Building a trauma-informed algorithmic assessment toolkit

Curated on Posted on by Stefaan Verhulst

Report by Suvradip Maitra, Lyndal Sleep, Suzanna Fay, Paul Henman: “Artificial intelligence (AI) and automated processes provide considerable promise to enhance human wellbeing by fully automating or co-producing services with human service providers. Concurrently, if not well considered, automation also provides ways in which to generate harms at scale and speed. To address this challenge, much discussion to date has focused on principles of ethical AI and accountable algorithms with a groundswell of early work seeking to translate these into practical frameworks and processes to ensure such principles are enacted. AI risk assessment frameworks to detect and evaluate possible harms is one dominant approach, as are a growing body of AI audit frameworks, with concomitant emerging governmental and organisational regulatory settings, and associate professionals.

The research outlined in this report took a different approach. Building on work in social services on trauma-informed practice, researchers identified key principles and a practical framework that framed AI design, development and deployment as a reflective, constructive exercise that resulting in algorithmic supported services to be cognisant and inclusive of the diversity of human experience, and particularly those who have experienced trauma. This study resulted in a practical, co-designed, piloted Trauma Informed Algorithmic Assessment Toolkit.

This Toolkit has been designed to assist organisations in their use of automation in service delivery at any stage of their automation journey: ideation; design; development; piloting; deployment or evaluation. While of particular use for social service organisations working with people who may have experienced past trauma, the tool will be beneficial for any organisation wanting to ensure safe, responsible and ethical use of automation and AI…(More)”.

Predicting hotspots of unsheltered homelessness using geospatial administrative data and volunteered geographic information

Curated on Posted on by Stefaan Verhulst

Paper by Jessie Chien, Benjamin F. Henwood, Patricia St. Clair, Stephanie Kwack, and Randall Kuhn: “Unsheltered homelessness is an increasingly prevalent phenomenon in major cities that is associated with adverse health and mortality outcomes. This creates a need for spatial estimates of population denominators for resource allocation and epidemiological studies. Gaps in the timeliness, coverage, and spatial specificity of official Point-in-Time Counts of unsheltered homelessness suggest a role for geospatial data from alternative sources to provide interim, neighborhood-level estimates of counts and trends. We use citizen-generated data from homeless-related 311 requests, provider-based administrative data from homeless street outreach cases, and expert reports of unsheltered count to predict count and emerging hotspots of unsheltered homelessness in census tracts across the City of Los Angeles for 2019 and 2020. Our study shows that alternative data sources can contribute timely insights into the state of unsheltered homelessness throughout the year and inform the delivery of interventions to this vulnerable population…(More)”.

Crowded Out: The True Costs of Crowdfunding Healthcare

Curated on Posted on by Stefaan Verhulst

Book by Nora Kenworthy: “Over the past decade, charitable crowdfunding has exploded in popularity across the globe. Sites such as GoFundMe, which now boasts a “global community of over 100 million” users, have transformed the ways we seek and offer help. When faced with crises—especially medical ones—Americans are turning to online platforms that promise to connect them to the charity of the crowd. What does this new phenomenon reveal about the changing ways we seek and provide healthcare? In Crowded Out, Nora Kenworthy examines how charitable crowdfunding so quickly overtook public life, where it is taking us, and who gets left behind by this new platformed economy.

Although crowdfunding has become ubiquitous in our lives, it is often misunderstood: rather than a friendly free market “powered by the kindness” of strangers, crowdfunding is powerfully reinforcing inequalities and changing the way Americans think about and access healthcare. Drawing on extensive research and rich storytelling, Crowded Out demonstrates how crowdfunding for health is fueled by—and further reinforces—financial and moral “toxicities” in market-based healthcare systems. It offers a unique and distressing look beneath the surface of some of the most popular charitable platforms and helps to foster thoughtful discussions of how we can better respond to healthcare crises both small and large…(More)”.

Behavioural Economics and Policy for Pandemics

Curated on Posted on by Stefaan Verhulst

Book edited by Joan Costa-Font, Matteo M. Galizzi: “Behavioural economics and behavioural public policy have been fundamental parts of governmental responses to the Covid-19 pandemic. This was not only the case at the beginning of the pandemic as governments pondered how to get people to follow restrictions, but also during delivery of the vaccination programme. Behavioural Economics and Policy for Pandemics brings together a world-class line-up of experts to examine the successes and failures of behavioural economics and policy in relation to the Covid-19 pandemic. It documents how people changed their behaviours and use of health care and discusses what we can learn in terms of addressing future pandemics. Featuring high-profile behavioural economists such as George Loewenstein, this book uniquely uncovers behavioural regularities that emerge in the different waves of COVID-19 and documents how pandemics change our lives.

  • Provides a selection of studies featuring behavoural regulaltities during COVID-19
  • Unique in that it brings together works from health economics and behavioural science that neither journals or other books do
  • Offers the first book on the behavioural economics of pandemics
  • Brings together works of behavoural scientists and the economists examining health behaviours on the effects of COVID-19 on health and health care…(More)”.

AI-Powered World Health Chatbot Is Flubbing Some Answers

Curated on Posted on by Stefaan Verhulst

Article by Jessica Nix: “The World Health Organization is wading into the world of AI to provide basic health information through a human-like avatar. But while the bot responds sympathetically to users’ facial expressions, it doesn’t always know what it’s talking about.

SARAH, short for Smart AI Resource Assistant for Health, is a virtual health worker that’s available to talk 24/7 in eight different languages to explain topics like mental health, tobacco use and healthy eating. It’s part of the WHO’s campaign to find technology that can both educate people and fill staffing gaps with the world facing a health-care worker shortage.

WHO warns on its website that this early prototype, introduced on April 2, provides responses that “may not always be accurate.” Some of SARAH’s AI training is years behind the latest data. And the bot occasionally provides bizarre answers, known as hallucinations in AI models, that can spread misinformation about public health.The WHO’s artificial intelligence tool provides public health information via a lifelike avatar.Source: Bloomberg

SARAH doesn’t have a diagnostic feature like WebMD or Google. In fact, the bot is programmed to not talk about anything outside of the WHO’s purview, including questions on specific drugs. So SARAH often sends people to a WHO website or says that users should “consult with your health-care provider.”

“It lacks depth,” Ramin Javan, a radiologist and researcher at George Washington University, said. “But I think it’s because they just don’t want to overstep their boundaries and this is just the first step.”..(More)”

The Global State of Social Connections

Curated on Posted on by Stefaan Verhulst

Gallup: “Social needs are universal, and the degree to which they are fulfilled — or not — impacts the health, well-being and resilience of people everywhere. With increasing global interest in understanding how social connections support or hinder health, policymakers worldwide may benefit from reliable data on the current state of social connectedness. Despite the critical role of social connectedness for communities and the people who live in them, little is known about the frequency or form of social connection in many — if not most — parts of the world.

Meta and Gallup have collaborated on two research studies to help fill this gap. In 2022, the Meta-Gallup State of Social Connections report revealed important variations in people’s sense of connectedness and loneliness across the seven countries studied. This report builds on that research by presenting data on connections and loneliness among people from 142 countries…(More)”.

AI Is Building Highly Effective Antibodies That Humans Can’t Even Imagine

Curated on Posted on by Stefaan Verhulst

Article by Amit Katwala: “Robots, computers, and algorithms are hunting for potential new therapies in ways humans can’t—by processing huge volumes of data and building previously unimagined molecules. At an old biscuit factory in South London, giant mixers and industrial ovens have been replaced by robotic arms, incubators, and DNA sequencing machines.

James Field and his company LabGenius aren’t making sweet treats; they’re cooking up a revolutionary, AI-powered approach to engineering new medical antibodies. In nature, antibodies are the body’s response to disease and serve as the immune system’s front-line troops. They’re strands of protein that are specially shaped to stick to foreign invaders so that they can be flushed from the system. Since the 1980s, pharmaceutical companies have been making synthetic antibodies to treat diseases like cancer, and to reduce the chance of transplanted organs being rejected. But designing these antibodies is a slow process for humans—protein designers must wade through the millions of potential combinations of amino acids to find the ones that will fold together in exactly the right way, and then test them all experimentally, tweaking some variables to improve some characteristics of the treatment while hoping that doesn’t make it worse in other ways. “If you want to create a new therapeutic antibody, somewhere in this infinite space of potential molecules sits the molecule you want to find,” says Field, the founder and CEO of LabGenius…(More)”.

Whatever Happened to All Those Care Robots?

Curated on Posted on by Stefaan Verhulst

Article by Stephanie H. Murray: “So far, companion robots haven’t lived up to the hype—and might even exacerbate the problems they’re meant to solve…There are likely many reasons that the long-predicted robot takeover of elder care has yet to take off. Robots are expensive, and cash-strapped care homes don’t have money lying around to purchase a robot, let alone to pay for the training needed to actually use one effectively. And at least so far, social robots just aren’t worth the investment, Wright told me. Pepper can’t do a lot of the things people claimed he could—and he relies heavily on humans to help him do what he can. Despite some research suggesting they can boost well-being among the elderly, robots have shown little evidence that they make life easier for human caregivers. In fact, they require quite a bit of care themselves. Perhaps robots of the future will revolutionize caregiving as hoped. But the care robots we have now don’t even come close, and might even exacerbate the problems they’re meant to solve…(More)”.

Using online search activity for earlier detection of gynaecological malignancy

Curated on Posted on by Stefaan Verhulst

Paper by Jennifer F. Barcroft et al: Ovarian cancer is the most lethal and endometrial cancer the most common gynaecological cancer in the UK, yet neither have a screening program in place to facilitate early disease detection. The aim is to evaluate whether online search data can be used to differentiate between individuals with malignant and benign gynaecological diagnoses.

This is a prospective cohort study evaluating online search data in symptomatic individuals (Google user) referred from primary care (GP) with a suspected cancer to a London Hospital (UK) between December 2020 and June 2022. Informed written consent was obtained and online search data was extracted via Google takeout and anonymised. A health filter was applied to extract health-related terms for 24 months prior to GP referral. A predictive model (outcome: malignancy) was developed using (1) search queries (terms model) and (2) categorised search queries (categories model). Area under the ROC curve (AUC) was used to evaluate model performance. 844 women were approached, 652 were eligible to participate and 392 were recruited. Of those recruited, 108 did not complete enrollment, 12 withdrew and 37 were excluded as they did not track Google searches or had an empty search history, leaving a cohort of 235.s

The cohort had a median age of 53 years old (range 20–81) and a malignancy rate of 26.0%. There was a difference in online search data between those with a benign and malignant diagnosis, noted as early as 360 days in advance of GP referral, when search queries were used directly, but only 60 days in advance, when queries were divided into health categories. A model using online search data from patients (n = 153) who performed health-related search and corrected for sample size, achieved its highest sample-corrected AUC of 0.82, 60 days prior to GP referral.

Online search data appears to be different between individuals with malignant and benign gynaecological conditions, with a signal observed in advance of GP referral date. Online search data needs to be evaluated in a larger dataset to determine its value as an early disease detection tool and whether its use leads to improved clinical outcomes…(More)”.

Unconventional data, unprecedented insights: leveraging non-traditional data during a pandemic

Curated on Posted on by Stefaan Verhulst

Paper by Kaylin Bolt et al: “The COVID-19 pandemic prompted new interest in non-traditional data sources to inform response efforts and mitigate knowledge gaps. While non-traditional data offers some advantages over traditional data, it also raises concerns related to biases, representativity, informed consent and security vulnerabilities. This study focuses on three specific types of non-traditional data: mobility, social media, and participatory surveillance platform data. Qualitative results are presented on the successes, challenges, and recommendations of key informants who used these non-traditional data sources during the COVID-19 pandemic in Spain and Italy….

Non-traditional data proved valuable in providing rapid results and filling data gaps, especially when traditional data faced delays. Increased data access and innovative collaborative efforts across sectors facilitated its use. Challenges included unreliable access and data quality concerns, particularly the lack of comprehensive demographic and geographic information. To further leverage non-traditional data, participants recommended prioritizing data governance, establishing data brokers, and sustaining multi-institutional collaborations. The value of non-traditional data was perceived as underutilized in public health surveillance, program evaluation and policymaking. Participants saw opportunities to integrate them into public health systems with the necessary investments in data pipelines, infrastructure, and technical capacity…(More)”.