Wastewater monitoring: ‘the James Webb Telescope for population health’

Curated on Posted on by Stefaan Verhulst

Article by Exemplars News: “When the COVID-19 pandemic triggered a lockdown across Bangladesh and her research on environmental exposure to heavy metals became impossible to continue, Dr. Rehnuma Haque began a search for some way she could contribute to the pandemic response.

“I knew I had to do something during COVID,” said Dr. Haque, a research scientist at the International Centre for Diarrheal Disease Research, Bangladesh (icddr,b). “I couldn’t just sit at home.”

Then she stumbled upon articles on early wastewater monitoring efforts for COVID in Australia, the Netherlands, Italy, and the United States. “When I read those papers, I was so excited,” said Dr. Haque. “I emailed my supervisor, Dr. Mahbubur Rahman, and said, ‘Can we do this?’”

Two months later, in June 2020, Dr. Haque and her colleagues had launched one of the most robust and earliest national wastewater surveillance programs for COVID in a low- or middle-income country (LMIC).

The initiative, which has now been expanded to monitor for cholera, salmonella, and rotavirus and may soon be expanded further to monitor for norovirus and antibiotic resistance, demonstrates the power and potential of wastewater surveillance to serve as a low-cost tool for obtaining real-time meaningful health data at scale to identify emerging risks and guide public health responses.

“It is improving public health outcomes,” said Dr. Haque. “We can see everything going on in the community through wastewater surveillance. You can find everything you are looking for and then prepare a response.”

A single wastewater sample can yield representative data about an entire ward, town, or county and allow LMICs to monitor for emerging pathogens. Compared with clinical monitoring, wastewater monitoring is easier and cheaper to collect, can capture infections that are asymptomatic or before symptoms arise, raises fewer ethical concerns, can be more inclusive and not as prone to sampling biases, can generate a broader range of data, and is unrivaled at quickly generating population-level data…(More)” – See also: The #Data4Covid19 Review

What can harnessing ‘positive deviance’ methods do for food security?

Curated on Posted on by Stefaan Verhulst

Article by Katrina J. Lane: “What the researchers identified in Niger, in this case, is known as “positive deviance”. It’s a concept that originated in 1991 during a nutrition program in Vietnam run by Save the Children. Instead of focusing on the population level, project managers studied outliers in the system — children who were healthier than their peers despite sharing similar circumstances, and then looked at what the parents of these children did differently.

Once the beneficial practices were identified — in this case, that included collecting wild foods, such as crab, shrimp, and sweet potato tops for their children — they encouraged mothers to tell other parents. Through this outlier-centric approach, the project was able to reduce malnourishment by 74%.

“The positive deviance approach assumes that in every community there are individuals or groups that develop uncommon behaviors or practices which help them cope better with the challenges they face than their peers,” said Boy.

It’s important to be respectful and acknowledge success stories already present in systems, added Duncan Green, a strategic adviser for Oxfam and a professor in practice in international development at the London School of Economics.

Positive deviance emphasizes the benefit of identifying and amplifying these “deviant behaviors”, as they hold the potential to generate scalable solutions that can benefit the entire community.

It can be broken down into three steps: First, identifying high-performing individuals or groups within a challenging context. Next, an investigative process in the community via in-person interviews, group discussions, and questionnaires to find what their behaviors and practices are. Finally, it means encouraging solutions to be spread throughout the community.

In the final stage, the approach relies on community-generated solutions — which Green explains are more likely to propagate and be engaged with…(More)”.

AI By the People, For the People

Curated on Posted on by Stefaan Verhulst

Article by Billy Perrigo/Karnataka: “…To create an effective English-speaking AI, it is enough to simply collect data from where it has already accumulated. But for languages like Kannada, you need to go out and find more.

This has created huge demand for datasets—collections of text or voice data—in languages spoken by some of the poorest people in the world. Part of that demand comes from tech companies seeking to build out their AI tools. Another big chunk comes from academia and governments, especially in India, where English and Hindi have long held outsize precedence in a nation of some 1.4 billion people with 22 official languages and at least 780 more indigenous ones. This rising demand means that hundreds of millions of Indians are suddenly in control of a scarce and newly-valuable asset: their mother tongue.

Data work—creating or refining the raw material at the heart of AI— is not new in India. The economy that did so much to turn call centers and garment factories into engines of productivity at the end of the 20th century has quietly been doing the same with data work in the 21st. And, like its predecessors, the industry is once again dominated by labor arbitrage companies, which pay wages close to the legal minimum even as they sell data to foreign clients for a hefty mark-up. The AI data sector, worth over $2 billion globally in 2022, is projected to rise in value to $17 billion by 2030. Little of that money has flowed down to data workers in India, Kenya, and the Philippines.

These conditions may cause harms far beyond the lives of individual workers. “We’re talking about systems that are impacting our whole society, and workers who make those systems more reliable and less biased,” says Jonas Valente, an expert in digital work platforms at Oxford University’s Internet Institute. “If you have workers with basic rights who are more empowered, I believe that the outcome—the technological system—will have a better quality as well.”

In the neighboring villages of Alahalli and Chilukavadi, one Indian startup is testing a new model. Chandrika works for Karya, a nonprofit launched in 2021 in Bengaluru (formerly Bangalore) that bills itself as “the world’s first ethical data company.” Like its competitors, it sells data to big tech companies and other clients at the market rate. But instead of keeping much of that cash as profit, it covers its costs and funnels the rest toward the rural poor in India. (Karya partners with local NGOs to ensure access to its jobs go first to the poorest of the poor, as well as historically marginalized communities.) In addition to its $5 hourly minimum, Karya gives workers de-facto ownership of the data they create on the job, so whenever it is resold, the workers receive the proceeds on top of their past wages. It’s a model that doesn’t exist anywhere else in the industry…(More)”.

China’s new AI rules protect people — and the Communist Party’s power

Curated on Posted on by Stefaan Verhulst

Article by Johanna M. Costigan: “In April, in an effort to regulate rapidly advancing artificial intelligence technologies, China’s internet watchdog introduced draft rules on generative AI. They cover a wide range of issues — from how data is trained to how users interact with generative AI such as chatbots. 

Under the new regulations, companies are ultimately responsible for the “legality” of the data they use to train AI models. Additionally, generative AI providers must not share personal data without permission, and must guarantee the “veracity, accuracy, objectivity, and diversity” of their pre-training data. 

These strict requirements by the Cyberspace Administration of China (CAC) for AI service providers could benefit Chinese users, granting them greater protections from private companies than many of their global peers. Article 11 of the regulations, for instance, prohibits providers from “conducting profiling” on the basis of information gained from users. Any Instagram user who has received targeted ads after their smartphone tracked their activity would stand to benefit from this additional level of privacy.  

Another example is Article 10 — it requires providers to employ “appropriate measures to prevent users from excessive reliance on generated content,” which could help prevent addiction to new technologies and increase user safety in the long run. As companion chatbots such as Replika become more popular, companies should be responsible for managing software to ensure safe use. While some view social chatbots as a cure for loneliness, depression, and social anxiety, they also present real risks to users who become reliant on them…(More)”.

If good data is key to decarbonization, more than half of Asia’s economies are being locked out of progress, this report says

Curated on Posted on by Stefaan Verhulst

Blog by Ewan Thomson: “If measuring something is the first step towards understanding it, and understanding something is necessary to be able to improve it, then good data is the key to unlocking positive change. This is particularly true in the energy sector as it seeks to decarbonize.

But some countries have a data problem, according to energy think tank Ember and climate solutions enabler Subak’s Asia Data Transparency Report 2023, and this lack of open and reliable power-generation data is holding back the speed of the clean power transition in the region.

Asia is responsible for around 80% of global coal consumption, making it a big contributor to carbon emissions. Progress is being made on reducing these emissions, but without reliable data on power generation, measuring the rate of this progress will be challenging.

These charts show how different Asian economies are faring on data transparency on power generation and what can be done to improve both the quality and quantity of the data.

Infographic showing the number of economies by overall transparency score.

Over half of Asian countries lack reliable data in their power sectors, Ember says. Image: Ember

There are major data gaps in 24 out of the 39 Asian economies covered in the Ember research. This means it is unclear whether the energy needs of the nearly 700 million people in these 24 economies are being met with renewables or fossil fuels…(More)”.

Air-Pollution Knowledge Is Power

Curated on Posted on by Stefaan Verhulst

Article by Chana R. Schoenberger: “What happens when people in countries where the government offers little pollution monitoring learn that the air quality is dangerous? A new study details how the US Embassy in Beijing began to monitor the Chinese capital’s air-pollution levels and tweet about them in 2008. The program later extended to other US embassies in cities around the world. The practice led to a measurable decline in air pollution in those cities, few of which had local pollution monitoring before, the researchers found.

The paper’s authors, Akshaya Jha, an assistant professor of economics and public policy at Carnegie Mellon University, and Andrea La Nauze, a lecturer at the School of Economics at the University of Queensland, used satellite data to compare pollution levels, measured annually. The researchers found that the level of air pollution went down after the local US embassy began tweeting pollution numbers from monitoring equipment that diplomatic personnel had installed.

The embassy program yielded a drop in fine-particulate concentration levels of 2 to 4 micrograms per square meter, leading to a decline in premature mortality worth $127 million for the median city in 2019. “Our findings point to the substantial benefits of improving the availability and salience of air-quality information in low- and middle-income countries,” Jha and La Nauze write.

News coverage of the US government’s Beijing pollution monitoring sparked the researchers’ interest, La Nauze says. At the time, American diplomats were quoted saying that the embassy’s tweets led to marked changes in pollution levels in Beijing. When the researchers learned that the US State Department had extended the program to embassies around the world, they thought there might be a way to evaluate the diplomats’ claims empirically.

A problem the researchers confronted was how to quantify the impact of measuring something that had never been measured before…(More)” – See also: US Embassy Air-Quality Tweets Led to Global Health Benefits

Gaming Public Opinion

Curated on Posted on by Stefaan Verhulst

Article by Albert Zhang , Tilla Hoja & Jasmine Latimore: “The Chinese Communist Party’s (CCP’s) embrace of large-scale online influence operations and spreading of disinformation on Western social-media platforms has escalated since the first major attribution from Silicon Valley companies in 2019. While Chinese public diplomacy may have shifted to a softer tone in 2023 after many years of wolf-warrior online rhetoric, the Chinese Government continues to conduct global covert cyber-enabled influence operations. Those operations are now more frequent, increasingly sophisticated and increasingly effective in supporting the CCP’s strategic goals. They focus on disrupting the domestic, foreign, security and defence policies of foreign countries, and most of all they target democracies.

Currently—in targeted democracies—most political leaders, policymakers, businesses, civil society groups and publics have little understanding of how the CCP currently engages in clandestine activities online in their countries, even though this activity is escalating and evolving quickly. The stakes are high for democracies, given the indispensability of the internet and their reliance on open online spaces, free from interference. Despite years of monitoring covert CCP cyber-enabled influence operations by social-media platforms, governments, and research institutes such as ASPI, definitive public attribution of the actors driving these activities is rare. Covert online operations, by design, are difficult to detect and attribute to state actors. 

Social-media platforms and governments struggle to devote adequate resources to identifying, preventing and deterring increasing levels of malicious activity, and sometimes they don’t want to name and shame the Chinese Government for political, economic and/or commercial reasons…(More)”.

AI translation is jeopardizing Afghan asylum claims

Curated on Posted on by Stefaan Verhulst

Article by Andrew Deck: “In 2020, Uma Mirkhail got a firsthand demonstration of how damaging a bad translation can be.

A crisis translator specializing in Afghan languages, Mirkhail was working with a Pashto-speaking refugee who had fled Afghanistan. A U.S. court had denied the refugee’s asylum bid because her written application didn’t match the story told in the initial interviews.

In the interviews, the refugee had first maintained that she’d made it through one particular event alone, but the written statement seemed to reference other people with her at the time — a discrepancy large enough for a judge to reject her asylum claim.

After Mirkhail went over the documents, she saw what had gone wrong: An automated translation tool had swapped the “I” pronouns in the woman’s statement to “we.”

Mirkhail works with Respond Crisis Translation, a coalition of over 2,500 translators that provides interpretation and translation services for migrants and asylum seekers around the world. She told Rest of World this kind of small mistake can be life-changing for a refugee. In the wake of the Taliban’s return to power in Afghanistan, there is an urgent demand for crisis translators working in languages such as Pashto and Dari. Working alongside refugees, these translators can help clients navigate complex immigration systems, including drafting immigration forms such as asylum applications. But a new generation of machine translation tools is changing the landscape of this field — and adding a new set of risks for refugees…(More)”.

China’s fake science industry: how ‘paper mills’ threaten progress

Curated on Posted on by Stefaan Verhulst

Article by Eleanor Olcott, Clive Cookson and Alan Smith at the Financial Times: “…Over the past two decades, Chinese researchers have become some of the world’s most prolific publishers of scientific papers. The Institute for Scientific Information, a US-based research analysis organisation, calculated that China produced 3.7mn papers in 2021 — 23 per cent of global output — and just behind the 4.4mn total from the US.

At the same time, China has been climbing the ranks of the number of times a paper is cited by other authors, a metric used to judge output quality. Last year, China surpassed the US for the first time in the number of most cited papers, according to Japan’s National Institute of Science and Technology Policy, although that figure was flattered by multiple references to Chinese research that first sequenced the Covid-19 virus genome.

The soaring output has sparked concern in western capitals. Chinese advances in high-profile fields such as quantum technology, genomics and space science, as well as Beijing’s surprise hypersonic missile test two years ago, have amplified the view that China is marching towards its goal of achieving global hegemony in science and technology.

That concern is a part of a wider breakdown of trust in some quarters between western institutions and Chinese ones, with some universities introducing background checks on Chinese academics amid fears of intellectual property theft.

But experts say that China’s impressive output masks systemic inefficiencies and an underbelly of low-quality and fraudulent research. Academics complain about the crushing pressure to publish to gain prized positions at research universities…(More)”.

Common Data Environment: Bridging the Digital Data Sharing Gap Among Construction Organizations

Curated on Posted on by Stefaan Verhulst

Paper by Yong Jia Tan et al: “Moving into the 21st century, digital data sharing is pertinent towards the construction industry technology advancement. Preeminent digital data sharing revolves around construction organizations’ effective data management and digital data utilization within the Common Data Environment (CDE). Interconnected data is the heart of the construction industry’s future digital utility. Albeit the progressive digitalization uptake, the absence of integrated digital data collaboration efforts due to working-in-silo facet impedes the Malaysian construction organizations capability to capitalize the technology potential at best. To identify the types of digital data and the potential of digital data sharing through Common Data Environment within the Malaysian construction industry, this study adopts thematic analysis methodology on five in-depth case study on CDE adoption among construction organizations. The presented case study further identified through snowball sampling method. The analysis reveals the three main data categories created by construction organization in CDE are graphical data, non-graphical data, and associated construction project documents. Findings further identifies eight potentials of CDE data sharing namely improved efficiency, productivity, collaboration, effective decision making, cost and time savings, security, and accessibility. Ultimately, this study presents insights and explorative avenues for construction stakeholders to transcend advanced technology maximization and boost the industry productivity gain…(More)”.