How Smart Tech Tried to Solve the Mental Health Crisis and Only Made It Worse

Curated on Posted on by Stefaan Verhulst

Article by Emma Bedor Hiland: “Crisis Text Line was supposed to be the exception. Skyrocketing rates of depression, anxiety, and mental distress over the last decade demanded new, innovative solutions. The non-profit organization was founded in 2013 with the mission of providing free mental health text messaging services and crisis intervention tools. It seemed like the right moment to use technology to make the world a better place. Over the following years, the accolades and praise the platform received reflected its success. But their sterling reputation was tarnished overnight at the beginning of 2022 when Politico published an investigation into the way Crisis Text Line had handled and shared user data. The problem with the organization, however, goes well beyond its alleged mishandling of user information.

Despite Crisis Text Line’s assurance that its platform was anonymous, Politico’s January report showed that the company’s private messaging sessions were not actually anonymous. Data about users, including what they shared with Crisis Text Line’s volunteers, had been provided and sold to an entirely different company called Loris.ai, a tech startup that specializes in artificial intelligence software for human resources and customer service. The report brought to light a troubling relationship between the two organizations. Both had previously been headed by the same CEO, Nancy Lublin. In 2019, however, Lublin had stepped down from Loris, and in 2020 Crisis Text Line’s board ousted her following allegations that she had engaged in workplace racism.

But the troubles that enveloped Crisis Text Line can’t be blamed on one bad apple. Crisis Text Line’s board of directors had approved the relationship between the entities. In the technology and big data sectors, commodification of user data is fundamental to a platform or toolset’s economic survival, and by sharing data with Loris.ai, Crisis Text Line was able to provide needed services. The harsh reality revealed by the Politico report was that even mental healthcare is not immune from commodification, despite the risks of aggregating and sharing information about experiences and topics which continue to be stigmatized.

In the case of the Crisis Text Line-Loris.ai partnership, Loris used the nonprofit’s data to improve its own, for-profit development of machine learning algorithms sold to corporations and governments. Although Crisis Text Line maintains that all of the data shared with Loris was anonymized, the transactional nature of the relationship between the two was still fundamentally an economic one. As the Loris.ai website states, “Crisis Text Line is a Loris shareholder. Our success offers material benefit to CTL, helping this non-profit organization continue its important work. We believe this model is a blueprint for ways for-profit companies can infuse social good into their culture and operations, and for nonprofits to prosper.”…(More)”.

Better data for better therapies: The case for building health data platforms

Curated on Posted on by Stefaan Verhulst

Paper by Matthias Evers, Lucy Pérez, Lucas Robke, and Katarzyna Smietana: “Despite expanding development pipelines, many pharmaceutical companies find themselves focusing on the same limited number of derisked areas and mechanisms of action in, for example, immuno-oncology. This “herding” reflects the challenges of advancing understanding of disease and hence of developing novel therapeutic approaches. The full promise of innovation from data, AI, and ML has not yet materialized.

It is increasingly evident that one of the main reasons for this is insufficient high-quality, interconnected human data that go beyond just genes and corresponding phenotypes—the data needed by scientists to form concepts and hypotheses and by computing systems to uncover patterns too complex for scientists to understand. Only such high-quality human data would allow deployment of AI and ML, combined with human ingenuity, to unravel disease biology and open up new frontiers to prevention and cure. Here, therefore, we suggest a way of overcoming the data impediment and moving toward a systematic, nonreductionist approach to disease understanding and drug development: the establishment of trusted, large-scale platforms that collect and store the health data of volunteering participants. Importantly, such platforms would allow participants to make informed decisions about who could access and use their information to improve the understanding of disease….(More)”.

The Food Aid Delivery App

Curated on Posted on by Stefaan Verhulst

Essay by Trish Bendix: “Between 30 and 40 percent of the US food supply goes to waste each year. The US Environmental Protection Agency estimates that nearly 80 billion pounds of food end up in landfills annually. This figure takes on a greater significance in the context of another food crisis: food insecurity. More than 10 percent of US households are food insecure, and the nonprofit Feeding America reports that this number will increase due to the economic and unemployment consequences of the COVID-19 pandemic.

The food waste crisis is not new. Wasted, a 2012 report from the Natural Resources Defense Council, recorded Americans’ annual food waste at 40 percent. Horrified by the report’s findings, Leah Lizarondo, a food and health advocate who began her career working in consumer-packaged goods and technology, was inspired to find a solution.

“I tried to figure out why this inefficiency was happening—where the failing was in the supply chain,” Lizarondo says. She knew that consumer-facing businesses such as grocery stores and restaurants were the second-biggest culprits of food waste—behind American households. And even though these businesses didn’t intend to waste food, they lacked the logistics, structures, or incentives to redirect the food surplus to people experiencing food insecurity. Furthermore, because most wasted food is perishable, traditional waste methods didn’t work within the food-banking structure.

“It was so cheap to just throw food in a landfill,” Lizarondo comments. “There’s no legislation [in the United States] that prevents us from doing that, unlike other countries.” For example, France banned food waste in 2016, while Norway has stores that sell food past their sell-by dates, and Asian countries like Japan and South Korea have adopted their own regulations, including the latter charging a fee to citizens for each pound of food waste. Currently, California, Connecticut, Massachusetts, Rhode Island, and Vermont are the only US states with legislation enforcing organic waste bans.

In 2016, Lizarondo launched the nonprofit Food Rescue Hero, a technology platform that redirects food waste to the food insecure in cities across America.

Since its launch, Food Rescue Hero has given more than 68 million pounds of food to people in need. Currently, it operates in 12 cities in the United States and Canada, with more than 22,000 drivers volunteering their time….(More)”.

Health Data Governance Principles

Curated on Posted on by Stefaan Verhulst

Principles prepared by Transform health: “Data-driven approaches are increasingly the norm or aspiration in the operation of health systems. The collection, processing, storage, analysis, use, sharing and disposal of health data has grown in complexity. This exponential increase in data use necessitates robust and equitable governance of health data. Countries and regions around the world are instituting health data governance policies and legislation. However, there is not yet a comprehensive, global set of principles to guide the governance of health data across public health systems and policies. The Health Data Governance Principles respond to that need.

The Principles are intended as a resource for, and have applicability to, a range of stakeholders involved in the collection and use of health data, including governments, the private sector, international organisations, civil society, among others. We encourage all stakeholders to endorse the Principles.

We want to see the Principles adopted by governments, technology companies, and other institutions responsible for collecting and managing health data…(More)”.

Trust the Science But Do Your Research: A Comment on the Unfortunate Revival of the Progressive Case for the Administrative State

Curated on Posted on by Stefaan Verhulst

Essay by Mark Tushnet: “…offers a critique of one Progressive argument for the administrative state, that it would base policies on what disinterested scientific inquiries showed would best advance the public good and flexibly respond to rapidly changing technological, economic, and social conditions. The critique draws on recent scholarship in the field of Science and Technology Studies, which argues that what counts as a scientific fact is the product of complex social, political, and other processes. The critique is deployed in an analysis of the responses of the U.S. Centers for Disease Control and Food and Drug Administration to some important aspects of the COVD crisis in 2020.

A summary of the overall argument is this: The COVID virus had characteristics that made it exceptionally difficult to develop policies that would significantly limit its spread until a vaccine was available, and some of those characteristics went directly to the claim that the administrative state could respond flexibly to rapidly changing conditions. But, and here is where the developing critique of claims about scientific expertise enters, the relevant administrative agencies were bureaucracies with scientific staff members, and what those bureaucracies regard as “the science” was shaped in part by bureaucratic and political considerations, and the parts that were so shaped were important components of the overall policy response.

Part II describes policy-relevant characteristics of knowledge about the COVID virus and explains why those characteristics made it quite difficult for more than a handful of democratic nations to adopt policies that would effectively limit its penetration of their populations. Part III begins with a short presentation of the aspects of the STS critique of claims about disinterested science that have some bearing on policy responses to the pandemic. It then provides an examination shaped by that critique of the structures of the Food and Drug Administration and the Centers for Disease Control, showing how those structural features contributed to policy failures. Part IV concludes by sketching how the STS critique might inform efforts to reconstruct rather than deconstruct the administrative state, proposing the creation of Citizen Advisory Panels in science-based agencies…(More)”.

Lessons from the COVID data wizards

Curated on Posted on by Stefaan Verhulst

Article by Lynne Peeples: “In March 2020, Beth Blauer started hearing anecdotally that COVID-19 was disproportionately affecting Black people in the United States. But the numbers to confirm that disparity were “very limited”, says Blauer, a data and public-policy specialist at Johns Hopkins University in Baltimore, Maryland. So, her team, which had developed one of the most popular tools for tracking the spread of COVID-19 around the world, added a new graphic to their website: a colour-coded map tracking which US states were — and were not — sharing infection and death data broken down by race and ethnicity.

They posted the map to their data dashboard — the Coronavirus Resource Center — in mid-April 2020 and promoted it through social media and blogs. At the time, just 26 states included racial information with their death data. “Then we started to see the map rapidly filling in,” says Blauer. By the middle of May 2020, 40 states were reporting that information. For Blauer, the change showed that people were paying attention. “And it confirmed that we have the ability to influence what’s happening here,” she says.

COVID-19 dashboards mushroomed around the world in 2020 as data scientists and journalists shifted their work to tracking and presenting information on the pandemic — from infection and death rates, to vaccination data and other variables. “You didn’t have any data set before that was so essential to how you plan your life,” says Lisa Charlotte Muth, a data designer and blogger at Datawrapper, a Berlin-based company that helps newsrooms and journalists to enrich their reporting with embeddable charts. “The weather, maybe, was the closest thing you could compare it to.” The growth in the service’s popularity was impressive. In January 2020 — before the pandemic — Datawrapper had 260 million chart views on its clients’ websites. By April that year, that monthly figure had shot up to more than 4.7 billion.

Policymakers, too, have leaned on COVID-19 data dashboards and charts to guide important decisions. And they had hundreds of local and global examples to reference, including academic enterprises such as the Coronavirus Resource Center, as well as government websites and news-media projects…(More)”.

Mapping of exposed water tanks and swimming pools based on aerial images can help control dengue

Curated on Posted on by Stefaan Verhulst

Press Release by Fundação de Amparo à Pesquisa do Estado de São Paulo: “Brazilian researchers have developed a computer program that locates swimming pools and rooftop water tanks in aerial photographs with the aid of artificial intelligence to help identify areas vulnerable to infestation by Aedes aegypti, the mosquito that transmits dengue, zika, chikungunya and yellow fever. 

The innovation, which can also be used as a public policy tool for dynamic socio-economic mapping of urban areas, resulted from research and development work by professionals at the University of São Paulo (USP), the Federal University of Minas Gerais (UFMG) and the São Paulo State Department of Health’s Endemic Control Superintendence (SUCEN), as part of a project supported by FAPESP. An article about it is published in the journal PLOS ONE. 

“Our work initially consisted of creating a model based on aerial images and computer science to detect water tanks and pools, and to use them as a socio-economic indicator,” said Francisco Chiaravalloti Neto, last author of the article. He is a professor in the Epidemiology Department at USP’s School of Public Health (FSP), with a first degree in engineering. 

As the article notes, previous research had already shown that dengue tends to be most prevalent in deprived urban areas, so that prevention of dengue, zika and other diseases transmitted by the mosquito can be made considerably more effective by use of a relatively dynamic socio-economic mapping model, especially given the long interval between population censuses in Brazil (ten years or more). 

“This is one of the first steps in a broader project,” Chiaravalloti Neto said. Among other aims, he and his team plan to detect other elements of the images and quantify real infestation rates in specific areas so as to be able to refine and validate the model. 

“We want to create a flow chart that can be used in different cities to pinpoint at-risk areas without the need for inspectors to call on houses, buildings and other breeding sites, as this is time-consuming and a waste of the taxpayer’s money,” he added…(More)”.

Crowdsourcing and COVID-19: How public administrations mobilize crowds to find solutions to problems posed by the pandemic

Curated on Posted on by Stefaan Verhulst

Paper by Ana Colovic, Annalisa Caloffi, and Federica Rossi: “We discuss how public administrations have used crowdsourcing to find solutions to specific problems posed by the COVID-19 pandemic, and to what extent crowdsourcing has been instrumental in promoting open innovation and service co-creation. We propose a conceptual typology of crowdsourcing challenges based on the degree of their openness and collaboration with the crowd that they establish. Using empirical evidence collected in 2020 and 2021, we examine the extent to which these types have been used in practice. We discuss each type of crowdsourcing challenge identified and draw implications for public policy…(More)”.

“Medical Matchmaking” provides personalized insights

Curated on Posted on by Stefaan Verhulst

Matthew Hempstead at Springwise: “Humanity is a collection of unique individuals who represent a complex mixture of medical realities. Yet traditional medicine is based on a ‘law of averages’ – treating patients based on generalisations about the population as a whole. This law of averages can be misleading, and in a world where the average American spends 52 hours looking for health information online each year, generalisations create misunderstandings. Information provided by ‘Dr. Google’ or Facebook is inadequate and doesn’t account for the specific characteristics of each individual.

Israeli startup Alike has come up with a novel multidisciplinary solution to this problem – using health data and machine learning to match people who are alike on a holistic level. The AI’s matchmaking takes into account considerations such as co-morbidities, lifestyle factors, age, and gender.

Patients are then put into contact with an anonymised community of ‘Alikes’ – people who share their exact clinical journey, lifestyle, and interests. Members of this community can share or receive relevant and personalised insights that help them to better manage their conditions.

The new technology is possible due to regulatory changes that make it possible for everyone to gain instant electronic access to their personal health records. The app allows users to automatically create a health profile through a direct connection with their health provider.

Given the sensitive nature of medical information, Alike has put in place stringent privacy controls. The data shared on the app is completely de-identified, which means all personal identifiers are removed. Every user is verified by their healthcare provider, and further measures including data encryption and data fuzzing are employed. This means that patients can benefit from the insights of other patients while maintaining their privacy…(More)”.

The #Data4Covid19 Review

Curated on Posted on by Stefaan Verhulst

Press Release: “The Governance Lab (The GovLab), an action research center at New York University Tandon School of Engineering, with the support of the Knight Foundation, today announced the launch of The #Data4Covid19 Review. Through this initiative, The GovLab will evaluate how select countries used data to respond to the COVID-19 pandemic. The findings will be used to identify lessons that can be applied to future data-driven crisis management.

The initiative launches within the context of the 2nd anniversary of the announcement that COVID-19 was a global pandemic and the resulting lockdown restrictions. Countries around the world have since undertaken varied approaches to minimizing the spread of the virus and managing the aftermath. Many of these efforts are driven by data. While the COVID-19 pandemic continues to be a global challenge, there have been few attempts to review and evaluate how data use played a role holistically in the global pandemic response.

The #Data4Covid19 Review aims to fill this gap in the current research by providing an assessment of how data was used during the different waves of the pandemic and guidance for the improvement of future data systems. The GovLab will develop case studies and compare a select group of countries from around the world, with the input and support of a distinguished advisory group of public health, technology, and human rights experts. These case studies will investigate how data use impacted COVID-19 responses. Outputs will include recommendations for decision makers looking to improve their capacity to use data in a responsible way for crisis management and an assessment framework that could be used when designing future data-driven crisis responses. By learning from our response to the pandemic, we can better understand how the use of data should be used in crisis management…(More)”.