commercial purposes are currently allowed in. Malamud says his team does plan to allow remote access in the future. “The hope is to do this slowly and deliberately. We are not throwing this open right away,” he says….(More)”.
What Restaurant Reviews Reveal About Cities
Linda Poon at CityLab: “Online review sites can tell you a lot about a city’s restaurant scene, and they can reveal a lot about the city itself, too.
Researchers at MIT recently found that information about restaurants gathered from popular review sites can be used to uncover a number of socioeconomic factors of a neighborhood, including its employment rates and demographic profiles of the people who live, work, and travel there.
A report published last week in the Proceedings of the National Academy of Sciences explains how the researchers used information found on Dianping—a Yelp-like site in China—to find information that might usually be gleaned from an official government census. The model could prove especially useful for gathering information about cities that don’t have that kind of reliable or up-to-date government data, especially in developing countries with limited resources to conduct regular surveys….
Zheng and her colleagues tested out their machine-learning model using restaurant data from nine Chinese cities of various sizes—from crowded ones like Beijing, with a population of more than 10 million, to smaller ones like Baoding, a city of fewer than 3 million people.
They pulled data from 630,000 restaurants listed on Dianping, including each business’s location, menu prices, opening day, and customer ratings. Then they ran it through a machine-learning model with official census data and with anonymous location and spending data gathered from cell phones and bank cards. By comparing the information, they were able to determine where the restaurant data reflected the other data they had about neighborhoods’ characteristics.
They found that the local restaurant scene can predict, with 95 percent accuracy, variations in a neighborhood’s daytime and nighttime populations, which are measured using mobile phone data. They can also predict, with 90 and 93 percent accuracy, respectively, the number of businesses and the volume of consumer consumption. The type of cuisines offered and kind of eateries available (coffeeshop vs. traditional teahouses, for example), can also predict the proportion of immigrants or age and income breakdown of residents. The predictions are more accurate for neighborhoods near urban centers as opposed to those near suburbs, and for smaller cities, where neighborhoods don’t vary as widely as those in bigger metropolises….(More)”.
Stop Surveillance Humanitarianism
Mark Latonero at The New York Times: “A standoff between the United Nations World Food Program and Houthi rebels in control of the capital region is threatening the lives of hundreds of thousands of civilians in Yemen.
Alarmed by reports that food is being diverted to support the rebels, the aid program is demanding that Houthi officials allow them to deploy biometric technologies like iris scans and digital fingerprints to monitor suspected fraud during food distribution.
The Houthis have reportedly blocked food delivery, painting the biometric effort as an intelligence operation, and have demanded access to the personal data on beneficiaries of the aid. The impasse led the aid organization to the decision last month to suspend food aid to parts of the starving population — once thought of as a last resort — unless the Houthis allow biometrics.
With program officials saying their staff is prevented from doing its essential jobs, turning to a technological solution is tempting. But biometrics deployed in crises can lead to a form of surveillance humanitarianism that can exacerbate risks to privacy and security.
By surveillance humanitarianism, I mean the enormous data collection systems deployed by aid organizations that inadvertently increase the vulnerability of people in urgent need….(More)”.
Betting on biometrics to boost child vaccination rates
Ben Parker at The New Humanitarian: “Thousands of children between the ages of one and five are due to be fingerprinted in Bangladesh and Tanzania in the largest biometric scheme of its kind ever attempted, the Geneva-based vaccine agency, Gavi, announced recently.
Although the scheme includes data protection safeguards – and its sponsors are cautious not to promise immediate benefits – it is emerging during a widening debate on data protection, technology ethics, and the risks and benefits of biometric ID in development and humanitarian aid.
Gavi, a global vaccine provider, is teaming up with Japanese and British partners in the venture. It is the first time such a trial has been done on this scale, according to Gavi spokesperson James Fulker.
Being able to track a child’s attendance at vaccination centres, and replace “very unreliable” paper-based records, can help target the 20 million children who are estimated to miss key vaccinations, most in poor or remote communities, Fulker said.
Up to 20,000 children will have their fingerprints taken and linked to their records in existing health projects. That collection effort will be managed by Simprints, a UK-based not-for-profit enterprise specialising in biometric technology in international development, according to Christine Kim, the company’s head of strategic partnerships….
Ethics and legal safeguards
Kim said Simprints would apply data protection standards equivalent to the EU’s General Directive on Privacy Regulation (GDPR), even if national legislation did not demand it. Families could opt out without any penalties, and informed consent would apply to any data gathering. She added that the fieldwork would be approved by national governments, and oversight would also come from institutional review boards at universities in the two countries.
Fulker said Gavi had also commissioned a third-party review to verify Simprints’ data protection and security methods.
For critics of biometrics use in humanitarian settings, however, any such plan raises red flags….
Data protection analysts have long been arguing that gathering digital ID and biometric data carries particular risks for vulnerable groups who face conflict or oppression: their data could be shared or leaked to hostile parties who could use it to target them.
In a recent commentary on biometrics and aid, Linda Raftree told The New Humanitarian that “the greatest burden and risk lies with the most vulnerable, whereas the benefits accrue to [aid] agencies.”
And during a panel discussion on “Digital Do No Harm” held last year in Berlin, humanitarian professionals and data experts discussed a range of threats and unintended consequences of new technologies, noting that they are as yet hard to predict….(More)”.
New App Uses Crowdsourcing to Find You an EpiPen in an Emergency
Article by Shaunacy Ferro: “Many people at risk for severe allergic reactions to things like peanuts and bee stings carry EpiPens. These tools inject the medication epinephrine into one’s bloodstream to control immune responses immediately. But exposure can turn into life-threatening situations in a flash: Without EpiPens, people could suffer anaphylactic shock in less than 15 minutes as they wait for an ambulance. Being without an EpiPen or other auto-injector can have deadly consequences.
EPIMADA, a new app created by researchers at Israel’s Bar-Ilan University, is designed to save the lives of people who go into anaphylactic shock when they don’t have EpiPens handy. The app uses the same type of algorithms that ride-hailing services use to match drivers and riders by location—in this case, EPIMADA matches people in distress with nearby strangers carrying EpiPens. David Schwartz, director of the university’s Social Intelligence Lab and one of the app’s co-creators, told The Jerusalem Post that the app currently has hundreds of users….
EPIMADA serves as a way to crowdsource medication from fellow patients who might be close by and able to help. While it may seem unlikely that people would rush to give up their own expensive life-saving tool for a stranger, EPIMADA co-creator Michal Gaziel Yablowitz, a doctoral student in the Social Intelligence Lab, explained in a press release that “preliminary research results show that allergy patients are highly motivated to give their personal EpiPen to patient-peers in immediate need.”…(More)”.
How can Indigenous Data Sovereignty (IDS) be promoted and mainstreamed within open data movements?
OD Mekong Blog: “Considering Indigenous rights in the open data and technology space is a relatively new concept. Called “Indigenous Data Sovereignty” (IDS), it is defined as “the right of Indigenous peoples to govern the collection, ownership, and application of data about Indigenous communities, peoples, lands, and resources”, regardless of where the data is held or by whom. By default, this broad and all-encompassing framework bucks fundamental concepts of open data, and asks traditional open data practitioners to critically consider how open data can be used as a tool of transparency that also upholds equal rights for all…
Four main areas of concern and relevant barriers identified by participants were:
Self-determination to identify their membership
- National governments in many states, particularly across Asia and South America, still do not allow for self-determination under the law. Even when legislation offers some recognition these are scarcely enforced, and mainstream discourse demonises Indigenous self-determination.
- However, because Indigenous and ethnic minorities frequently face hardships and persecution on a daily basis, there were concerns about the applicability of data sovereignty at the local levels.
Intellectual Property Protocols
- It has become the norm in the everyday lives of people for big tech companies to extract data in excessive amounts. How do disenfranchised communities combat this?
- Indigenous data is often misappropriated to the detriment of Indigenous peoples.
- Intellectual property concepts, such as copyright, are not an ideal approach for protecting Indigenous knowledge and intellectual property rights because they are rooted in commercialistic ideals that are difficult to apply to Indigenous contexts. This is especially so because many groups do not practice commercialization in the globalized context. Also, as a concept based on exclusivity (i.e., when licenses expire knowledge gets transferred over as public goods), it doesn’t take into account the collectivist ideals of Indigenous peoples.
Data Governance
- Ultimately, data protection is about protecting lives. Having the ability to use data to direct decisions on Indigenous development places greater control in the hands of Indigenous peoples.
- National governments are barriers due to conflicts in sovereignty interests. Nation-state legal systems are often contradictory to customary laws, and thus don’t often reflect rights-based approaches.
Consent — Free Prior and Informed Consent (FPIC)
- FPIC, referring to a set of principles that define the process and mechanisms that apply specifically to Indigenous peoples in relation to the exercise of their collective rights, is a well-known phrase. They are intended to ensure that Indigenous peoples are treated as sovereign peoples with their own decision-making power, customary governance systems, and collective decision-making processes, but it is questionable as to what level one can ensure true FPIC in the Indigenous context.²
- It remains a question as too how effectively due diligence can be applied to research protocols, so as to ensure that the rights associated with FPIC and the UNDRIP framework are upheld….(More)”.
How an AI Utopia Would Work
Sami Mahroum at Project Syndicate: “…It is more than 500 years since Sir Thomas More found inspiration for the “Kingdom of Utopia” while strolling the streets of Antwerp. So, when I traveled there from Dubai in May to speak about artificial intelligence (AI), I couldn’t help but draw parallels to Raphael Hythloday, the character in Utopia who regales sixteenth-century Englanders with tales of a better world.
As home to the world’s first Minister of AI, as well as museums, academies, and foundations dedicated to studying the future, Dubai is on its own Hythloday-esque voyage. Whereas Europe, in general, has grown increasingly anxious about technological threats to employment, the United Arab Emirates has enthusiastically embraced the labor-saving potential of AI and automation.
There are practical reasons for this. The ratio of indigenous-to-foreign labor in the Gulf states is highly imbalanced, ranging from a high of 67% in Saudi Arabia to a low of 11% in the UAE. And because the region’s desert environment cannot support further population growth, the prospect of replacing people with machines has become increasingly attractive.
But there is also a deeper cultural difference between the two regions. Unlike Western Europe, the birthplace of both the Industrial Revolution and the “Protestant work ethic,” Arab societies generally do not “live to work,” but rather “work to live,” placing a greater value on leisure time. Such attitudes are not particularly compatible with economic systems that require squeezing ever more productivity out of labor, but they are well suited for an age of AI and automation….
Fortunately, AI and data-driven innovation could offer a way forward. In what could be perceived as a kind of AI utopia, the paradox of a bigger state with a smaller budget could be reconciled, because the government would have the tools to expand public goods and services at a very small cost.
The biggest hurdle would be cultural: As early as 1948, the German philosopher Joseph Pieper warned against the “proletarianization” of people and called for leisure to be the basis for culture. Westerners would have to abandon their obsession with the work ethic, as well as their deep-seated resentment toward “free riders.” They would have to start differentiating between work that is necessary for a dignified existence, and work that is geared toward amassing wealth and achieving status. The former could potentially be all but eliminated.
With the right mindset, all societies could start to forge a new AI-driven social contract, wherein the state would capture a larger share of the return on assets, and distribute the surplus generated by AI and automation to residents. Publicly-owned machines would produce a wide range of goods and services, from generic drugs, food, clothes, and housing, to basic research, security, and transportation….(More)”.